A Systematic Review of Energy Recovery and Regeneration Systems in Hydrogen-Powered Vehicles for Deployment in Developing Nations

Abstract

Improving the efficiency and range of hydrogen-powered electric vehicles (HPEVs) is essential for their global adoption, especially in developing countries with limited resources. This study systematically evaluates regenerative braking and suspension systems in HPEVs and proposes a deployment-focused framework tailored to the needs of developing nations. A comprehensive search was performed across multiple databases to identify relevant studies. The selected studies are screened, assessed for quality, and analyzed based on predefined criteria. The data is synthesized and interpreted to identify patterns, gaps, and conclusions. The findings show that regeneration systems, such as regenerative braking and regenerative suspension, are the most effective energy recovery systems in most electric and hydrogen-powered vehicles. Although the regenerative braking system (RBS) offers higher energy efficiency gains that enhance cost-effectiveness despite its high initial investment, the regenerative suspension system (RSS) involves increased complexity. Still, it offers comparatively efficient energy recovery, particularly in developing countries with patchy road infrastructure. The gaps highlighted in this review will aid researchers and vehicle manufacturers in designing, optimizing, developing, and commercializing HPEVs for deployment in developing countries.

1. Introduction

As technology advances and infrastructure expands worldwide, HPEVs have been identified to play a key role in achieving long-term sustainability goals by reducing dependence on fossil fuels and combating climate change [1,2,3]. By utilizing hydrogen as a clean fuel, HPEVs emit only water vapor, thereby significantly reducing harmful emissions and contributing to improved air quality. Additionally, as hydrogen can be produced from renewable sources such as solar, wind, and hydropower, it supports the transition to a low-carbon economy [2,3].

Hydrogen-powered vehicles are considered a viable solution for sustainable transportation, particularly in developing nations where the need for clean, efficient alternatives to fossil fuel-based transportation is urgent. According to [3], HPEVs offer the advantage of faster refueling times compared to battery electric vehicles (BEVs), thereby enhancing convenience for users, as illustrated in

Table 1. Comparison of battery and hydrogen-powered electric vehicles.

Feature	Battery Electric Vehicles	Hydrogen-Powered Vehicles
Energy Source	Electricity is stored in batteries	Hydrogen gas is used in fuel cells to generate electricity
Refueling Time	Typically, 30 min to 1 h	3 to 5 min, similar to conventional combustion engines
Driving Range	150 to 350 miles, depending on the size of the battery	300 to 400 miles, depending on fuel tank capacity
Infrastructural Availability	Growing charging network (home public stations)	Limited refueling stations
Efficiency	High efficiency (80 to 90% energy conversion)	Moderate efficiency (40 to 60% energy conversion)
Environmental	Low emissions, with potential for zero emissions when powered using renewable sources	Zero emissions at the vehicle level, except that hydrogen production is not from renewable sources
Energy Storage	Large and heavy battery occupying significant space, leading to increased weight	Hydrogen storage tanks are lighter but need to be pressurized or liquefied
Cost	The high initial cost of battery production decreases over time.	High cost of hydrogen production, fuel cells, and refueling infrastructure
Vehicle Life Span	Battery degradation over time (between 8 and 10 years)	Fuel cell degradation over time (5 to 8 years)
Maintenance	Low maintenance (no engine, fewer moving parts)	Require maintenance of fuel cells and the hydrogen storage system
Energy Source Availability	Dependent on electricity generation, either renewable or non-renewable	Hydrogen availability depends on the production method (renewable or non-renewable)
Weight	Heavy batteries lead to a reduction in overall efficiency and performance	Hydrogen tanks are lighter, but fuel cells can add weight
Public Perception	More established and widely accepted	Emerging technology is met with more skepticism and less widespread awareness

.

However, the widespread adoption of HPEVs in developing countries faces significant challenges, including limited hydrogen refueling infrastructure and high vehicle costs. For HPEVs to become more practical and appealing in these regions, improving their energy efficiency and driving range becomes crucial. The efficiency of HPEVs is influenced by several factors, including energy losses in hydrogen production, storage, and conversion in the fuel cell [4,5]. However, the fuel cell itself is relatively efficient at converting hydrogen into electricity, with an efficiency rate typically ranging between 40% and 60%, which is higher than traditional internal combustion engines (ICEs) [5,6]. Conventional methods for improving the efficiency of HPEVs focused on optimizing key components such as the fuel cell, storage system, and powertrain configuration [7,8,9]. One key approach is to enhance the performance of proton exchange membrane fuel cells (PEMFCs), which convert hydrogen into electricity, by improving catalyst materials, reducing the use of precious metals, and increasing the overall cell’s durability and efficiency [6,10]. Advances in hydrogen storage also contribute to efficiency, as high-pressure tanks and cryogenic storage systems can be refined to maximize hydrogen density, reducing weight and increasing the vehicle range [9].

However, many of these traditional approaches are being thwarted by various challenges relating to cost, infrastructure, and technological limitations [8,11]. A critical evaluation of the available options for improving the efficiency and range of HPEVs for deployment in developing nations has pointed in the direction of energy recovery systems. Energy recovery in electric vehicles (EVs) is a process of capturing kinetic energy during deceleration and converting it into electrical energy [10,12].

The energy wasted as heat in traditional braking systems is converted to useful energy when the vehicle’s electric motor reverses its function and performs the work of a generator. The captured energy is then sent back to the vehicle’s battery for later use, which helps extend the vehicle’s range and improve its overall energy efficiency. This process is particularly suitable for developing economies where stop-and-go driving conditions are frequently experienced, and the need for frequent braking provides continuous opportunities for energy recovery [9,12,13].

Different researchers have employed various types of energy recovery systems to enhance efficiency and reduce hydrogen consumption in HPEVs [13,14,15,16,17]. The most common method is an RBS, where the vehicle’s electric motor functions as a generator during braking, converting kinetic energy into electrical energy, which is then stored in the vehicle’s battery or supercapacitor [5,18]. Other energy recovery approaches include an RSS, flywheel energy storage systems, among others [18,19,20]. A broad view of the existing energy recovery approaches used in the design of most EVs is presented in Figure 1.

Many of these systems are still in the developmental stage in HPEVs but offer a potential alternative. Additionally, some advanced hydrogen vehicles integrate energy recovery strategies that combine both an RBS and energy management systems that optimize the use of stored energy across different driving conditions [5,18,21].

The primary role of an energy recovery system is to improve the efficiency, range, and sustainability of HPEVs [5,18,21]. By capturing and storing energy that would otherwise be lost during vehicle operation, energy recovery systems help reduce the overall demand on the hydrogen fuel cell, increasing the vehicle’s range and making it more viable for developing countries [5,18]. While energy recovery systems are essential to the efficiency of HPEVs, they remain underdeveloped or poorly implemented in many developing nations.

Many roads in these regions are poorly maintained, with potholes, uneven surfaces, and inadequate infrastructure, which may lead to higher wear and tear on vehicles. In addition, the lack of proper signage, traffic management, and road safety features in many developing nations also contributes to unpredictable driving conditions, requiring more resilient vehicle systems. A comparison of roads found in developed and developing countries is presented in

Table 2. Comparison of stop-and-go traffic and highway roads.

Feature	Stop-and-Go Traffic (Urban Roads)	Highways (Intercity and Express Roads)
Traffic Flow	Frequent stops due to traffic lights, congestion, and pedestrian crossings.	Smoother flow but interrupted by toll gates, checkpoints, and road conditions.
Speed Variation	Highly variable speeds, frequent acceleration, and deceleration.	Higher average speed but can be interrupted by slow-moving vehicles and obstacles.
Primary Users	Private cars, minibuses (e.g., matatus, taxis), motorcycles, bicycles, and pedestrians.	Mostly private cars, buses, heavy trucks, and some motorcycles.
Congestion Levels	High, due to poor traffic management, informal transport, and high vehicle density.	Lower, but congestion can occur at toll gates, checkpoints, and accident zones.
Road Conditions	Often poor, with potholes, inadequate drainage, and unpaved sections.	Varies; some highways are well-maintained, while others suffer from neglect.
Braking and Acceleration	Frequent braking and acceleration due to obstacles, junctions, and traffic signals.	Less frequent braking, but may slow down for checkpoints, toll booths, and rough sections.
Energy Efficiency for EVs	Lower, as regenerative braking is used more frequently, energy losses are higher due to the frequent acceleration.	Higher, as EVs can maintain steady speeds with fewer braking events, optimizing battery usage.
Infrastructure Challenges	Poor road signage, lack of lane discipline, and presence of informal markets.	Insufficient service areas, poorly maintained rest stops, and limited bypass routes.

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However, these challenges also create an opportunity for HPEVs to demonstrate their potential in harsh environments, where low-emission, long-range capabilities can be particularly beneficial. The integration of energy recovery systems, such as an RBS and RSS, can mitigate some of the efficiency losses caused by rough roads, thereby improving the vehicle’s performance and making it more suitable for the diverse and often challenging road networks found in developing countries.

This review thus combines an RBS and RSS within HPEVs’ powertrains, compares their combined energy-recovery potential against real-world constraints in developing countries, and proposes a phased deployment plan that links technical performance, infrastructure readiness, and cost/benefit ratios. Previous reviews have either addressed an RBS or RSS in battery EVs; none have integrated both for HPEVs or considered conditions in emerging economies. Therefore, this work fills a vital gap and sets out a research agenda for high-efficiency, hydrogen-based mobility in resource-limited regions. The rest of the paper is structured as follows: Section 2 outlines the methodology for the systematic literature review; the findings from the analysis carried out on the reviewed literature are presented in Section 3; Section 4 discusses the results and proposes a framework for integrating an RBS and RSS in HPEVs for deployment in developing nations; meanwhile, Section 5 and Section 6 highlight the conclusions inferred from this study and future research directions, respectively.

2. Materials and Methods

A systematic review approach was employed to comprehensively collect, evaluate, and synthesize existing studies on energy recovery and regeneration systems in EVs using a structured and transparent approach. The primary objective was to provide an unbiased and comprehensive overview of the existing evidence by identifying patterns, gaps, or inconsistencies in the literature. This approach has been employed in various engineering reviews with a high degree of accuracy, utilizing an evidence-based approach [11,22,23,24,25]. By using this approach, valuable insights into the potential impact and feasibility of deploying HPEVs in developing countries can be provided, ensuring that recommendations are based on robust and evidence-based findings.

To ensure the comprehensibility, transparency, and reproducibility of a systematic review, it must follow an organized procedure [22]. Research studies related to various energy recovery mechanisms used in enhancing the efficiency of EVs, particularly battery electric vehicles (BEVs) and HEVs, were systematically gathered, assessed, and analyzed. The various procedures used in this review are subsequently presented.

2.1. Stage 1: Formulation of Research Questions

This is the stage where the research questions or hypotheses are clearly defined. As HPEVs are gradually gaining ground around the world, it is crucial to explore the benefits of energy recovery systems in all types of EVs. As such, the following questions are posed as hypotheses in this review.

What are the key energy recovery systems in EVs?

What are the factors affecting the energy recovered in EVs?

How are these systems optimized for the deployment of HPEVs in developing countries?

What are the challenges associated with the implementation and scalability of these systems?

2.2. Stage 2: Search Strategy

This involves several key steps to ensure comprehensive and reproducible results. Firstly, relevant databases such as Scopus, Web of Science, IEEE Xplore, MDPI, and ScienceDirect were queried for records from 2010 to 2025 to reflect the latest innovations, materials, and system designs in energy recovery technologies specific to BEVs and HPEVs. Boolean operators such as “AND” (for battery/hydrogen/fuel cell vehicles and energy recovery) and “OR” (for regeneration systems) were used to ensure broad yet focused coverage. The specific search keywords are presented in

Table 3. Keyword search.

Components	Search Terms
Keywords	hydrogen-powered vehicles, energy recovery, energy recovery approaches, regenerative systems, energy storage in HPEVs, fuel cell vehicles, battery electric vehicles developing countries.

.

2.3. Stage 3: Inclusion Criteria

This is the stage at which the specific characteristics of the reviewed papers are evaluated against certain criteria to determine their inclusion in the review. Articles were included based on the following criteria:

• Studies focused on either BEVs or HPEVs, specifically addressing energy recovery or regeneration systems;
• Studies with original research, such as experimental, simulation, or theoretical studies;
• Studies that are peer-reviewed to ensure scientific thoroughness;
• Studies relevant to the advancement or evaluation of energy recovery technologies;
• Studies published within the predefined timeframe (2010 to 2025).

2.4. Stage 4: Exclusion Criteria

This stage involves identifying studies that do not meet the defined scope or quality standards. Articles were excluded based on the following criteria:

• Publications that are not peer-reviewed, such as conference abstracts, opinion pieces, or non-scientific reports;
• Research that does not specifically address energy recovery or regeneration systems;
• Studies published before 2010, as they may not reflect the latest advancements in the field;
• Articles written in languages other than English;
• Studies that do not provide sufficient data or methodology to assess the relevance and reliability of the findings.

2.5. Stage 5: Data Extraction

At this stage, relevant information from selected studies is systematically collected to assess and synthesize findings. Key fields, including vehicle type, recovery method, storage medium, test cycle, efficiency, and cost metrics, were logged in a structured spreadsheet. Energy-recovery values were normalized to $\mathrm{W}\mathrm{h}/{\mathrm{k}\mathrm{m}}^{-1}$ for cross-study comparison. This procedure step ensured that all relevant data was captured, facilitating a thorough and comparative analysis of the technologies and trends in energy recovery and regeneration systems.

2.6. Stage 6: Quality Assessment

This represents the stage where the methodological thoroughness and reliability of the included articles in the review are evaluated. The Critical Appraisal Skills Programme (CASP) checklist tool was used to assess key factors, including study design, data collection methods, and statistical analysis. Studies were evaluated for potential biases, such as selection bias, performance bias, or reporting bias, and the robustness of the findings was considered based on the clarity and duplicability of the results. This process ensured that only studies with adequate scientific quality and methodological accuracy contributed to the review’s findings and conclusions.

2.7. Stage 7: Findings and Documentation

At this stage, the findings from the selected studies are presented in a clear and structured format. Firstly, key data from each study, such as energy recovery mechanisms, vehicle efficiency, storage technologies, control, and integration strategies, were summarized, categorized, and tabulated. The findings were then documented in a uniform manner, ensuring results, discussion, and conclusions were accurately represented. The documentation also included a section for future research.

3. Results

3.1. Selection of Studies

The results of the selection process, conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) procedure to ensure transparency and reproducibility, are presented in this section. Initially, a total of 210 articles were identified and selected through database searches, followed by the removal of 54 duplicates using the EndNote referencing tool. The remaining 156 articles were screened based on titles and abstracts to exclude irrelevant studies, resulting in a total of 27 articles being considered irrelevant.

Subsequently, 123 articles were assessed for eligibility, with a total of 27 articles excluded as they did not meet the predefined criteria. The remaining 96 articles include studies that provide original, high-quality data and reviews on energy recovery systems in BEVs and HPEVs. The entire process is documented in a PRISMA flow diagram depicted in Figure 2.

3.2. Main Findings

3.2.1. Broad Category of Electric Vehicles

The findings showed that EVs exist in several categories, each offering distinct technologies to enhance efficiency and reduce emissions. Generally, they are classified into four major categories, as depicted in Figure 3 [5,18,26,27,28]. The first category of EVs is the plug-in hybrid electric vehicles (PHEVs); this category of EVs combines both an ICE and an electric motor, allowing for electric-only driving over short distances, while using the engine for longer trips. They can be recharged through an external power source. The second category is the hybrid electric vehicles (HEVs); this category also integrates an ICE and an electric motor but does not require external charging. The charging is achieved via an RBS and the engine [26,27,28].

Battery electric vehicles are the third category of EVs; this category of EVs is fully electric and relies mainly on large battery packs to store energy that powers the electric motor, with no ICE involved. Lastly, HPEVs, also known as fuel cell electric vehicles, are the most recent category of EVs. This category of EVs utilizes hydrogen fuel cells to generate electricity, offering advantages such as fast refueling times and extended driving ranges [5,6,18].

According to [28], EVs are typically equipped with a powertrain that varies from one category to another. The powertrains of modern EVs offer a range of innovative technologies designed to improve efficiency and reduce emissions. Hence, the powertrain of EVs varies from one category to another. For instance, PHEVs combine a traditional ICE with an electric motor and thus allow the vehicle to run on either power source or both, providing flexibility and enhanced fuel efficiency [26,27,28].

In contrast, HEVs also integrate an ICE and an electric motor, but do not require external charging as they rely on an RBS and the ICE to recharge the battery, thus optimizing fuel usage without the need for plugging in. On the other hand, BEVs are entirely electric and are equipped with a powertrain designed to convert stored electrical energy from the battery into mechanical power to drive the vehicle. Meanwhile, HPEVs, when compared to BEVs as shown in

Table 4. Performance comparison of hydrogen-powered and battery electric vehicles.

Feature	Hydrogen-Powered Electric Vehicles (HPEVs)	Battery Electric Vehicles (BEVs)
Refueling Time	3 to 5 min	30 min to 12 h
Driving Range	500 to 800 km	250 to 500 km
Weight	Lighter (no heavy batteries)	Heavier (large battery packs)
Emissions	Zero (H2 + O2 → H2O)	Zero (but battery production has environmental impact)

Source: estimated based on the compiled literature and engineering judgement.

, employ a different approach by using hydrogen fuel cells to generate electricity, offering advantages such as rapid refueling times and long driving ranges [1,8,27,28,29]. As a result, the world’s attention is shifting towards the development of HPEVs.

The powertrain components of each category of EV, as reported in the literature, are presented in

Table 5. Powertrain components of different categories of electric vehicles.

S/N	Vehicle Type	Power Train Components
1	Plug-in Hybrid Electric Vehicles	Internal Combustion Engine, Fuel Tank, Battery, DC–DC Converter, Inverter, Power Controller, Electric Motor, Drive Train
2	Hybrid Electric Vehicles	Internal Combustion Engine, Fuel Tank, Battery, DC–DC Converter, Inverter, Power Controller, Electric Motor, Regeneration System, Drive Train
3	Battery Electric Vehicles	Battery, DC–DC Converter, Inverter, Power Controller, Electric Motor, Regeneration System, Drive Train
4	Hydrogen-Powered Vehicles	Fuel Cell Stack, Hydrogen Storage, Battery, Supercapacitors, DC–DC Converter, Inverter, Power Controller, Electric Motor, Regeneration System, Drive Train

. Studies indicate that an appropriate powertrain configuration could help improve the efficiency of any category of EV, and subsequently increase the driving range [5,18,30]. Studies also reported that each of the powertrain configurations of EVs differ from one category to the other; as such, it can be argued that the efficiency of the energy recovered in EVs varies from one category to the other [5,18,28]. As this review primarily focused on energy recovery and regeneration systems in HPEVs, it is therefore crucial to have a basic understanding of the types of power train configurations that have been used in the design of HPEVs.

3.2.2. Powertrain Configuration in Hydrogen-Powered Electric Vehicles

The diagrams in Figure 4 and Figure 5 illustrate the two types of powertrain configurations characteristic of the design of HPEVs. The powertrain can be either in series or parallel [26,31]. In most studies, the series configuration was considered; nevertheless, both configurations were reported to enhance fuel efficiency and reduce emissions, but the choice between parallel and series arrangements depends on the desired balance required among features such as power, efficiency, and complexity in the vehicle’s design [26,27,29]. Hence, when considering the deployment of HPEVs in developing economies, it is important to choose the appropriate powertrain configuration to maximize efficiency and improve driving range.

3.2.3. Energy Recovery in Electric Vehicles

Energy recovery in EVs involves capturing and reusing energy that would otherwise be lost during vehicle operation. When the vehicle decelerates, the electric motor switches role, acting as a generator to convert kinetic energy into electrical energy [12,13]. This recovered energy is stored in the vehicle’s battery, supercapacitor, or hydrogen fuel cell system, which can later be utilized to power the car. This process has proven highly effective in improving overall efficiency by reducing energy waste, helping to extend the vehicle’s range, and decreasing reliance on external hydrogen refueling, which is absent in most developing nations [10,12,20]. Several mechanisms have been designed to recover energy in different types of EVs, each with its own advantages, disadvantages, and complexities, as discussed in the next section.

3.2.4. Energy Recovery Mechanism

As reported in the studies of [10,18,20], energy recovery mechanisms refer to systems or technologies designed to capture and reuse energy that would otherwise be lost during a process, typically during vehicle operation. The authors in [5,20] further underscored the importance of these mechanism in improving efficiency by converting wasted energy into a usable form and consequently, contributing to reducing the consumption of hydrogen, as in the case of HPEVs.

Although limited studies have been conducted on energy recovery in HPEVs, it is essential to note that most HPEVs are equipped with either a battery storage system or a supercapacitor, or both, to store the recovered energy [5,18]. While the battery capacity is smaller compared to those found in full BEVs, many energy recovery systems used in BEVs can also be applied to HPEVs [5]. Therefore, this current review focused more on the literature incorporating different energy recovery in both BEVs and HPEVs.

Generally, the two most discussed energy recovery mechanisms in the literature are the RBS and RSS [5,18]. However, many studies have focused solely on the use of RBS in the design of EVs [14,16,17,31,32]. A few studies have also considered the use of RSSs, while very few studies have proposed the hybridization of the two approaches [33,34,35]. The performance comparison of RBSs and RSSs as found in the literature is depicted in Figure 6.

Other energy recovery mechanisms in EVs include regenerative fuel cells, flywheel energy storage, and various forms of energy harvesting, such as solar, wind, thermoelectric, piezoelectric, and radio frequency [5,18]. Nonetheless, since most of the studies have focused on the use of an RBS and RSS for energy recovery in BEVs and HPEVs, these two mechanisms are explored in detail in the subsequent sections.

• Regenerative Suspension System

A regenerative suspension system as defined by [36] is an innovative energy recovery method used in EVs that aims to harness the kinetic energy generated by the vehicle’s suspension system during motion [5,34,36] In RSSs, the suspension components, such as shock absorbers or dampers, are integrated with a mechanism that converts the vertical movement of the wheels (caused by road irregularities and bumps) into electrical energy, as depicted in Figure 7.

The total energy recovered through the RSS of an EV can be expressed using the principles of mechanical energy conversion, where the kinetic energy of the suspension components due to vertical movement is converted into electrical energy [5,37,38,39]. When the suspension system moves vertically due to road irregularities such as bumps and dips, among others, it absorbs mechanical energy. This mechanical energy is captured and converted into electrical energy using either a transducer, electromagnetic system, or hydraulic mechanism [5,39].

Hence, the energy recovered $E_{RSS}$ in RSSs is related to the mechanical work performed by the suspension system as it undergoes a vertical movement and can be expressed using Equation (1) [40].

$$E_{RSS}={\int }_{t_1}^{t_2}F\left(t\right).v\left(t\right)dt$$

(1)

where $F\left(t\right)$ is the force exerted by the suspension system as it compresses or rebounds; $v\left(t\right)$ is the velocity of the suspension components (shock absorbers) at time $t;$ $t_1$ and $t_2$ represent the time intervals during the movement of the suspension system.

The force $F\left(t\right)$ exerted by the suspension is related to the spring constant $c$ of the suspension and the displacement (deflection) $x\left(t\right)$ of the suspension components is given as follows:

$$F\left(t\right)=c.x\left(t\right)$$

(2)

Similarly, velocity can be associated with the rate of change in displacement, as given in Equation (3).

$$v\left(t\right)={\displaystyle \frac{dx\left(t\right)}{dt}}$$

(3)

Substituting Equations (2) and (3) into Equation (1), the total energy recovered over time intervals $t_1$ to $t_2$ as the suspension moves vertically is expressed as follows:

$$E_{RSS}={\int }_{t_1}^{t_2}c.x\left(t\right).{\displaystyle \frac{dx\left(t\right)}{dt}}dt$$

(4)

Practically, the energy recovered in an electric vehicle using the RSS is usually considered the efficiency of the generator/hydraulic systems and road irregularities. Thus, for periodic motions common in most practical EVs, the energy recovered is given as follows:

$$E_{RSS}=\epsilon .{\displaystyle \frac{1}{2}}c.A^2$$

(5)

Therefore, the total energy recovered by the RSS scheme is given as follows:

$$E_{RSS}=\epsilon .{\int }_{t_1}^{t_2}c.x\left(t\right).{\displaystyle \frac{dx\left(t\right)}{dt}}dt$$

(6)

The recovered energy in Equation (6) is then stored in the vehicle’s battery for later use, improving overall energy efficiency [37,38,40]. RSSs typically incorporate electromagnetic or hydraulic technology to capture the energy, which is then transformed into usable power, reducing the total dependence on hydrogen for HPEVs and subsequently enhancing the driving range energy [5,39]. It should, however, be noted from Equations (5) and (6) that the recovered energy in the RSS is influenced by four major factors as follows [5,38,39,40]:

• Suspension Displacement (Vertical Motion): The vertical displacement of the suspension components due to road irregularities plays a significant role in energy recovery. The larger the displacement (amplitude) of the suspension, the more mechanical energy available to be converted into electrical energy.
• Spring Constant (Stiffness of the Suspension): The spring constant $c$ determines the stiffness of the suspension system. It defines the amount of force required to compress the suspension by a given amount. A stiffer suspension (one with a higher spring constant) will resist vertical displacement more effectively than a softer suspension.
• Velocity of Suspension Movement: The speed at which the suspension components move (velocity) during compression or rebound directly impacts the amount of kinetic energy available for conversion into electrical energy. This velocity depends on factors like vehicle speed and road conditions.
• Efficiency of the Energy Conversion Mechanism: The different categories of RSSs also play a crucial role in determining how much mechanical energy (from the suspension) is successfully converted into electrical energy.

Several categories of RSSs exist in the literature; depending on the mode of operation, RSSs are categorized into three main categories: electromagnetic, hydraulic, and piezoelectric [5,40]. The performance comparison of the three categories in terms of efficiency, cost, amount of recovered energy, and maturity level, as found in most of the literature, is presented in

Table 6. Performance comparison of different types of regenerative suspension system.

Technology	Efficiency	Cost	Power Output	Maturity Level
Electromagnetic	High	High	Moderate–High	Developing
Hydraulic	Moderate	Medium	High	Some applications
Piezoelectric	Low	Low	Low	Experimental

Source: estimated based on the compiled literature and engineering judgement.

.

Moreover, depending on different degrees of control and energy recovery capability, the RSS is also categorized into active, semi-active, and passive systems. Passive RSSs are considered the simplest because the suspension components, such as dampers or shock absorbers, passively convert the energy generated from the vertical motion of the wheels into electrical energy using mechanical or electromagnetic piezoelectric [5,40]. This category of system has been reported to have minimal complexity and does not actively control the damping force but still recovers some energy. A semi-active RSS offers a higher level of control by adjusting the suspension’s damping properties in response to road conditions and driving behavior and therefore optimizing both ride comfort and energy recovery. This type of system typically utilizes actuators or variable damping mechanisms, which enable controlled energy harvesting while maintaining vehicle stability [5,18].

The most advanced among these categories of RSSs is the active system, which incorporates fully adjustable components that can independently control the suspension forces of each of the vehicle wheels. By actively controlling the suspension’s response to road conditions, this category of RSSs maximizes energy recovery, providing both superior ride quality and efficient energy capture. Blended RSSs can also adjust to varying driving conditions in real-time [5,18,40]. Each of these systems has been reported to progressively enhance the vehicle’s ability to recover energy and improve overall performance, with active systems offering the most significant potential for energy efficiency and ride comfort [5,38,39,40].

2.

Regenerative Braking System

The author in [18] defined an RBS as a groundbreaking technology that enhances energy efficiency in EVs by capturing and reusing the vehicle’s kinetic energy, which would typically be lost as heat in the conventional braking systems found in most ICE vehicles. The principle of operation of an RBS is such that upon the application of braking force by the driver, the electric motor switches to generator mode, converting the vehicle’s motion into electrical energy, as depicted in Figure 8 [5,12,18].

The recovered energy is then sent back to the battery or supercapacitor, helping to recharge it for future use [5]. By recovering energy during braking, the system not only boosts the vehicle’s overall range but also reduces wear on traditional braking components, thereby contributing to a more sustainable and cost-effective driving experience [5,12,18]. Mathematically, the energy recovered $E_{RBS}$ in a typical EV. An RBS is modeled using Equations (7)–(13) [12].

The vehicle kinetic energy is expressed as follows:

$$K.E={\displaystyle \frac{1}{2}}m\left(v_2^2-v_1^2\right)$$

(7)

where $m$ represents the mass of the vehicle, while $v_1$ and $v_2$ are the initial and final speeds of the vehicle.

Since the kinetic energy is converted into recovered electrical energy, Equation (7) can be rewritten as follows:

$$K.E=E_{RBS}$$

(8)

where $E_{RBS}$ represents the recovered energy and is given as follows:

$$E_{RBS}={\displaystyle \frac{IVt}{{\epsilon }_g}}$$

(9)

where $I$ is the output current; $V$ is the output voltage; and ${\epsilon }_g$ is the efficiency of the electric motor when acting as a generator.

Equating (7) and (9), the values of the voltage and current across the generator can be obtained as follows:

$${\displaystyle \frac{1}{2}}m\left(v_2^2-v_1^2\right)={\displaystyle \frac{IVt}{{\epsilon }_g}}$$

(10)

Provided the electric generator supplies a constant voltage, and considering the generated current depends on the rank of kinetic energy, Equation (10) can be reformulated as follows:

$${\sum }_{k=1}^n\left[{\displaystyle \frac{1}{2}}m\left(v_{2,k}^2-v_{1,k}^2\right)-V{\displaystyle \frac{I_k{∆t}_k}{{\epsilon }_{g,k}}}\right]=0$$

(11)

Considering different steps in the kinetic energy loss process for time intervals of $∆t$; for short time intervals, Equation (11) can be rewritten as follows:

$${\sum }_{k=1}^n\left[mv\left(v_{2,k}-v_{1,k}\right)-V{\displaystyle \frac{I_k{∆t}_k}{{\epsilon }_{g,k}}}\right]=0$$

(12)

Equation (12) is applicable in flat terrain where there are no significant changes in elevation, or where such changes are minimal. In this context, the variation in kinetic energy is primarily linked to a decrease in vehicle speed, either because of braking or when the accelerator pedal is released.

However, if the route is downhill, the variation in kinetic energy can be linked to changes in the elevation of the terrain; Equation (12) can be expressed in terms of the altitude z of the route.

$${\sum }_{k=1}^n\left[mg\left(z_{1,k}-z_{2,k}\right)-V{\displaystyle \frac{I_k{∆t}_k}{{\epsilon }_{g,k}}}\right]=0$$

(13)

It has been reported in many existing studies that the recovered energy in any EV using the RBS depends significantly on its speed and mass [13,17,32,41,42]. However, several other factors have been identified that must be considered when designing an efficient RBS for implementation in HPEVs for deployment in developing nations. Some of the most important factors identified in the recent literature include [5,12,13,18] the following:

• Vehicle Speed: Higher speeds generally result in more kinetic energy, but at certain speeds, the RBS may become less effective or inefficient. The efficiency of energy recovery tends to be higher at lower to moderate speeds, where braking occurs more frequently.
• Vehicle Weight: A heavier vehicle requires more energy to slow down, potentially increasing the amount of energy that can be recovered through the RBS. However, this also means more energy is required to overcome inertia and maintain motion.
• Driving Conditions: The terrain and driving style can impact energy recovery. For instance, driving on hilly terrain or in stop-and-go traffic allows for more frequent opportunities for the RBS. In contrast, constant high-speed driving on flat roads may offer fewer opportunities for energy recovery.
• Battery State of Charge (SoC): The level of charge in the vehicle’s battery impacts how much energy can be recovered. If the battery is near full charge, it may not be able to accept additional energy, reducing recovery efficiency.
• Brake Pedal Usage: The interaction of the driver with the brake pedal can also influence energy recovery. If the driver uses the brakes aggressively, more energy may be lost as heat rather than being recovered, whereas smooth braking tends to maximize energy regeneration.
• Motor and Controller Technology: The design and capabilities of the electric motor and the energy management system can greatly impact the efficiency of the regenerative braking process. Advanced systems may allow for better control and improved energy conversion.
• Temperature Conditions: Environmental temperature can also affect both battery performance and regenerative braking efficiency. Cold temperatures, for example, can reduce the battery’s ability to accept charge, limiting energy recovery, while hot temperatures can affect motor and braking system performance.
• Regenerative Braking Efficiency: The effectiveness of the RBS in converting kinetic energy into electrical energy plays a significant role. Factors like the braking force, motor efficiency, and the battery’s ability to accept charge can influence the amount of energy recovered.

The regenerative braking system is principally categorized into three main types: a series, parallel, and blended RBS. In a series RBS, the electric motor acts as the primary braking mechanism, converting kinetic energy into electrical energy before any mechanical braking is applied [18]. This system maximizes energy recovery but may require additional braking support at low speeds. In contrast, a parallel RBS allows both the regenerative and mechanical brakes to operate simultaneously, with the braking force divided between them based on system design and vehicle conditions. This ensures reliable braking even when regenerative capacity is limited, such as during a fully charged battery [5,18].

A blended RBS, as revealed in the study of [5], optimally integrates both methods using an advanced control strategy. It dynamically adjusts the proportion of regenerative and mechanical braking for seamless operation. This hybrid approach has been reported to enhance braking stability, maximizes energy recovery, and ensures driver comfort by mitigating abrupt transitions between braking [5,13,16,18]. Generally, blended systems have been reported to offer the best balance of efficiency and safety, making them ideal for modern EVs such as HPEVs [13,16]. A general comparison of the three major categories of the RBS in terms of braking mechanism, efficiency of energy recovered, braking stability, scalability, and complexity as reported in the literature is presented in

Table 7. Feature comparison of different categories of the regenerative braking system.

Feature	Series RBS	Parallel RBS	Blended RBS
Braking mechanism	Regenerative only	Regenerative and mechanical (Parallel)	Dynamic switching between regenerative and mechanical
Energy recovery efficiency	High	Moderate	Optimized
Braking stability	Low	Moderate	High
Complexity	Simple control architecture	Moderately complex	Most complex
Suitability	Urban, low-speed conditions	High-speed, highway driving	All driving conditions

Note: Energy efficiency and braking stability depend on integration with power management and control systems; values are qualitative.

.

Another important category of the RBS reported in the literature is based on the type of technology used in the design of the system. Under this category, the RBS is categorized as an electromagnetic (battery)-based RBS, supercapacitor-based RBS, flywheel-based RBS, and hydraulic-based RBS [5,18]. The performance comparison of this category in terms of energy recovery efficiency, cost, power density, and maturity level are presented in

Table 8. (a) Performance comparison of recovery efficiency and technological maturity across different regenerative braking technologies. (b) Performance comparison of relative cost and power density across different regenerative braking technologies.

(a)
Technology	Energy Recovery Efficiency	Maturity Level
Electromagnetic (Battery)	60–70%	Mature
Supercapacitor-Based	85–95%	Developing
Flywheel-Based	70–80%	Experimental
Hydraulic-Based	50–60%	Some Applications
(b)
Technology	Energy Recovery Efficiency	Maturity Level
Electromagnetic (Battery)	High	Medium
Supercapacitor-Based	High	High
Flywheel-Based	Medium	High
Hydraulic-Based	Medium	Low

Note: efficiency and cost values are indicative ranges based on the literature synthesis.

a,b.

To further illustrate how different factors affect the performance of energy recovery in an RBS and RSS, a conceptual meta-regression model depicted in Figure 9 is developed using synthesized data derived from the literature [13,15,16,17,32,33,34,35,38,39,40]. From the diagram in Figure 9, the recovery efficiency of an RBS increases with vehicle speed. It decreases as the battery approaches full charge, reflecting the constraints of both the controller and the battery [15,16,17,32,39]. On the other hand, RSS performance is positively correlated with suspension displacement and velocity, indicating its greater suitability for rough or uneven road profiles [33,34,35,38,40]. These insights reinforce the importance of context-specific optimization when integrating energy recovery systems into HPEVs.

3.2.5. Storage Solutions in Electric Vehicles

Energy storage plays a crucial role in maximizing the benefits of energy recovered in EVs [5,18]. As reported in several studies, the efficiency of any energy recovery mechanism depends on the storage system’s ability to capture, store, and release energy when needed quickly [2,4,7,9]. This section provides brief findings on the major energy storage technologies used in EVs, highlighting their advantages, limitations, and potential future improvements. Storage technologies are designed to efficiently store and release energy when needed, ensuring that the energy captured during the energy recovery process is effectively utilized [2,4,5,7,9,18]. The performance comparison in terms of energy density, power density, efficiency, response time, lifespan, and cost of the most popular storage technologies in BEVs and HPEVs, as reported in the literature, is presented in

Table 9. Performance comparison of popular storage technologies for electric vehicle applications.

Storage Type	Energy Density	Power Density	Efficiency	Response Time	Lifespan	Cost
Lithium-Ion Battery	High	Medium	85–95%	Slow	8–15 years	High
Supercapacitor	Low	Very High	90–98%	Fast	15–20 years	Medium
Flywheel	Medium	High	85–95%	Very Fast	10–20 years	High
Hydraulic Accumulator	Low	High	70–85%	Fast	10–15 years	Low

Source: estimated based on the compiled literature and engineering judgement.

, followed by a brief description of each storage technology.

• Battery Storage System

Among the various storage technologies in EVs, lithium-ion batteries dominate due to their superior energy density, ranging from 150 to 250 Wh/kg, high charge/discharge efficiency, and a life cycle of 1000 to 5000 cycles [5,18,43]. The electrochemical composition of a lithium-ion battery primarily consists of lithium cobalt oxide, lithium iron phosphate, or nickel manganese cobalt cathodes, paired with graphite or silicon anodes. Recent advances in silicon-dominant anodes have reportedly pushed energy densities beyond 300 $\mathrm{W}\mathrm{h}/\mathrm{k}\mathrm{g}$, subsequently leading to high efficiency and a more extended range in EVs [2,4,7,9,44].

Similarly, advancements in solid-state batteries are reshaping the landscape of many EV power sources. Solid-state batteries are reported to the liquid electrolyte in Li-ion cells with a solid electrolyte, offering higher energy density (400 $\mathrm{W}\mathrm{h}/\mathrm{k}\mathrm{g})$ and have improved safety and a longer lifespan. Nonetheless, challenges include high production costs, electrolyte stability, and scalability [2,4,5,7,9,18].

The findings also revealed that the battery size in BEVs is significantly larger than that of HPEVs due to the differing energy storage and power delivery mechanisms. BEVs rely solely on battery packs, often ranging from 40 $\mathrm{k}\mathrm{W}\mathrm{h}$ to over 100 $\mathrm{k}\mathrm{W}\mathrm{h}$, to power the drivetrain, whereas HPEVs use smaller battery packs (typically 1–10 $\mathrm{k}\mathrm{W}\mathrm{h}$) as a buffer to support peak power demands and the RBS [5,18,45,46]. HPEVs primarily store energy in hydrogen fuel tanks and convert it into electricity using fuel cells, thereby reducing reliance on ample battery storage but requiring additional space for hydrogen storage and fuel cell stacks [5,43,44]. Consequently, while BEVs emphasize higher energy density battery solutions, it is essential to optimize power management in HPEVs through hybridization of fuel cells and small battery packs and/or supercapacitors.

2.

Supercapacitors

Supercapacitors have been widely studied for their role in energy recovery in both BEVs and HPEVs due to their high-power density and rapid charge–discharge capabilities. Several studies have indicated that supercapacitors can significantly enhance the energy recuperation process by efficiently capturing high-power surges during regenerative braking [13,16,47]. Unlike lithium-ion batteries, which have limited charge acceptance rates at high currents, supercapacitors can absorb and release energy almost instantaneously, making them ideal for transient power applications [5,18]. Studies have reported that integrating supercapacitors with conventional battery storage in EVs can improve energy efficiency by up to 15% to 25% while also reducing stress on battery cells, thereby extending their lifespan [5,18,32,47].

In HPEVs, supercapacitors have been reported as playing a crucial role in managing power fluctuations and peak energy demands [32,47]. Studies have also revealed that HPEVs equipped with hybrid energy storage systems, consisting of fuel cells, batteries, and supercapacitors, demonstrate improved fuel economy, efficiency, driving range, and dynamic response [5,18,32,47]. Hence, supercapacitors are capable of effectively bridging the gap between the slow response of fuel cells and the instantaneous power demands of acceleration and regenerative braking. The hybridization of fuel cells with supercapacitors can reduce hydrogen consumption by optimizing energy utilization, resulting in a more efficient and sustainable vehicle design [5,18].

3.

Flywheel

Flywheels have also been explored as a viable solution for enhancing energy recovery, particularly in BEVs, due to their ability to store kinetic energy with high efficiency [5]. The literature findings suggest that flywheels offer rapid energy absorption and release, making them particularly effective in RBSs [18,20,45,48,49]. Unlike batteries, which rely on electrochemical storage, flywheels store energy mechanically in a rotating mass, reducing issues related to charge degradation and cycle life [5,50]. Studies have also reported that flywheel-integrated energy recovery systems can improve energy efficiency by 20% to 30%, particularly in heavy-duty and high-performance vehicle applications [5,18,45,49,50].

For HPEVs, flywheel energy storage offers an effective means of managing transient power demands and reducing reliance on hydrogen fuel during peak load conditions [5,18,45,48,49]. Research has indicated that integrating flywheels with fuel cell systems can enhance vehicle performance by stabilizing power fluctuations and improving the overall efficiency of hydrogen utilization [5,48,49]. Furthermore, the combination of flywheels with other energy storage technologies, such as batteries and supercapacitors, has been reported to optimize energy distribution and extend the lifespan of fuel cell stacks [5,18]. These advancements underscore the potential of the flywheel in improving the sustainability and operational efficiency of HPEVs in developed and developing nations.

4.

Hydraulic Accumulator

Hydraulic accumulator energy storage systems have been investigated as an effective means of energy recovery in both BEVs and HPEVs, particularly for applications requiring high power bursts and efficiency in the RBS [5,51]. The literature suggests that hydraulic accumulators, which store energy in the form of pressurized fluid, offer superior power density compared to batteries and can rapidly absorb and release energy with minimal losses. Studies have also reported that integrating hydraulic accumulators in EVs can enhance braking energy recovery efficiency by up to 25% to 35%, particularly in heavy-duty applications such as buses and industrial vehicles [45,51].

In HPEVs, hydraulic accumulators have demonstrated potential for complementing fuel cells by smoothing power fluctuations and providing additional energy during acceleration [51]. The literature findings indicate that hybrid energy storage configurations incorporating hydraulic accumulators can help reduce stress on both batteries and fuel cells. Consequently, this improves overall system efficiency and extends the lifetime of components. Additionally, advancements in lightweight materials and compact accumulator designs are making hydraulic energy storage systems increasingly viable for a wider range of vehicle applications [5,51].

5.

Compressed Air Energy Storage

Compressed air energy storage (CAES) has been investigated as an alternative method for energy recovery storage in BEVs and HPEVs due to its high-power density and sustainability [52,53]. The literature suggests that CAES systems are capable of efficiently capturing and storing excess energy by compressing air, which can later be expanded to generate mechanical or electrical power. Studies have also reported that integrating CAES with electric drivetrains enhances braking energy recovery by up to 30%, particularly in stop-and-go urban traffic conditions, making them suitable for vehicle deployment in developing nations [18,52,53].

In HPEVs, CAES has been explored to assist hydrogen fuel cells in handling peak power demands. The research indicates that hybrid CAES–fuel cell systems improve overall efficiency by smoothing power fluctuations and reducing fuel cell degradation. Furthermore, advancements in isothermal and adiabatic compression techniques have been identified as key factors in increasing CAES efficiency and making it a viable energy storage solution for sustainable transportation [52,53].

6.

Magnetic Energy Storage

Magnetic energy storage, particularly superconducting magnetic energy storage (SMES), has been explored for its potential in energy recovery applications in BEVs and HPEVs [54]. SMES systems store energy in the magnetic field created by the flow of direct current in a superconducting coil, offering rapid charge and discharge capabilities with minimal energy loss. The literature findings indicate that SMES can enhance the RBS efficiency by quickly absorbing and delivering high-power surges, thereby reducing energy wastage and improving vehicle performance [5,18,54].

For HPEVs, SMES plays a crucial role in stabilizing power fluctuations and improving transient response. The research highlights that hybridizing SMES with fuel cells can lead to increased energy efficiency, reduced fuel consumption, and improved system reliability [54]. Studies have also suggested that advancements in high-temperature superconductors and cryogenic cooling technologies are key to making SMES a viable solution for automotive applications, addressing challenges such as cost and operational complexity [5,54].

7.

Hybrid Energy Storage Systems (HESSs)

Hybrid energy storage systems, which combine different energy storage technologies such as batteries, supercapacitors, and flywheels, have been extensively studied for their benefits in BEVs and HPEVs [55]. The literature findings indicate that HESSs can significantly enhance energy recovery efficiency by optimizing power distribution and reducing the stress on individual storage components. Studies reported that HESSs can improve RBS efficiency by up to 30% by allowing for fast energy capture and controlled energy release, thus maximizing overall system performance [5,18,55].

Hybrid energy storage systems have been reported to play a crucial role in balancing power fluctuations and enhancing overall energy efficiency in EVs. Research has highlighted that integrating supercapacitors or flywheels with fuel cells can enhance the transient response and reduce hydrogen consumption in HPEVs, leading to improved vehicle efficiency and sustainability. Additionally, advancements in power management algorithms and energy control strategies are essential in optimizing HESS performance for both BEVs and HPEVs [5,55].

Moreover, integrating intelligent energy management systems with supercapacitor-battery hybrid storage has been reported to enhance the effectiveness of the RBS, particularly in urban driving cycles with frequent stop-and-go conditions [5,18,55,56]. These findings emphasize that a well-designed control strategy and power management optimization technique are critical for improving the RBS performance, extending battery lifespan, and ensuring seamless braking transitions, ultimately leading to a more energy-efficient and sustainable vehicle system.

The findings have also shown that without an optimized control mechanism, the energy recovered in any category of EV can be inconsistent. This can lead to inefficient power distribution and excessive reliance on mechanical braking, which typically results in increased wear and tear and a reduction in the vehicle’s lifespan [18,56]. The next section highlights the various categories of control strategies used to improve the efficiency of energy recovery in EVs, utilizing either an RBS or RSS.

3.2.6. Control Strategies in Energy Recovery Systems

As reported in the study of [21], control strategies are crucial in energy recovery systems for effectively managing the conversion of mechanical energy into electrical energy while ensuring vehicle safety and performance. Effective control strategies are fundamental to optimizing the performance and efficiency of the powertrains of HPEVs, particularly in configurations involving multiple energy sources such as fuel cells, batteries, and supercapacitors [42,47,57].

In an RBS, the control system must enable real-time adjustments to braking torque distribution between regenerative and friction brakes, optimizing energy recovery while maintaining vehicle safety. The literature has also highlighted the need for strategies to account for factors such as battery state-of-charge (SOC), road conditions, and driver behavior to dynamically adjust the braking force and prevent regenerative braking saturation [42,57].

Similarly, in RSSs, the control strategy must accurately sense and filter road-induced vibrations and vehicle dynamic responses in real-time; it must also modulate the suspension’s damping and stiffness characteristics accordingly to maintain ride comfort and vehicle dynamics while harvesting energy from road-induced vibrations [33,58,59]. Moreover, studies have also reported that control strategies need to incorporate predictive and adaptive algorithms that can anticipate changes in road conditions and adjust the energy recovery process without compromising safety [42,57,59].

The need for these strategies arises from the inherent trade-offs between maximizing energy recovery and maintaining dynamic stability and comfort, particularly in the presence of system nonlinearities, uncertainties, and varying driving conditions both in developed and developing countries [42,57]. A range of control strategies has been explored in the literature to address these challenges. A broad view of the hierarchical structure of control strategies for regeneration systems (RBSs or RSSs) in BEVs and HPEVs, as reported in the literature, is illustrated in

Table 10. Hierarchical structure of control strategies for regeneration systems in electric vehicles.

Level 1	Level 2	Level 3	Level 4
Regenerative Braking System	Braking Force Distribution	Front–Rear Torque Distribution
		Mechanical vs. Electrical Braking Balance
	Control Algorithms	Rule-Based Control
		Fuzzy Logic Control
		Model Predictive Control
		Sliding Mode Control
	Energy Recovery Optimization	Maximum Energy Recovery Strategy
		Battery State of Charge (SOC) Management
		Battery Thermal Management
	Safety and Stability	Anti-lock Braking System (ABS) Integration
		Traction Control System (TCS) Integration
		Vehicle Stability Control (VSC)
Regenerative Suspension System	Energy Harvesting Mechanisms	Linear Electromagnetic Dampers
		Rotary Electromagnetic Dampers
		Hydraulic-Pneumatic Systems
	Control Strategies	Passive Control
		Semi-Active Control
		Active Control
	Energy Management	Power–Electronics Interface
		Energy Storage Integration	Supercapacitors
			Batteries
	Ride Comfort and Handling	Vibration Damping Control
		Road Profile Adaptation
		Vehicle Dynamics Optimization
Integrated Control Strategies	Coordinated Braking and Suspension	Unified Energy Management
		Holistic Vehicle Dynamics Control
	Adaptive Strategies	Real-Time Road Condition Adaptation
		Driver Behavior Adaptation

Source: compiled based on the reviewed literature.

.

Techniques such as the linear quadratic regulator, model predictive control (MPC), and adaptive or fuzzy logic controllers (FLCs) have been applied to both RBSs and RSSs [60,61]. The use of MPC in predicting future vehicle states and optimizing control actions over a horizon is well-documented in several studies, while sliding mode control offers robustness against system uncertainties [39,62]. Recent studies have also demonstrated that FLC can be an effective tool for optimizing control strategies in both single and dual wheel configurations in EVs [32,56,57].

For single-wheel applications, FLCs have been reported as handling the inherent non-linearities and uncertainties present in vehicle dynamics, particularly under varying road conditions and friction coefficients [56,63]. By employing linguistic rules that encapsulate expert knowledge, FLCs dynamically adjust parameters such as braking force or motor torque to optimize energy recovery and improve traction. This adaptive behavior has been found to not only enhance energy recuperation efficiency during regenerative braking but also contribute to improved ride stability and safety in real-world driving scenarios [32,56,57].

In dual wheel configurations, FLC offers the added advantage of coordinating control actions between the wheels to achieve balanced performance [32]. Research findings have indicated that when FLC is applied to dual-wheel systems, it can effectively manage the distribution of forces, thereby reducing wheel slip and enhancing overall regenerative efficiency [32,56,57,61]. The controller’s ability to seamlessly integrate feedback from both wheels enables real-time adjustments that better account for differences in road contact and load distribution [32,61]. While these benefits contribute to improved energy efficiency and vehicle stability, challenges such as increased computational complexity and the fine-tuning of fuzzy membership functions for diverse driving conditions remain areas for further investigation.

Nevertheless, several studies have also reported the significant benefits of various control strategies for regeneration systems in EVs, which include extended vehicle range and improved integration of energy recovery functions into the overall vehicle dynamics [32,56,57,61]. However, challenges persist in terms of controller complexity, real-time computational demands, and the need to finely balance energy recovery with safety and vehicle performance [64,65].

Table 11. Comparison of different control strategies for the regenerative braking system.

Control Method	Efficiency	Computational Complexity	Adaptability	Implementation Cost
Rule-Based Control (RBC)	Medium	Low	Low	Low
Fuzzy Logic Control (FLC)	High	Medium	Medium	Medium
Model Predictive Control (MPC)	Very High	High	High	High
AI-Based Control	Very High	Very High	Very High	High

Source: estimated based on the compiled literature and engineering judgement.

presents a performance comparison of the most common control strategies in terms of efficiency, computational complexity, adaptability, and cost, as found in the literature.

3.2.7. Power Management Optimization Techniques in BEVs and HPEVs

The findings have also revealed that efficient power management is crucial to maximizing the performance, efficiency, and longevity of EVs. Different researchers have developed various optimization techniques to ensure optimal energy utilization, reduce energy losses, and enhance driving range [1,3,4,5,66,67,68,69,70]. These techniques are broadly categorized into several categories, including rule-based, model-based, artificial intelligence (AI)-based methods, among others, as illustrated in Figure 10. A brief description of some of these techniques is subsequently presented.

• Rule-Based Power Management Strategies

The rule-based power management strategy has been widely employed in various studies. It operates using a set of heuristic or deterministic control rules that govern the power distribution among the fuel cell, battery, and supercapacitor within HPEVs’ powertrains [5,67]. These rules are typically formulated based on expert knowledge and system thresholds such as state of charge, load demand, and offline simulations. Although they are computationally light and suitable for real-time control, rule-based strategies lack adaptability and optimization capability under dynamic and uncertain driving conditions, often resulting in sub-optimal fuel cell utilization and increased degradation of energy storage components [3,5,69,70].

2.

Artificial Intelligence-Based Optimization

Artificial intelligence-based optimization techniques, such as neural networks, reinforcement learning, and fuzzy inference systems, have also been employed as powerful tools for power management in the powertrains of HPEVs. They can improve energy recovery efficiency and enhance vehicle driving range [20,70,71]. These methods enable the system to learn optimal power distribution strategies through data-driven modeling and adaptive control, even under highly nonlinear and uncertain driving conditions. Unlike rule-based or fixed-logic approaches, AI-based optimization can continuously improve its performance over time, offering superior adaptability, real-time decision-making, and enhanced energy efficiency [5,20]. However, findings have revealed that challenges such as computational complexity, training data requirements, and real-time feasibility need to be carefully addressed for practical deployment [5,70,71].

3.

Model-Based Optimization Techniques

Model-based optimization techniques, also known as predictive control methods, were reported to rely mainly on mathematical models of the powertrain in HPEVs to determine the optimal power split among the fuel cell, battery, and supercapacitor [5,72,73]. These techniques typically involve the formulation of an objective function such as minimizing hydrogen consumption or maximizing system efficiency subject to dynamic and operational constraints [1,4,66,73]. Methods like dynamic programming (DP), MPC, and Pontryagin’s minimum principle fall under this category. While it was argued in most of the literature that model-based approaches can yield globally or near-globally optimal solutions, they often require accurate system modeling and may involve high computational overhead, limiting their real-time applicability in embedded vehicle systems [1,5,73].

4.

Fuzzy Logic Controller

A fuzzy logic controller offers a robust and flexible framework for power management in HPEV powertrains by mimicking human decision-making through linguistic rules and fuzzy inference [61,74]. It effectively handles system uncertainties and non-linearities without requiring precise mathematical models. Several studies have reported that FLC can regulate the power flow among various energy sources in HPEVs, based on input variables such as state of charge, load demand, and acceleration [41,57,60,61,65]. Its rule-based structure enables real-time implementation; however, the design of membership functions and rule sets requires expert knowledge, and performance may degrade if not properly tuned or adapted to varying driving profiles [57,60,61].

5.

Hybrid Power Management Strategies

A novel technique common in different optimization problems is to hybridize two or more strategies such that the merits of one can compensate for the flaws of the other and vice versa. Hybrid power management is also peculiar in the design of HPEVs; this strategy combines multiple control techniques, such as rule-based methods, fuzzy logic, and optimization algorithms, to leverage the strengths of each approach for managing the power split in HPEV powertrains [3,5,75,76,77].

The findings have also revealed that the primary objective of this strategy is to strike a balance between computational efficiency and optimal performance by selecting the most suitable technique based on the current system state or operating conditions [3,5,55,75,77,78]. For example, FLC may be used for real-time adjustments, while optimization algorithms such as particle swarm optimization (PSO) or DP have been employed for global performance enhancement. Hybrid strategies have also been reported in several studies to improve energy efficiency and system robustness but may introduce increased complexity and computational demands in real-time applications [3,5,25,27,79,80].

4. Discussion

This section discusses the key research gaps in the existing literature on energy recovery and regeneration systems in HPEVs, particularly for deployment in developing nations. It highlights the challenges faced by these systems in terms of efficiency, integration, and scalability in regions with little or no infrastructure. It provides a cost/benefit ratio analysis for the implementation of HPEVs in developing nations, with an emphasis on developing cost-effective and practical solutions tailored to the unique needs of these nations.

4.1. Energy Recovery Approach

Regenerative braking systems are widely implemented by authors in most BEVs and HPEVs to capture kinetic energy during deceleration. Authors have highlighted the suitability of the approach to enhance vehicle efficiency by reducing hydrogen fuel consumption and improving driving range. Passenger BEVs form most of the RBS studies, while electric buses and driverless vehicles utilize RBSs combined with advanced speed planning and brake blending to optimize energy capture in urban stop-and-go cycles. Energy recovery rates reported vary between 10% and 35% of the vehicle’s kinetic energy during braking phases.

This is mostly applicable to developing countries, where the hydrogen refueling infrastructure is still in its early stages. RBSs can lower operational costs by minimizing the frequency of refueling. Similarly, since access to low-cost renewable hydrogen production is often limited in these regions, improving energy efficiency directly translates into lower emissions and a reduced environmental footprint. Additionally, it reduces brake wear, resulting in lower maintenance expenses, a crucial factor for cost-sensitive markets. Nevertheless, RBSs primarily benefit vehicles operating in urban environments with frequent stop-and-go conditions, making their effectiveness dependent on driving patterns.

However, in developing countries, where road infrastructure is often in poor condition, RSSs could present a unique solution by capitalizing on the uneven terrain to recover additional energy. The reported energy harvested typically ranges from 5 W to 15 W per suspension unit. Piezoelectric and electromagnetic harvesters recover about 10% to 20% of the energy dissipated in suspension systems. Hydraulic interconnected suspensions were also reported to show potential for higher energy recovery due to the ability to integrate energy regeneration and ride comfort, with reports indicating recovery rates up to 12% to 18% of suspension damping energy.

Reports have also indicated the suitability of RSSs for passenger cars and buses, with an emphasis on energy harvesting without compromising ride quality. This makes it particularly beneficial for commercial vehicles, public transportation, and off-road applications where frequent suspension movement is common. Unlike RBSs, which primarily function during braking events, RSSs have been reported as operating continuously, offering a more consistent energy recovery approach. Nevertheless, the contribution to overall energy savings is very low when compared to RBSs. Also, the technology is still in its early adoption phase, with higher initial costs potentially limiting widespread implementation in developing economies with limited resources.

Most of the reviewed literature has argued that both RBSs and RSSs contribute to sustainability by reducing overall energy losses and optimizing hydrogen fuel usage, as highlighted in the key insights drawn from the various studies in the literature presented in

Table 12. (a) Key insights from the reviewed papers on RBSs. (b) Key insights from the reviewed papers on RSSs.

(a)
Regeneration Systems	Authors	Core Feature Pinpointed
Regenerative Braking System	[12,13,14,15,16,17,19,31,32,39,41,42,46,47,52,57,60,61,63,64,65,66,71,72,73,74,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122]	Converts kinetic energy to electrical energy during braking via an electric motor acting as a generator. Improves vehicle efficiency by reducing energy loss during braking; reduces brake wear; and extends the vehicle’s range. Integrates directly with the vehicle’s powertrain and braking systems. It can be easily managed with existing EV control units. Highly compatible with existing EV technology and infrastructure, as an RBS is standard in most modern electric vehicles. Energy recovery rate depends on the frequency and intensity of braking, typically recovering up to 10-20% of energy during braking. Typically recovers energy during deceleration or braking events, with recovery efficiency depending on braking force. Relatively simple; integrates with the existing braking system of EVs. Well-suited to developing countries due to simplicity, lower cost, and ease of implementation.
(b)
Regeneration Systems	Authors	Core Feature Pinpointed
Regenerative Suspension System	[33,34,35,36,37,38,40,58,59,62,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137]	Converts vertical suspension motion into electrical energy. Enhances ride quality and comfort by reducing the impact of road shocks, while recovering additional energy, especially on rough terrain. Requires integration with advanced suspension control systems, which may increase system complexity. Less compatible with existing EV technology and infrastructure and requires specialized knowledge and maintenance capabilities. Can recover energy from continuous suspension movement, potentially recovering more energy in areas with rough terrain or frequent undulations. Recovers energy continuously, capturing energy from road-induced shocks and vibrations, resulting in higher potential overall recovery. More complex, requiring advanced suspension components for energy harvesting. Less suitable due to higher cost, complexity, and potential difficulty in servicing.

a,b. However, RBSs were reported to have a more immediate and measurable impact on vehicle efficiency due to its higher energy recovery potential. Also, they can lower fuel consumption, extend vehicle driving range, and reduce hydrogen demand (a critical factor for developing nations struggling with hydrogen production costs and infrastructure challenges).

Conversely, an RSS offers long-term benefits by improving ride quality, reducing mechanical stress on suspension components, and providing a secondary energy source. Although the cost-efficiency of RSSs may currently be limited due to higher technological investment, advancements in low-cost materials and mass production could enhance their viability for developing markets in the future.

Although RBSs are the more mature and economically viable solution for improving hydrogen vehicle efficiency in developed countries, RSSs present an emerging opportunity, particularly in regions with poor road infrastructure. A summary of energy recovery performance in both RBSs and RSSs is presented in

Table 13. Summary of energy recovery performance between RBSs and RSSs.

System Type	Recovery Efficiency (%)	Road Surface Variability	Comments
Regenerative Braking System (RBS)	12% to 35%	Urban stop–go driving	Higher recovery under frequent braking
Regenerative Suspension System (RSS)	5% to 10%	Rough or uneven roads	Performance depends on damping technology

Note: summary of recovery efficiency estimates are based on a synthesis of the compiled literature.

. While performance varies across test conditions and system design, RBSs generally show higher gains in urban driving, whereas RSSs perform better in rough terrains.

It is worth mentioning that while RBSs have been widely studied in isolation, and RSSs are emerging in the recent literature, few studies have analyzed their combined potential within HPEVs. It would be interesting to see how the adoption of hybrid systems, as proposed in Figure 11, can further improve energy recovery efficiency, range, fuel economy, and infrastructure requirements, while enhancing sustainability and cost-effectiveness in HPEVs for deployment in developing countries.

4.2. Energy Storage

Most of the reviewed literature on EVs, specifically focusing on HPEVs, have extensively utilized lithium-ion batteries as the energy storage component. This extensive utilization can be attributed to their high energy and power density, fast transient response, long cycle life, and commercial maturity, as reported in Table 9. Although the battery found in the powertrain of HPEVs is reported to be smaller in size as compared to BEVs, it provides an effective means of managing the variable power demands of automotive applications, especially when paired with PEMFCs. The ability of the battery to absorb energy during regenerative braking and supply rapid bursts of power during acceleration can help reduce the dynamic burden on the PEMFC, subsequently improving the overall efficiency of the vehicle powertrain.

Nonetheless, the widespread application of lithium-ion batteries in the literature is not without its limitations. Although they have been reported to have the best energy-to-weight ratio and perform better under dynamic load conditions, they suffer from high initial costs, especially in regions where raw materials are not locally sourced. In addition, the need to optimize their usage to adapt to different climatic conditions in most developing countries remains a challenge, with safety risks associated with overheating or thermal runaway.

Many authors also recommend HESSs that incorporate supercapacitors alongside lithium-ion batteries and fuel cells. This configuration has been reported to permit more refined energy management, where the supercapacitor handles short-term power fluctuations, the battery manages mid-range energy needs, and the fuel cell supplies the base load. This makes it possible to reduce stress on the battery and fuel cell, thereby extending the operational lifespan.

However, for developing nations, the adoption of lithium-ion batteries may not always be feasible due to cost and infrastructure limitations. A more viable alternative is to use a lithium iron phosphate battery, which offers a favorable balance of safety, thermal stability, lifecycle, and affordability. Lithium iron phosphate has been reported to be less prone to thermal runaway, has a lower environmental impact, and is better suited to hot climatic regions. Its cost-effectiveness and robustness make it a strong candidate for sustainable deployment in developing economies.

The integration of lithium iron phosphate batteries into the powertrain of HPEVs, particularly when hybridized with a supercapacitor and optimized using an AI-based energy management scheme, could offer numerous advantages for developing nations considering the deployment of HPEVs. These benefits, including improved safety, reduced lifecycle costs, enhanced vehicle performance under varying load conditions, and increased system resilience, can be compared with those of lithium-ion batteries to gain a better understanding of how different configurations align with the deployment of HPEVs in developing countries.

4.3. Control Strategies

According to most of the reviewed literature, the rule-based control strategy is the most widely employed. This strategy is based on the use of predefined thresholds or lookup tables to determine the power contribution from each energy source, taking into account real-time energy demand, battery state of charge, and vehicle operating conditions. The strategy has been reported to be less complex, easy to implement, and has low computational demand. These benefits can be attributed to their transparency and predictability, making them suitable for real-time control without the need for intensive computation or advanced modeling. In addition, rule-based strategies were also reported to be hardware-friendly, making them ideal for early-stage prototyping of HPEVs for deployment in developing regions with limited access to high-performance control units.

Nevertheless, authors have identified a lack of adaptability and optimization capabilities under varying driving conditions as one of the issues with the rule-based approach, which may result in a reduction in overall efficiency. Authors have also reported the inability of the rule-based approach to learn or evolve with the system’s performance history and to exploit the full potential of hybrid configurations, especially in highly dynamic environments such as urban driving cycles. Furthermore, the extensive tuning time may result in suboptimal fuel economy and energy utilization, particularly in complex energy management scenarios.

As a result, recent studies have shifted toward intelligent and optimization-based control strategies, such as FLC, MPC, and AI-based methods. Among these strategies, FLC has been extensively adopted due to its ability to handle uncertainty and nonlinearities in system dynamics, as well as its capacity to mimic human reasoning in making control decisions. FLC and PI controllers are widely used for smooth RBS transitions, improving energy recovery by 3% to 5% compared to conventional methods. On the other hand, semi-active and active RSSs using FLC or model-based strategies exhibit improved energy regeneration and ride comfort. Additionally, FLC was reported to be very effective for real-time power-split operations in hybrid powertrains recommended for HPEVs in developing countries.

Moreover, AI-based techniques, including metaheuristic optimization algorithms, like PSO, firefly algorithm (FA), and genetic algorithm (GA), are gaining attention for their potential in developing adaptive and learning-based control systems. These algorithms have demonstrated immense potential in optimizing control parameters based on real-time objectives such as fuel economy, battery health, or emission reduction, offering superior performance over static control rules.

Optimal blending methods were also reported as achieving significant braking energy maximization with safety guarantees. Authors have reported that the adoption of advanced energy management techniques can help improve the energy efficiency, fuel economy, and component durability of HPEVs for dynamic energy allocation that responds to real-time operational conditions, resulting in smoother energy delivery, reduced hydrogen consumption, and extended battery lifespan. Real-time dynamic programming and pulse width modulation strategies have also been reported to effectively balance regenerative braking and friction braking, thereby improving efficiency.

Therefore, in developing nations, where computational resources may be limited, a hybrid control approach combining FLC and AI algorithms such as PSO, FA, or simplified GA variants could be implemented to analyze how the approach can be customized to local driving conditions and infrastructure limitations.

4.4. Cost-to-Benefit Ratio Analysis

The economic viability of HPEVs in developing nations is a critical factor influencing their widespread adoption. A comprehensive cost/benefit ratio analysis, as detailed in

Table 14. Cost-to-benefit ratio analysis of HPEVs in developing nations.

Considered Factors	Challenges (Current Scenario)	Potential Benefits with Improved Energy Recovery
Initial Vehicle Cost	High manufacturing costs due to expensive fuel cells and components.	Lower production costs with optimized fuel cell technology and hybrid energy storage (flywheels, supercapacitors).
Fuel Cost and Consumption	Hydrogen fuel is expensive due to production, storage, and distribution constraints.	Improved regenerative braking, suspension, and waste heat recovery reduce fuel consumption, lowering refueling frequency.
Infrastructure Readiness	Limited hydrogen refueling stations and high setup costs.	More efficient vehicles require less frequent refueling, making HPVs viable even with limited infrastructure.
Maintenance and Component Wear	High cost of replacing fuel cell stacks and brake systems due to wear.	Regenerative braking reduces brake wear; enhanced cooling systems extend fuel cell lifespan.
Operational Efficiency	Energy losses from braking, road vibrations, and waste heat reduce efficiency.	Energy recovery systems capture and reuse lost energy, increasing driving range and reducing running costs.
Long-Term Cost Savings	High total cost of ownership due to fuel and maintenance expenses.	Lower running costs over time through fuel efficiency, reduced component replacement, and fewer breakdowns.
Adoption Feasibility	Cost barriers make HPVs less attractive compared to ICEs and hybrid vehicles.	Improved cost/benefit ratio encourages adoption by fleet operators and public transport services.

Source: estimated based on the compiled literature.

, is presented in this section. It highlights the relationship between current cost-related challenges and the potential advantages arising from advanced energy recovery systems. Several studies have reported on the high capital expenditure associated with HPEVs when compared to conventional ICE vehicles or even hybrid EVs. This is primarily attributed to the high cost of PEMFCs, hydrogen storage systems, and associated power electronics. However, it would be interesting to see how advances in scalable manufacturing techniques, material cost reductions, and the integration of hybridized energy storage could reduce the initial costs of HPEVs.

Although many studies also reported on the economic burden of hydrogen fuel, which is compounded by its limited availability and the energy-intensive nature of current production methods, such as steam methane reforming and electrolysis. However, various energy recovery and regeneration systems, such as RBSs and RSSs, among others, could help improve energy efficiency, significantly reduce costs, driving range, and overall hydrogen consumption. These systems have been reported to enable partial recuperation of kinetic, mechanical, and thermal energy, and could help limit refueling frequency and improve cost-effectiveness over the vehicle’s operational life.

Furthermore, the underdevelopment of hydrogen refueling infrastructure in most developing economies remains a major barrier for the deployment of HPEVs. The high capital investment required for establishing hydrogen stations is difficult to justify without substantial vehicle penetration. However, vehicles incorporating advanced energy recovery and regeneration systems have been reported to demonstrate extended driving ranges, thereby reducing hydrogen consumption per kilometer, and improved energy economy metrics.

Ongoing discussions have shown that HPEVs struggle to compete economically with ICE and hybrid vehicles, particularly in cost-sensitive developing markets. Nonetheless, improvements in energy efficiency, fuel economy, and component reliability have the potential to significantly enhance the cost/benefit ratio. This may speed up adoption among early users such as public transport operators, municipal fleets, and logistics providers, who prioritize long-term sustainability and operational efficiency.

To further enhance the cost/benefit ratio, funding strategies could play a crucial role in the deployment of HPEVs in developing countries. Developing nations can leverage various financing mechanisms to support the high initial costs associated with hydrogen vehicle development and infrastructure. Government incentives and subsidies can help lower the entry cost for HPEVs and refueling infrastructure. Additionally, there is a need for public–private partnerships to facilitate shared investment risks and responsibilities, ensuring the sustainability of the hydrogen mobility ecosystem.

Although the initial capital costs of HPEVs and the supporting infrastructure remain high, the long-term socio-economic, environmental, and energy security benefits offer compelling reasons for investment. By adopting a phased deployment model, as illustrated in Figure 12, and supported by strategic funding mechanisms, developing nations can overcome financial barriers and pave the way for cleaner, more sustainable transportation systems. Ultimately, the integration of hydrogen mobility with local renewable energy resources and public–private collaborations will also be key in realizing the full potential of HPEVs’ deployment in developing economies.

4.5. Real-World Deployment Potential in Developing Nations

The deployment of energy recovery systems in developing nations requires careful adaptation to local realities, as summarized in

Table 15. Analysis of regenerative system deployment in developing nations.

Factor	Strength $\mathbf{or} \mathbf{Weakness} (\times$)	Comments
Road Quality	For RSS	Poor roads increase energy harvest
Vehicle Electrification	$\times$	Many fleets still fossil-based
Policy Support	$\times$	Lacking or inconsistent
Maintenance Skills	$\times$	Requires technical training
Deployment Cost	$\times$	High upfront costs, low-income levels

Note: Based on the authors’ synthesis of contextual challenges and opportunities for deploying regenerative systems in low- and middle-income countries.

. Unlike developed countries, where the BEV and HPEV infrastructure is relatively mature, regions such as Sub-Saharan Africa and Southeast Asia face both unique constraints and promising opportunities. In Kenya, a recent review [138] highlighted the expansion of electric mobility initiatives in Kisumu, including the use of electric motorcycles (boda-bodas) and the deployment of solar-powered charging hubs. These developments support the practical application of RBSs/RSSs in HPEVs for deployment in stop-and-go urban transport settings.

In India, PMI Electro Mobility has launched hydrogen mobility pilots, with hydrogen fuel cell bus trials conducted in high-density urban environments [139]. These projects have revealed both the technical feasibility of RBSs in HPEVs and contextual challenges, including high ambient temperatures and policy coordination gaps. In Nigeria, assessments by the World Bank indicate that poor road infrastructure remains a persistent barrier to fuel efficiency, particularly in cities such as Lagos and Ibadan [140]. However, this condition also presents an opportunity for deploying RSSs, particularly in commercial minibuses operating on unpaved or degraded road surfaces.

Recent progress in South Africa further illustrates the regional potential of hydrogen mobility. A pilot fleet of BMW iX5 HPEVs was launched in Midrand, Johannesburg, through a collaboration between BMW Group South Africa, Anglo American Platinum, and Sasol. Simultaneously, the Hydrogen South Africa (HySA) consortium continues to support research and demonstration projects under the national Hydrogen Valley initiative. These efforts reflect a growing ecosystem for hydrogen-powered mobility across strategic transport corridors [141,142].

Collectively, these examples highlight the need for tailored deployment strategies that take into account road quality, vehicle type, fuel availability, and local maintenance capacity. Incorporating such regional factors is essential for realizing the performance and sustainability benefits of energy recovery and regeneration systems in real-world HPEV applications

4.6. Policy and Socio-Economic Considerations for Deployment of HPEVs in Developing Nations

Beyond technical feasibility, the widespread adoption of RBSs and RSSs in HPEVs can be influenced by policy frameworks, economic constraints, and social readiness, factors that are especially pronounced in developing countries. Financial barriers remain significant; components such as magnetorheological dampers in RSSs and advanced power electronics for RBSs can substantially increase vehicle costs. Without targeted financial instruments, these costs may render HPEVs inaccessible to key user sectors [138,142]. Hence, government interventions such as tax incentives, import duty exemptions, or public fleet procurement policies could play a vital role in accelerating deployment.

From a socio-technical standpoint, the diffusion of HPEV technologies is further challenged by limited public awareness and a shortage of skilled maintenance personnel. Structured public education campaigns and vocational training programs may be necessary to support system familiarity, user confidence, and long-term operational sustainability. Moreover, aligning national transportation and energy policies with hydrogen development strategies can help institutionalize these technologies within broader decarbonization and mobility goals. Lastly, integrated planning that links hydrogen production, energy recovery systems, and sustainable transport targets can create a more conducive environment for large-scale HPEV deployment in resource-constrained regions [142].

5. Conclusions

This study has presented a systematic review of the energy recovery and regeneration systems used in BEVs and HPEVs. It further highlights the critical role of these technologies in enhancing efficiency, reducing operating costs, and improving sustainability for the deployment of HPEVs in developing nations. The two key energy recovery mechanisms explored are RBSs and RSSs, each offering distinct benefits for improving fuel efficiency, driving range, and reducing energy wastage.

The control strategies and energy management optimization techniques which determine the power contribution of each energy source in the HPEV powertrain were also discussed. Additionally, the cost/benefit ratio analysis, real-world deployment potential, as well as policy and socio-economic considerations of HPEVs’ deployment in developing countries were also discussed and analyzed. This review emphasizes the importance of energy recovery and regeneration systems in enhancing the efficiency and driving range of HPEVs.

It pinpoints how RBSs, which convert kinetic energy into electrical power during deceleration, are well-suited for urban driving conditions, where frequent stops can maximize energy recovery, reduce hydrogen fuel consumption, and lower operating expenses. It also identifies how RSSs, which capture vibrational and oscillatory energy from rough terrains, are particularly suitable for developing regions with a poor road infrastructure, providing a continuous source of auxiliary power and extending the lifespan of fuel cells. This review further underscores the need for hybridization and cost-effective adaptations of these technologies to align with local infrastructure and economic conditions.

A hybrid energy storage solution, such as integrating supercapacitors/batteries with hydrogen fuel cells, to maximize the energy recovery efficiency of HPEVs’ powertrains and minimize reliance on expensive lithium-ion batteries, was also recommended. The use of a single control approach was identified as unsuitable for controlling the power contribution of the powertrain energy sources due to varying local driving conditions in developing countries. A hybrid control strategy was proposed to adapt the powertrain configurations of HPEVs to these driving conditions.

Additionally, a cost/benefit ratio analysis was conducted. However, it was observed that the initial cost of existing ICEs in developing nations is incomparable to that of HPEVs. The long-term socio-economic, environmental, and energy security benefits present reasons for optimism. It is also recommended that localized research and development initiatives, along with government incentives, be implemented to drive cost reductions and encourage the widespread adoption of HPEVs.

Overall, the findings contribute to the field of sustainable transportation by contextualizing RBS and RSS technologies within the unique constraints of developing nations; combined with supportive policies and infrastructure investments offering practical deployment insights and identifying pathways for scaling energy recovery in HPEVs in developing economies. While this study is focused on in-vehicle energy recovery technologies, it assumes hydrogen, ideally produced through renewable pathways, as the reference energy carrier. The question of hydrogen production and storage lies outside the technical scope of this review, but its relevance to broader sustainability debates is well acknowledged.

6. Future Research

Despite significant advancements in energy recovery and regeneration systems for HPEVs, several critical gaps remain in the current literature, necessitating further research to enhance the efficiency, affordability, and applicability in developing nations. Most existing studies have focused on energy recovery under ideal or urban driving conditions. In contrast, developing countries often have poor road infrastructure and high vehicle loads, which may impact the efficiency of these systems. Therefore, the following are recommended for future research.

6.1. Integration of a Hybrid System of RBSs and RSSs

Future studies should explore the integration of the proposed hybrid regenerative systems (RBSs and RSSs) within the powertrain configuration of HPEVs. Such integration has the potential to significantly enhance overall energy recovery efficiency and reduce hydrogen fuel consumption, particularly in developing countries where fuel cost sensitivity and infrastructure limitations demand maximized system efficiency.

6.2. Adaptive Control Strategies for Hybrid RBS–RSS Systems in Variable Terrain

Future research should prioritize the integration of control strategies for combined RBSs and RSSs, particularly under non-ideal or variable driving conditions such as unpaved roads, steep gradients, and mixed traffic patterns.

6.3. Integration of Hybrid Energy Storage Solutions

Hybrid energy storage solutions, such as the integration of supercapacitors and batteries with hydrogen fuel cells, should be investigated to determine optimal configurations that maximize energy efficiency while minimizing cost and weight constraints.

6.4. AI-Based Energy Management for Dynamic Recovery Optimization

Future studies should explore AI-driven or adaptive energy management systems that can dynamically allocate recovery energy between storage components (such as battery vs. supercapacitor) depending on terrain and load.

6.5. Field Testing in Sub-Saharan African and Southeast Asian Cities

Real-world testing in developing countries under harsh environmental conditions and varying operational demands is necessary to validate theoretical models and assess the long-term reliability and scalability of energy recovery systems in terms of recovery efficiency, component durability, and maintenance requirements.

6.6. Lifecycle and Socio-Economic Impact Assessments for HPEV Recovery Systems

Beyond technical optimization, future studies should consider a cross-disciplinary approach to support the deployment of HPEVs in developing countries. Research focusing on lifecycle environmental assessment to quantify long-term emission reduction and the embedded carbon impact of RBS/RSS components is recommended.

Addressing these research gaps will be crucial for advancing hydrogen mobility solutions, ensuring sustainable, cost-effective, and efficient transportation systems in emerging economies.