Search Results (209)

The increasing depletion of fossil fuels and their environmental impact have led to the development of fuel cell hybrid electric vehicles. By combining fuel cells with batteries, these vehicles offer greater efficiency and zero emissions. However, their energy management remains a challenge requiring advanced strategies. This paper presents a comparative study of two developed energy management strategies: a deterministic rule-based approach and a fuzzy logic approach. The proposed system consists of a proton exchange membrane fuel cell (PEMFC) as the primary energy source and a lithium-ion battery as the secondary source. A comprehensive model of the hybrid powertrain is developed to evaluate energy distribution and system behaviour. The control system includes a model predictive control (MPC) method for fuel cell current regulation and a PI controller to maintain DC bus voltage stability. The proposed strategies are evaluated under standard driving cycles (UDDS and NEDC) using a simulation in MATLAB/Simulink. Key performance indicators such as fuel efficiency, hydrogen consumption, battery state-of-charge, and voltage stability are examined to assess the effectiveness of each approach. Simulation results demonstrate that the deterministic strategy offers a structured and computationally efficient solution, while the fuzzy logic approach provides greater adaptability to dynamic driving conditions, leading to improved overall energy efficiency. These findings highlight the critical role of advanced control strategies in improving FCHEV performance and offer valuable insights for future developments in hybrid-vehicle energy management. Full article

Inspired by the Toyota Mirai, this study presents a high-fidelity data-driven approach for modelling and simulation of a fuel cell hybrid electric powertrain. This study utilises technical assessment data sourced from Argonne National Laboratory’s publicly available report, faithfully modelling most of the vehicle subsystems as data-driven entities. The simulation framework is developed in the MATLAB/Simulink environment and is based on a power dynamics approach, capturing nonlinear interactions and performance intricacies between different powertrain elements. This study investigates subsystem synergies and performance boundaries under a combined driving cycle composed of the NEDC, WLTP Class 3 and US06 profiles, representing urban, extra-urban and aggressive highway conditions. To emulate the real-world load-following strategy, a state transition power management and allocation method is synthesised. The proposed method dynamically governs the power flow between the fuel cell stack and the traction battery across three operational states, allowing the battery to stay within its allocated bounds. This simulation framework offers a near-accurate and computationally efficient digital counterpart to a commercial hybrid powertrain, serving as a valuable tool for educational and research purposes. Full article

Driven by carbon neutrality and peak carbon policies, hydrogen energy, due to its zero-emission and renewable properties, is increasingly being used in hydrogen fuel cell vehicles (H-FCVs). However, the high cost and limited durability of H-FCVs hinder large-scale deployment. Hydrogen internal combustion engine hybrid electric vehicles (H-HEVs) are emerging as a viable alternative. Research on the techno-economics of H-HEVs remains limited, particularly in systematic comparisons with H-FCVs. This paper provides a comprehensive comparison of H-FCVs and H-HEVs in terms of total cost of ownership (TCO) and hydrogen consumption while proposing a multi-objective powertrain parameter optimization model. First, a quantitative model evaluates TCO from vehicle purchase to disposal. Second, a global dynamic programming method optimizes hydrogen consumption by incorporating cumulative energy costs into the TCO model. Finally, a genetic algorithm co-optimizes key design parameters to minimize TCO. Results show that with a battery capacity of 20.5 Ah and an H-FC peak power of 55 kW, H-FCV can achieve optimal fuel economy and hydrogen consumption. However, even with advanced technology, their TCO remains higher than that of H-HEVs. H-FCVs can only become cost-competitive if the unit power price of the fuel cell system is less than 4.6 times that of the hydrogen engine system, assuming negligible fuel cell degradation. In the short term, H-HEVs should be prioritized. Their adoption can also support the long-term development of H-FCVs through a complementary relationship. Full article

Due to climate change, the electric vehicle (EV) industry is rapidly growing and drawing researchers interest. Driving conditions like mountainous roads, slick surfaces, and rough terrains illuminate the vehicles inherent nonlinearities. Under such scenarios, the behavior of power sources (fuel cell, battery, and super-capacitor), power processing units (converters), and power consuming units (traction motors) deviates from nominal operation. The increasing demand for FCHEVs necessitates control systems capable of handling nonlinear dynamics, while ensuring robust, precise energy distribution among fuel cells, batteries, and super-capacitors. This paper presents a DSMC strategy enhanced with Robust Uniform Exact Differentiators for FCHEV energy management. To optimally tune DSMC parameters, reduce chattering, and address the limitations of conventional methods, a hybrid metaheuristic framework is proposed. This framework integrates moth flame optimization (MFO) with the gravitational search algorithm (GSA) and Fractal Heritage Evolution, implemented through three spiral-based variants: MFOGSAPSO-A (Archimedean), MFOGSAPSO-H (Hyperbolic), and MFOGSAPSO-L (Logarithmic). Control laws are optimized using the Integral of Time-weighted Absolute Error (ITAE) criterion. Among the variants, MFOGSAPSO-L shows the best overall performance with the lowest ITAE for the fuel cell (56.38), battery (57.48), super-capacitor (62.83), and DC bus voltage (4741.60). MFOGSAPSO-A offers the most accurate transient response with minimum RMSE and MAE FC (0.005712, 0.000602), battery (0.004879, 0.000488), SC (0.002145, 0.000623), DC voltage (0.232815, 0.058991), and speed (0.030990, 0.010998)—outperforming MFOGSAPSO, GSA, and PSO. MFOGSAPSO-L further reduces the ITAE for fuel cell tracking by up to 29% over GSA and improves control smoothness. PSO performs moderately but lags under transient conditions. Simulation results conducted under EUDC validate the effectiveness of the MFOGSAPSO-based DSMC framework, confirming its superior tracking, faster convergence, and stable voltage control under transients making it a robust and high-performance solution for FCHEV. Full article

This paper presents a methodology for systematically scaling vehicle powertrain and other models and an approach for using model parameters and scaling variables to perform controller design. The parameter scaling method allows for high degrees of scaling while maintaining the target performance metrics, such as vehicle speed tracking, with minimal changes to the model code by the researcher. A comparison of proportional-integral, Youla parameterization, ${\mathrm{\text{H}}}_{\infty }$, and hybrid Youla-${\mathrm{H}}_{\infty }$ controllers is provided, along with the respective methods for maintaining controller performance metrics across degrees of model scaling factors. The application of the scaling and various control design methods to an existing model of a hydrogen fuel cell and a battery electric vehicle powertrain allows for the development of a representative scale model to be compared with experimental data generated by an actual scale vehicle. The comparison between scaled simulation and experimental data will eventually be used to inform the expected performance of the full-size electric vehicle based on full-size simulation results. Full article

This study presents the design of a hybrid powerplant for unmanned aerial vehicles (UAVs), improving its autonomy compared to power systems based solely on batteries. The powerplant is designed for the Mugin EV-350 aircraft. Using experimental data from electric motors in a wind tunnel and fuel cells, a comparative analysis of different energy management strategies, such as fuzzy logic and passive, is conducted to reduce the operational and maintenance costs. A Python-based software program is developed and utilized for the real-time implementation and simulation of energy management strategies, with data collected in databases. This study integrates experimental data (wind tunnel and fuel cells) with real-time EMS strategies, and simulation-based predictions indicate practical improvements in endurance and cost reduction, as well as an increase in flight autonomy of 50%. Full article

In response to the global imperative to reduce greenhouse gas emissions and fossil fuel dependency, electric vehicles (EVs) have emerged as a sustainable transportation alternative, primarily utilizing lithium-ion batteries (LIBs) due to their high energy density and efficiency. However, LIBs are highly sensitive to temperature fluctuations, significantly affecting their performance, lifespan, and safety. One of the most critical threats to the safe operation of LIBs is thermal runaway (TR), an uncontrollable exothermic process that can lead to catastrophic failure under abusive conditions. Moreover, thermal runaway propagation (TRP) can rapidly spread failures across battery cells, intensifying safety threats. To address these challenges, developing advanced battery thermal management systems (BTMS) is essential to ensure optimal temperature control and suppress TR and TRP within LIB modules. This review systematically evaluates advanced cooling strategies, including indirect liquid cooling, water mist cooling, immersion cooling, phase change material (PCM) cooling, and hybrid cooling based on the latest studies published between 2020 and 2025. The review highlights their mechanisms, effectiveness, and practical considerations for preventing TR initiation and suppressing TRP in battery modules. Finally, key findings and future directions for designing next-generation BTMS are proposed, contributing valuable insights for enhancing the safety and reliability of LIB applications. Full article

Proton exchange membrane fuel cell (PEMFC) hybrid vehicles offer a long driving range but are heavily dependent on energy management strategies (EMS). Traditional EMS methods, such as rule-based approaches and optimization-based methods like model predictive control (MPC), either lack flexibility or are computationally complex and rely on prior driving experience. To overcome these limitations, this study proposes a semi-empirical approach that combines state machine (SM) and MPC in a novel hybrid EMS (SM-MPC) to optimize power distribution in a 100 kW PEMFC hybrid vehicle. The SM-MPC strategy uses SM to handle fast power fluctuations and MPC to manage slow variations, balancing real-time adaptability and efficiency. Simulation results based on the NEDC and HWFET driving cycles show that compared to the traditional MPC method, SM-MPC significantly reduces hydrogen consumption by 7.11 g (NEDC) and 1.89 g (HWFET). Additionally, the proposed method effectively maintains the state of charge (SOC) of the lithium-ion battery using a PID controller and ensures the PEMFC stack temperature remains within ±5.8 °C. Overall, the SM-MPC strategy improves energy efficiency, reduces fuel consumption, and enhances the stability of the hybrid power system, offering a promising solution for real-time energy optimization in fuel cell vehicles. Full article

Electric Vehicles (EV) significantly contribute to reducing carbon emissions and promoting sustainable transportation. Among EV technologies, hybrid energy storage systems (HESS), which combine fuel cells, power batteries, and supercapacitors, have been widely adopted to enhance energy density, power density, and system efficiency. Bidirectional DC-DC converters are pivotal in HESS, enabling efficient energy management, voltage matching, and bidirectional energy flow between storage devices and vehicle systems. This paper provides a comprehensive review of bidirectional DC-DC converter topologies for EV applications, which focuses on both non-isolated and isolated designs. Non-isolated topologies, such as Buck-Boost, Ćuk, and interleaved converters, are featured for their simplicity, efficiency, and compactness. Isolated topologies, such as dual active bridge (DAB) and push-pull converters, are featured for their high voltage gain and electrical isolation. An evaluation framework is proposed, incorporating key performance metrics such as voltage stress, current stress, power density, and switching frequency. The results highlight the strengths and limitations of various converter topologies, offering insights into their optimization for EV applications. Future research directions include integrating wide-bandgap devices, advanced control strategies, and novel topologies to address challenges such as wide voltage gain, high efficiency, and compact design. This work underscores the critical role of bidirectional DC-DC converters in advancing energy-efficient and sustainable EV technologies. Full article

Transitioning to clean energy in off-grid remote locations is essential to reducing fossil-fuel-generated greenhouse gas emissions and supporting renewable energy growth. While hybrid renewable energy systems (HRES), including multiple renewable energy (RE) sources and energy storage systems are instrumental, it requires technical reliability with economic efficiency. This study examines the feasibility of an HRES incorporating solar, wind, hydrogen, and biofuel energy at a remote location in Australia. An electric vehicle charging load alongside a residential load is considered to lower transportation-based emissions. Additionally, the input data (load profile and solar data) is validated through statistical analysis, ensuring data reliability. HOMER Pro software is used to assess the techno-economic and environmental performance of the hybrid systems. Results indicate that the optimal HRES comprising of photovoltaic, wind turbines, fuel cell, battery, and biodiesel generators provides a net present cost of AUD 9.46 million and a cost of energy of AUD 0.183, outperforming diesel generator-inclusive systems. Hydrogen energy-based FC offered the major backup supply, indicating the potential role of hydrogen energy in maintaining reliability in off-grid hybrid systems. Sensitivity analysis observes the effect of variations in biodiesel price and electric load on the system performance. Environmentally, the proposed system is highly beneficial, offering zero carbon dioxide and sulfur dioxide emissions, contributing to the global net-zero target. The implications of this research highlight the necessity of a regional clean energy policy facilitating energy planning and implementation, skill development to nurture technology-intensive energy projects, and active community engagement for a smooth energy transition. Potentially, the research outcome advances the understanding of HRES feasibility for remote locations and offers a practical roadmap for sustainable energy solutions. Full article

Battery longevity and hydrogen consumption efficiency are primary optimization goals for EMS in high-performance fuel cell hybrid electric vehicles (FCHEVs). This article provides an overview of an FCHEV powertrain and a hierarchical control scheme that includes low-level controllers for key components. Finally, a higher-level control architecture for power management combines a fuzzy logic controller with an H-infinity controller to ensure reliable power management. The aim is to enhance EMS performance and overall robustness to uncertainties by implementing the higher-level control architecture. The effectiveness of the proposed strategy is demonstrated through simulations in the MATLAB/SIMULINK 2024a environment. Full article

Unmanned aerial vehicles, known today as drones, in the beginning, were small-dimension research models powered by small electric motors fed from electrical batteries. The propulsion system for these drones had to be adapted to the specific applications along their development. Electric and hybrid-electric propulsion drones represent a rapidly developing field in the aerospace industry. Electric drones are those with purely electric propulsion fed from batteries, while hybrid-electric ones have a hybrid propulsion system combining a thermal engine and an electric motor. Another class of hybrid-electric drones includes those with an electric propulsion system fed from fuel cells and batteries. This paper proposes the configuration of an electric propulsion system with a hybrid power source for a transport drone, as well as an analysis of the special electrical components onboard an electric drone, such as batteries, fuel cells, and electric motors. In the final part of the paper, this propulsion system is modeled and analyzed in Matlab/Simulink version 2021a. Design software and simulation tools specifically developed for hybrid-electric drones are essential for ensuring the accuracy and efficiency of these processes. Electric drones have the advantage of zero emissions, but at present, the batteries are still too heavy for aviation applications. By using hydrogen fuel cells as the main power source, it is possible to considerably reduce the power source weight. This is an important advantage of the system proposed in this work. Using hydrogen fuel cells in aircraft and drone propulsion is an important trend in the scientific world. This technology seems to be mature enough to be implemented in aviation. From a technical point of view, these kinds of systems are already feasible. Their usefulness and reliability have to be proven in time. Full article

As global initiatives to reduce greenhouse gas emissions and combat climate change expand, electric vehicles (EVs) powered by fuel cells and lithium-ion batteries are gaining global recognition as solutions for sustainable transportation due to their high energy conversion efficiency. Considering the driving range limitations of battery electric vehicles (BEVs) and the low efficiency of internal combustion engines (ICEs), fuel cell hybrid vehicles offer a compelling alternative for long-distance, low-emission driving with less refuelling time. To facilitate their wider scale adoption, it is essential to understand their energy performance through models that consider external weather effects, driving styles, road gradients, and their simultaneous interaction. This paper presents a microlevel, multicriteria assessment framework to investigate the performance of BEVs, fuel cell electric vehicles (FCEVs), and hybrid electric vehicles (HEVs), with a focus on energy consumption, drive systems, and emissions. Simulation models were developed using MATLAB 2021a Simulink environment, thus enabling the integration of standardized driving cycles with real-world wind and terrain variations. The results are presented for various trip scenarios, employing quantitative and qualitative analysis methods to identify the most efficient vehicle configuration, also validated through the simulation of three commercial EVs. Predictive modelling approaches are utilized to estimate a vehicle’s performance under unexplored conditions. Results indicate that trip conditions have a significant impact on the performance of all three vehicles, with HEVs emerging as the most efficient and balanced option, followed by FCEVs, making them strong candidates compared with BEVs for broader adoption in the transition toward sustainable transportation. Full article

Fuel economy and system durability are critical yet interdependent performance metrics for fuel cell hybrid vehicles (FCHVs). This paper devises an integrated framework for optimizing component sizing and energy management in a fuel cell/battery hybrid passenger vehicle. A unified cost function is proposed, combining fuel economy and system durability through a weighting coefficient, based on a comprehensive model of the hydrogen consumption and degradation characteristics of fuel cells and batteries. Utilizing the dynamic programming (DP) algorithm, the total cost is optimized to derive the optimal weighting factors and component sizing, effectively addressing the multi-objective optimization problem and balancing efficiency and durability. Furthermore, the impact of power prices on the optimal parameters is carefully examined. The simulation results indicate that a battery capacity of 44 Ah and a fuel cell maximum power of 80 kW represent the optimal sizing configuration. A weighting factor of 0.5 achieves the minimum equivalent total cost by effectively balancing fuel economy and system durability for the light-duty fuel cell passenger vehicle. Additionally, the battery price affects the weighting factor, indicating that future reductions in power source costs will shift focus away from system durability to fuel economy in FCHV optimization. These findings provide recommendations for FCHV manufacturers to advance the application of fuel cells in passenger vehicles. Full article

Electric vertical take-off and landing vehicles introduce challenges in powertrain design with short but high peak loads and low-load phases over longer periods of time during wing-borne flight. In this paper, three powertrain topologies are analyzed for a tilt-rotor urban air mobility vehicle with an expected entry into service after 2030. The powertrains are studied on the level of preliminary sizing for the design mission of the vehicle. The three powertrain topologies studied and compared are battery-only, fuel cell-only and a hybrid of the two energy sources. Parameter studies on the gearbox transmission ratio, the design point of the fuel cell system as well as the degree of hybridization were carried out. The combination of fuel cell and battery was found to be most beneficial in terms of mass when the fuel cell is sized for slightly more than cruise power. In flight phases with higher power requirements, the batteries would provide the additional boost. Full article