Search Results (227)

Dynamic wireless charging systems have emerged as a promising solution to extend the driving range of electric vehicles by enabling energy transfer while the vehicle is in motion. However, the segment-based charging lane structure introduces challenges such as pulsation of the output power and the need for precise switching control of the transmitting segments. This paper proposes a position-sensorless control method for managing transmitting lines in a dynamic wireless charging system. The proposed approach uses a segmented charging lane structure combined with two receiving coils and LCC compensation circuits on both the transmitting and receiving sides. Based on theoretical analysis, the study determines the optimal switching positions and signals to reduce the current fluctuation. To validate the proposed method, a dynamic wireless charging system prototype with a power rating of $3kW$ was designed, constructed, and tested in a laboratory environment. The results demonstrate that the proposed position-sensorless control method effectively mitigates power fluctuations and enhances the stability and efficiency of the wireless charging process. Full article

The transition to electric mobility has significantly increased the demand for lithium-ion batteries, raising concerns about their end-of-life management. Therefore, this study presents the design, development and first implementation steps of a stationary energy storage system utilizing second-life electric vehicle (EV) batteries. These batteries, no longer suitable for traction applications due to a reduced state of health (SoH) below 80%, retain sufficient capacity for less demanding stationary applications. The proposed system is designed to be flexible and scalable, serving both research and commercial purposes. Key challenges include heterogeneous battery characteristics, safety considerations due to increased internal resistance and battery aging, and the need for flexible power electronics. An optimized dual active bridge (DAB) converter topology is introduced to connect several batteries in parallel and to ensure efficient bidirectional power flow over a wide voltage range. A first prototype, rated at 50 $\mathrm{k}$$\mathrm{W}$, has been built and tested in the laboratory. This study contributes to sustainable energy storage solutions by extending battery life cycles, reducing waste, and promoting economic viability for industrial partners. Full article

Electric buses are key in the strategy towards a greenhouse-gas-neutral fleet. However, their restrictions in terms of range and refueling as well as their increased price point present new challenges for public transport companies. This study aims to address, based on real-world operational data, how energy consumption and charging behavior affect battery aging and how operational strategies can be optimized to extend battery life under realistic conditions. This article presents an energy consumption analysis with respect to ambient temperatures and average vehicle speed based exclusively on real-world data of an urban bus fleet, providing a data foundation for range forecasting and infrastructure planning optimized for public transport needs. Additionally, the State of Charge (SOC) window during operation and vehicle idle time as well as the charging power were analyzed in this case study to formulate recommendations towards a more battery-friendly treatment. The central research question is whether battery-friendly operational strategies—such as reduced charging power and lower SOC windows—can realistically be implemented in daily public transport operations. The impact of the recommendations on battery lifetime is estimated using a battery aging model on drive cycles. Finally, the reduction in CO₂ emissions compared to diesel buses is estimated. Full article

In air-conditioning compressors operating under ultra-low temperature conditions, both the rotational speed and load torque are at high levels, demanding pump motors that offer high efficiency and high power at high speeds. Electrically excited synchronous motors (EESMs) satisfy these operational requirements by leveraging their inherent wide-speed field-weakening capability and superior high-speed performance characteristics. Current research on EESM primarily targets electric vehicle applications, with a high-efficiency design focused on medium and low speeds. Excitation design under constant-power–speed extension remains insufficiently explored. To address it, this paper proposes an EESM design methodology optimized for high-speed efficiency and constant-power excitation control. Key EESM parameters are determined through a dynamic phasor diagram, and design methods for turn number, split ratio, and other parameters are proposed to extend the high-efficiency region into the high-speed range. Additionally, a power output modulation strategy in the field-weakening region is introduced, enabling dynamic high-power regulation at high speed through excitation adjustment. Compared to similarly sized PMSMs, the proposed EESM exhibits consistently superior efficiency beyond 10,000 rpm, delivering 19% and 49% higher power output at 12,000 rpm and 14,000 rpm, respectively, relative to conventional pump-drive PMSMs. Experimental validation via a prototype confirms excellent high-speed efficiency and sustained constant-power performance, in alignment with the design targets. Full article

Due to the limitations of current battery technologies—such as lower energy density and high cost compared to fossil fuels—electric vehicles (EVs) face constraints in applications requiring extended range or heavy payloads, such as refuse trucks. As a midterm solution, hybrid electric vehicles (HEVs) combine internal combustion engines (ICEs) and electric powertrains to enable flexible energy usage, particularly in urban duty cycles characterized by frequent stopping and idling. This study introduces a model-based energy management strategy using the Equivalent Consumption Minimization Strategy (ECMS), tailored for a retrofitted series hybrid refuse truck. A conventional ISUZU NPR 10 truck was instrumented to collect real-world driving and operational data, which guided the development of a vehicle-specific ECMS controller. The proposed strategy was evaluated over five driving cycles—including both standardized and measured urban scenarios—under varying load conditions: Tare Mass (TM) and Gross Vehicle Mass (GVM). Compared with a rule-based control approach, ECMS demonstrated up to 14% improvement in driving range and significant reductions in exhaust gas emissions (CO, NO_x, and CO₂). The inclusion of auxiliary load modeling further enhances the realism of the simulation results. These findings validate ECMS as a viable strategy for optimizing fuel economy and reducing emissions in hybrid refuse truck applications. Full article

Since 1 January 2024, newly produced heavy-duty trailers are subject to the assessment of their performance regarding CO₂ and fuel consumption according to Implementing Regulation (EU) 2022/1362. The method is based on the already established approach for the CO₂ and energy consumption evaluation of trucks and buses, i.e., applying a combination of component testing and vehicle simulation using the software VECTO (Vehicle Energy Consumption calculation TOol). For the evaluation of trailers, generic conventional towing vehicles in combination with the specific CO₂ and fuel consumption-relevant properties of the trailer, such as mass, aerodynamics, rolling resistance etc., are simulated in the “VECTO Trailer” software. The corresponding results are used in the European HDV CO₂ standards with which manufacturers must comply to avoid penalty payments (2030: −10% for semitrailers and −7.5% for trailers compared with the baseline year 2025). Methodology and legislation are currently being extended to also cover the effects of electrified trailers (trailers with an electrified axle and/or electrically supplied auxiliaries) on CO₂, electrical energy consumption, and electric range extension (special use case in combination with a battery-electric towing vehicle). This publication gives an overview of the developed regulatory framework and methods to be implemented in a future extension of VECTO Trailer as well as a comparison of different e-trailer configurations and usage scenarios regarding their impact on CO₂, energy consumption, and electric range by applying the developed methods in a preliminary potential analysis. Results from this analysis indicate that e-trailers that use small batteries (5–50 kWh) to power electric refrigeration units achieve a CO₂ reduction of 5–10%, depending primarily on battery capacity. In contrast, e-trailers designed for propulsion support with larger batteries (50–500 kWh) and e-axle(s) (50–500 kW) demonstrate a reduction potential of up to 40%, largely determined by battery capacity and e-axle rating. Despite their reduction potential, market acceptance of e-trailers remains uncertain as the higher number of trailers compared with towing vehicles could lead to slow adoption, especially of the more expensive configurations. Full article

Lithium batteries have become one of the best choices for current consumer electric vehicle batteries due to their good stability and high energy density. To ensure the safety and reliability of electric vehicles (EVs), the battery management system (BMS) must provide accurate and real-time information on the usage status of the onboard battery. This article highlights the precise estimation of the state of charge (SOC) applied to four models of lithium-ion batteries (Turnigy, LG, SAMSUNG, and PANASONIC) for electric vehicles in order to ensure optimal use of the battery and extend its lifespan, which is frequently influenced by certain parameters such as temperature, current, number of charge and discharge cycles, and so on. Because of the work’s novelty, the methodological approach combines the extended Kalman filter algorithm (EKF) with the noise matrix, which is updated in this case through an iterative process. This leads to the migration to a new adaptive extended Kalman filter algorithm (AEKF) in the MATLAB Simulink 2022.b environment, which is novel or original in the sense that it has a first-order association. The four models of batteries from various manufacturers were directly subjected to the Venin estimator, which allowed for direct comparison of the models under a variety of temperature scenarios while keeping an eye on performance metrics. The results obtained were mapped charging status (SOC) versus open circuit voltage (OCV), and the high-performance primitives collection (HPPC) tests were carried out at 40 °C, 25 °C, 10 °C, 0 °C and −10 °C. At these temperatures, their corresponding values for the root mean square error (RMSE) of (SOC) for the Turnigy graphene battery model were found to be: 1.944, 9.6237, 1.253, 1.6963, 16.9715, and for (OCV): 1.3154, 4.895, 4.149, 4.1808, and 17.2167, respectively. The tests cover the SOC range, from 100% to 5% with four different charge and discharge currents at rates of 1, 2, 5 and 10 A. After characterization, the battery was subjected to urban dynamometer driving program (UDDS), Energy Saving Test (HWFET) driving cycles, LA92 (Dynamometric Test), US06 (aggressive driving), as well as combinations of these cycles. Driving cycles were sampled every 0.1 s, and other tests were sampled at a slower or variable frequency, thus verifying the reliability and robustness of the estimator to 97%. Full article

Although the transition to electric vehicles (EVs) is well underway and expected to continue in global car markets, most vehicles on the world’s roads will be powered by internal combustion engine vehicles (ICEVs) and fossil fuels for the foreseeable future, possibly well past 2050. Thus, good environmental performance and effective emission control of ICE vehicles will continue to be of paramount importance if the world is to achieve the stated air and climate pollution reduction goals. In this study, we review 228 publications and identify four main issues confronting these objectives: (1) cheating by vehicle manufacturers, (2) tampering by vehicle owners, (3) malfunctioning emission control systems, and (4) inadequate in-service emission programs. With progressively more stringent vehicle emission and fuel quality standards being implemented in all major markets, engine designs and emission control systems have become increasingly complex and sophisticated, creating opportunities for cheating and tampering. This is not a new phenomenon, with the first cases reported in the 1970s and continuing to happen today. Cheating appears not to be restricted to specific manufacturers or vehicle types. Suspicious real-world emissions behavior suggests that the use of defeat devices may be widespread. Defeat devices are primarily a concern with diesel vehicles, where emission control deactivation in real-world driving can lower manufacturing costs, improve fuel economy, reduce engine noise, improve vehicle performance, and extend refill intervals for diesel exhaust fluid, if present. Despite the financial penalties, undesired global attention, damage to brand reputation, a temporary drop in sales and stock value, and forced recalls, cheating may continue. Private vehicle owners resort to tampering to (1) improve performance and fuel efficiency; (2) avoid operating costs, including repairs; (3) increase the resale value of the vehicle (i.e., odometer tampering); or (4) simply to rebel against established norms. Tampering and cheating in the commercial freight sector also mean undercutting law-abiding operators, gaining unfair economic advantage, and posing excess harm to the environment and public health. At the individual vehicle level, the impacts of cheating, tampering, or malfunctioning emission control systems can be substantial. The removal or deactivation of emission control systems increases emissions—for instance, typically 70% (NO_x and EGR), a factor of 3 or more (NO_x and SCR), and a factor of 25–100 (PM and DPF). Our analysis shows significant uncertainty and (geographic) variability regarding the occurrence of cheating and tampering by vehicle owners. The available evidence suggests that fleet-wide impacts of cheating and tampering on emissions are undeniable, substantial, and cannot be ignored. The presence of a relatively small fraction of high-emitters, due to either cheating, tampering, or malfunctioning, causes excess pollution that must be tackled by environmental authorities around the world, in particular in emerging economies, where millions of used ICE vehicles from the US and EU end up. Modernized in-service emission programs designed to efficiently identify and fix large faults are needed to ensure that the benefits of modern vehicle technologies are not lost. Effective programs should address malfunctions, engine problems, incorrect repairs, a lack of servicing and maintenance, poorly retrofitted fuel and emission control systems, the use of improper or low-quality fuels and tampering. Periodic Test and Repair (PTR) is a common in-service program. We estimate that PTR generally reduces emissions by 11% (8–14%), 11% (7–15%), and 4% (−1–10%) for carbon monoxide (CO), hydrocarbons (HC), and oxides of nitrogen (NO_x), respectively. This is based on the grand mean effect and the associated 95% confidence interval. PTR effectiveness could be significantly higher, but we find that it critically depends on various design factors, including (1) comprehensive fleet coverage, (2) a suitable test procedure, (3) compliance and enforcement, (4) proper technician training, (5) quality control and quality assurance, (6) periodic program evaluation, and (7) minimization of waivers and exemptions. Now that both particulate matter (PM, i.e., DPF) and NO_x (i.e., SCR) emission controls are common in all modern new diesel vehicles, and commonly the focus of cheating and tampering, robust measurement approaches for assessing in-use emissions performance are urgently needed to modernize PTR programs. To increase (cost) effectiveness, a modern approach could include screening methods, such as remote sensing and plume chasing. We conclude this study with recommendations and suggestions for future improvements and research, listing a range of potential solutions for the issues identified in new and in-service vehicles. Full article

To address energy management challenges for intelligent connected automated range-extended electric vehicles under vehicle-road cooperative environments, a hierarchical energy management strategy (EMS) based on speed prediction is proposed from the perspective of multi-objective optimization (MOO), with comprehensive system performance being significantly enhanced. Focusing on connected car-following scenarios, acceleration sequence prediction is performed based on Kalman filtering and preceding vehicle acceleration. A dual-layer optimization strategy is subsequently developed: in the upper layer, optimal speed curves are planned based on road network topology and preceding vehicle trajectories, while in the lower layer, coordinated multi-power source allocation is achieved through EMS_MPC-P, a Bayesian-optimized model predictive EMS based on Pontryagin’ s minimum principle (PMP). A MOO model is ultimately formulated to enhance comprehensive system performance. Simulation and bench test results demonstrate that with SoC₀ = 0.4, 7.69% and 5.13% improvement in fuel economy is achieved by EMS_MPC-P compared to the charge depleting-charge sustaining (CD-CS) method and the charge depleting-blend (CD-Blend) method. Travel time reductions of 62.2% and 58.7% are observed versus CD-CS and CD-Blend. Battery lifespan degradation is mitigated by 16.18% and 5.89% relative to CD-CS and CD-Blend, demonstrating the method’s marked advantages in improving traffic efficiency, safety, battery life maintenance, and fuel economy. This study not only establishes a technical paradigm with theoretical depth and engineering applicability for EMS, but also quantitatively reveals intrinsic mechanisms underlying long-term prediction accuracy enhancement through data analysis, providing critical guidance for future vehicle–road–cloud collaborative system development. Full article

The thermal management system (TMS) of electric vehicles (EVs) plays a pivotal role in vehicle performance, driving range, battery lifespan, and passenger comfort. Precise control of compressor speed, informed by real-time sensor data, is essential for improving TMS efficiency and extending EV range. This study proposes a control strategy based on the PID Search Algorithm (PSA), ensuring optimal thermal management for an integrated battery and cabin TMS. A co-simulation platform combining AMESim and Simulink is developed for validation, utilizing various sensors to monitor system performance. Simulations are conducted under target temperatures of 20 °C and 25 °C to replicate various operating conditions. The optimized strategy is compared with the most commonly used PID controllers, fuzzy controllers, and PID fuzzy control strategies. The results demonstrate that the PSA-Optimized control strategy significantly outperforms the other three strategies. For a target of 25 °C, the PSA-Optimized control strategy shows a minimal temperature overshoot of 0.012 °C, with COP improvements of 0.06, 0.04, and 0.03 compared to the other three control strategies, respectively. For a target of 20 °C, the overshoot is further reduced to 0.010 °C, while the coefficient of performance (COP) increases by 0.14, 0.01, and 0.07 relative to the same benchmarks. Overall, the results indicate that the PSA-Optimized control strategy effectively utilizes sensor data to reduce cabin temperature overshoot, stabilize compressor speed fluctuations, slow the decay of the battery’s state of charge (SOC), and enhance the system’s COP. Full article

Due to global warming, ozone depletion and their ramifications on the Arctic and Antarctic snowscapes, there has been an incentivized drive towards net zero-carbon emission policies by several countries. These policies extend to several sectors, including several manufacturing and processing industries and transportation, which are a few of their notable stakeholders. In the transportation sector, this journey towards net zero-carbon emissions is aided by the adoption of battery electric vehicles (BEVs) due to their zero-carbon emissions during operation. However, they might have zero running emissions, but they do have emissions when charging through conventional sources. This research paper looks at the carbon emissions produced by both electric vehicles (EVs) and internal combustion engine (ICE) vehicles during their operational stages and compares them based on a 200,000 km driving range, battery manufacturing emissions and different power production alternatives to draw up some very important recommendations. The analysis presented in this paper helps in drawing conclusions and proposes ideas which, when included in transport policies, will help curb global warming and eventually lead to the sustainable development of the transport sector. The analysis in this study shows that the emissions needed to produce a single battery unit have increased by approximately 258.7% with the change in battery production locations. Furthermore, charging EVs with a fossil-fuel-dominated grid has shown an increase in emissions of 17.98% compared to the least emissive ICE car considered in the study. Finally, policy update recommendations which are essential for the sustainable development of the transport sector are discussed. Full article

While Battery Electric Vehicles (BEVs) offer environmental benefits by reducing carbon emissions during use, their range remains limited compared to conventionally fuelled vehicles. This paper focuses on identifying factors that directly influence BEV range and explores strategies to mitigate range anxiety among potential users. Specifically, it reviews the impact of battery cell characteristics and vehicle lightweighting. Using the WLTP Class 3B drive cycle, energy consumption and Depth of Discharge (DoD) were evaluated across various battery capacities. Multiple Lithium-Ion battery models were simulated to analyse discharge behaviour, while vehicle mass composition was examined to assess the effectiveness of lightweighting in extending driving range. A lower initial State of Charge (SoC) and a standard discharge rate were used to estimate the remaining range, highlighting an approximate gain of up to 6 km at lower DoD levels. This work aims to accurately demonstrate how battery technology and structural weight impact energy consumption and usable range in BEVs. Current modelling approaches often overlook the relationship between driver discomfort and battery performance metrics. The main contribution is to address the gap by integrating Li-ion discharge modelling with vehicle dynamics to estimate range and compare cell characteristics. The ultimate goal is to support cost-effective strategies for increasing BEV usability, aligning them more closely with conventional vehicle expectations and enhancing journey flexibility. Full article

Battery electric vehicles (BEVs) have emerged as a cornerstone of sustainable transportation systems, driving a fundamental transformation in public transport (PT) operations over the past decade. The unique characteristics of BEVs, including range limitations and battery degradation dynamics, necessitate a multi-dimensional optimization framework that simultaneously considers energy supply management, operational efficiency, and battery lifecycle optimization in transit scheduling and timetabling. This paper presents a systematic review of BEV timetabling and scheduling research, structured around three main contributions. First, it comprehensively examines the evolution of electric vehicle timetabling problems, providing a detailed comparative analysis of methodological approaches in this domain. Second, it identifies and critically evaluates key developments in electric vehicle scheduling, including extended research directions (such as the integration with crew scheduling) and their practical implications. Third, it investigates the integration of BEV scheduling and timetabling, synthesizing the strengths and limitations of current methodologies while outlining promising avenues for future research. By offering a comprehensive analysis of the advancements in battery electric public transport scheduling over the past decade, this review serves as both a technical reference and a strategic guide for researchers and practitioners in the field of sustainable transportation systems. Full article

The uncoordinated charging behaviors of electric vehicles (EVs) challenge the stable operation of the grid, e.g., increasing the peak-to-valley ratio of the grid and diminishing power supply reliability. A Monte Carlo sampling method is employed to develop a charging behavior model for EVs to solve the problems raised by random charge mode. The probability densities of daily driving distance, initial charging time, charging power, and charging duration are incorporated and analyzed. The proposed model enables multiple random sample values for EVs, considering varying weather conditions and time-of-use electricity prices. For charge and discharge optimization, an EV charge and discharge scheduling model is constructed, aiming to balance multiple objective functions, including battery degradation costs, user charging costs, grid load fluctuations, and peak-to-valley differences. The weighting method is applied to transform the multi-objective framework into a single-objective comprehensive solution, facilitating the identification of optimal charge and discharge strategies. Results demonstrate that the Monte Carlo sampling can satisfactorily generate datasets with realistic characteristics on the driving range and charging initiation time of the EVs. Furthermore, the load results achieved through multi-objective optimization demonstrate that the proposed strategy effectively mitigates peak-to-valley disparities. The peak load reduction and trough load increment are 27.6% and 160.1%, respectively. Through post-peak load balancing, the average costs of each EV for daily charging and battery degradation are reduced to be 7.58 yuan and 15.68 yuan, respectively. This approach can significantly enhance the grid stability, simultaneously address the economic interests of users, and extend battery lifespan. Full article

In response to escalating environmental concerns and the imperative for a transition to a more sustainable economy, the European Union enacted a new regulation on the electric battery market in July 2023. This regulation integrates the principles of the circular economy, as outlined in the European Green Deal, addressing all phases of the battery life cycle, including the mining of raw materials, product design, production processes, reuse, and recycling. In light of this development, the principal manufacturers of electric vehicles (EVs) and hybrid electric vehicles (HEVs) have undertaken various circular economy (CE) and life cycle (LC) strategies. Their objective is to align their operations with these new regulatory requirements and enhance their sustainability credentials. The global automotive industry, encompassing thousands of entities with an annual turnover exceeding USD 3 trillion, is a significant economic sector. Within this industry, it is estimated that more than 50 manufacturers are involved in the production of EVs, ranging from established automakers to emerging startups. This study applies content analysis to obtain qualitative and quantitative information from data disclosed by companies and organizations, with a specific focus on entities that currently feature EVs or HEVs. The methodology involves examining publicly available reports and corporate disclosures to assess industry trends and regulatory compliance. For this purpose, the analysis selected the 10 largest EV manufacturers in the world, based on sales reports provided by the manufacturers themselves and their respective market shares, as reported by automotive news portals and blogs. The evaluation of their actions was derived from the annual sustainability reports of these companies, with the aim of identifying the practices already implemented and their anticipated contributions to extending battery life and minimizing environmental impact. Full article