Battery Electric Vehicles Research Articles

To reduce emissions in the existing transportation system and lower carbon dioxide (CO2) output, battery electric vehicles (BEVs) offer a promising approach due to their higher energy efficiency. However, their driving range still falls short compared to conventional vehicles. Optimizing the heating, ventilation, and air conditioning (HVAC) system can help save energy and improve passenger comfort. This study investigates an advanced thermal management system for an electric truck cabin with heating panels and added insulation. A one-dimensional (1D) cabin thermal model was also developed and validated with experimental data. The model integrates insulation, heating panels, and a 1D comfort simulation. It is functional mock-up unit (FMU) compatible and connects to larger system simulations and real-time applications. The results show that energy consumption can be reduced by up to 50% with these thermal measures. In the future, further research and new approaches will be necessary to identify even more efficient subsystems and cost-effective solutions.

This paper presents an integrated approach to optimizing microgrid management and electric truck logistics for transportation research. The experiment involves a 100 kW solar photovoltaic system, a 500 kWh battery energy storage system, the electric demand of a commercial building, and a heavy-duty vehicle charging system. The study aims to demonstrate how synchronized optimization of a microgrid control algorithm and a truck route algorithm can reduce overall system costs. The microgrid management system is designed to meet the constraints and requirements of a commercial electric truck charging scheduler. This integrated approach is an improvement over previous systems as it uses the scheduler’s outputs—such as time frames and energy requirements—as constraints for microgrid management. The truck scheduling algorithm iteratively learned to optimize charging times, ensuring that charging occurs during low-cost periods or when renewable energy is available. The electric vehicle scheduler adjusted truck arrival times based on the availability of clean energy sources, creating a feedback loop that continuously improves cost efficiency. Results indicated significant cost savings, with electric utility costs for electric vehicle (EV) charging being only 0% to 20% of the original value while the transportation system is only 23% to 64%, compared with the baseline scenario without the co-optimization framework. These findings suggest that the proposed integrated approach can effectively reduce costs and improve the efficiency of microgrid and electric truck operations. Uncoordinated charging schedules leads to a higher power demand than a well-organized battery electric truck (BET) dispatching strategy. Optimizing truck charging times and energy needs based on microgrid conditions can significantly reduce electricity and transportation costs.

Electric Vehicles (EVs) are still facing prejudices about limited range, making them unattractive for many customers. However, their locally emission-free operation and the ability to recover kinetic energy during braking manoeuvres are significant advances against conventional drivetrains. Especially the function of one-pedal driving (OPD) can further reduce the energy consumption of EVs if properly realized and tuned. In this research, the optimisation and evaluation of an adaptive OPD strategy for a battery electric vehicle (BEV) with the aim of improving energy efficiency and driving comfort, which was previously introduced by the authors, is presented. Therefore, an adaptive pedal curve was designed first and extended through the integration of a fuzzy controller that considers the trade-off between efficient operation and driver intention based on vehicle speed and the drive pedal position signals. The strategy was extended by the incorporation of another input to represent the traffic area. The efficiency was evaluated in a proband study using virtual driving tests in a static simulator, in which different configurations were analysed and rated. It was found that the optimised strategy achieved the best overall result. Compared to pure regenerative braking as the benchmark, energy consumption as well as the amount of pedal changes were reduced by 8.45% as well as 62.27%, respectively, and the rate of energy recovery was increased by 67.8%.

The paper studies and analyzes electric vehicle engines powered by hydrogen under the WLTP standard driving protocol. The driving range extension is estimated using a specific protocol developed for FCEV compared with the standard value for battery electric vehicles. The driving range is extended by 10 km, averaging over the four protocols, with a maximum of 11.6 km for the FTP-75 and a minimum of 7.7 km for the WLTP. This driving range extension represents a 1.8% driving range improvement, on average. Applying the FCEV current weight, the driving range is extended to 18.9 km and 20.4 km, on average, when using power source energy capacity standards for BEVs and FCEVs.

The rise in motorcycle ownership in Indonesia has increased energy consumption and greenhouse gas emissions, challenging the country's net-zero target by 2060. To mitigate this, the government is promoting the adoption and conversion of two-wheeled Battery Electric Vehicles (BEVs), but implementation remains below target, implying behavioral factors as a major barrier. This study analyzes the determinants influencing consumer and potential consumer behavior in adopting two-wheeled BEVs in East Kalimantan, a strategic region supporting the Indonesian Capital City. Using the Field Theory framework, the model integrates the Theory of Planned Behavior (TPB), which represents personal factors (Attitude, Subjective Norm, Perceived Behavioral Control, and Intention), and the Electric Vehicle Ecosystem (EVE), which represents environmental factors (Performance, Infrastructure, Price, and Features). Data from 400 respondents were analyzed using SEM-PLS, which explained 65.8% of the variance in adoption intention. The results show that Subjective Norms, Perceived Behavioral Control, Performance, Price, and Features significantly influence intention, while Attitude and Infrastructure do not. These findings reveal that consumers view two-wheeled BEVs primarily as functional alternatives to conventional motorcycles, rather than as environmentally friendly innovations. The contributes of this study is that it extends behavioral research by integrating TPB and EVE into Field Theory, and, practically, it highlights the need for policies that combine economic incentives with behavioral interventions to accelerate BEV adoption in Indonesia.

Replacement of internal combustion engine vehicles with battery electric vehicles (EVs) is expected to impact air quality. Previous projections, often relying on emissions inventories of precursors with high uncertainties, have yielded results that vary by model parameters and assumptions. There remains little empirical investigation of the real-world effects, particularly for the low yet growing levels of electrification in the United States. Here county-level vehicle registrations and measurements from ground-level air monitors from 2018 through 2023 were used to investigate the impacts of EV penetration on annual and seasonal concentrations of criteria air pollutants in the United States. Fixed effects regression analysis revealed that rising EV penetration was associated with reductions in mean annual concentrations of nitrogen oxides (NOx as the sum of NO2 and NO), carbon monoxide (CO), and fine particulate matter (PM2.5) and in mean summer season concentrations of ozone (O3). By contrast, there was a potential increase in sulfur dioxide (SO2). The findings demonstrate empirical improvements in air quality associated with EV adoption yet highlight the risk of a continued reliance on fossil fuels. Strategic policies that support enhanced EV adoption must support commensurate expansion of renewable energy access in order to maximize the air quality benefits of the technology.

Opening the hood: a critical assessment of European renewable hydrogen trucking policies

With rising travel demand and the need to tackle both the air quality and climate change challenges caused by fossil fuel vehicles, there is an urgent need to transition to cleaner and more sustainable fuels. While lithium-ion battery electric vehicles (BEVs) produce no emissions during operation, they increase electricity consumption, affecting emissions from that activity. Furthermore, there is an ongoing debate about the overall cleanliness of lithium-ion batteries when assessing emissions throughout their lifecycle compared to fossil fuels. To address these concerns, we use the Global Change Analysis Model (GCAM) integrated assessment model (IAM) to evaluate criteria air pollutants and carbon dioxide (CO 2 ) emissions across four scenarios of increasing BEV adoption in the United States (US). We include emissions from fuel and battery production, vehicle manufacturing, and operation for both BEV and fossil-based internal combustion engine (ICE) vehicles. Results indicate that each additional kWh of lithium-ion battery output leads to an average reduction of 220 kg of CO 2 in 2030 and 127 kg of CO 2 in 2050. There are also substantial decreases in CO emissions, although relatively small changes in SO 2 and NO X . In a life cycle assessment, all else equal, the CO 2 emissions associated with BEVs are 30% higher than those of ICE vehicles during the first two years. However, after the second year, BEVs result in a reduction in cumulative CO 2 emissions. Accounting for the effects of both air pollution and climate change, the economic value of the damages attributable to ICEs over their lifetime is currently 2 to 3.5 times that of BEVs. This ratio increases over the coming decades as the emissions intensity of the electricity sector decreases.

Purpose This study aims to evaluate the economic and environmental performance of different vehicle operation strategies for medical waste collection and transportation in Beijing's Huairou District, within the context of global climate change and carbon emission reduction. Design/methodology/approach A simulation model was developed using AnyLogic software to simulate three vehicle operation strategies: fossil fuel vehicles (FFVs), battery electric vehicles (BEVs), and a mixed strategy combining FFVs and BEVs. These strategies were comprehensively evaluated by using the entropy method through the Stata software. The three evaluation indexes considered were carbon emissions, transportation costs, and fixed costs. Findings The results indicate that the BEV strategy demonstrates superior overall performance, achieving a good balance between environmental sustainability and economic efficiency. Although the mixed strategy is not as efficient as BEVs, it can effectively supplement the BEV strategy. The FFV strategy, despite its lower initial investment, has higher long-term operating costs and environmental burdens, which makes it less sustainable in the context of low-carbon development. Originality/value This study provides novel insights into the application of sustainable vehicle operation strategies for medical waste management in Beijing, especially in the context of the transition to a low-carbon economy. It offers valuable insights into the transition from FFVs to BEVs and proposes an incremental strategy for the adoption of BEVs, addressing the practical challenges of full vehicle replacement in the real situation. It also provides a reference for the collection and transportation of medical waste in similar cities.

As more and more technology advancement of transportation and electrification of heating system, residents nowadays usually had the less demand for using the fossil fuel which causes the carbon emission. For instance, most peoples vehicles had converted from ICE (internal combustion engine) vehicles to the BEVs (Battery electric vehicles). Another example, domestic heating pumps, use electricity instead of using fossil fuel (natural gas, propane, heating oil, charcoal etc.) nowadays to transfer heat from a cool space to a warm space and reverse this process if in summer. Electrification refers to the source of generating the electricity and their usage are renewable such as photovoltaic, wind electricity, hydrogen-powered electricity etc. These source of electricity can supply the electric vehicles and the electric heat pumps sufficiently. However, the cost of source of generating the electricity and technology impede the electrification. For materials perspective, like battery, electromotor, conductors & insulators, heat exchange, and refrigeration materials. These materials can determine the efficiency, energy density and the life span. Nevertheless, these materials are also limited and difficult to manufacture. Thus, this paper will provide the clear and executable ideas for the strategies and material selection of small cars and heat pump renovations in electrification and explain the limitation in mechanism perspective.

Evaluating battery electric vehicle policies: a benefit-cost analysis framework

The increased energy efficiency of electrified vehicles and their potential to reduce CO2 emissions through the use of environmentally friendly materials are highlighted as reasons for the shift to electrified vehicles. Brief trends on the development of electric vehicles (EVs) have been discussed, presenting outstanding improvement towards the actualization of the green economy. The state of the art in lubrication has been thoroughly investigated as one of the factors influencing energy efficiency and the lifespan of machine components. As a result, many reports on the effectiveness of specific lubricants in electric vehicle applications have been developed. Good thermal and corrosion-resistant lubricants are necessary because of the emergence of several new tribological difficulties, especially in areas that interact with greater temperatures and currents. To avoid fluidity and frictional problems that may be experienced over its lifetime, a good viscosity level of lubricant was also mentioned as a crucial component in the formulation of EV lubricant. New lubricants are also necessary for the gearbox systems of electric vehicles. Furthermore, battery electric vehicles (BEVs) require a suitable cooling system for the batteries; thus, a compatible nano-fluid is recommended. Sustainable battery cooling options support global energy efficiency and carbon emission reduction while extending the life of EV batteries. The path for future advancements or the creation of the most useful and efficient EV lubricants is provided by this review study.

Hydrogen fuel cell electric trucks (FCETs) have been seen as an important decarbonization pathway for heavy-duty trucks, but their real-world operational performance and costs remain uncertain, posing challenges to the widespread adoption. This study presents the largest analysis to date of real-world operational data from 106 heavy-duty FCETs across six application scenarios in China. We examine usage patterns, energy consumption, life-cycle greenhouse gas (GHG) emissions, and total cost of ownership (TCO). FCETs are deployed across diverse application scenarios, with most operating on short- to medium-distance routes (average daily mileage <300 km), and some utilizing both hydrogen refueling and grid charging. In Beijing, where hydrogen is primarily sourced from industrial byproducts, FCETs generally exhibit lower life-cycle GHG emissions than diesel and battery-electric trucks, except in low-utilization scenarios. Currently, the unsubsidized TCO of FCETs is 42-152% higher than that of diesel trucks (DTs). However, with purchase, operational, and hydrogen subsidies, the TCO can be 13-36% lower than that of DTs. While FCETs offer strong carbon reduction potential, achieving TCO parity requires alignment with appropriate application scenarios and adequate refueling infrastructure, particularly for long-haul operations by 2030.

The adoption of Interior Permanent Magnet Synchronous Motor (IPMSM) in Battery Electric Vehicle (BEV) and Plug-in Hybrid Electric Vehicle (PHEV) drives the need for innovative approaches to improve control performance and power conversion efficiency. This paper aims at evaluating advanced Model Predictive Control (MPC) strategies for IPMSM drives in a methodic comparison with the most widespread Field Oriented Control (FOC). Different extensions of direct Finite Control Set MPC (FCS-MPC) and indirect Continuous Control Set MPC (CCS-MPC) MPCs are considered and evaluated in terms of reference tracking performance, robustness, power efficiency, and complexity based on Matlab, Simulink™ simulations. Results confirm the inherent better control quality of MPCs over FOC in general and allow us to further identify some possible directions for improvement. Moreover, indirect MPCs perform better, but complexity may prevent them from supporting real-time implementation in some cases. On the other hand, direct MPCs are less complex and reduce inverter losses but at the cost of increased Total Harmonic Distortion (THD) and decreased robustness to parameters deviations. These results also highlight various trade-offs between different predictive control strategies and their feasibility for high-performance automotive applications.

The rapid adoption of electric vehicles (BEVs) has increased the need to understand how fast-charging strategies influence long-distance travel times under real-world conditions. While most manufacturers specify maximum charging power and standardized driving ranges, these figures often fail to reflect actual highway operation, particularly in adverse weather. This study addresses this gap by analyzing the fast-charging behaviour, net battery capacity and highway energy consumption of 62 EVs from different market segments. Charging power curves were obtained experimentally at high-power DC stations, with data recorded through both the charging infrastructure and the vehicles’ battery management systems. Tests were conducted, under optimal conditions, between 10% and 90% state of charge (SoC), with additional sessions performed under both cold and preconditioned battery conditions to show thermal effects on the batteries’ fast-charging capabilities. Real-world highway consumption values were applied to simulate 1000 km journeys at 120 km/h under cold (−10 °C, cabin heating) and mild (23 °C, no AC) weather scenarios. An optimization model was developed to minimize total trip time by adjusting the number and duration of charging stops, including a 5 min detour for each charging session. Results show that the optimal charging cutoff point consistently emerges around 59% SoC, with a typical deviation of 10, regardless of ambient temperature. Charging beyond 70% SoC is generally inefficient unless dictated by charging station availability. The optimal strategy involves increasing the number of shorter stops—typically every 2–3 h of driving—thereby reducing total trip.

Understanding vehicle acceleration behavior during intersection departures is critical for advancing traffic safety, sustainable mobility, and intelligent transport systems. This study presents a high-resolution kinematic analysis of 714 vehicle departures from signalized intersections, encompassing straight crossings, left turns, and right turns, and involving a diverse sample of internal combustion engine (ICE), hybrid electric (HEV), and battery electric vehicles (BEV). Using synchronized Micro Electro-Mechanical Systems (MEMS) accelerometers and Real-Time Kinematic (RTK)-GPS systems, the study captures longitudinal acceleration and velocity profiles over fixed distances. Results indicate that BEVs exhibit significantly higher acceleration and final speeds than ICE and HEV vehicles, particularly during straight crossings and longer left-turn maneuvers. Several mathematical models—including polynomial, arctangent, and Akçelik functions—were calibrated to describe acceleration and velocity dynamics. Findings contribute by modeling jerk and delay propagation, supporting better calibration of AV acceleration profiles and the optimization of intersection control strategies. Moreover, the study provides validated acceleration benchmarks that enhance the accuracy of forensic engineering and road accident reconstruction, particularly in scenarios involving intersection dynamics, and demonstrates that BEVs accelerate more rapidly than ICE and HEV vehicles, especially in straight crossings, with direct implications for traffic simulation, ADAS calibration, and urban crash analysis.

Battery Electric Vehicles (BEVs) experience significant reductions in driving range under subzero temperatures due to the increased thermal management demands, a reduction in available electric energy of battery, the reduced powertrain efficiency, and the higher rolling resistance. This study proposed an advanced thermal management strategy to enhance BEV driving range under cold climate. A heat-coupled energy balance model was established to evaluate the impact of different configurations of the thermal management system (TMS) as well as the control parameters at −7°C. A neural network-based parametric analysis was conducted under the China Light-Duty Vehicle Test Cycle (CLTC) to identify the optimal control strategy. Simulation results showed that the proposed strategy could increase driving range by up to 15.1% compared to the baseline. Experimental validation on an A-class sedan further confirmed the effectiveness of the strategy, which combined a direct heat pump, aerogel-based thermal insulation, and advanced control settings—including a heating activation State of Charge (SOC) of 20%, target battery temperature of 31°C, blower level 3, and an air recirculation ratio of 0.8. The optimized system could increase driving range by up to 17.1% compared to the baseline, which showed good agreement with the simulation results. This work provided a practical solution for extending BEV range under subzero temperature in cold climate regions.

The Covid-19 pandemic significantly affected national economic performance, including the automotive industry which experienced a decline in production and sales. To address this issue while promoting a transition to environmentally friendly energy, the government introduced the Luxury Goods Tax Borne by the Government (PPnBM DTP) incentive for battery electric vehicles under Minister of Finance Regulation No. 9 of 2024. This study aims to evaluate the effectiveness of the policy on public purchasing power. The research applies a descriptive qualitative evaluative method using secondary data from regulations and previous studies. The findings reveal that the PPnBM DTP incentive has increased consumer interest and sales of electric cars in Indonesia, although the growth is not evenly distributed across all market segments. The main barriers remain the relatively high prices of electric vehicles and the limited availability of charging infrastructure. These results imply that additional policy support, particularly in infrastructure development and extended incentives, is essential to strengthen public purchasing power and encourage broader adoption of electric vehicles.

Abstract Metamaterials have gained an increasing attention as a way of absorbing noise to achieve improved acoustic performance on vehicles, and thanks to their novel functionalities compared to traditional designs, these structures are employed by many automotive companies as noise-reduction solutions for engineering applications. One of the key challenges for automotive original equipment manufacturers (OEMs) in the noise, vibration, and harshness (NVH) development process is absorption performance in the frequency range of 400 Hz–800 Hz. Although sound engineers use porous polyurethane in these frequency ranges, the absorption performance of these designs is limited to meet increasing customer expectations. Managing airborne noise in vehicles is particularly challenging in the low frequency spectrum, where Helmholtz resonators are widely used. The main purpose of this study is to develop a metaporous sound barrier incorporating a Helmholtz resonator, effective in the low to mid-frequency range of the spectrum. For this purpose, a frequency domain simulation was carried out to obtain the absorption coefficient, analyze frequency-dependent effects, and identify critical frequencies in vehicle acoustics. Furthermore, local resonance effects to prevent acoustic waves were investigated and design parameters of metastructure were analyzed using a multi-physics based simulation model. These results were validated experimentally using an acoustic impedance tube. The methodology is demonstrated in a battery electric vehicle (BEV) to improve airborne compressor noise during engine idling. The optimum design parameters were determined using the Taguchi design method. Finally, the performance of developed metaporous material was validated through vehicle-level tests, with results showing an improvement of 3 dB(A).

Battery Electric Vehicles (BEVs) technology is rapidly emerging as the cornerstone of sustainable transportation, driven by advancements in battery technology, power electronics, and modern drivetrains. This paper presents a comprehensive review of current and next-generation BEV powertrain architectures, focusing on five key subsystems: battery energy storage system, electric propulsion motors, energy management systems, power electronic converters, and charging infrastructure. The review traces the evolution of battery technology from conventional lithium-ion to solid-state chemistries and highlights the critical role of battery management systems in ensuring optimal state of charge, health, and safety. Recent innovations by leading automakers are examined, showcasing advancements in cell formats, motor designs, and thermal management for enhanced range and performance. The role of power electronics and the integration of AI-driven strategies for vehicle control and vehicle-to-grid (V2G) are analyzed. Finally, the paper identifies ongoing research gaps in system integration, standardization, and advanced BMS solutions. This review provides a comprehensive roadmap for innovation, aiming to guide researchers and industry stakeholders in accelerating the adoption and sustainable advancement of BEV technologies.