World Electric Vehicle Journal

30 pages, 2986 KiB

Open AccessArticle

The Overlooked Role of Battery Cell Relaxation: How Reversible Effects Manipulate Accelerated Aging Characterization

by Markus Schreiber, Theresa Steiner, Jonas Kayl, Benedikt Schönberger, Cristina Grosu and Markus Lienkamp

World Electr. Veh. J. 2025, 16(5), 255; https://doi.org/10.3390/wevj16050255 (registering DOI) - 30 Apr 2025

Abstract

Aging experiments are pivotal for car manufacturers to ensure the reliability of their battery cells. However, realistic aging methods are time-consuming and resource-intensive, necessitating accelerated aging techniques. While these techniques reduce testing time, they can also lead to distorted results due to the [...] Read more.

Aging experiments are pivotal for car manufacturers to ensure the reliability of their battery cells. However, realistic aging methods are time-consuming and resource-intensive, necessitating accelerated aging techniques. While these techniques reduce testing time, they can also lead to distorted results due to the partially reversible nature of cell behavior, which stems from the inhomogenization and rehomogenization of conducting salt and lithium distribution in the electrode. To accurately capture these phenomena, cell relaxation must be incorporated into the test design. This work investigates the impact of the test procedure and several stress factors, namely depth of discharge and C- rate, on the formation and rehomogenization of cell inhomogeneities. The experimental results reveal increasing cell inhomogenization, leading to growing reversible capacity losses, particularly under conditions with shorter cycling interruptions (check ups and rest phases). These reversible capacity losses are associated with a significant reduction in cycle life performance of up to 400 under identical cycling conditions but shorter cycling interruptions. Similar trends are observed for increasing cycle depths and C-rates. Optimized recovery cycles effectively mitigate cell inhomogenization, doubling cycle stability without requiring considerable additional testing time. Furthermore, a clear correlation is found between increasing inhomogenization and cell failure, with lithium stripping confirming the occurrence of lithium plating shortly before failure. These findings emphasize the critical importance of considering cell relaxation in cycle aging studies to ensure reliable and accurate lifetime predictions. Under realistic conditions, substantially enhanced cycle stability is expected. Full article

(This article belongs to the Special Issue EVS37—International Electric Vehicle Symposium and Exhibition (Seoul, Republic of Korea))

18 pages, 4513 KiB

Open AccessArticle

An Improved Finite-Set Predictive Control for Permanent Magnet Synchronous Motors Based on a Neutral-Point-Clamped Three-Level Inverter

by Guozheng Zhang, Jiangyi Zhao, Yufei Liu, Xin Gu, Chen Li and Wei Chen

World Electr. Veh. J. 2025, 16(5), 254; https://doi.org/10.3390/wevj16050254 (registering DOI) - 30 Apr 2025

Abstract

Numerous voltage vectors exist in a neutral-point-clamped (NPC) three-level inverter. Traditional three-level model predictive control incurs a heavy online computational burden. This paper proposes a model predictive torque control strategy for NPC three-level inverters with permanent magnet synchronous motor systems. First, the relationship [...] Read more.

Numerous voltage vectors exist in a neutral-point-clamped (NPC) three-level inverter. Traditional three-level model predictive control incurs a heavy online computational burden. This paper proposes a model predictive torque control strategy for NPC three-level inverters with permanent magnet synchronous motor systems. First, the relationship among the stator flux linkage vector position, the torque–flux linkage increment, and the stator flux linkage variation is analyzed. Then, the candidate voltage vector sector is determined, and the candidate voltage vectors are selected from it. Meanwhile, the direction of the load current flowing to the neutral point and the voltage difference between the upper and lower capacitors are evaluated. As a result, redundant small vectors are effectively selected, reducing the number of candidate voltage vectors to six and avoiding the computation of all possible vectors. The experimental results from an NPC three-level inverter–permanent magnet synchronous motor system verify that this strategy significantly reduces the computational complexity and provides excellent dynamic and steady-state performance. Full article

(This article belongs to the Special Issue Design and Control of Electrical Machines in Electric Vehicles, 2nd Edition)

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26 pages, 5418 KiB

Open AccessArticle

Research on the Evaluation of Urban Green Transportation Development Level in Guangzhou Under the Promotion of New Energy Vehicles

by Yanlong Dong, Fanlong Zeng and Huaping Sun

World Electr. Veh. J. 2025, 16(5), 253; https://doi.org/10.3390/wevj16050253 - 29 Apr 2025

Abstract

Assessing the urban green transportation development level (UGTDL) is of great significance for addressing traffic issues in megacities and promoting urban sustainable development. An evaluation framework for the UGTDL is proposed based on Multi-Criteria Decision Analysis (MCDA) methods. Firstly, from both macro and [...] Read more.

Assessing the urban green transportation development level (UGTDL) is of great significance for addressing traffic issues in megacities and promoting urban sustainable development. An evaluation framework for the UGTDL is proposed based on Multi-Criteria Decision Analysis (MCDA) methods. Firstly, from both macro and micro perspectives, a comprehensive evaluation indicator system is constructed, covering multiple dimensions such as traffic spatial organization efficiency, green travel, new energy vehicle development, traffic safety, and the traffic environment. Secondly, to address the uncertainties and fuzziness in the evaluation process, the Probability Language Term Set (PLTS) is introduced to represent expert evaluation information, thereby reducing the information loss. Thirdly, the improved Step-wise Weight Assessment Ratio Analysis (SWARA) method is employed to calculate the weights of the indicators, improving the computational efficiency. Finally, the extended Combined Compromise Solution (CoCoSo) method is used to calculate the UGTDL, avoiding the compensatory issues in the traditional decision-making methods. The proposed approach is applied to assess the UGTDL in Guangzhou from 2020 to 2023. The results show that the UGTDL scores for Guangzhou from 2020 to 2023 are 1.6367, 2.2325, 2.1141, and 1.8575, respectively. Sensitivity analysis verifies the effectiveness and stability of the approach. Further obstacle analysis shows that the promotion of new energy vehicles (NEVs) has led to a marginal decrease in the utility of Guangzhou’s UGTDL. In the future, Guangzhou should take further measures to improve the traffic space organization efficiency and traffic safety. Full article

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23 pages, 10006 KiB

Open AccessArticle

Research on Unbalanced Electromagnetic Force Under Static Eccentricity of the Wheel Hub Motor Based on BP Neural Network

by Xiangpeng Meng, Yunquan Zhang, Renkai Ding, Wei Liu and Ruochen Wang

World Electr. Veh. J. 2025, 16(5), 252; https://doi.org/10.3390/wevj16050252 - 28 Apr 2025

Abstract

Aiming at exploring a high-precision unbalanced electromagnetic force model suitable for the dynamic simulation of wheel hub direct-drive electric vehicles, this article establishes the unbalanced electromagnetic force model under static eccentricity of a wheel hub motor by an analytical method and verifies its [...] Read more.

Aiming at exploring a high-precision unbalanced electromagnetic force model suitable for the dynamic simulation of wheel hub direct-drive electric vehicles, this article establishes the unbalanced electromagnetic force model under static eccentricity of a wheel hub motor by an analytical method and verifies its accuracy by finite element modeling. Then, it optimizes the unbalanced electromagnetic force model based on a BP neural network and couples it with the 1/2 vehicle vertical vibration model to improve its calculation and operation efficiency. Finally, the correctness of the coupling model is further verified by bench experiments. The results show that the analytical model of the unbalanced electromagnetic force is accurate. A BP neural network optimization algorithm can reduce the time of electromagnetic force model simulation for 10 s from 1 h to about 50 s, which greatly improves the calculation efficiency of the electromagnetic force on the basis of ensuring the accuracy of the model, thus providing an unbalanced electromagnetic force model that is more suitable for the dynamic simulation of wheel hub direct-drive electric vehicles, which effectively solves the problem that the traditional electromagnetic force is difficult to couple with the vehicle dynamics model and lays a better foundation for subsequent research on the vertical vibration effect of wheel hub direct-drive electric vehicles. Full article

(This article belongs to the Special Issue Design, Analysis and Optimization of Electrical Machines and Drives for Electric Vehicles, 2nd Edition)

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18 pages, 2433 KiB

Open AccessArticle

Design and Analysis of an MPC-PID-Based Double-Loop Trajectory Tracking Algorithm for Intelligent Sweeping Vehicles

by Zhijun Guo, Mingtian Pang, Shiwen Ye and Yangyang Geng

World Electr. Veh. J. 2025, 16(5), 251; https://doi.org/10.3390/wevj16050251 - 28 Apr 2025

Abstract

To enhance the precision and real-time performance of trajectory tracking control in differential-steering intelligent sweeping robots and to improve the adaptability of the control algorithm to errors caused by sensor noise, tire slip, and skid, an MPC-PID (Model Predictive Control–Proportional-Integral-Derivative) dual closed-loop control [...] Read more.

To enhance the precision and real-time performance of trajectory tracking control in differential-steering intelligent sweeping robots and to improve the adaptability of the control algorithm to errors caused by sensor noise, tire slip, and skid, an MPC-PID (Model Predictive Control–Proportional-Integral-Derivative) dual closed-loop control strategy was proposed. This strategy integrates a Kalman filter-based state estimator and a sliding compensation module. Based on the kinematic model of the intelligent sweeping robot, a model predictive controller (MPC) was designed to regulate the vehicle’s pose, while a PID controller was used to adjust the longitudinal speed, forming a dual closed-loop control algorithm. A Kalman filter was employed for state estimation, and a sliding compensation module was introduced to mitigate wheel slip and lateral drift, thereby improving the stability of the control system. Simulation results demonstrated that, compared to traditional MPC control, the maximum lateral deviation, maximum heading angle deviation, and speed response time were reduced by 50.83%, 53.65%, and 7.10%, respectively, during sweeping operations. In normal driving conditions, these parameters were improved by 41.58%, 45.54%, and 24.17%, respectively. Experimental validation on an intelligent sweeper platform demonstrates that the proposed algorithm achieves a 16.48% reduction in maximum lateral deviation and 9.52% faster speed response time compared to traditional MPC, effectively validating its enhanced tracking effectiveness in intelligent cleaning operations. Full article

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31 pages, 7481 KiB

Open AccessArticle

A Multi-Scheme Comparison Framework for Ultra-Fast Charging Stations with Active Load Management and Energy Storage Under Grid Capacity Constraints

by Qingyu Yin, Lili Li, Jian Zhang, Xiaonan Liu and Boqiang Ren

World Electr. Veh. J. 2025, 16(5), 250; https://doi.org/10.3390/wevj16050250 - 27 Apr 2025

Abstract

Grid capacity constraints present a prominent challenge in the construction of ultra-fast charging (UFC) stations. Active load management (ALM) and battery energy storage systems (BESSs) are currently two primary countermeasures to address this issue. ALM allows UFC stations to install larger-capacity transformers by [...] Read more.

Grid capacity constraints present a prominent challenge in the construction of ultra-fast charging (UFC) stations. Active load management (ALM) and battery energy storage systems (BESSs) are currently two primary countermeasures to address this issue. ALM allows UFC stations to install larger-capacity transformers by utilizing valley capacity margins to meet the peak charging demand during grid valley periods, while BESSs rely more on energy storage batteries to solve the gap between the transformer capacity and charging demand This paper proposes a four-quadrant classification method and defines four types of schemes for UFC stations to address grid capacity constraints: (1) ALM with a minimal BESS (ALM-Smin), (2) ALM with a maximal BESS (ALM-Smax), (3) passive load management (PLM) with a minimal BESS (PLM-Smin), and (4) PLM with a maximal BESS (PLM-Smax). A generalized comparison framework is established as follows: First, daily charging load profiles are simulated based on preset vehicle demand and predefined charger specifications. Next, transformer capacity, BESS capacity, and daily operational profiles are calculated for each scheme. Finally, a comprehensive economic evaluation is performed using the levelized cost of electricity (LCOE) and internal rate of return (IRR). A case study of a typical public UFC station in Tianjin, China, validates the effectiveness of the proposed schemes and comparison framework. A sensitivity analysis explored how grid interconnection costs and BESS costs influence decision boundaries between schemes. The study concludes by highlighting its contributions, limitations, and future research directions. Full article

(This article belongs to the Special Issue Fast-Charging Station for Electric Vehicles: Challenges and Issues)

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26 pages, 14549 KiB

Open AccessArticle

Research on Energy-Saving Control Strategy of Nonlinear Thermal Management System for Electric Tractor Power Battery Under Plowing Conditions

by Xiaoshuang Guo, Ruiliang Xu, Junjiang Zhang, Xianghai Yan, Mengnan Liu and Mingyue Shi

World Electr. Veh. J. 2025, 16(5), 249; https://doi.org/10.3390/wevj16050249 - 25 Apr 2025

Abstract

To address the issue of over-regulation of the temperature of a liquid-cooled power battery thermal management system under the plowing condition of electric tractors, which leads to high energy consumption, a nonlinear model prediction control (NMPC) algorithm for the thermal management system of [...] Read more.

To address the issue of over-regulation of the temperature of a liquid-cooled power battery thermal management system under the plowing condition of electric tractors, which leads to high energy consumption, a nonlinear model prediction control (NMPC) algorithm for the thermal management system of the power battery of electric tractors applicable to the plowing condition is proposed. Firstly, a control-oriented electric tractor power battery heat production model and a heat transfer model were established based on the tractor operating conditions and Bernardi’s theory of battery heat production. Secondly, in order to improve the accuracy of temperature prediction, a prediction method of future working condition information based on the moving average theory is proposed. Finally, a nonlinear model predictive control cooling optimization strategy is proposed, with the optimization objectives of quickly achieving battery temperature regulation and reducing compressor energy consumption. The proposed control strategy is validated by simulation and a hardware-in-the-loop (HIL) testbed. The results show that the proposed NMPC strategy can control the battery temperature better, that in the holding phase the proposed control strategy reduces the compressor speed variation range by 24.6% compared with PID, and that it reduces the compressor energy consumption by 23.1% in the whole temperature control phase. Full article

(This article belongs to the Special Issue New Energy Vehicle Thermal and Energy Management Systems Design and Collaborative Control)

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23 pages, 2616 KiB

Open AccessArticle

Investigation of Harmonic Losses to Reduce Rotor Copper Loss in Induction Motors for Traction Applications

by Muhammad Salik Siddique, Hulusi Bülent Ertan, Muhammad Shahab Alam and Muhammad Umer Khan

World Electr. Veh. J. 2025, 16(5), 248; https://doi.org/10.3390/wevj16050248 - 25 Apr 2025

Abstract

The focus of this paper is to seek means of increasing induction motor efficiency to a comparable level to a permanent magnet motor. Harmonic and high-frequency losses increase the rotor core and copper loss, often limiting IM efficiency. The research in this study [...] Read more.

The focus of this paper is to seek means of increasing induction motor efficiency to a comparable level to a permanent magnet motor. Harmonic and high-frequency losses increase the rotor core and copper loss, often limiting IM efficiency. The research in this study focuses on reducing rotor core and copper losses for this purpose. An accurate finite element model of a prototype motor is developed. The accuracy of this model in predicting the performance and losses of the prototype motor is verified with experiments over a 32 Hz–125 Hz supply frequency range. The verified model of the motor is used to identify the causes of the rotor core and copper losses of the motor. It is found that the air gap flux density of the motor contains many harmonics, and the slot harmonics are dominant. The distribution of the core loss and the copper loss is investigated on the rotor side. It is discovered that up to 35% of the rotor copper losses and 90% rotor core losses occur in the regions up to 4 mm from the airgap where the harmonics penetrate. To reduce these losses, one solution is to reduce the magnitude of the air gap flux density harmonics. For this purpose, placing a sleeve to cover the slot openings is investigated. The FEA indicates that this measure reduces the harmonic magnitudes and reduces the core and bar losses. However, its effect on efficiency is observed to be limited. This is attributed to the penetration depth of flux density harmonics inside the rotor conductors. To remedy this problem, several FEA-based modifications to the rotor slot shape are investigated to place rotor bars deeper than the harmonic penetration. It is found that placing the bars further away from the rotor surface is very effective. Using a 1 mm sleeve across the stator’s open slots combined with a rotor tapered slot lip positions the bars slightly deeper than the major harmonic penetration depth, making it the optimal solution. This reduces the bar loss by 70% and increases the motor efficiency by 1%. Similar loss reduction is observed over the tested supply frequency range. Full article

(This article belongs to the Special Issue Propulsion Systems of EVs 2.0)

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16 pages, 7117 KiB

Open AccessArticle

Performance Evaluation of Outer Rotor Permanent Magnet Direct Drive In-Wheel Motor Based on Air-Gap Field Modulation Effect

by Qin Wang

World Electr. Veh. J. 2025, 16(5), 247; https://doi.org/10.3390/wevj16050247 - 25 Apr 2025

Abstract

The different pole–slot combinations of outer rotor surface-mounted permanent magnet (ORSPM) motors are designed and analyzed to satisfy EV driving requirements. Firstly, the analytical model for various slot–pole combinations of ORSPM motors is proposed based on the air-gap field modulation effect. Then, some [...] Read more.

The different pole–slot combinations of outer rotor surface-mounted permanent magnet (ORSPM) motors are designed and analyzed to satisfy EV driving requirements. Firstly, the analytical model for various slot–pole combinations of ORSPM motors is proposed based on the air-gap field modulation effect. Then, some of the in-wheel motor parameters and requirements are obtained for the vehicle system. In addition, some special pole–slot combination ORSPM motors are built to achieve higher flux density, and the electromagnetic performance is compared based on the finite element (FE) model, revealing that the 56-slot/48-pole (54s48p) in-wheel motor has a higher torque density and superior flux weakening capability than other cases. Finally, a 13 kW prototype with 54s48p is manufactured and tested to confirm the effectiveness of the FE analysis. Full article

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28 pages, 2961 KiB

Open AccessArticle

Impact Assessment of Integrating AVs in Optimizing Urban Traffic Operations for Sustainable Transportation Planning in Riyadh

by Nawaf Mohamed Alshabibi

World Electr. Veh. J. 2025, 16(5), 246; https://doi.org/10.3390/wevj16050246 - 24 Apr 2025

Abstract

Integrating autonomous vehicles (AVs) into urban traffic systems presents significant opportunities for optimizing traffic flow, reducing congestion, and enhancing transportation efficiency. This study proposes a comprehensive framework that combines mathematical optimization techniques, policy planning, and AV adoption modeling to improve urban mobility. Using [...] Read more.

Integrating autonomous vehicles (AVs) into urban traffic systems presents significant opportunities for optimizing traffic flow, reducing congestion, and enhancing transportation efficiency. This study proposes a comprehensive framework that combines mathematical optimization techniques, policy planning, and AV adoption modeling to improve urban mobility. Using Highway Capacity Manual (HCM) Optimization methods, the research fine-tunes traffic signal timings, dynamically allocates green time, and enhances intersection coordination to maximize throughput. The study evaluates the impact of AV penetration on traffic flow efficiency, congestion reduction, and infrastructure readiness using real-world urban data from Riyadh. The results indicate that AV integration leads to a 40% increase in traffic throughput, a 60% reduction in congestion levels, and a 45% improvement in infrastructure readiness, highlighting the effectiveness of AV-driven traffic optimization strategies. Additionally, policy interventions aimed at reducing legal constraints and increasing societal acceptance contribute to the successful implementation of AV technology. The findings provide a data-driven roadmap for city planners and policymakers, demonstrating how a well-structured AV deployment strategy can significantly enhance urban transportation efficiency. Full article

(This article belongs to the Special Issue Advancements in Autonomous Vehicles: Security, Optimization and Future Challenges)

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25 pages, 5857 KiB

Open AccessArticle

Evaluation of the Intersection Sight Distance at Stop-Controlled Intersections in a Mixed Vehicle Environment

by Jana Sarran and Sean Sarran

World Electr. Veh. J. 2025, 16(5), 245; https://doi.org/10.3390/wevj16050245 - 23 Apr 2025

Abstract

The introduction of autonomous vehicles (AVs) on roadways will result in a mixed vehicle environment consisting of these vehicles and manual vehicles (MVs). This vehicular environment will impact intersection sight distances (ISDs) due to differences in the driving behaviors of AVs and MVs. [...] Read more.

The introduction of autonomous vehicles (AVs) on roadways will result in a mixed vehicle environment consisting of these vehicles and manual vehicles (MVs). This vehicular environment will impact intersection sight distances (ISDs) due to differences in the driving behaviors of AVs and MVs. Currently, ISD design values for stop-controlled intersections are based on AASHTO’s guidelines, which account only for human driver behaviors. However, with AVs in the traffic stream, it is important to assess whether the existing MV-based ISDs are compliant when an AV is present at an intersecting roadway. Hence, this study utilizes the Monte Carlo Simulation method to compute the PNC of various object locations on the major and minor roadways for possible vehicle interaction types in a mixed vehicle environment at a stop-controlled intersection. Scenarios generated considered these variables and the major roadway speed limits and sight distance triangles (SDTs). ISD non-compliance was determined by examining the PNC metric, which occurred when the demand exceeded the supply. The results indicated that when AV–MV interaction was present at the intersection, the MV-based ISD design was non-compliant. However, it is possible to correct this non-compliance issue by reducing the AV speed limit. Full article

(This article belongs to the Special Issue Recent Advances in Autonomous Vehicles)

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21 pages, 13843 KiB

Open AccessArticle

Improved Quintic Polynomial Autonomous Vehicle Lane-Change Trajectory Planning Based on Hybrid Algorithm Optimization

by Yuelou Zhang, Lingshan Chen and Ning Li

World Electr. Veh. J. 2025, 16(5), 244; https://doi.org/10.3390/wevj16050244 - 23 Apr 2025

Abstract

A trajectory planning method is proposed to address the lane-changing problem in intelligent vehicles. The method is based on quintic polynomial improvement. The transit position is determined according to the position and state of motion of the vehicle and the obstacle vehicle; the [...] Read more.

A trajectory planning method is proposed to address the lane-changing problem in intelligent vehicles. The method is based on quintic polynomial improvement. The transit position is determined according to the position and state of motion of the vehicle and the obstacle vehicle; the lane-changing process is divided into two segments. The quintic polynomials are commonly applied in trajectory planning, respectively, in the two segments. According to the different characteristics of the lane-changing paths in the front and rear segments, a multi-objective optimization function with different weight coefficients is established. A safe and comfortable lane-changing trajectory is achieved through the improved particle swarm optimization algorithm. Real-time simulation tests of lane-changing method are conducted on the hardware-in-the-loop platform. The method can be used in different scenarios to plan safe and comfortable trajectories. Full article

(This article belongs to the Special Issue Motion Planning and Control of Autonomous Vehicles)

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24 pages, 5964 KiB

Open AccessArticle

A Privacy-Preserving Scheme for Charging Reservations and Subsequent Deviation Settlements for Electric Vehicles Based on a Consortium Blockchain

by Beibei Wang, Yikun Yang, Wenjie Liu and Lun Xu

World Electr. Veh. J. 2025, 16(5), 243; https://doi.org/10.3390/wevj16050243 - 22 Apr 2025

Abstract

Electric vehicles have garnered substantial attention as an environmentally sustainable transportation alternative amid escalating global concerns regarding ecological preservation and energy resource management. While the proliferation of electric vehicles necessitates the development of efficient and secure charging infrastructure, the inherent communication-intensive nature of [...] Read more.

Electric vehicles have garnered substantial attention as an environmentally sustainable transportation alternative amid escalating global concerns regarding ecological preservation and energy resource management. While the proliferation of electric vehicles necessitates the development of efficient and secure charging infrastructure, the inherent communication-intensive nature of the charging processes has raised concerns regarding potential privacy vulnerabilities. Our paper introduces a privacy protection scheme specifically designed for electric vehicle charging reservations to address this issue. The primary goal of this scheme is to protect user privacy while maintaining operational efficiency and economic viability for charging providers. Our proposed solution ensures a secure and private environment for charging reservation transactions and subsequent deviation settlements by incorporating advanced technologies, including zero-knowledge proof, a consortium blockchain, and homomorphic encryption. The scheme encrypts charging reservation information and securely transmits it via a consortium blockchain, effectively shielding the sensitive data of all participating parties. Notably, the experimental findings establish the robustness of our scheme in terms of its security and privacy protection, aligning with the stringent demands of electric vehicle charging operations. Full article

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15 pages, 242 KiB

Open AccessCommunication

Enhancing Sustainable Last-Mile Delivery: The Impact of Electric Vehicles and AI Optimization on Urban Logistics

by Joao C. Ferreira and Marco Esperança

World Electr. Veh. J. 2025, 16(5), 242; https://doi.org/10.3390/wevj16050242 - 22 Apr 2025

Abstract

The rapid growth of e-commerce has intensified the need for efficient and sustainable last-mile delivery solutions in urban environments. This paper explores the integration of electric vehicles (EVs) and artificial intelligence (AI) into a combined framework to enhance the environmental, operational, and economic [...] Read more.

The rapid growth of e-commerce has intensified the need for efficient and sustainable last-mile delivery solutions in urban environments. This paper explores the integration of electric vehicles (EVs) and artificial intelligence (AI) into a combined framework to enhance the environmental, operational, and economic performance of urban logistics. Through a comprehensive literature review, we examine current trends, technological developments, and implementation challenges at the intersection of smart mobility, green logistics, and digital transformation. We propose an operational framework that leverages AI for route optimization, fleet coordination, and energy management in EV-based delivery networks. This framework is validated through a real-world case study conducted in Lisbon, Portugal, where a logistics provider implemented a city consolidation center model supported by AI-driven optimization tools. Using key performance indicators—including delivery time, energy consumption, fleet utilization, customer satisfaction, and CO₂ emissions—we measure the pre- and post-AI deployment impacts. The results demonstrate significant improvements across all metrics, including a 15–20% reduction in delivery time, a 10–25% gain in energy efficiency, and up to a 40% decrease in emissions. The findings confirm that the synergy between EVs and AI provides a robust and scalable model for achieving sustainable last-mile logistics, supporting broader urban mobility and climate objectives. Full article

(This article belongs to the Special Issue Theory, Method and Application of New Energy and Intelligent Transportation)

19 pages, 5405 KiB

Open AccessArticle

Research on Trajectory Prediction Based on Front Vehicle Sideslip Recognition

by Jian Ou, Xiaolong Cheng and Pengju Zhang

World Electr. Veh. J. 2025, 16(4), 241; https://doi.org/10.3390/wevj16040241 - 21 Apr 2025

Abstract

In order to solve the problem of emergency collision avoidance of autonomous vehicles when the front vehicle is unstable and sliding under high-speed conditions, a research method for the state recognition of the front side-skid vehicle and the trajectory prediction of the front [...] Read more.

In order to solve the problem of emergency collision avoidance of autonomous vehicles when the front vehicle is unstable and sliding under high-speed conditions, a research method for the state recognition of the front side-skid vehicle and the trajectory prediction of the front side-skid vehicle was proposed. By extracting the key features of the vehicle in front of the vehicle in danger of sliding to build a skidding recognition model of the vehicle in front, a skidding recognition strategy of the vehicle in front was designed based on the extracted skidding feature indexes to judge the skidding state of the vehicle in front. The state quantity of the sliding vehicle in front is selected, and the constant rotation rate and acceleration model (CTRA) is established to predict the trajectory of the sliding vehicle in front in a short time. Considering the simplified assumptions of the model and the noise in the process of sensor perception information, the Unscented Kalman Filter (UKF) is used to deal with the uncertainty in the trajectory prediction process, the possible position and covariance of the front sideslipping vehicle are calculated, and the possible future area of the front sideslipping vehicle is estimated under the condition of a probability of 0.9. Through the established Carsim and Simulink co-simulation platform, the effectiveness of the front vehicle skidding state recognition strategy and the accuracy of the trajectory prediction of the sliding vehicle are verified under the condition of high speed and low attachment. Full article

(This article belongs to the Special Issue Motion Planning and Control of Autonomous Vehicles)

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26 pages, 8624 KiB

Open AccessArticle

Analysis of the Correlation Between Electric Bus Charging Strategies and Carbon Emissions from Electricity Production

by Szabolcs Kocsis Szürke, Roland Pál and Gábor Saly

World Electr. Veh. J. 2025, 16(4), 240; https://doi.org/10.3390/wevj16040240 - 20 Apr 2025

Abstract

Reducing carbon dioxide emissions in transportation has become a priority for achieving emission targets. Transitioning to electric vehicles significantly decreases global CO₂ emissions and reduces urban noise and air pollution. The selection of efficient charging strategies for electric bus fleets substantially influences [...] Read more.

Reducing carbon dioxide emissions in transportation has become a priority for achieving emission targets. Transitioning to electric vehicles significantly decreases global CO₂ emissions and reduces urban noise and air pollution. The selection of efficient charging strategies for electric bus fleets substantially influences their environmental impact. This study analyzes the charging strategy for electric bus fleets based on real operational data from Győr, Hungary. It evaluates the impact of different charging times and strategies on CO₂ emissions, considering the energy mixes of Hungary, Poland, Germany, and Sweden. A methodology has been developed for defining sustainable and environmentally friendly charging strategies by incorporating operational conditions as well as daily, monthly, and seasonal fluctuations in emission factors. Results indicate substantial potential for emission reduction through the recommended alternative charging strategies, although further studies regarding battery lifespan and economic feasibility of infrastructure investments are recommended. The novelty of this work lies in integrating real charging data with hourly country-specific emission intensity values to assess environmental impacts dynamically. A comparative framework of four charging strategies provides quantifiable insights into emission reduction potential under diverse national energy mixes. Full article

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13 pages, 2215 KiB

Open AccessArticle

Estimation Algorithm for Vehicle Motion Parameters Based on Innovation Covariance in AC Chassis Dynamometer

by Xiaorui Zhang, Xingyuan Xu and Hengliang Shi

World Electr. Veh. J. 2025, 16(4), 239; https://doi.org/10.3390/wevj16040239 - 20 Apr 2025

Abstract

When the alternating current (AC) chassis dynamometer system measures the motion parameters of a test vehicle, it is subject to interference from measurement noise, leading to an increase in testing errors. An innovative adaptive Kalman Filtering (KF) algorithm based on innovation covariance is [...] Read more.

When the alternating current (AC) chassis dynamometer system measures the motion parameters of a test vehicle, it is subject to interference from measurement noise, leading to an increase in testing errors. An innovative adaptive Kalman Filtering (KF) algorithm based on innovation covariance is proposed. This algorithm facilitates the optimal estimation of vehicle motion parameters without necessitating prior error statistics. The loading model of the measurement and control system is optimized, enabling the precise loading of the dynamometer. The test results indicate that the testing error of the optimized algorithm for the loading model decreases from 6.4% to 1.8%. This improvement establishes a foundation for achieving accurate control of the chassis dynamometer and minimizing testing errors. Full article

(This article belongs to the Special Issue Intelligent Control and Energy Systems for Modern Mobility and Industry)

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19 pages, 4643 KiB

Open AccessArticle

Fault Diagnosis of Permanent Magnet Synchronous Motor Based on Wavelet Packet Transform and Genetic Algorithm-Optimized Back Propagation Neural Network

by Ming Ye, Run Gong, Wanjun Wu, Zhiyuan Peng and Kelin Jia

World Electr. Veh. J. 2025, 16(4), 238; https://doi.org/10.3390/wevj16040238 - 18 Apr 2025

Abstract

In this paper, a fault diagnosis method for permanent magnet synchronous motors is proposed, combining wavelet packet transform (WPT) energy feature extraction and a genetic algorithm (GA)-optimized back propagation (BP) neural network. Firstly, for the common types of motor faults (turn-to-turn short-circuit, phase-to-phase [...] Read more.

In this paper, a fault diagnosis method for permanent magnet synchronous motors is proposed, combining wavelet packet transform (WPT) energy feature extraction and a genetic algorithm (GA)-optimized back propagation (BP) neural network. Firstly, for the common types of motor faults (turn-to-turn short-circuit, phase-to-phase short-circuit, loss of magnetism, inverter open-circuit, rotor eccentricity), a corresponding motor fault model is established. The stator current signals during motor operation are analyzed using wavelet packet transform, and energy features are extracted from them as feature vectors for fault diagnosis. Then, a BP neural network is constructed, and a genetic algorithm is used to optimize its initial weights and thresholds, thereby improving the network’s classification accuracy. The results show that the GA-BP model outperforms the SSA-PNN diagnostic model in terms of fault classification accuracy. In particular, for the diagnosis of normal operation, inverter open-circuit, and demagnetization faults, the accuracy rate reaches 100%. This method demonstrates high diagnostic accuracy and practical application value. Full article

(This article belongs to the Special Issue Permanent Magnet Motors and Driving Control for Electric Vehicles)

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19 pages, 6428 KiB

Open AccessArticle

Design, Modeling, and Experimental Validation of a Hybrid Piezoelectric–Magnetoelectric Energy-Harvesting System for Vehicle Suspensions

by Hicham Mastouri, Amine Ennawaoui, Mohammed Remaidi, Erroumayssae Sabani, Meryiem Derraz, Hicham El Hadraoui and Chouaib Ennawaoui

World Electr. Veh. J. 2025, 16(4), 237; https://doi.org/10.3390/wevj16040237 - 18 Apr 2025

Abstract

The growing demand for sustainable and self-powered technologies in automotive applications has led to increased interest in energy harvesting from vehicle suspensions. Recovering mechanical energy from road-induced vibrations offers a viable solution for powering wireless sensors and autonomous electronic systems, reducing dependence on [...] Read more.

The growing demand for sustainable and self-powered technologies in automotive applications has led to increased interest in energy harvesting from vehicle suspensions. Recovering mechanical energy from road-induced vibrations offers a viable solution for powering wireless sensors and autonomous electronic systems, reducing dependence on external power sources. This study presents the design, modeling, and experimental validation of a hybrid energy-harvesting system that integrates piezoelectric and magnetoelectric effects to efficiently convert mechanical vibrations into electrical energy. A model-based systems engineering (MBSE) approach was used to optimize the system architecture, ensuring high energy conversion efficiency, durability, and seamless integration into suspension systems. The theoretical modeling of both piezoelectric and magnetoelectric energy harvesting mechanisms was developed, providing analytical expressions for the harvested power as a function of system parameters. The designed system was then fabricated and tested under controlled mechanical excitations to validate the theoretical models. Experimental results demonstrate that the hybrid system achieves a maximum power output of 16 µW/cm² from the piezoelectric effect and 3.5 µW/cm² from the magnetoelectric effect. The strong correlation between theoretical predictions and experimental measurements confirms the feasibility of this hybrid approach for self-powered automotive applications. Full article

(This article belongs to the Special Issue Design, Modelling and Control Strategies for Hybrid and Electric Vehicles)

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