Journal Description
World Electric Vehicle Journal
World Electric Vehicle Journal
is the first peer-reviewed, international, scientific journal that comprehensively covers all studies related to battery, hybrid, and fuel cell electric vehicles. The journal is owned by the World Electric Vehicle Association (WEVA) and its members, the European Association for e-Mobility (AVERE), Electric Drive Transportation Association (EDTA), and Electric Vehicle Association of Asia Pacific (EVAAP). It has been published monthly online by MDPI since Volume 9, Issue 1 (2018).
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, ESCI (Web of Science), Ei Compendex, and other databases.
- Journal Rank: CiteScore - Q2 (Automotive Engineering)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 14.1 days after submission; acceptance to publication is undertaken in 3.7 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
2.3 (2022)
Latest Articles
Beyond Tailpipe Emissions: Life Cycle Assessment Unravels Battery’s Carbon Footprint in Electric Vehicles
World Electr. Veh. J. 2024, 15(6), 245; https://doi.org/10.3390/wevj15060245 (registering DOI) - 2 Jun 2024
Abstract
While electric vehicles (EVs) offer lower life cycle greenhouse gas emissions in some regions, the concern over the greenhouse gas emissions generated during battery production is often debated. This literature review examines the true environmental trade-offs between conventional lithium-ion batteries (LIBs) and emerging
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While electric vehicles (EVs) offer lower life cycle greenhouse gas emissions in some regions, the concern over the greenhouse gas emissions generated during battery production is often debated. This literature review examines the true environmental trade-offs between conventional lithium-ion batteries (LIBs) and emerging technologies such as solid-state batteries (SSBs) and sodium-ion batteries (SIBs). It emphasizes the carbon-intensive nature of LIB manufacturing and explores how alternative technologies can enhance efficiency while reducing the carbon footprint. We have used a keyword search technique to review articles related to batteries and their environmental performances. The study results reveal that the greenhouse gas (GHG) emissions of battery production alone range from 10 to 394 kgCO2 eq./kWh. We identified that lithium manganese cobalt oxide and lithium nickel cobalt aluminum oxide batteries, despite their high energy density, exhibit higher GHGs (20–394 kgCO2 eq./kWh) because of the cobalt and nickel production. Lithium iron phosphate (34–246 kgCO2 eq./kWh) and sodium-ion (40–70 kgCO2 eq./kWh) batteries showed lower environmental impacts because of the abundant feedstock, emerging as a sustainable choice, especially when high energy density is not essential. This review also concludes that the GHGs of battery production are highly dependent on the regional grid carbon intensity. Batteries produced in China, for example, have higher GHGs than those produced in the United States (US) and European Union (EU). Understanding the GHGs of battery production is critical to fairly evaluating the environmental impact of battery electric vehicles.
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(This article belongs to the Special Issue Electric Vehicle Technology Development, Energy and Environmental Implications, and Decarbonization)
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Open AccessArticle
Research on a Multi-Strategy Improved Sand Cat Swarm Optimization Algorithm for Three-Dimensional UAV Trajectory Path Planning
by
Lili Liu, Yixin Lu, Bufan Yang, Longyue Yang, Jianyong Zhao, Yue Chen and Longhai Li
World Electr. Veh. J. 2024, 15(6), 244; https://doi.org/10.3390/wevj15060244 (registering DOI) - 31 May 2024
Abstract
In response to the issues of premature convergence, lack of population diversity, and poor convergence accuracy in the traditional Sand Cat Swarm Optimization (SCSO) algorithm, a Multi-Strategy Improved SCSO (MISCSO) algorithm is proposed. Firstly, multiple population strategies are used to avoid premature convergence
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In response to the issues of premature convergence, lack of population diversity, and poor convergence accuracy in the traditional Sand Cat Swarm Optimization (SCSO) algorithm, a Multi-Strategy Improved SCSO (MISCSO) algorithm is proposed. Firstly, multiple population strategies are used to avoid premature convergence and falling into local optima traps. Secondly, a distribution estimation learning strategy is introduced to represent the relationships between individuals, using probability models to improve algorithm performance. Next, the diversity of candidate solutions in the elite pool is utilized to expand the search space and enhance the algorithm’s ability to avoid local solutions. Lastly, a Cauchy disturbance strategy is adopted to accelerate the convergence speed of the algorithm, thereby improving the search efficiency and convergence accuracy. The experimental results of CEC2017 tests show that the improved algorithm balances convergence speed and global search capabilities effectively. Finally, the algorithm is applied to actual drone path planning and compared with six other intelligent algorithms, demonstrating the practicality and effectiveness of the improved algorithm.
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Open AccessArticle
Adaptive Fuzzy Control of an Electronic Differential Based on the Stability Criterion of the Phase Plane Method
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Shaopeng Zhu, Yekai Xu, Linlin Li, Yong Ren, Chenyang Kuang, Huipeng Chen and Jian Gao
World Electr. Veh. J. 2024, 15(6), 243; https://doi.org/10.3390/wevj15060243 - 31 May 2024
Abstract
To improve the handling stability of distributed drive electric vehicles, this paper introduces an electronic differential control strategy based on the stability criterion of the phase plane method. The strategy first plots the distributed electric vehicle’s center of mass side angle and center
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To improve the handling stability of distributed drive electric vehicles, this paper introduces an electronic differential control strategy based on the stability criterion of the phase plane method. The strategy first plots the distributed electric vehicle’s center of mass side angle and center of mass angular speed on the phase plane, and then it analyzes the vehicle’s stability under various working conditions to determine the parameters that ensure the stability performance. Subsequently, an adaptive fuzzy control strategy is employed to achieve fast and accurate distribution of the torque to each wheel, thereby enhancing the vehicle’s stability. A joint simulation platform is constructed using MATLAB/Simulink and CarSim. A comparison with the traditional electronic differential strategy demonstrates that the proposed distribution strategy based on phase plane stability exhibited excellent stability.
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(This article belongs to the Special Issue Dynamics, Control and Simulation of Electrified Vehicles)
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Research on Vertical Cooperation and Pricing Strategy of Electric Vehicle Supply Chain
by
Dou-Dou Wu
World Electr. Veh. J. 2024, 15(6), 242; https://doi.org/10.3390/wevj15060242 - 30 May 2024
Abstract
To determine a vertical cooperation strategy and address the optimal pricing problem of the electric vehicle (EV) supply chain, a supply chain system consisting of two competing EV manufacturers (M1 and M2) and a battery supplier is studied. Firstly, three
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To determine a vertical cooperation strategy and address the optimal pricing problem of the electric vehicle (EV) supply chain, a supply chain system consisting of two competing EV manufacturers (M1 and M2) and a battery supplier is studied. Firstly, three cooperation strategy models were constructed for the battery supplier and the EV manufacturers, namely: Strategy N (neither the battery supplier nor the two manufacturers cooperate with each other); Strategy I (M1 cooperates with the battery supplier); and Strategy II (M2 cooperates with the battery supplier). Then, the Stackelberg solution method was used to obtain the optimal equilibrium decisions under the three strategic models. Finally, the effect of the preference coefficient of consumers for leasing EVs per unit on the optimal equilibrium decision was analyzed. We found that: (1) The wholesale price of batteries provided by the battery supplier to M1 is always greater than to M2. (2) Strategies I and II prompt M1 and M2 to reduce the unit and fixed rental prices of EVs to some extent, while intensifying the competition between the two manufacturers in terms of EV lease prices. (3) When the consumer preference coefficient (θ) for leasing EVs per unit provided by manufacturer M1 is relatively small, the cooperation alliance S2 and the supply chain achieve the maximum profit under Strategy II; however, while θ is large, M1, cooperative alliance S1, and the entire supply chain could benefit the most under Strategy I.
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Open AccessArticle
Study on Obstacle Detection Method Based on Point Cloud Registration
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Hongliang Wang, Jianing Wang, Yixin Wang, Dawei Pi, Yijie Chen and Jingjing Fan
World Electr. Veh. J. 2024, 15(6), 241; https://doi.org/10.3390/wevj15060241 - 30 May 2024
Abstract
An efficient obstacle detection system is one of the most important guarantees for improving the active safety performance of autonomous vehicles. This paper proposes an obstacle detection method based on high-precision positioning applied to blocked zones to solve the problems of the high
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An efficient obstacle detection system is one of the most important guarantees for improving the active safety performance of autonomous vehicles. This paper proposes an obstacle detection method based on high-precision positioning applied to blocked zones to solve the problems of the high complexity of detection results, low computational efficiency, and high load in traditional obstacle detection methods. Firstly, an NDT registration method which uses the likelihood function as the optimal value of the registration score function to calculate the registration parameters is designed to match the scanning point cloud and the target point cloud. Secondly, a target reduction method combined with threshold judgment and the binary tree search algorithm is designed to filter the point cloud of non-road obstacles to improve the processing speed of the computing platform. Meanwhile, KD-tree is used to speed up the clustering process. Finally, a vehicle remote control simulation platform with the combination of a cloud platform and mobile terminal is designed to verify the effectiveness of the strategy in practical application. The results prove that the proposed obstacle detection method can improve the efficiency and accuracy of detection.
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Open AccessArticle
Theoretical Analysis of Plate-Type Thermoelectric Generator for Fluid Waste Heat Recovery Using Thermal Resistance and Numerical Models
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Yongfei Jia, Ruochen Wang and Jie Chen
World Electr. Veh. J. 2024, 15(6), 240; https://doi.org/10.3390/wevj15060240 - 30 May 2024
Abstract
In current research, there are excessive assumptions and simplifications in the mathematical models developed for thermoelectric generators. In this study, a comprehensive mathematical model was developed based on a plate-type thermoelectric generator divided into multiple thermoelectric units. The model takes into account temperature-dependent
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In current research, there are excessive assumptions and simplifications in the mathematical models developed for thermoelectric generators. In this study, a comprehensive mathematical model was developed based on a plate-type thermoelectric generator divided into multiple thermoelectric units. The model takes into account temperature-dependent thermoelectric material parameters and fluid flow. The model was validated, and a maximum error of 6.4% was determined. Moreover, the model was compared and analyzed with a numerical model, with a maximum discrepancy of 7.2%. The model revealed the factors and their degree of influence on the performance of the thermoelectric generator unit. In addition, differences in temperature distribution, output power, and conversion efficiency between multiple thermoelectric units were clearly studied. This study can guide modeling and some optimization measures to improve the overall performance of thermoelectric generators.
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(This article belongs to the Special Issue Electric Vehicle Technology Development, Energy and Environmental Implications, and Decarbonization)
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Open AccessArticle
Decoupled Adaptive Motion Control for Unmanned Tracked Vehicles in the Leader-Following Task
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Jingjing Fan, Pengxiang Yan, Ren Li, Yi Liu, Falong Wang, Yingzhe Liu and Chang Chen
World Electr. Veh. J. 2024, 15(6), 239; https://doi.org/10.3390/wevj15060239 - 30 May 2024
Abstract
As a specific task for unmanned tracked vehicles, leader-following imposes high-precision requirements on the vehicle’s motion control, especially the steering control. However, due to characteristics such as the frequent changes in off-road terrain and steering resistance coefficients, controlling tracked vehicles poses significant challenges,
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As a specific task for unmanned tracked vehicles, leader-following imposes high-precision requirements on the vehicle’s motion control, especially the steering control. However, due to characteristics such as the frequent changes in off-road terrain and steering resistance coefficients, controlling tracked vehicles poses significant challenges, making it difficult to achieve stable and precise leader-following. This paper decouples the leader-following control into speed and curvature control to address such issues. It utilizes model reference adaptive control to establish reference models for the speed and curvature subsystems and designs corresponding parameter adaptive control laws. This control method enables the actual vehicle speed and curvature to effectively track the response of the reference model, thereby addressing the impact of frequent changes in the steering resistance coefficient. Furthermore, this paper demonstrates significant improvements in leader-following performance through a series of simulations and experiments. Compared with the traditional PID control method, the results shows that the maximum following distance has been reduced by at least approximately 12% (ensuring the ability to keep up with the leader), the braking distance has effectively decreased by 22% (ensuring a safe distance in an emergency braking scenario and improving energy recovery), the curvature tracking accuracy has improved by at least 11% (improving steering performance), and the speed tracking accuracy has increased by at least 3.5% (improving following performance).
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(This article belongs to the Special Issue Intelligent Electric Vehicle Control, Testing and Evaluation)
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Open AccessArticle
A Study on the Performance Improvement of a Conical Bucket Detection Algorithm Based on YOLOv8s
by
Xu Li, Gang Li and Zhe Zhang
World Electr. Veh. J. 2024, 15(6), 238; https://doi.org/10.3390/wevj15060238 - 29 May 2024
Abstract
In driverless formula car racing, cone detection faces two significant challenges: one is recognizing cones at long distances accurately, and the other is being prone to leakage under bright light conditions. These challenges directly affect the detection accuracy and response speed. In order
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In driverless formula car racing, cone detection faces two significant challenges: one is recognizing cones at long distances accurately, and the other is being prone to leakage under bright light conditions. These challenges directly affect the detection accuracy and response speed. In order to cope with these problems, the thesis is based on YOLOv8s to improve the cone bucket detection algorithm. Firstly, a P2 detection layer for detecting tiny objects is added on top of YOLOv8s to detect small targets with 160 × 160 pixels, which improves the detection of small conical buckets in the distant view. At the same time, to reduce the network’s complexity to achieve lightweightness, the original 20 × 20 pixel detection header is deleted. Second, the head of the original YOLOv8 is replaced with a multi-scale fusion Dynamic Head, designed to improve the head’s ability in scale, space, and task perception to enhance the detection performance of the model in complex scenes. Again, a novel loss function, MPDIoU, is introduced, which has advantages in simplifying the bounding box similarity comparison, and it can adapt to the overlapping or non-overlapping situation of the bounding box more effectively. It reduces the phenomenon of missed detection caused by overlapping conical buckets. Finally, the LAMP pruning method is used to trim the model to make the model lightweight. By adding and modifying the above modules, the improved algorithm improves the detection accuracy from 92.2% to 95.2%, the recall rate from 84.2% to 91.8%, and the average accuracy from 91.3% to 96%, while the number of parameters is reduced from 28.7 M to 26.6 M. The detection speed still meets the real-time requirement in real-vehicle testing compared to the original algorithm. In the real car test, compared with the original algorithm, the improved algorithm shows apparent advantages in reducing the missed detection of cones and barrels, which meets the demand for high accuracy of cones and barrel detection in the complex race environment and also meets the conditions for deployment on small devices with limited resources.
Full article
(This article belongs to the Special Issue Electric Vehicle Autonomous Driving Based on Image Recognition)
Open AccessArticle
Vehicle Trajectory-Prediction Method Based on Driver Behavior-Classification and Informer Models
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Jianyu Su, Muyang Li, Langqian Zhu, Sijia Zhang and Mingjian Liu
World Electr. Veh. J. 2024, 15(6), 237; https://doi.org/10.3390/wevj15060237 - 29 May 2024
Abstract
In order to improve the accuracy of vehicle trajectories and ensure driving safety, and considering the differences in driver behavior and the impact of these differences on vehicle trajectories, a vehicle trajectory-prediction method (DBC-Informer) based on the categorization of driver behavior is proposed:
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In order to improve the accuracy of vehicle trajectories and ensure driving safety, and considering the differences in driver behavior and the impact of these differences on vehicle trajectories, a vehicle trajectory-prediction method (DBC-Informer) based on the categorization of driver behavior is proposed: firstly, the characteristic driver feature data are extracted through data preprocessing; secondly, descriptive statistical data are obtained through the classification of the driver’s behavior into categories; finally, based on the Informer model, a two-layer driver category trajectory-prediction network architecture is established, which inputs the vehicle trajectories of different driving types into independent prediction sub-networks, respectively, to realize the accurate prediction of vehicle trajectories. The experimental results show that the MAE and MSE values of trajectory prediction of the DBC-Informer model in different time domains are much smaller than those of other comparative models, and the improvement of accuracy is more obvious in the long-term domain trajectory-prediction task scenario, and the increase in prediction error of the DBC-Informer model is significantly reduced after the prediction time exceeds 1 s. The on-line behavioral categorization is achieved by comparing different categorization models; it reaches 98% in classification accuracy and, according to the results of ablation experiments, the addition of the driver behavior-classification method to the prediction model improves the accuracy of prediction in longitudinal and lateral motion by 56% and 61%, respectively, which verifies the effectiveness of the driver behavior-classification method. It can be seen that the DBC-Informer model can more accurately portray the effects of different driving behaviors on vehicle trajectories and improve the accuracy of vehicle trajectory prediction, which provides important data support for vehicle warning systems.
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Open AccessArticle
A Scalable Joint Estimation Algorithm for SOC and SOH of All Individual Cells within the Battery Pack and Its HIL Implementation
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Yongshan Liu, Di Zhang, Fan Wang, Tengfei Huang, Yuanbin Yu and Fangjie Sun
World Electr. Veh. J. 2024, 15(6), 236; https://doi.org/10.3390/wevj15060236 - 29 May 2024
Abstract
Accurately obtaining the state of charge (SOC) and health (SOH) of all individual batteries in a battery pack can provide support for data acquisition, state estimation, and fault diagnosis. To verify the real-time performance and accuracy of the joint estimation algorithm for high-voltage
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Accurately obtaining the state of charge (SOC) and health (SOH) of all individual batteries in a battery pack can provide support for data acquisition, state estimation, and fault diagnosis. To verify the real-time performance and accuracy of the joint estimation algorithm for high-voltage battery packs composed of 96 individual cells in series, this article applies Simulink to develop a joint estimation algorithm for SOC and SOH based on the first-order RC equivalent circuit model (1RC ECM) and implements the algorithm’s cyclic calling for series nodes, enhancing the algorithm’s scalability. In the algorithm, the recursive least square method with fitting factor (FFRLS) is applied to calculate OCV, R0, and R1 in the time domain, and dual adaptive extended Kalman filter (DAEKF) is applied to joint estimation of SOC and SOH at multiple time scales. Finally, with the help of dSPACE and FASECU controllers, hardware in the loop (HIL) testing was completed in multiple scenarios. The results showed that the algorithm can accurately calculate the state of individual cells in real time, and even under various initial value deviations, it still has good regression performance, laying the foundation for future applications of electric vehicles.
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Open AccessReview
Review and Evaluation of Automated Charging Technologies for Heavy-Duty Vehicles
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Emma Piedel, Enrico Lauth, Alexander Grahle and Dietmar Göhlich
World Electr. Veh. J. 2024, 15(6), 235; https://doi.org/10.3390/wevj15060235 - 29 May 2024
Abstract
Automated charging technologies are becoming increasingly important in the electrification of heavy road freight transport, especially in combination with autonomous driving. This study provides a comprehensive analysis of automated charging technologies for electric heavy-duty vehicles (HDVs). It encompasses the entire spectrum of feasible
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Automated charging technologies are becoming increasingly important in the electrification of heavy road freight transport, especially in combination with autonomous driving. This study provides a comprehensive analysis of automated charging technologies for electric heavy-duty vehicles (HDVs). It encompasses the entire spectrum of feasible technologies, including static and dynamic approaches, with each charging technology evaluated for its advantages, potentials, challenges and technology readiness level (TRL). Static conductive charging methods such as charging robots, underbody couplers, or pantographs show good potential, with pantographs being the most mature option. These technologies are progressing towards higher TRLs, with a focus on standardization and adaptability. While static wireless charging is operational for some prototype solutions, it encounters challenges related to implementation and efficiency. Dynamic conductive charging through an overhead contact line or contact rails holds promise for high-traffic HDV routes with the overhead contact line being the most developed option. Dynamic wireless charging, although facing efficiency challenges, offers the potential for seamless integration into roads and minimal wear and tear. Battery swapping is emerging as a practical solution to reduce downtime for charging, with varying levels of readiness across different implementations. To facilitate large-scale deployment, further standardization efforts are required. This study emphasizes the necessity for continued research and development to enhance efficiency, decrease costs and ensure seamless integration into existing infrastructures. Technologies that achieve this best will have the highest potential to significantly contribute to the creation of an efficiently automated and environmentally friendly transport sector.
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Open AccessArticle
A Path-Planning Approach for an Unmanned Vehicle in an Off-Road Environment Based on an Improved A* Algorithm
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Gaoyang Xie, Liqing Fang, Xujun Su, Deqing Guo, Ziyuan Qi, Yanan Li and Jinli Che
World Electr. Veh. J. 2024, 15(6), 234; https://doi.org/10.3390/wevj15060234 - 29 May 2024
Abstract
Path planning for an unmanned vehicle in an off-road uncertain environment is important for navigation safety and efficiency. Regarding this, a global improved A* algorithm is presented. Firstly, based on remote sensing images, the artificial potential field method is used to describe the
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Path planning for an unmanned vehicle in an off-road uncertain environment is important for navigation safety and efficiency. Regarding this, a global improved A* algorithm is presented. Firstly, based on remote sensing images, the artificial potential field method is used to describe the distribution of risk in the uncertain environment, and all types of ground conditions are converted into travel time costs. Additionally, the improvements of the A* algorithm include a multi-directional node search algorithm, and a new line-of-sight algorithm is designed which can search sub-nodes more accurately, while the risk factor and the passing-time cost factor are added to the cost function. Finally, three kinds of paths can be calculated, including the shortest path, the path of less risk, and the path of less time-cost. The results of the simulation show that the improved A* algorithm is suitable for the path planning of unmanned vehicles in a complex and uncertain environment. The effectiveness of the algorithm is verified by the comparison between the simulation and the actual condition verification.
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(This article belongs to the Special Issue Cooperative Perception, Communication and Computing for Autonomous Vehicles)
Open AccessArticle
Study on the Emission of Connected Autonomous Vehicle Considering the Control of Electronic Throttle Opening
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Yirong Kang and Chuan Tian
World Electr. Veh. J. 2024, 15(6), 233; https://doi.org/10.3390/wevj15060233 - 28 May 2024
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Aiming at the networked cruise control scenario of CAV (connected autonomous vehicle) queue, we propose a new networked cruise control strategy for CAV by introducing the average information of ET (electronic throttle) opening of the downstream vehicle group as a feedback signal. By
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Aiming at the networked cruise control scenario of CAV (connected autonomous vehicle) queue, we propose a new networked cruise control strategy for CAV by introducing the average information of ET (electronic throttle) opening of the downstream vehicle group as a feedback signal. By performing linear stability analysis on the new model, we derive its linear stability conditions. Further, we design exhaustive numerical simulation experiments aiming to systematically investigate the effect of the multi-vehicle ahead electronic throttle opening average feedback signal on CAV traffic stability, fuel consumption, and key emission factors, such as CO, HC, and NOx, during the cruise control process. The results show that the feedback signal can not only significantly improve the operational stability of the CAV traffic flow but also significantly improve its fuel consumption and the emission levels of CO, HC, and NOx. When the number of CAV vehicles in the feedback signal is set to three, the levels of CO, HC, and NOx emissions as well as fuel consumption in the road system can reach a stable and optimized state.
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Open AccessArticle
Design and Optimization of External Rotor Consequent Pole Permanent Magnet Motor with Low Iron Loss and Low Torque Ripple
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Liyan Guo, Hubin Yu and Huimin Wang
World Electr. Veh. J. 2024, 15(6), 232; https://doi.org/10.3390/wevj15060232 - 28 May 2024
Abstract
To reduce the iron loss and torque ripple of an external rotor consequent pole (ERCP) motor used in an electric vehicle air-conditioning compressor, the magnetic pole structure of the motor was improved, and an unequal piecewise consequent pole (CP) structure was designed. The
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To reduce the iron loss and torque ripple of an external rotor consequent pole (ERCP) motor used in an electric vehicle air-conditioning compressor, the magnetic pole structure of the motor was improved, and an unequal piecewise consequent pole (CP) structure was designed. The performance of the motor is optimized by reducing the harmonic content in the air gap flux density and reducing the iron saturation degree of the motor. The designed CP structure can significantly reduce the iron loss and torque ripple of the motor. Based on the Taguchi method, the optimal size parameters of the unequal piecewise CP structure are determined, and the final optimization design scheme is obtained. The results of finite element simulation and high-precision iron loss model show the following: compared with the original motor, the iron loss and torque ripple of the motor with the final optimized design scheme are significantly reduced.
Full article
(This article belongs to the Special Issue Design and Control of Electrical Machines in Electric Vehicles, 2nd Edition)
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Open AccessArticle
Control of Pivot Steering for Bilateral Independent Electrically Driven Tracked Vehicles Based on GWO-PID
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Jun Liu, Shuoyan Yang and Ziheng Xia
World Electr. Veh. J. 2024, 15(6), 231; https://doi.org/10.3390/wevj15060231 - 27 May 2024
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In this study, the optimization problem for controlling the pivot steering function of tracked vehicles is addressed. Firstly, kinematic modeling of the pivot steering process of tracked vehicles is conducted. Secondly, the control system of tracked vehicles is decoupled, and PID control algorithms
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In this study, the optimization problem for controlling the pivot steering function of tracked vehicles is addressed. Firstly, kinematic modeling of the pivot steering process of tracked vehicles is conducted. Secondly, the control system of tracked vehicles is decoupled, and PID control algorithms for vehicle speed and yaw rate are separately designed. Furthermore, the parameters of the PID controllers are optimized using the Grey Wolf Optimizer algorithm. Finally, by constructing a joint simulation model using Matlab/Simulink + RecurDyn (V9R4), the simulation results indicate that the above control algorithm can effectively improve the tracking speed of tracked vehicles on vehicle speed and yaw rate under the pivot steering condition, quickly respond to the driver’s driving intention, and ensure the stability of the pivot steering process, providing an effective basis for further research on the pivot steering function of tracked vehicles.
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Open AccessArticle
Application of Improved Ant Colony Algorithm in Optimizing the Charging Path of Electric Vehicles
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Zhiqun Qi
World Electr. Veh. J. 2024, 15(6), 230; https://doi.org/10.3390/wevj15060230 - 24 May 2024
Abstract
In current traffic congestion scenarios, electric vehicles (EVs) have the problem of reduced battery life and continuous decline in endurance. Therefore, this study proposes an optimization method for electric vehicle charging scheduling based onthe ant colony optimization algorithm with adaptive dynamic search (ADS-ACO),
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In current traffic congestion scenarios, electric vehicles (EVs) have the problem of reduced battery life and continuous decline in endurance. Therefore, this study proposes an optimization method for electric vehicle charging scheduling based onthe ant colony optimization algorithm with adaptive dynamic search (ADS-ACO), and conducts experimental verification on it. The experiment revealed that in the four benchmark functions, the research algorithm has the fastest convergence speed and can achieve convergence in most of them. In the validation of effectiveness, the optimal solution for vehicle time consumption under the ADS-ACO algorithm in the output of the algorithm with a stationary period and a remaining battery energy of 15 kW·h was 2.146 h in the regular road network. In the initial results of 15 kW·h under changes in road conditions from peak to peak periods, the total energy consumption of vehicles under the research algorithm was 4.678 kW·h and 4.656 kW·h under regular and irregular road networks, respectively. The change results were 4.509 kW·h and 4.656 kW·h, respectively. The initial results of 10 kW·h were 4.755 kW·h and 4.873 kW·h, respectively. The change results were 4.461 kW·h and 4.656 kW·h, respectively, which are lower than the comparison algorithm. In stability verification, research algorithms can find the optimal path under any conditions. The algorithm proposed in the study has been demonstrated to be highly effective and stable in electric vehicle charging path planning. It represents a novel solution for electric vehicle charging management and is expected to significantly enhance the range of electric vehicles in practical applications.
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Open AccessArticle
Detection and Analysis of Abnormal High-Current Discharge of Cylindrical Lithium-Ion Battery Based on Acoustic Characteristics Research
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Nan Zhou, Kunbai Wang, Xiang Shi and Zeyu Chen
World Electr. Veh. J. 2024, 15(6), 229; https://doi.org/10.3390/wevj15060229 - 24 May 2024
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The improvement of battery management systems (BMSs) requires the incorporation of advanced battery status detection technologies to facilitate early warnings of abnormal conditions. In this study, acoustic data from batteries under two discharge rates, 0.5 C and 3 C, were collected using a
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The improvement of battery management systems (BMSs) requires the incorporation of advanced battery status detection technologies to facilitate early warnings of abnormal conditions. In this study, acoustic data from batteries under two discharge rates, 0.5 C and 3 C, were collected using a specially designed battery acoustic test system. By analyzing selected acoustic parameters in the time domain, the acoustic signals exhibited noticeable differences with the change in discharge current, highlighting the potential of acoustic signals for current anomaly detection. In the frequency domain analysis, distinct variations in the frequency domain parameters of the acoustic response signal were observed at different discharge currents. The identification of acoustic characteristic parameters demonstrates a robust capability to detect short-term high-current discharges, which reflects the sensitivity of the battery’s internal structure to varying operational stresses. Acoustic emission (AE) technology, coupled with electrode measurements, effectively tracks unusually high discharge currents. The acoustic signals show a clear correlation with discharge currents, indicating that selecting key acoustic parameters can reveal the battery structure’s response to high currents. This approach could serve as a crucial diagnostic tool for identifying battery abnormalities.
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Open AccessArticle
Research on Stability Control of Distributed Drive Vehicle with Four-Wheel Steering
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Jiahao Zhang, Chengye Liu, Jingbo Zhao and Haimei Liu
World Electr. Veh. J. 2024, 15(6), 228; https://doi.org/10.3390/wevj15060228 - 23 May 2024
Abstract
The four-wheel steering distributed drive vehicle is a novel type of vehicle with independent control over the four-wheel angle and wheel torque. A method for jointly controlling the distribution of the wheel angle and torque is proposed based on this characteristic. Firstly, the
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The four-wheel steering distributed drive vehicle is a novel type of vehicle with independent control over the four-wheel angle and wheel torque. A method for jointly controlling the distribution of the wheel angle and torque is proposed based on this characteristic. Firstly, the two-degrees-of-freedom model and ideal reference model of four-wheel steering vehicle are established; then, the four-wheel steering controller and torque distribution controller are designed. The rear wheel angle is controlled by the feedforward controller and the feedback controller. The feedforward controller takes the side slip angle of the center of mass as the control target, and the feedback controller takes the yaw angle as the control target. Torque is controlled by two control layers, the additional yaw moment of the upper layer is calculated by the vehicle motion state and fuzzy control theory, and the lower layer distributes wheel torque through the road adhesion coefficient and wheel load. Finally, a simulation platform is established to verify the effectiveness of the proposed control algorithm.
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(This article belongs to the Special Issue Vehicle System Dynamics and Intelligent Control for Electric Vehicles)
Open AccessArticle
Free Riding of Vehicle Companies under Dual-Credit Policy: An Agent-Based System Dynamics Model
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Zhong Zhou and Yuqi Shen
World Electr. Veh. J. 2024, 15(6), 227; https://doi.org/10.3390/wevj15060227 - 23 May 2024
Abstract
The dual-credit policy promotes green transition in automobile companies. This paper investigates the dual-credit policy framework in the Chinese automotive industry, with a focus on the phenomenon of free riding. This occurs when traditional vehicle manufacturers within an alliance benefit from the excess
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The dual-credit policy promotes green transition in automobile companies. This paper investigates the dual-credit policy framework in the Chinese automotive industry, with a focus on the phenomenon of free riding. This occurs when traditional vehicle manufacturers within an alliance benefit from the excess credits generated by a transitioning vehicle company without fully committing to their own green transitioning. The focus of this study lies on an alliance constituted by a transitioning vehicle company in partnership with two traditional vehicle manufacturers, all interconnected via equity ties. Utilizing an agent-based system dynamics model, this study explores the strategic behaviors emerging from such credit collaborations and their consequent effects on operational efficiency and financial performance. The findings reveal that 1. free riding negatively impacts the transitioning company’s revenue but benefits the alliance by easing transition pressures and boosting collective performance; 2. stricter policies increase intra-alliance credit transfers and performance, while lower credit prices reduce transfer value and harm the transitioning company’s earnings. This study implies that transitioning vehicle companies with equity-linked partners can benefit from a nuanced understanding of how policy mechanisms interact with alliance dynamics under free riding. By adjusting credit transfer strategies in line with market conditions and policy trends, they can better navigate the dual-credit policy landscape, balancing individual profitability with the needs of the broader alliance and long-term sustainability goals.
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(This article belongs to the Special Issue New Energy Special Vehicle, Tractor and Agricultural Machinery)
Open AccessArticle
A Novel Rotor Harmonic Winding Configuration for the Brushless Wound Rotor Synchronous Machine
by
Farhan Arif, Arsalan Arif, Qasim Ali, Asif Hussain, Abid Imran, Mukhtar Ullah and Asif Khan
World Electr. Veh. J. 2024, 15(6), 226; https://doi.org/10.3390/wevj15060226 - 23 May 2024
Abstract
In the last decade, permanent magnet (PM)-free or hybrid PM machines have been extensively researched to find an alternative for high cost rare-earth PM machines. Brushless wound rotor synchronous machines (BL-WRSMs) are one of the alternatives to these PM machines. BL-WRSMs have a
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In the last decade, permanent magnet (PM)-free or hybrid PM machines have been extensively researched to find an alternative for high cost rare-earth PM machines. Brushless wound rotor synchronous machines (BL-WRSMs) are one of the alternatives to these PM machines. BL-WRSMs have a lower torque density compared to PM machines. In this paper, a new topology is introduced to improve the torque producing capability of the existing BL-WRSM by utilizing the vacant spaces in the rotor slots. The new topology has two harmonic windings placed on the rotor which induce separate currents. A capacitor is used between the two harmonic windings to bring the currents in phase with each other. The harmonic winding currents are fed to the rectifier which is also placed on the rotor. Due to additional harmonic winding, the overall field current fed to the rotor field winding has been increased and hence the average torque has also increased. Finite element analysis (FEA)-based simulations are performed using ANSYS Maxwell to validate the proposed topology. The results show that the average torque of the machine has been significantly increased compared to the reference model. The detailed comparison results are provided in this paper.
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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