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
A Study on the Performance Improvement of a Conical Bucket Detection Algorithm Based on YOLOv8s
World Electr. Veh. J. 2024, 15(6), 238; https://doi.org/10.3390/wevj15060238 (registering DOI) - 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
by
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 (registering DOI) - 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.
Full article
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 (registering DOI) - 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.
Full article
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 (registering DOI) - 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.
Full article
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 (registering DOI) - 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.
Full article
(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
by
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
by
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.
Full article
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Open AccessArticle
Application of Improved Ant Colony Algorithm in Optimizing the Charging Path of Electric Vehicles
by
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.
Full article
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.
Full article
(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.
Full article
(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
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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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Open AccessArticle
Analysis of Leakage Current in Dynamic Wireless Power Transfer Systems Based on LCC-S Architecture
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Siyu Hou, Benhui Zhang, Yanjin Hou, Xuenan Sun, Tongkun Zhang, Xiaoyu Zhang and Qianfang Sun
World Electr. Veh. J. 2024, 15(6), 225; https://doi.org/10.3390/wevj15060225 - 22 May 2024
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This paper investigates the issue of leakage current at the transmitter in the Dynamic Wireless Power Transfer (DWPT) system for electric vehicles and puts forward a novel bilateral resonant compensation topology structure based on the conventional LCC-S architecture. Based on the LCC-S framework,
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This paper investigates the issue of leakage current at the transmitter in the Dynamic Wireless Power Transfer (DWPT) system for electric vehicles and puts forward a novel bilateral resonant compensation topology structure based on the conventional LCC-S architecture. Based on the LCC-S framework, a circuit model was developed for traditional (unilateral)/bilateral resonant compensation topologies. The Fourier series voltage-to-earth expansions for the power supply rail were deduced for both topologies. Subsequently, the voltage-to-earth waveforms for the power supply rail were obtained by utilizing the Fourier series expansions of the voltage-to-earth and the corresponding circuit simulation models. The results demonstrate the efficacy of the bilateral resonant compensation topology in mitigating higher-order harmonics of the voltage to earth on the power supply rail by effectively suppressing the distortion in the leakage current and minimizing its conduction. The effectiveness of the double-ended resonant compensation topology in suppressing leakage current conduction has been verified through experimental tests and waveform comparisons of the voltage to earth and leakage current on the power supply rail under two different topologies. Through experimental testing, during which the unilateral/bilateral resonant compensation topologies were compared, an analysis was conducted on the waveforms of the voltage to earth and leakage current of the power supply rail. The results verified the effectiveness of the bilateral resonant compensation topology in mitigating the conduction of leakage current. This study provides empirical evidence supporting the use of the bilateral resonant compensation topology for suppressing leakage current in power rail applications.
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Open AccessArticle
A Predictive Cabin Conditioning Strategy for Battery Electric Vehicles
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Patrick Schutzeich, Stefan Pischinger, David Hemkemeyer, Kai Franke and Paul Hamelbeck
World Electr. Veh. J. 2024, 15(6), 224; https://doi.org/10.3390/wevj15060224 - 22 May 2024
Abstract
This paper is based on the work presented at EVS36 in Sacramento. The core of the work deals with the cabin climate control of battery electric vehicles (BEV) using model predictive control (MPC) approaches. These aim to reduce the energy demand for cabin
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This paper is based on the work presented at EVS36 in Sacramento. The core of the work deals with the cabin climate control of battery electric vehicles (BEV) using model predictive control (MPC) approaches. These aim to reduce the energy demand for cabin air conditioning while maintaining comfort and air quality. The first step briefly overviews model predictive control approaches and the respective fundamentals. Afterward, the modeling for the system dynamics is explained. The challenge for the system model considering humid air is discussed, and the first implementation method is presented. With the added equations for the air quality and humidity, a logic to prevent window fogging was developed to improve safety. Ultimately, model-in-the-loop (MiL) investigations identified an energy-saving potential of up to 15.4% for cold and 39.7% for hot conditions compared to a rule-based strategy. In addition, the investigations carried out showed that it was also possible to improve indoor comfort by specifically influencing the air quality and humidity. Together with the safety criteria introduced to prevent window fogging, it was possible to present a strategy that can significantly improve thermal management for the cabin in modern BEVs.
Full article
(This article belongs to the Special Issue EVS36—International Electric Vehicle Symposium and Exhibition (California, USA))
Open AccessArticle
Analysis of the Driving Range Evaluation Method for Fuel-Cell Electric Vehicles
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Ting Guo, Letian Sun, Guozhuo Wang and Shiyu Wu
World Electr. Veh. J. 2024, 15(6), 223; https://doi.org/10.3390/wevj15060223 - 21 May 2024
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The range is one of the most important performance indicators for fuel-cell electric vehicles. This article focuses on the analysis of GB/T 43252-2023 “Energy Consumption and Range Test Methods for Fuel-Cell Electric Vehicles” from the perspective of a standard analysis, and conducts actual
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The range is one of the most important performance indicators for fuel-cell electric vehicles. This article focuses on the analysis of GB/T 43252-2023 “Energy Consumption and Range Test Methods for Fuel-Cell Electric Vehicles” from the perspective of a standard analysis, and conducts actual vehicle tests on the range test method and process. It introduces the measurement method of hydrogen gas filling for test vehicles, and explains the main content of the new standard revision and the main differences between the new and old standards. This article takes the fuel-cell dump truck as an example, and analyzed the relationship between the output power of fuel-cell stacks and power batteries during vehicle operation and driving conditions, as well as the proportion of fuel cell output power. The results show that the optimal output power range of fuel cells is 20–40 kW, accounting for 45.2% of the total operating time. When driving at high speeds, the output power of fuel cells is greater than that of power batteries.
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Open AccessArticle
Advancements in Battery Management Systems for Electric Vehicles: A MATLAB-Based Simulation of 4S3P Lithium-Ion Battery Packs
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Rakesh P. Tapaskar, Prashant P. Revankar and Sharanabasava V. Ganachari
World Electr. Veh. J. 2024, 15(6), 222; https://doi.org/10.3390/wevj15060222 - 21 May 2024
Abstract
As electric vehicles (EVs) gain momentum in the shift towards sustainable transportation, the efficiency and reliability of energy storage systems become paramount. Lithium-ion batteries stand at the forefront of this transition, necessitating sophisticated battery management systems (BMS) to enhance their performance and lifespan.
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As electric vehicles (EVs) gain momentum in the shift towards sustainable transportation, the efficiency and reliability of energy storage systems become paramount. Lithium-ion batteries stand at the forefront of this transition, necessitating sophisticated battery management systems (BMS) to enhance their performance and lifespan. This research presents an innovative simulation of a 4S3P lithium-ion battery pack using MATLAB R2023b, designed to refine BMS capabilities by employing advanced mathematical modelling and computational intelligence. The simulation meticulously analyses critical operational metrics such as state of charge (SOC), state of health (SOH), temperature variations, and electrical behaviour under diverse load scenarios, offering deep insights into the intricate dynamics of lithium-ion batteries in EV applications. The results corroborate the simulation model’s accuracy in reflecting actual battery pack performance and underscore significant improvements in BMS strategies, especially concerning predictive maintenance and adaptive charging techniques. By seamlessly integrating computational intelligence into BMS, this study lays the groundwork for more durable, efficient, and intelligent energy storage systems in electric vehicles, marking a significant stride in e-mobility technology.
Full article
(This article belongs to the Special Issue Lithium-Ion Batteries for Electric Vehicle)
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Open AccessViewpoint
Path-Following Control of Unmanned Vehicles Based on Optimal Preview Time Model Predictive Control
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Xinyu Wang, Xiao Ye, Yipeng Zhou and Cong Li
World Electr. Veh. J. 2024, 15(6), 221; https://doi.org/10.3390/wevj15060221 - 21 May 2024
Abstract
In order to reduce the lateral error of path-following control of unmanned vehicles under variable curvature paths, we propose a path-following control strategy for unmanned vehicles based on optimal preview time model predictive control (OP-MPC). The strategy includes the longitudinal speed limit, the
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In order to reduce the lateral error of path-following control of unmanned vehicles under variable curvature paths, we propose a path-following control strategy for unmanned vehicles based on optimal preview time model predictive control (OP-MPC). The strategy includes the longitudinal speed limit, the optimal preview time surface, and the model predictive control (MPC)controller. The longitudinal speed limit controls speed to prevent vehicle rollover and sideslip. The optimal preview time surface adjusts the preview time according to the vehicle speed and path curvature. The preview point determined by the preview time is used as the reference waypoint of OP-MPC controller. Finally, the effectiveness of the strategy was verified through simulation and with the real unmanned vehicle. The maximum lateral deviation obtained by the OP-MPC controller was reduced from 0.522 m to 0.145 m under the simulation compared with an MPC controller. The maximum lateral deviation obtained by the OP-MPC controller was reduced from 0.5185 m to 0.2298 m under the real unmanned vehicle compared with the MPC controller.
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(This article belongs to the Special Issue Vehicle-Road Collaboration and Connected Automated Driving)
Open AccessArticle
Impact of Engine Inertia on P2 Mild HEV Fuel Consumption
by
Gulnora Yakhshilikova, Sanjarbek Ruzimov, Andrea Tonoli and Akmal Mukhitdinov
World Electr. Veh. J. 2024, 15(5), 220; https://doi.org/10.3390/wevj15050220 - 19 May 2024
Abstract
The energy management system (EMS) of a hybrid electric vehicle (HEV) is an algorithm that determines the power split between the electrical and thermal paths. It defines the operating state of the power sources, i.e., the electric motor (EM) and the internal combustion
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The energy management system (EMS) of a hybrid electric vehicle (HEV) is an algorithm that determines the power split between the electrical and thermal paths. It defines the operating state of the power sources, i.e., the electric motor (EM) and the internal combustion engine (ICE). It is therefore one of the main factors that can significantly influence the fuel consumption and performance of hybrid vehicles. In the transmission path, the power generated by the ICE is in part employed to accelerate the rotating components of the powertrain, such as the crankshaft, flywheel, gears, and shafts. The main inertial components are the crankshaft and the flywheel. This additional power is significant during high-intensity acceleration. Therefore, the actual engine operation is different from that required by the power split unit. This study focuses on exploring the influence of engine inertia on HEV fuel consumption by developing a controller based on an equivalent consumption minimisation strategy (ECMS) that considers crankshaft and flywheel inertia. The optimal solution obtained by the ECMS controller is refined by incorporating the inertia effect of the main rotating components of the engine into the cost function. This reduces the engine operation during high inertial torque transient phases, resulting in a decrease in vehicle CO2 emissions by 2.34, 2.22, and 1.13 g/km for the UDDS, US06, and WLTC driving cycles, respectively.
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(This article belongs to the Special Issue Vehicle Dynamics Control to Enhance Energy Efficiency and Safety of Electric and Hybrid Vehicles)
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Open AccessArticle
Advancements in Battery Cell Finalization: Insights from an Expert Survey and Prospects for Process Optimization
by
Tobias Robben, Christian Offermanns, Heiner Heimes and Achim Kampker
World Electr. Veh. J. 2024, 15(5), 219; https://doi.org/10.3390/wevj15050219 - 17 May 2024
Abstract
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Battery cell finalization is a crucial process chain in battery manufacturing, contributing to a significant share of CAPEX and OPEX. Thus, there is a high cost-saving potential by improving the process chain. This research paper investigates various crucial facets of the cell finalization
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Battery cell finalization is a crucial process chain in battery manufacturing, contributing to a significant share of CAPEX and OPEX. Thus, there is a high cost-saving potential by improving the process chain. This research paper investigates various crucial facets of the cell finalization process in battery cell production through an expert survey. These include investment cost allocation, potential cost savings in sub-processes, reject generation, early detection of faulty cells, quality measurement techniques, and the utilization of inline data for early quality determination and real-time process control during the formation process. A solution approach for the implementation of electrochemical impedance spectroscopy for inline early quality determination is given. The results yield valuable insights for optimizing the formation process and enhancing product quality.
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