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: JCR - Q2 (Transportation Science and Technology) / CiteScore - Q2 (Automotive Engineering)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 15.7 days after submission; acceptance to publication is undertaken in 3.6 days (median values for papers published in this journal in the first half of 2024).
- 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:
2.6 (2023)
Latest Articles
Distribution of the Burden of Proof in Autonomous Driving Tort Cases: Implications of the German Legislation for China
World Electr. Veh. J. 2024, 15(7), 305; https://doi.org/10.3390/wevj15070305 (registering DOI) - 12 Jul 2024
Abstract
In the realm of autonomous driving tort, a significant disparity exists in the parties’ access to autonomous driving data and essential technical information, resulting in challenges in unilateral proof. The traditional burden of proof framework in driving litigation is inadequate for direct application
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In the realm of autonomous driving tort, a significant disparity exists in the parties’ access to autonomous driving data and essential technical information, resulting in challenges in unilateral proof. The traditional burden of proof framework in driving litigation is inadequate for direct application in the autonomous driving sphere. As we approach the era of widespread autonomous driving operations, there is an urgent need to clarify and redefine the allocation of the burden of proof in specific litigations. Utilizing comparative legal analysis and case studies, this paper delves into the disparities in the legislative provisions concerning the burden of proof for autonomous driving in Germany and China. China can learn from Germany’s legislative precedence in shifting the burden of proof for “product defect” and “fault” onto the manufacturer, thereby requiring the infringed party to merely furnish preliminary evidence indicating a “causal relationship between the defect and the damage”. This approach mitigates the evidentiary burden on the aggrieved party, clarifies the litigation procedures, incentivizes manufacturers to enhance the technology, reinforces risk management, and ultimately facilitates the progression of autonomous driving technology.
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Open AccessArticle
The Impact of R&D and Non-R&D Subsidies on Technological Innovation in Chinese Electric Vehicle Enterprises
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Qiu Zhao, Zhuoqian Li and Chao Zhang
World Electr. Veh. J. 2024, 15(7), 304; https://doi.org/10.3390/wevj15070304 (registering DOI) - 11 Jul 2024
Abstract
The effectiveness of government subsidies for electric vehicle (EV) enterprises and future improvements to subsidy policies to promote industry development have garnered widespread attention. Distinct mechanisms exist through which R&D and non-R&D subsidies impact enterprise innovation. This paper differentiates between R&D and non-R&D
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The effectiveness of government subsidies for electric vehicle (EV) enterprises and future improvements to subsidy policies to promote industry development have garnered widespread attention. Distinct mechanisms exist through which R&D and non-R&D subsidies impact enterprise innovation. This paper differentiates between R&D and non-R&D subsidies and uses data from listed companies and New Third Board companies in China from 2013 to 2022 to empirically analyze the effects of these two types of subsidies on the innovation of EV enterprises from the perspectives of innovation strategy and the industrial chain. The results show that both R&D and non-R&D subsidies effectively alleviate the inhibiting effects of financing constraints. R&D subsidies significantly incentivize innovation in EV enterprises, whereas the effect of non-R&D subsidies is not as pronounced. The incentivizing effect of R&D subsidies exhibits two distinct characteristics: first, R&D subsidies compel enterprises to choose an innovation strategy that prioritizes “quantity over quality”; second, R&D subsidies exert a more pronounced influence on enterprises in the upper and middle sectors of the EV industrial chain compared to downstream enterprises, which tend to engage in more strategic innovation behaviors.
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(This article belongs to the Special Issue Electric Vehicle Technology Development, Energy and Environmental Implications, and Decarbonization)
Open AccessArticle
Development of an Improved Communication Control System for ATV Electric Vehicles Using MRS Developers Studio
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Natthapon Donjaroennon, Wattana Nambunlue, Suphatchakan Nuchkum and Uthen Leeton
World Electr. Veh. J. 2024, 15(7), 303; https://doi.org/10.3390/wevj15070303 - 9 Jul 2024
Abstract
Transmission, energy management, and distribution systems are critical components of modern electric vehicles, encompassing all sectors of the power system through communication control technology. One widely used communication system in electric vehicles is the Controller Area Network (CAN). This research aims to investigate
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Transmission, energy management, and distribution systems are critical components of modern electric vehicles, encompassing all sectors of the power system through communication control technology. One widely used communication system in electric vehicles is the Controller Area Network (CAN). This research aims to investigate the development of CAN BUS technology, adapted from large trucks, to control the communication system within an ATV electric vehicle using a communication format similar to bus Communication. The communication control system includes several components: the engine switch, headlight, turn signal, emergency light, horn, forward/reverse gear, and accelerator. The system’s communication protocols were developed using MRS Developers Studio version 1.40 software to create the data transmission and reception formats for the vehicle’s components. The communication system employs three PLC 1.033.30B.00 type E control boxes, each with limited analog and digital input/output ports. The sequence of communication control begins with the engine start/stop operation, as the system will not function unless the engine is started first. The headlight operation is processed within the CAN BUS1 control box. Simultaneously, the turn signal and emergency light functions are controlled by CAN BUS1 and displayed on both the CAN BUS2 (front of the vehicle) and CAN BUS3 (rear of the vehicle) control boxes. Additionally, the accelerator function is managed within the CAN BUS2 control box and displayed on the CAN BUS3 control box. However, this operation is contingent upon the forward/reverse gear selection, managed by CAN BUS1 and processed by CAN BUS3. All system operations are designed within the software’s programming paths. The communication system operates using CAN-High and CAN-Low lines, and communication data fields can be monitored using the PCAN-View software version 4.2.1.533. This study demonstrates the feasibility and effectiveness of adapting CAN BUS technology for ATV electric vehicles, providing insights into the integration and control of various vehicular components within a unified communication framework.
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(This article belongs to the Special Issue Cooperative Perception, Communication and Computing for Autonomous Vehicles)
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Open AccessArticle
Research on Experimental and Simulated Temperature Control Performance of Power Batteries Based on Composite Phase Change Materials
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Yanchao Dong, Xiaozhong Ma, Chao Wang and Yuejuan Xu
World Electr. Veh. J. 2024, 15(7), 302; https://doi.org/10.3390/wevj15070302 - 9 Jul 2024
Abstract
The power battery is a key component of electric vehicles and its performance is greatly affected by temperature. Battery thermal management systems based on phase change materials can effectively control the battery temperature and at the same time have the advantages of simple
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The power battery is a key component of electric vehicles and its performance is greatly affected by temperature. Battery thermal management systems based on phase change materials can effectively control the battery temperature and at the same time have the advantages of simple structures, energy savings, and good temperature uniformity, and has broad development prospects. In this paper, expanded graphite–paraffin composite phase change materials were prepared, phase change material cooling experiments were carried out, and a phase change material cooling simulation model was also established using the Fluent software to study the influence of phase change material thermophysical parameters on thermal management performance. The results show that the phase change material thermal management method has excellent cooling performance. The best thermal management performance is achieved at the 3C discharge rate, with a phase change material filling thickness of 4 mm, a melting point of 40 °C above ambient temperature, and a thermal conductivity of 3 W/(m·K). When the phase change latent heat was increased from 150 J/g to 250 J/g, the liquid phase ratio decreased from 0.84 to 0.51, and the subsequent cooling performance was greatly improved, so the phase change latent heat should be increased as much as possible.
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(This article belongs to the Topic Advanced Battery Thermal Management Solution for Electric Vehicles)
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Consumer Segmentation and Market Analysis for Sustainable Marketing Strategy of Electric Vehicles in the Philippines
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John Robin R. Uy, Ardvin Kester S. Ong, Danica Mariz B. De Guzman, Irish Tricia Dela Cruz and Juliana C. Dela Cruz
World Electr. Veh. J. 2024, 15(7), 301; https://doi.org/10.3390/wevj15070301 - 8 Jul 2024
Abstract
Despite the steady rise of electric vehicles (EVs) in other countries, the Philippines has yet to capitalize on its proliferation due to several mixed concerns. Status, socio-demographic characteristics, and availability have been the main concerns with purchasing EVs in the country. Consumer segmentation
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Despite the steady rise of electric vehicles (EVs) in other countries, the Philippines has yet to capitalize on its proliferation due to several mixed concerns. Status, socio-demographic characteristics, and availability have been the main concerns with purchasing EVs in the country. Consumer segmentation and analysis for EV acceptance and utility in the Philippines were determined in this study due to the need for understanding consumer preferences and market segmentation towards EVs in the Philippines. A total of 311 valid responses coming from EV owners were collected through purposive and snowball sampling approaches. The data were collected via face-to-face distribution and online distribution of a questionnaire covering demographic characteristics for market segmentation. Demographic data such as gender, age, residence type, car ownership, and income were used to identify consumer segments using the K-means clustering approach. Jupyter Notebook v7.1.3 was used for the overall analysis, and the number of clusters was optimized, ensuring precise segmentation. The results indicated a strong correlation between car ownership and the ability to purchase EVs, where K-means clustering effectively identified consumer groups. The groupings also included “Not Capable at All” to “Highly Capable” individuals based on their likelihood to purchase EVs. Based on the results, the core-value customers of EVs are male, older than 55 years old, live in urban areas, own a vehicle and car insurance, and have a monthly income of more than PHP 130,000. Following those are high-value customers, considered target users expected to use EVs frequently. It could be posited that customers are frequent purchasers of products and services. Based on the results, high-value customers are male, aged 36–45 years old, live in urban areas, own a car, have car insurance, and have a monthly income of PHP 100,001–130,000. Both of these should be highly considered by EV industries, as these characteristics would be the driving market of EVs in the Philippines. The constructed segmentation provided valuable insights for the EV industry, academic institutions, and policymakers, offering a foundation for targeted marketing strategies and promoting EV adoption in the Philippines. Moreover, the sustainable marketing strategies developed could be adopted and extended among other developing countries wanting to adopt EVs for utility. Future works are also suggested based on the study limitations for researchers to consider as study extensions, such as a holistic approach to EV adoption that considers environmental, social, and economic factors, as well as policies and promotion development.
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(This article belongs to the Special Issue Deep Learning Applications for Electric Vehicles)
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Open AccessArticle
An Obstacle Avoidance Trajectory Planning Methodology Based on Energy Minimization (OTPEM) for the Tilt-Wing eVTOL in the Takeoff Phase
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Guangyu Zheng, Peng Li and Dongsu Wu
World Electr. Veh. J. 2024, 15(7), 300; https://doi.org/10.3390/wevj15070300 - 6 Jul 2024
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Electric tilt-wing flying cars are an efficient, economical, and environmentally friendly solution to urban traffic congestion and travel efficiency issues. This article addresses the high energy consumption and obstacle interference during the takeoff phase of the tilt-wing eVTOL (electric Vertical Takeoff and Landing),
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Electric tilt-wing flying cars are an efficient, economical, and environmentally friendly solution to urban traffic congestion and travel efficiency issues. This article addresses the high energy consumption and obstacle interference during the takeoff phase of the tilt-wing eVTOL (electric Vertical Takeoff and Landing), proposing a trajectory planning method based on energy minimization and obstacle avoidance. Firstly, based on the dynamics analysis, the relationship between energy consumption, spatial trajectory, and obstacles is sorted out and the decision variables for the trajectory planning problem with obstacle avoidance are determined. Secondly, based on the power discretization during the takeoff phase, the energy minimization objective function is established and the constraints of performance limitations and spatial obstacles are derived. Thirdly, by integrating the optimization model with the SLSQP (Sequential Least Squares Quadratic Programming algorithm), the second-order sequential quadratic programming model and decision variable update equations are derived, establishing the solution process for the trajectory planning problem of the tilt-wing eVTOL takeoff with obstacle avoidance. Finally, the Airbus Vahana A3 is taken as an example to verify and validate the effectiveness, stability, and robustness of the model and optimization algorithm proposed. The validation results show that the OTPEM (obstacle avoidance trajectory planning methodology based on energy minimization) can effectively handle changes in the takeoff end state and exhibits good stability and robustness in different obstacle environments. It can provide a certain reference for the three-dimensional obstacle avoidance trajectory planning of Airbus Vahana A3 and other tilt-wing eVTOL trajectory planning problems.
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Open AccessArticle
Ultra-Fast Nonlinear Model Predictive Control for Motion Control of Autonomous Light Motor Vehicles
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Vaishali Patne, Pramod Ubare, Shreya Maggo, Manish Sahu, G. Srinivasa Rao, Deepak Ingole and Dayaram Sonawane
World Electr. Veh. J. 2024, 15(7), 299; https://doi.org/10.3390/wevj15070299 - 4 Jul 2024
Abstract
Advanced Driver Assistance System (ADAS) is the latest buzzword in the automotive industry aimed at reducing human errors and enhancing safety. In ADAS systems, the choice of control strategy is not straightforward due to the highly complex nonlinear dynamics, control objectives, and safety
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Advanced Driver Assistance System (ADAS) is the latest buzzword in the automotive industry aimed at reducing human errors and enhancing safety. In ADAS systems, the choice of control strategy is not straightforward due to the highly complex nonlinear dynamics, control objectives, and safety critical constraints. Nonlinear Model Predictive Control (NMPC) has evolved as a favorite option for optimal control due to its ability to handle such constrained, Multi-Input Multi-Output (MIMO) systems efficiently. However, NMPC suffers from a bottleneck of high computational complexity, making it unsuitable for fast real-time applications. This paper presents a generic framework using Successive Online Linearization-based NMPC (SOL-NMPC) for for the control in ADAS. The nonlinear system is linearized and solved using Linear Model Predictive Control every iteration. Furthermore, offset-free MPC is developed with the Extended Kalman Filter for reducing model mismatch. The developed SOL-NMPC is validated using the 14-Degrees-of-Freedom (DoF) model of a D-class light motor vehicle. The performance is simulated in matlab/Simulink and validated using the CarSim® software (Version 2016). The real-time implementation of the proposed strategy is tested in the Hardware-In-the-Loop (HIL) co-simulation using the STM32-Nucleo-144 development board. The detailed performance analysis is presented along with time profiling. It can be seen that the loss of accuracy can be counteracted by the fast response of the proposed framework.
Full article
(This article belongs to the Special Issue Advanced Vehicle System Dynamics and Control)
Open AccessArticle
Simple Method for Determining Loss Parameters of Electric Cars
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Ansgar Wego and Stefan Schubotz
World Electr. Veh. J. 2024, 15(7), 298; https://doi.org/10.3390/wevj15070298 - 3 Jul 2024
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Manufacturers of electric cars provide their vehicles with many technical data that are important for the user. This includes information on dimensions, mass, performance, consumption, battery capacity, range, payload, etc. However, some interesting parameters are usually withheld from the end user. These parameters
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Manufacturers of electric cars provide their vehicles with many technical data that are important for the user. This includes information on dimensions, mass, performance, consumption, battery capacity, range, payload, etc. However, some interesting parameters are usually withheld from the end user. These parameters include, for example, the loss in the energy flow from the battery to the driving wheels or the rolling resistance of the vehicle. However, since these loss parameters have a significant influence on the vehicle’s consumption, it is of interest to know them. This article presents a method for determining these two parameters. The basis for this are simple driving tests that can be carried out by anyone on public roads.
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Open AccessArticle
Enhanced Object Detection in Autonomous Vehicles through LiDAR—Camera Sensor Fusion
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Zhongmou Dai, Zhiwei Guan, Qiang Chen, Yi Xu and Fengyi Sun
World Electr. Veh. J. 2024, 15(7), 297; https://doi.org/10.3390/wevj15070297 - 3 Jul 2024
Abstract
To realize accurate environment perception, which is the technological key to enabling autonomous vehicles to interact with their external environments, it is primarily necessary to solve the issues of object detection and tracking in the vehicle-movement process. Multi-sensor fusion has become an essential
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To realize accurate environment perception, which is the technological key to enabling autonomous vehicles to interact with their external environments, it is primarily necessary to solve the issues of object detection and tracking in the vehicle-movement process. Multi-sensor fusion has become an essential process in efforts to overcome the shortcomings of individual sensor types and improve the efficiency and reliability of autonomous vehicles. This paper puts forward moving object detection and tracking methods based on LiDAR—camera fusion. Operating based on the calibration of the camera and LiDAR technology, this paper uses YOLO and PointPillars network models to perform object detection based on image and point cloud data. Then, a target box intersection-over-union (IoU) matching strategy, based on center-point distance probability and the improved Dempster–Shafer (D–S) theory, is used to perform class confidence fusion to obtain the final fusion detection result. In the process of moving object tracking, the DeepSORT algorithm is improved to address the issue of identity switching resulting from dynamic objects re-emerging after occlusion. An unscented Kalman filter is utilized to accurately predict the motion state of nonlinear objects, and object motion information is added to the IoU matching module to improve the matching accuracy in the data association process. Through self-collected data verification, the performances of fusion detection and tracking are judged to be significantly better than those of a single sensor. The evaluation indexes of the improved DeepSORT algorithm are 66% for MOTA and 79% for MOTP, which are, respectively, 10% and 5% higher than those of the original DeepSORT algorithm. The improved DeepSORT algorithm effectively solves the problem of tracking instability caused by the occlusion of moving objects.
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(This article belongs to the Special Issue Advanced Vehicle Dynamics Identification, Control and Observer Methods for Autonomous, Electrified Vehicles)
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Open AccessArticle
Robot Motion Planning Based on an Adaptive Slime Mold Algorithm and Motion Constraints
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Rong Chen, Huashan Song, Ling Zheng and Bo Wang
World Electr. Veh. J. 2024, 15(7), 296; https://doi.org/10.3390/wevj15070296 - 3 Jul 2024
Abstract
The rapid advancement of artificial intelligence technology has significantly enhanced the intelligence of mobile robots, facilitating their widespread utilization in unmanned driving, smart home systems, and various other domains. As the scope, scale, and complexity of robot deployment continue to expand, there arises
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The rapid advancement of artificial intelligence technology has significantly enhanced the intelligence of mobile robots, facilitating their widespread utilization in unmanned driving, smart home systems, and various other domains. As the scope, scale, and complexity of robot deployment continue to expand, there arises a heightened demand for enhanced computational power and real-time performance, with path planning emerging as a prominent research focus. In this study, we present an adaptive Lévy flight–rotation slime mold algorithm (LRSMA) for global robot motion planning, which incorporates LRSMA with the cubic Hermite interpolation. Unlike traditional methods, the algorithm eliminates the need for a priori knowledge of appropriate interpolation points. Instead, it autonomously detects the convergence status of LRSMA, dynamically increasing interpolation points to enhance the curvature of the motion curve when it surpasses the predefined threshold. Subsequently, it compares path lengths resulting from two different objective functions to determine the optimal number of interpolation points and the best path. Compared to LRSMA, this algorithm reduced the minimum path length and average processing time by (2.52%, 3.56%) and (38.89%, 62.46%), respectively, along with minimum processing times. Our findings demonstrate that this method effectively generates collision-free, smooth, and curvature-constrained motion curves with the least processing time.
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(This article belongs to the Special Issue Design Theory, Method and Control of Intelligent and Safe Vehicles)
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Open AccessArticle
Research on a Path Tracking Control Strategy for Autonomous Vehicles Based on State Parameter Identification
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Dapai Shi, Fulin Chu, Qingling Cai, Zhanpeng Wang, Zhilong Lv and Jiaheng Wang
World Electr. Veh. J. 2024, 15(7), 295; https://doi.org/10.3390/wevj15070295 - 2 Jul 2024
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With the rapid development of autonomous driving technology, estimating and controlling key vehicle state parameters under complex road conditions have become critical challenges. This study combines Unscented Kalman Filtering (UKF) and Sliding Mode Control (SMC) methods to propose an integrated control model for
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With the rapid development of autonomous driving technology, estimating and controlling key vehicle state parameters under complex road conditions have become critical challenges. This study combines Unscented Kalman Filtering (UKF) and Sliding Mode Control (SMC) methods to propose an integrated control model for achieving more efficient control. First, a three-degrees-of-freedom vehicle dynamics model based on the Dugoff tire model is constructed to accurately estimate key vehicle state parameters. Next, UKF is used to estimate road friction coefficients and key vehicle state parameters, and its performance is compared with Extended Kalman Filtering (EKF) under various conditions. The results show the superiority of UKF in identifying road friction coefficients. Based on SMC theory, a sliding surface is designed, and the functional relationship between state variables and control variables is derived to establish the corresponding control model. Joint simulations using Carsim and Simulink under different conditions validate the real-time performance and effectiveness of the designed UKF-SMC integrated control strategy in the presence of external disturbances and system uncertainties. Simulation results indicate that this strategy effectively enhances the overall performance and safety of autonomous vehicles, providing an accurate real-time solution capable of handling complex and variable road conditions. The proposed UKF-SMC integrated control strategy not only proves its theoretical superiority but also demonstrates promising practical applications in simulation experiments. This study provides reliable technical support for the development of autonomous driving technology under complex road conditions.
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Open AccessArticle
Exploring the Relationship between Supply Chain Agility, Consumer and Electric Vehicle Characteristics, and Purchase Intentions in Thailand: A Structural Equation Modeling Approach
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Adisak Suvittawat
World Electr. Veh. J. 2024, 15(7), 294; https://doi.org/10.3390/wevj15070294 - 2 Jul 2024
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This research on electric vehicle purchasing intentions in Thailand using Structural Equation Modeling aimed to achieve the following objectives: Firstly, to investigate the factors influencing consumers’ intentions to purchase electric vehicles. Secondly, to examine the impact of consumer characteristics on supply chain agility
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This research on electric vehicle purchasing intentions in Thailand using Structural Equation Modeling aimed to achieve the following objectives: Firstly, to investigate the factors influencing consumers’ intentions to purchase electric vehicles. Secondly, to examine the impact of consumer characteristics on supply chain agility (SCA). Thirdly, to analyze how electric vehicle characteristics influence supply chain agility. Lastly, to assess the influence of supply chain agility on consumers’ purchasing intentions. The study sampled individuals in Thailand holding personal driver’s licenses and intending to purchase electric cars, totaling 350 respondents selected randomly. Data analysis employed descriptive statistics including frequency, percentage, and mean values. The validity and reliability of the questionnaires were ensured through factor loading and Cronbach’s Alpha tests. Our findings indicated that consumer characteristics, electric vehicle features, and supply chain agility significantly affect purchasing intentions. Consumer-specific factors like social influence, environmental concern, and perceptions of electric vehicles were found to impact purchase intentions. Electric vehicle characteristics such as battery longevity, perceived benefits, and value also influenced purchase intentions. Additionally, supply chain agility factors including flexibility, speed in innovation, and responsiveness to customer needs were identified as influential. The research underscores the importance for manufacturers to prioritize initiatives that enhance customer experience with electric vehicles, alleviating concerns and fostering confidence in their use, thereby encouraging adoption without apprehensions about potential issues.
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Open AccessArticle
A Novel Robust H∞ Control Approach Based on Vehicle Lateral Dynamics for Practical Path Tracking Applications
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Jie Wang, Baichao Wang, Congzhi Liu, Litong Zhang and Liang Li
World Electr. Veh. J. 2024, 15(7), 293; https://doi.org/10.3390/wevj15070293 - 30 Jun 2024
Abstract
This paper proposes a robust lateral control scheme for the path tracking of autonomous vehicles. Considering the discrepancies between the model parameters and the actual values of the vehicle and the fluctuation of parameters during driving, the norm-bounded uncertainty is utilized to deal
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This paper proposes a robust lateral control scheme for the path tracking of autonomous vehicles. Considering the discrepancies between the model parameters and the actual values of the vehicle and the fluctuation of parameters during driving, the norm-bounded uncertainty is utilized to deal with the uncertainty of model parameters. Because some state variables in the model are difficult to measure, an observer is designed to estimate state variables and provide accurate state information to improve the robustness of path tracking. An state feedback controller is proposed to suppress system nonlinearity and uncertainty and produce the desired steering wheel angle to solve the path tracking problem. A feedforward control is designed to deal with road curvature and further reduce tracking errors. In summary, a path tracking method with performance is established based on the linear matrix inequality (LMI) technique, and the gains in observer and controller can be obtained directly. The hardware-in-the-loop (HIL) test is built to validate the real-time processing performance of the proposed method to ensure excellent practical application potential, and the effectiveness of the proposed control method is validated through the utilization of urban road and highway scenes. The experimental results indicate that the suggested control approach can track the desired trajectory more precisely compared with the model predictive control (MPC) method and make tracking errors within a small range in both urban and highway scenarios.
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(This article belongs to the Special Issue Dynamics, Control and Simulation of Electrified Vehicles)
Open AccessArticle
Research on Unmanned Vehicle Path Planning Based on the Fusion of an Improved Rapidly Exploring Random Tree Algorithm and an Improved Dynamic Window Approach Algorithm
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Shuang Wang, Gang Li and Boju Liu
World Electr. Veh. J. 2024, 15(7), 292; https://doi.org/10.3390/wevj15070292 - 30 Jun 2024
Abstract
Aiming at the problem that the traditional rapidly exploring random tree (RRT) algorithm only considers the global path of unmanned vehicles in a static environment, which has the limitation of not being able to avoid unknown dynamic obstacles in real time, and that
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Aiming at the problem that the traditional rapidly exploring random tree (RRT) algorithm only considers the global path of unmanned vehicles in a static environment, which has the limitation of not being able to avoid unknown dynamic obstacles in real time, and that the traditional dynamic window approach (DWA) algorithm is prone to fall into a local optimum during local path planning, this paper proposes a path planning method for unmanned vehicles that integrates improved RRT and DWA algorithms. The RRT algorithm is improved by introducing strategies such as target-biased random sampling, adaptive step size, and adaptive radius node screening, which enhance the efficiency and safety of path planning. The global path key points generated by the improved RRT algorithm are used as the subtarget points of the DWA algorithm, and the DWA algorithm is optimized through the design of an adaptive evaluation function weighting method based on real-time obstacle distances to achieve more reasonable local path planning. Through simulation experiments, the fusion algorithm shows promising results in a variety of typical static and dynamic mixed driving scenarios, can effectively plan a path that meets the driving requirements of an unmanned vehicle, avoids unknown dynamic obstacles, and shows higher path optimization efficiency and driving stability in complex environments, which provides strong support for an unmanned vehicle’s path planning in complex environments.
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(This article belongs to the Special Issue Research on Intelligent Vehicle Path Planning Algorithm)
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Open AccessArticle
Parametric Correlation Analysis between Equivalent Electric Circuit Model and Mechanistic Model Interpretation for Battery Internal Aging
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Humberto Velasco-Arellano, Néstor Castillo-Magallanes, Nancy Visairo-Cruz, Ciro Alberto Núñez-Gutiérrez and Isabel Lázaro
World Electr. Veh. J. 2024, 15(7), 291; https://doi.org/10.3390/wevj15070291 - 29 Jun 2024
Abstract
In modern electric vehicle applications, understanding the evolution of the internal electrochemical reaction throughout the aging of batteries is as relevant as knowing their state of health. This article demonstrates the feasibility of correlating a mechanistic model of the battery internal electrochemical reactions
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In modern electric vehicle applications, understanding the evolution of the internal electrochemical reaction throughout the aging of batteries is as relevant as knowing their state of health. This article demonstrates the feasibility of correlating a mechanistic model of the battery internal electrochemical reactions with an equivalent electrical circuit (EEC) model, providing a practical and understandable interpretation of the internal reactions for electrical specialists. By way of electrochemical impedance spectroscopy analysis and automatic control theory, a methodology for correlating the resistance and capacitance variations of the EEC model and how they reflect the electrochemical reaction changes is proposed. These changes are represented through the time constants of the three parallel arrays from an EEC model. PS-260 lead–acid batteries were analyzed throughout the SOC and their useful life to validate this methodology. The result analysis allows us to establish that the first array corresponds to the negative electrode reactions in the range of 1.48 Hz to 10 kHz, the second array to the positive electrode reactions and generation of sulfates in the range of 0.5 to 1.48 Hz, and the third array to the generation of sulfates and their diffusion in the range of 0.01 to 0.5 Hz.
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(This article belongs to the Topic Battery Design and Management)
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A Review of Key Technologies for Environment Sensing in Driverless Vehicles
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Yuansheng Huo and Chengwei Zhang
World Electr. Veh. J. 2024, 15(7), 290; https://doi.org/10.3390/wevj15070290 - 29 Jun 2024
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Environment perception technology is the most important part of driverless technology, and driverless vehicles need to realize decision planning and control by virtue of perception feedback. This paper summarizes the most promising technology methods in the field of perception, namely visual perception technology,
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Environment perception technology is the most important part of driverless technology, and driverless vehicles need to realize decision planning and control by virtue of perception feedback. This paper summarizes the most promising technology methods in the field of perception, namely visual perception technology, radar perception technology, state perception technology, and information fusion technology. Regarding the current development status in the field, the development of the main perception technology is mainly the innovation of information fusion technology and the optimization of algorithms. Multimodal perception and deep learning are becoming popular. The future of the field can be transformed by intelligent sensors, promote edge computing and cloud collaboration, improve system data processing capacity, and reduce the burden of data transmission. Regarding driverless vehicles as a future development trend, the corresponding technology will become a research hotspot.
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Open AccessArticle
An Effective Strategy for Achieving Economic Reliability by Optimal Coordination of Hybrid Thermal–Wind–EV System in a Deregulated System
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Ravindranadh Chowdary Vankina, Sadhan Gope, Subhojit Dawn, Ahmed Al Mansur and Taha Selim Ustun
World Electr. Veh. J. 2024, 15(7), 289; https://doi.org/10.3390/wevj15070289 - 28 Jun 2024
Abstract
This paper describes an effective operating strategy for electric vehicles (EVs) in a hybrid facility that leverages renewable energy sources. The method is to enhance the profit of the wind–thermal–EV hybrid plant while maintaining the grid frequency (fPG) and energy level
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This paper describes an effective operating strategy for electric vehicles (EVs) in a hybrid facility that leverages renewable energy sources. The method is to enhance the profit of the wind–thermal–EV hybrid plant while maintaining the grid frequency (fPG) and energy level of the EV battery storage system. In a renewable-associated power network, renewable energy producers must submit power supply proposals to the system operator at least one day before operations begin. The market managers then combine the power plans for the next several days based on bids from both power providers and distributors. However, due to the unpredictable nature of renewable resources, the electrical system cannot exactly adhere to the predefined power supply criteria. When true and estimated renewable power generation diverges, the electrical system may experience an excess or shortage of electricity. If there is a disparity between true and estimated wind power (TWP, EWP), the EV plant operates to minimize this variation. This lowers the costs associated with the discrepancy between actual and projected wind speeds (TWS, EWS). The proposed method effectively reduces the uncertainty associated with wind generation while being economically feasible, which is especially important in a deregulated power market. This study proposes four separate energy levels for an EV battery storage system (EEV,max, EEV,opt, EEV,low, and EEV,min) to increase system profit and revenue, which is unique to this work. The optimum operating of these EV battery energy levels is determined by the present electric grid frequency and the condition of TWP and EWP. The proposed approach is tested on a modified IEEE 30 bus system and compared to an existing strategy to demonstrate its effectiveness and superiority. The entire work was completed using the optimization technique called sequential quadratic programming (SQP).
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(This article belongs to the Special Issue Data Exchange between Vehicle and Power System for Optimal Charging)
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Design of an Electric Vehicle Charging System Consisting of PV and Fuel Cell for Historical and Tourist Regions
by
Suleyman Emre Dagteke and Sencer Unal
World Electr. Veh. J. 2024, 15(7), 288; https://doi.org/10.3390/wevj15070288 - 28 Jun 2024
Abstract
One of the most important problems in the widespread use of electric vehicles is the lack of charging infrastructure. Especially in tourist areas where historical buildings are located, the installation of a power grid for the installation of electric vehicle charging stations or
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One of the most important problems in the widespread use of electric vehicles is the lack of charging infrastructure. Especially in tourist areas where historical buildings are located, the installation of a power grid for the installation of electric vehicle charging stations or generating electrical energy by installing renewable energy production systems such as large-sized PV (photovoltaic) and wind turbines poses a problem because it causes the deterioration of the historical texture. Considering the need for renewable energy sources in the transportation sector, our aim in this study is to model an electric vehicle charging station using PVPS (photovoltaic power system) and FC (fuel cell) power systems by using irradiation and temperature data from historical regions. This designed charging station model performs electric vehicle charging, meeting the energy demand of a house and hydrogen production by feeding the electrolyzer with the surplus energy from producing electrical energy with the PVPS during the daytime. At night, when there is no solar radiation, electric vehicle charging and residential energy demand are met with an FC power system. One of the most important advantages of this system is the use of hydrogen storage instead of a battery system for energy storage and the conversion of hydrogen into electrical energy with an FC. Unlike other studies, in our study, fossil energy sources such as diesel generators are not included for the stable operation of the system. The system in this study may need hydrogen refueling in unfavorable climatic conditions and the energy storage capacity is limited by the hydrogen fuel tank capacity.
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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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Harmonic Resonance Mechanisms and Influencing Factors of Distributed Energy Grid-Connected Systems
by
Minrui Xu, Zhixin Li, Shufeng Lu, Tianyang Xu, Zhanqi Zhang and Xiangjun Quan
World Electr. Veh. J. 2024, 15(7), 287; https://doi.org/10.3390/wevj15070287 - 26 Jun 2024
Abstract
With the rapid development of global energy transformation and new power system, ensuring the stability of distributed energy grid connections is the key to maintaining the reliable operation of the whole power system. This paper constructs detailed impedance models of grid-following (GFL) and
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With the rapid development of global energy transformation and new power system, ensuring the stability of distributed energy grid connections is the key to maintaining the reliable operation of the whole power system. This paper constructs detailed impedance models of grid-following (GFL) and grid-forming (GFM) inverters using a harmonic linearization method and thoroughly investigates the mechanisms of resonance when inverters are connected to the grid, as well as the impact of model parameters on the stability of the grid system. This paper also briefly analyzes the scenario where distributed energy and electric vehicles are integrated into the grid simultaneously, demonstrating that grid system stability can be ensured in complex grid situations through reasonable parameter design. Lastly, the accuracy of the proposed impedance models and analysis is verified through MATLAB/Simulink simulations.
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(This article belongs to the Special Issue Active Voltage and Frequency Support Control by the EV, New Energy and Energy Storages)
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A Comprehensive Review on Smart Electromobility Charging Infrastructure
by
Idowu Adetona Ayoade and Omowunmi Mary Longe
World Electr. Veh. J. 2024, 15(7), 286; https://doi.org/10.3390/wevj15070286 - 26 Jun 2024
Abstract
This study thoroughly analyses Smart Electromobility Charging Infrastructure (SECI), exploring its multifaceted dimensions and advancements. Delving into the intricate landscape of SECI, the study critically evaluates existing technologies, integration methodologies, and emerging trends. Through a systematic examination of literature and empirical studies, the
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This study thoroughly analyses Smart Electromobility Charging Infrastructure (SECI), exploring its multifaceted dimensions and advancements. Delving into the intricate landscape of SECI, the study critically evaluates existing technologies, integration methodologies, and emerging trends. Through a systematic examination of literature and empirical studies, the article elucidates the evolving ecosystem of smart charging solutions, considering aspects including advancements in charging protocols. Additionally, the review highlights challenges and prospects in the SECI domain, providing insightful information for scholars, practitioners, and policymakers involved in the dynamic field of electromobility. Technical potentials, including functionalities and integration with the smart grid, have been thoroughly reviewed. An analysis is conducted on the effects of intelligent charging on power distribution systems and strategies to lessen these effects. This study also examines the development of intelligent charging algorithms, optimisation methods, and security analysis. This paper, therefore, contributes to fostering a more thorough comprehension of the current state and future trajectories of Smart Electromobility Charging Infrastructure.
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(This article belongs to the Special Issue Smart Charging Strategies for Plug-In Electric Vehicles)
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