World Electric Vehicle Journal最新文献_第3页

Exploring the Relationship between Supply Chain Agility, Consumer and Electric Vehicle Characteristics, and Purchase Intentions in Thailand: A Structural Equation Modeling Approach 探索泰国供应链敏捷性、消费者和电动汽车特征与购买意向之间的关系：结构方程模型法

World Electric Vehicle Journal Pub Date : 2024-07-02 DOI: 10.3390/wevj15070294

Adisak Suvittawat

{"title":"Exploring the Relationship between Supply Chain Agility, Consumer and Electric Vehicle Characteristics, and Purchase Intentions in Thailand: A Structural Equation Modeling Approach","authors":"Adisak Suvittawat","doi":"10.3390/wevj15070294","DOIUrl":"https://doi.org/10.3390/wevj15070294","url":null,"abstract":"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.","PeriodicalId":507038,"journal":{"name":"World Electric Vehicle Journal","volume":"9 28","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141684125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on a Path Tracking Control Strategy for Autonomous Vehicles Based on State Parameter Identification 基于状态参数识别的自动驾驶汽车路径跟踪控制策略研究

World Electric Vehicle Journal Pub Date : 2024-07-02 DOI: 10.3390/wevj15070295

Dapai Shi, Fulin Chu, Qingling Cai, Zhanpeng Wang, Zhilong Lv, Jiaheng Wang

{"title":"Research on a Path Tracking Control Strategy for Autonomous Vehicles Based on State Parameter Identification","authors":"Dapai Shi, Fulin Chu, Qingling Cai, Zhanpeng Wang, Zhilong Lv, Jiaheng Wang","doi":"10.3390/wevj15070295","DOIUrl":"https://doi.org/10.3390/wevj15070295","url":null,"abstract":"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.","PeriodicalId":507038,"journal":{"name":"World Electric Vehicle Journal","volume":"28 41","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141685243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Automatic Emergency Braking Control Method for Improving Ride Comfort 提高乘坐舒适性的自动紧急制动控制方法

World Electric Vehicle Journal Pub Date : 2024-06-14 DOI: 10.3390/wevj15060259

Fei Lai, Junbo Liu, Yuanzhi Hu

引用次数: 0

Global Patent Analysis of Battery Recycling Technologies: A Comparative Study of Korea, China, and the United States 电池回收技术的全球专利分析：韩国、中国和美国的比较研究

World Electric Vehicle Journal Pub Date : 2024-06-14 DOI: 10.3390/wevj15060260

Chae-Hoon Lee

{"title":"Global Patent Analysis of Battery Recycling Technologies: A Comparative Study of Korea, China, and the United States","authors":"Chae-Hoon Lee","doi":"10.3390/wevj15060260","DOIUrl":"https://doi.org/10.3390/wevj15060260","url":null,"abstract":"This study provides a comprehensive analysis of global patent trends in battery recycling, focusing on secondary batteries and related technologies across Korea, China, and the United States. The methodology involved collecting data from various patent databases, followed by quantitative analysis to identify technology trends and guide future development. The research employed statistical tools to analyze patent activities, including the frequency and scope of patent filings, and comparative analysis to highlight differences between countries. This study reveals distinct emphases on technologies such as lithium-ion and waste battery recycling, highlighting notable differences in patent activities among key companies and countries. China’s large number of patents in battery manufacturing processes contrasts with the USA’s focus on electrochemical cell construction and storage systems, while Korea shows significant activity in waste battery technology. The novelty of this paper lies in its detailed comparative analysis of patent trends across these three major economies, providing insights into the technological focuses and priorities of each country. The study also identifies key challenges, such as the need for consistent innovation and broader geographic coverage in Korea, enhancing patent influence and international presence in China, and ensuring high patent quality and fostering innovation in lagging sectors in the United States. Addressing these challenges through enhanced collaboration, increased R&D investments, and supportive policies is crucial for strengthening the global position and driving further innovation in the battery recycling sector.","PeriodicalId":507038,"journal":{"name":"World Electric Vehicle Journal","volume":"40 19","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141344445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Exploring User Attitudes and Behavioral Intentions towards Augmented Reality Automotive Assistants: A Mixed-Methods Approach 探索用户对增强现实汽车助手的态度和行为意向：混合方法

World Electric Vehicle Journal Pub Date : 2024-06-12 DOI: 10.3390/wevj15060258

Fucheng Wan, Jian Teng, Lisi Feng

{"title":"Exploring User Attitudes and Behavioral Intentions towards Augmented Reality Automotive Assistants: A Mixed-Methods Approach","authors":"Fucheng Wan, Jian Teng, Lisi Feng","doi":"10.3390/wevj15060258","DOIUrl":"https://doi.org/10.3390/wevj15060258","url":null,"abstract":"As augmented reality (AR) technology is increasingly permeating the automotive industry, this study investigates users’ attitudes towards AR automotive assistants and their impact on usage behavior. Using the theory of reasoned action (TRA) and integrating insights from the Kano model, critical factors driving user acceptance and engagement were identified. The research reveals that trust in AR technology, perceived utility, and ease of interaction are prioritized by users. Clustering analysis identified three distinct user groups: a ‘Safety-Conscious Group’, a ‘Technology Enthusiast Group’, and an ‘Experience-Seeking Group’, each displaying unique preferences towards AR features. Additionally, a support vector machine (SVM) model effectively predicted user behavior with a training set accuracy of 89.96%. These findings provide valuable insights for the design and marketing of AR automotive assistants, acknowledging both essential features and delighters identified through the Kano model. By understanding user preferences and expectations, tailored AR solutions can be developed to enhance user satisfaction and adoption rates in the automotive sector. Moreover, this research contributes to the sustainable development goals related to the automotive industry by fostering innovation in vehicle technology, promoting eco-friendly driving practices, and enhancing overall mobility efficiency.","PeriodicalId":507038,"journal":{"name":"World Electric Vehicle Journal","volume":"70 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141353023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design and Construction of a Multipole Electric Motor Using an Axial Flux Configuration 使用轴向磁通配置设计和制造多极电机

World Electric Vehicle Journal Pub Date : 2024-06-12 DOI: 10.3390/wevj15060256

A. González-Parada, Francisco Moreno Del Valle, R. Bosch-Tous

{"title":"Design and Construction of a Multipole Electric Motor Using an Axial Flux Configuration","authors":"A. González-Parada, Francisco Moreno Del Valle, R. Bosch-Tous","doi":"10.3390/wevj15060256","DOIUrl":"https://doi.org/10.3390/wevj15060256","url":null,"abstract":"In the transportation industry, the use of renewable energies has been implemented in conjunction with the development of higher-power electric motors and, consequently, the development of intelligent control systems for torque and speed control. Currently, the coupling between both systems is being developed through mechanical systems, affecting the efficient transmission of energy and the useful life of the components. On the other hand, new configurations of electric motors are being developed, such as axial flux motors (AFM), because these can be coupled directly without a mechanical coupling, given their characteristics of high torque at low speeds. In the present work, an innovative design of a multipole axial flux motor (MAFM) is introduced. General criteria for the design and construction are presented considering the geometry in axial flux and permanent magnets. The performance of the system is evaluated through finite element magnetic simulations (FEMM) and compared with experimental measurements of the developed prototype; confirming the effectiveness of the design, obtaining torques of up to 1.784 Nm without extra mechanical couplings and maximum speed regulation errors of 8.43%. The motor was controlled by a digital pole switching system whit six control mode, applied to a permanent magnet MFA for speed and torque control at constant speed. This control can be extended to conventional radial flux electric motor configurations and intelligent traction applications, based on torque demand.","PeriodicalId":507038,"journal":{"name":"World Electric Vehicle Journal","volume":"27 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141354753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on Filtering Algorithm of Vehicle Dynamic Weighing Signal 车辆动态称重信号的滤波算法研究

World Electric Vehicle Journal Pub Date : 2024-06-12 DOI: 10.3390/wevj15060254

Lingcong Xiong, Tieyi Zhang, Anlu Yuan, Zhipeng Zhang

{"title":"Research on Filtering Algorithm of Vehicle Dynamic Weighing Signal","authors":"Lingcong Xiong, Tieyi Zhang, Anlu Yuan, Zhipeng Zhang","doi":"10.3390/wevj15060254","DOIUrl":"https://doi.org/10.3390/wevj15060254","url":null,"abstract":"This study analyzes the advantages and disadvantages of filtering algorithms for dynamic weighing signals. Highway road surface has road surface unevenness and other influencing factors. The body vibration of the vehicle driving process produces a certain amount of interference signals collected by the load cell to form noise signals. In addition, piezoelectric sensors and amplification circuits introduce a large amount of electrical noise. These noise signals are non-smooth, nonlinear, and have other characteristics. We study the filtering effects of moving average (MA), wavelet transform (WT), and variational mode decomposition (VMD) filtering algorithms on axle weight signals and evaluate the performance of the filtering algorithms through the Root Mean Square Error (RMSE), signal-to-noise ratio (SNR), and Normalized Correlation Coefficient (NCC). The comprehensive analysis shows that the variational modal decomposition filtering algorithm is more advantageous for axial weight signal processing. The design of the axle weight signal noise filtering algorithm is of great significance for improving the accuracy of the overall dynamic weighing system of the vehicle.","PeriodicalId":507038,"journal":{"name":"World Electric Vehicle Journal","volume":"36 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141354350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Novel Deep Learning Domain Adaptation Approach for Object Detection Using Semi-Self Building Dataset and Modified YOLOv4 使用半自建数据集和修改后的 YOLOv4 进行物体检测的新型深度学习领域自适应方法

World Electric Vehicle Journal Pub Date : 2024-06-12 DOI: 10.3390/wevj15060255

Ahmed Gomaa, Ahmad Abdalrazik

{"title":"Novel Deep Learning Domain Adaptation Approach for Object Detection Using Semi-Self Building Dataset and Modified YOLOv4","authors":"Ahmed Gomaa, Ahmad Abdalrazik","doi":"10.3390/wevj15060255","DOIUrl":"https://doi.org/10.3390/wevj15060255","url":null,"abstract":"Moving object detection is a vital research area that plays an essential role in intelligent transportation systems (ITSs) and various applications in computer vision. Recently, researchers have utilized convolutional neural networks (CNNs) to develop new techniques in object detection and recognition. However, with the increasing number of machine learning strategies used for object detection, there has been a growing need for large datasets with accurate ground truth used for the training, usually demanding their manual labeling. Moreover, most of these deep strategies are supervised and only applicable for specific scenes with large computational resources needed. Alternatively, other object detection techniques such as classical background subtraction need low computational resources and can be used with general scenes. In this paper, we propose a new a reliable semi-automatic method that combines a modified version of the detection-based CNN You Only Look Once V4 (YOLOv4) technique and background subtraction technique to perform an unsupervised object detection for surveillance videos. In this proposed strategy, background subtraction-based low-rank decomposition is applied firstly to extract the moving objects. Then, a clustering method is adopted to refine the background subtraction (BS) result. Finally, the refined results are used to fine-tune the modified YOLO v4 before using it in the detection and classification of objects. The main contribution of this work is a new detection framework that overcomes manual labeling and creates an automatic labeler that can replace manual labeling using motion information to supply labeled training data (background and foreground) directly from the detection video. Extensive experiments using real-world object monitoring benchmarks indicate that the suggested framework obtains a considerable increase in mAP compared to state-of-the-art results on both the CDnet 2014 and UA-DETRAC datasets.","PeriodicalId":507038,"journal":{"name":"World Electric Vehicle Journal","volume":"7 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141353584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improved Model Predictive Control Path Tracking Approach Based on Online Updated Algorithm with Fuzzy Control and Variable Prediction Time Domain for Autonomous Vehicles 基于模糊控制和可变预测时域的在线更新算法的改进型模型预测控制路径跟踪方法，适用于自动驾驶汽车

World Electric Vehicle Journal Pub Date : 2024-06-12 DOI: 10.3390/wevj15060257

Binshan Liu, Zhaoqiang Wang, Hui Guo, Guoxiang Zhang

{"title":"Improved Model Predictive Control Path Tracking Approach Based on Online Updated Algorithm with Fuzzy Control and Variable Prediction Time Domain for Autonomous Vehicles","authors":"Binshan Liu, Zhaoqiang Wang, Hui Guo, Guoxiang Zhang","doi":"10.3390/wevj15060257","DOIUrl":"https://doi.org/10.3390/wevj15060257","url":null,"abstract":"The design of trajectory tracking controllers for smart driving cars still faces problems, such as uncertain parameters and it being time-consuming. To improve the tracking performance of the trajectory tracking controller and reduce the computation of the controller, this paper proposes an improved model predictive control (MPC) method based on fuzzy control and an online update algorithm. First, a vehicle dynamics model is constructed and a feedforward MPC controller is designed; second, a real-time updating method of the time domain parameters is proposed to replace the previous method of empirically selecting the time domain parameters; lastly, a fuzzy controller is proposed for the real-time adjustment of the weight coefficient matrix of the model predictive controller according to the lateral and heading errors of the vehicle, and a state matrix-based cosine similarity updating mechanism is developed for determining the updating nodes of the state matrix to reduce the controller computation caused by the continuous updating of the state matrix when the longitudinal vehicle speed changes. Finally, the controller is compared with the traditional model prediction controller through the co-simulation of CARSIM and MATLAB/Simulink, and the results show that the controller has great improvement in terms of tracking accuracy and controller computational load.","PeriodicalId":507038,"journal":{"name":"World Electric Vehicle Journal","volume":"13 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141351074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Intelligent Vehicle Formation System Based on Information Interaction 基于信息交互的智能车辆编队系统

World Electric Vehicle Journal Pub Date : 2024-06-11 DOI: 10.3390/wevj15060252

Peng Wang, Ouyang Tao, Shixin Zhao, Xuelin Wang, Zhewen Ni, Yuezhen Fan

{"title":"Intelligent Vehicle Formation System Based on Information Interaction","authors":"Peng Wang, Ouyang Tao, Shixin Zhao, Xuelin Wang, Zhewen Ni, Yuezhen Fan","doi":"10.3390/wevj15060252","DOIUrl":"https://doi.org/10.3390/wevj15060252","url":null,"abstract":"Urban traffic congestion has become an increasingly serious problem, and the transportation industry is gradually becoming a high-energy-consuming industry. Intelligent Transportation System (ITSs) that integrate technologies such as electronic sensing, data transmission, and intelligent control have emerged as a new approach to fundamentally solving transportation problems. As one of the cores of intelligent transportation systems, multi-vehicle formation technology has the advantage of promoting vehicle information interaction, improving vehicle mobility, and enhancing traffic conditions. Due to the high cost and risk of conducting multi-vehicle formation experiments using real vehicles, experimenting with intelligent vehicles has become a viable option. Based on the leader–follower formation strategy, this study designed an intelligent vehicle formation system using the Arduino platform. It utilizes infrared sensors, ultrasonic sensors, and photoelectric encoders to perceive information about the vehicle fleet and the road. Information is aggregated to the master vehicle through ZigBee communication modules. The controller of the master vehicle applies a PID algorithm, combined with a differential steering model, to solve the speed instructions for each vehicle in the fleet. Motion control instructions are then transmitted to each slave vehicle through ZigBee communication modules, enabling the automatic adjustment of the fleet’s traveling speed and spacing. Additionally, a Bluetooth app has been designed for users to monitor and control the movement status of the fleet dynamically in real time. Experimental verification has shown that this research effectively improves intelligent fleets’ capabilities in environmental perception, intelligent decision-making, collaborative control, and motion execution. It also enhances road traffic efficiency and safety, providing new ideas and methods for the development of autonomous driving technology.","PeriodicalId":507038,"journal":{"name":"World Electric Vehicle Journal","volume":"31 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141357458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0