Next Issue
Volume 15, July
Previous Issue
Volume 15, May
 
 

World Electr. Veh. J., Volume 15, Issue 6 (June 2024) – 55 articles

Cover Story (view full-size image): Automated charging technologies are becoming important in the electrification of road transport, especially together with automated driving. This study analyzes automated charging technologies for heavy-duty vehicles, with each technology evaluated for advantages, potential, challenges, and technological maturity. Amongst the static conductive charging methods, i.e., robots, underbody-couplers, and pantographs, the latter is the most advanced option. Static wireless charging is operational but faces efficiency challenges. Battery swapping reduces downtime but varies in readiness across implementations. Dynamic charging via an overhead contact line or contact rails is suitable for high-traffic routes. Dynamic wireless charging enables smooth integration into roads and reduced wear and tear. View this paper
  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.
Order results
Result details
Select all
Export citation of selected articles as:
31 pages, 2274 KiB  
Article
Overview of Sustainable Mobility: The Role of Electric Vehicles in Energy Communities
by Jozsef Menyhart
World Electr. Veh. J. 2024, 15(6), 275; https://doi.org/10.3390/wevj15060275 - 20 Jun 2024
Viewed by 389
Abstract
From 2035 onward, the registration of new conventional internal combustion engine vehicles will be prohibited in the European Union. This shift is driven by steadily rising fuel prices and growing concerns over carbon dioxide emissions. Electric vehicles (EVs) are becoming increasingly popular across [...] Read more.
From 2035 onward, the registration of new conventional internal combustion engine vehicles will be prohibited in the European Union. This shift is driven by steadily rising fuel prices and growing concerns over carbon dioxide emissions. Electric vehicles (EVs) are becoming increasingly popular across Europe, and many manufacturers now offer modified models, making pure internal combustion versions unavailable for certain types. Additionally, the comparatively lower operational costs of EVs for end users further bolster their appeal. In the European Union, new directives have been established to define innovative approaches to energy use in Member States, known as energy communities. This article provides a comprehensive overview of the architecture of energy communities, electric vehicles, and the V2X technologies currently on the market. It highlights the evolution of electric vehicle adoption in the EU, contextualizing it within broader energy trends and presenting future challenges and development opportunities related to energy communities. The paper details the diversification of electricity sources among Member States and the share of generated electricity that is utilized for transport. Full article
(This article belongs to the Special Issue Power and Energy Systems for E-mobility)
17 pages, 2326 KiB  
Article
Design and Experiment on Heat Dissipation Structures of Ducted Fan Motor for Flying Electric Vehicle
by Ye Li, Qi Li, Tao Fan, Xuhui Wen and Junhui Xiong
World Electr. Veh. J. 2024, 15(6), 274; https://doi.org/10.3390/wevj15060274 - 20 Jun 2024
Viewed by 333
Abstract
Ducted fan motors play a crucial role in promoting various applications of flying electric vehicles. In ducted fan motor systems, motor performance affects the speed of the fan, the flow field of the fan affects the thermal field of the motor, and the [...] Read more.
Ducted fan motors play a crucial role in promoting various applications of flying electric vehicles. In ducted fan motor systems, motor performance affects the speed of the fan, the flow field of the fan affects the thermal field of the motor, and the thermal field influences the performance of the motor. The coupling model between fan static thrust, motor power, and motor temperature rise is established in this paper. After confirming the external dimensions of the motor, three cooling schemes of the motor casing are designed. The casing forms are as follows: model 1 with smooth surface, model 2 with circular fins, and model 3 with longitudinal fins. The optimization work was carried out on the geometric dimensions of two types of fins for model 2 and model 3, and the static thrust and heat transfer performance of the motors were calculated. This study proposes that the ratio of thrust-to-temperature rise is an indicator for future optimization design of ducted fan motors. Model 3 with longitudinal fins has a higher thrust-to-temperature rise ratio. The thrust temperature rise in model 3 has increased by 24.77% compared to model 1. Full article
(This article belongs to the Special Issue Thermal Management System for Battery Electric Vehicle)
14 pages, 1334 KiB  
Article
Height Control Strategy Design and Simulation of Electronic Control Air Suspension for Trucks
by Hao Zhang, Hao Zhang, Leilei Zhao, Chuanjin Ou, Yuechao Liu and Xiyu Shan
World Electr. Veh. J. 2024, 15(6), 273; https://doi.org/10.3390/wevj15060273 - 20 Jun 2024
Viewed by 330
Abstract
To address the large height error and attitude destabilization phenomenon in regulating the frame height of trucks with electronic control air suspension (ECAS), a height control strategy was designed. Firstly, the fundamental principles of height control were elucidated based on the single degree-of-freedom [...] Read more.
To address the large height error and attitude destabilization phenomenon in regulating the frame height of trucks with electronic control air suspension (ECAS), a height control strategy was designed. Firstly, the fundamental principles of height control were elucidated based on the single degree-of-freedom (DOF) vehicle model. The limitations of the classic non-linear mathematical model for the air spring were also highlighted. Thus, a dynamic model was constructed, consisting of an AEMSim model for the ECAS and a Simulink model for the truck. A frame height fuzzy controller was designed based on the fuzzy control theory to improve the height control accuracy and to solve the control conflict problem of the solenoid valves. Additionally, three typical control modes of the height and corresponding control strategies were proposed based on the practical requirements of usage scenarios for trucks. Finally, dynamic simulations were conducted under different modes. The results show that, compared to the existing switching control method, the proposed control approach can reduce height control errors by an order of magnitude and decrease the pitch angle by over 30%. The steady-state error remains nearly unchanged under the 30% variation of the sprung mass. The proposed control approach exhibits the superior control performance and robustness. It effectively reduces height errors and avoids the posture instability during the adjustment of the ECAS. Full article
(This article belongs to the Special Issue Vehicle System Dynamics and Intelligent Control for Electric Vehicles)
9 pages, 6634 KiB  
Communication
Defects and Mechanical Properties of Silicon Nitride Ball Bearings for Electric Vehicle Reducers
by Jinhyeok Jang, Youngmin Lee, Hoonhee Cheong and Jeongho Yang
World Electr. Veh. J. 2024, 15(6), 272; https://doi.org/10.3390/wevj15060272 - 20 Jun 2024
Viewed by 349
Abstract
In this study, two types of Si3N4 ball bearings for integrated-type EV reducers developed via different manufacturing processes were analyzed to study the microstructure of the balls and the defects that may occur during the manufacturing process. Three types of [...] Read more.
In this study, two types of Si3N4 ball bearings for integrated-type EV reducers developed via different manufacturing processes were analyzed to study the microstructure of the balls and the defects that may occur during the manufacturing process. Three types of defects were confirmed that can reduce the fatigue life of Si3N4 ball bearings in operating environments. The microstructure was analyzed to identify the main additive components of each bearing, and pore defects with a size of less than 1 μm, and the types (particle defects or surface defects) and sizes of defects, were analyzed using LSCM, OM, and SEM. Hardness and fracture toughness, which are representative mechanical properties of ceramic materials, were evaluated. The results, evaluated using a Vickers indentation crack-based method, were statistically analyzed to confirm differences in hardness and fracture toughness between the two samples. Full article
Show Figures

Figure 1

18 pages, 5451 KiB  
Article
Permanent Magnet Installation Optimization of Outer Rotor PMSM Depending on Adding Auxiliary Teeth
by Jiayin Su, Rui Nie, Peixin Wang, Shuai Xu, Jing Liang and Jikai Si
World Electr. Veh. J. 2024, 15(6), 271; https://doi.org/10.3390/wevj15060271 - 19 Jun 2024
Viewed by 413
Abstract
To reduce the influence of the permanent magnet (PM) installation error on the electromagnetic characteristics of the outer rotor permanent magnet synchronous motor (OPMSM), the rotor structure of the OPMSM is optimized in this paper. The optimization method of adding auxiliary teeth on [...] Read more.
To reduce the influence of the permanent magnet (PM) installation error on the electromagnetic characteristics of the outer rotor permanent magnet synchronous motor (OPMSM), the rotor structure of the OPMSM is optimized in this paper. The optimization method of adding auxiliary teeth on the surface of the rotor core is studied, and the influence of different auxiliary teeth heights on the electromagnetic performance of OPMSM is analyzed. It is found that adding auxiliary teeth with suitable height can greatly reduce the installation error of the PM, increase the mechanical stability of the motor, and ensure that the electromagnetic characteristics of the motor remain at a good level. Firstly, the topology and parameters of the motor proposed in this paper are introduced and analyzed. Secondly, the influence of PM installation error on the electromagnetic performance of the motor is analyzed based on the finite element method (FEM), and the necessity of eliminating PM installation error is demonstrated. Then, the parametric scanning method is used to analyze the influence of auxiliary teeth height change on the electromagnetic performance of the motor, and the selection standard of the optimal auxiliary teeth height is determined. By comparing and analyzing OPMSM with different sizes and different pole–slot ratios, the universality of the conclusions is demonstrated. Full article
Show Figures

Figure 1

16 pages, 5335 KiB  
Article
Internal Temperature Estimation of Lithium Batteries Based on a Three-Directional Anisotropic Thermal Circuit Model
by Xiangyu Meng, Huanli Sun, Tao Jiang, Tengfei Huang and Yuanbin Yu
World Electr. Veh. J. 2024, 15(6), 270; https://doi.org/10.3390/wevj15060270 - 19 Jun 2024
Viewed by 234
Abstract
In order to improve the accuracy of internal temperature estimation in batteries, a 10-parameter time-varying multi-surface heat transfer model including internal heat production, heat transfer and external heat transfer is established based on the structure of a lithium iron phosphate pouch battery and [...] Read more.
In order to improve the accuracy of internal temperature estimation in batteries, a 10-parameter time-varying multi-surface heat transfer model including internal heat production, heat transfer and external heat transfer is established based on the structure of a lithium iron phosphate pouch battery and its three directional anisotropic heat conduction characteristics. The entropy heat coefficient, internal equivalent heat capacity and internal equivalent thermal resistance related to the SOC and temperature state of the battery were identified using experimental tests and the least square fitting method, and were then used for online calculation of internal heat production and heat transfer in the battery. According to the time-varying and nonlinear characteristics of the heat transfer between the surface and the environment of the battery, an internal temperature estimation algorithm based on the square root cubature Kalman filter was designed and developed. By iteratively calculating the estimated surface temperature and the measured value, dynamic tracking and online correction of the internal temperature of the battery can be achieved. The verification results using FUDS and US06 dynamic working condition data show that the proposed method can quickly eliminate the influence of initial temperature deviations and accumulated process errors and has the characteristics of a high estimation accuracy and good robustness. Compared with the estimation results of the adaptive Kalman filter, the proposed method improves the estimation accuracy of FUDS and US06 working conditions by 67% and 54%, respectively, with a similar computational efficiency. Full article
Show Figures

Figure 1

17 pages, 10625 KiB  
Article
A Predictive Model for Voltage Transformer Ratio Error Considering Load Variations
by Zhenhua Li, Jiuxi Cui, Paulo R. F. Rocha, Ahmed Abu-Siada, Hongbin Li and Li Qiu
World Electr. Veh. J. 2024, 15(6), 269; https://doi.org/10.3390/wevj15060269 - 19 Jun 2024
Viewed by 352
Abstract
The accuracy of voltage transformer (VT) measurements is imperative for the security and reliability of power systems and the equitability of energy transactions. The integration of a substantial number of electric vehicles (EVs) and their charging infrastructures into the grid poses new challenges [...] Read more.
The accuracy of voltage transformer (VT) measurements is imperative for the security and reliability of power systems and the equitability of energy transactions. The integration of a substantial number of electric vehicles (EVs) and their charging infrastructures into the grid poses new challenges for VT measurement fidelity, including voltage instabilities and harmonic disruptions. This paper introduces an innovative transformer measurement error prediction model that synthesizes Multivariate Variational Mode Decomposition (MVMD) with a deep learning framework integrating Bidirectional Temporal Convolutional Network and Multi-Head Attention mechanism (BiTCN-MHA). The paper is aimed at enhancing VT measurement accuracy under fluctuating load conditions. Initially, the optimization of parameter selection within the MVMD algorithm enhances the accuracy and interpretability of bi-channel signal decomposition. Subsequently, the model applies the Spearman rank correlation coefficient to extract dominant modal components from both the decomposed load and original ratio error sequences to form the basis for input signal channels in the BiTCN-MHA model. By superimposing predictive components, an effective prediction of future VT measurement error trends can be achieved. This comprehensive approach, accounting for input load correlations and temporal dynamics, facilitates robust predictions of future VT measurement error trends. Computational example analysis of empirical operational VT data shows that, compared to before decomposition, the proposed method reduces the Root-Mean-Square Error (RMSE) by 17.9% and the Mean Absolute Error (MAE) by 23.2%, confirming the method’s robustness and superiority in accurately forecasting VT measurement error trends. Full article
(This article belongs to the Topic Modern Power Systems and Units)
Show Figures

Figure 1

32 pages, 34127 KiB  
Article
Quantifying the State of the Art of Electric Powertrains in Battery Electric Vehicles: Comprehensive Analysis of the Tesla Model 3 on the Vehicle Level
by Nico Rosenberger, Philipp Rosner, Philip Bilfinger, Jan Schöberl, Olaf Teichert, Jakob Schneider, Kareem Abo Gamra, Christian Allgäuer, Brian Dietermann, Markus Schreiber, Manuel Ank, Thomas Kröger, Alexander Köhler and Markus Lienkamp
World Electr. Veh. J. 2024, 15(6), 268; https://doi.org/10.3390/wevj15060268 - 18 Jun 2024
Viewed by 217
Abstract
Data on state-of-the-art battery electric vehicles are crucial to academia; however, these data are not published due to non-disclosure policies in the industry. As a result, simulation models and their analyses are based on assumptions or insider information. To fill this information gap, [...] Read more.
Data on state-of-the-art battery electric vehicles are crucial to academia; however, these data are not published due to non-disclosure policies in the industry. As a result, simulation models and their analyses are based on assumptions or insider information. To fill this information gap, we present a comprehensive analysis of the electric powertrain of a Tesla Model 3 SR from 2020 with LFP cells, focusing on the overall range. On the vehicle level, we observe the resulting range in multiple test scenarios, tracing the energy path from source to sink by conducting different test series on the vehicle dynamometer and through AC and DC charging measurements. In addition to absolute electric range tests in different operating scenarios and electric and thermal operation strategies on the vehicle level, we analyze the energy density and the power unit’s efficiency on the component level. These tests are performed through procedures on the chassis dynamometer as well as efficiency analysis and electric characterization tests in charge/discharge scenarios. This study includes over 1 GB of attached measurement data on the battery pack and vehicle level from the lab to the real-world environment available as open-source data. Full article
23 pages, 1462 KiB  
Article
Consumers’ Purchase Intention toward Electric Vehicles from the Perspective of Perceived Green Value: An Empirical Survey from China
by Haipeng Zhao, Fumitaka Furuoka, Rajah AL Rasiah and Erhuan Shen
World Electr. Veh. J. 2024, 15(6), 267; https://doi.org/10.3390/wevj15060267 - 18 Jun 2024
Viewed by 307
Abstract
This study aims to expand the current understanding of the antecedents and consequences of green purchase intention within the context of perceived green value (PGV). This study uniquely combines PLS-SEM and NCA to provide a comprehensive analysis of the factors influencing green purchase [...] Read more.
This study aims to expand the current understanding of the antecedents and consequences of green purchase intention within the context of perceived green value (PGV). This study uniquely combines PLS-SEM and NCA to provide a comprehensive analysis of the factors influencing green purchase intention, offering a novel methodological contribution to the field. By examining the roles of influence and interaction as key precursors to perceived responsibility and self-efficacy, the research adds new dimensions to understanding how these factors shape green purchase intentions. Additionally, we explore how PER and PSE impact green purchase intention (GPI), primarily through their mediating effects. The survey data collected from consumers reveal that PGV positively influences GPI. Furthermore, both PER and PSE exhibit significant chain mediation effects, with the mediation effect of perceived environmental responsibility being particularly strong. This study provides actionable insights for policymakers and electric vehicle manufacturers, emphasizing the importance of green education, certification systems, and the promotion of environmental and economic attributes to foster green purchasing behavior. The findings suggest that government efforts should focus on intensifying green education and promoting the establishment of certification and evaluation systems for electric vehicle products. Meanwhile, electric vehicle manufacturers should highlight the environmental and economic benefits of their products to stimulate green purchasing behavior. Full article
Show Figures

Figure 1

15 pages, 3619 KiB  
Article
Mass, Centre of Gravity Location and Inertia Tensor of Electric Vehicles: Measured Data for Accurate Accident Reconstruction
by Giorgio Previati, Gianpiero Mastinu and Massimiliano Gobbi
World Electr. Veh. J. 2024, 15(6), 266; https://doi.org/10.3390/wevj15060266 - 17 Jun 2024
Viewed by 367
Abstract
Accurate accident reconstruction requires the knowledge of the mass properties of vehicles, namely the centre of gravity location, the mass and the inertia tensor. Such data are seldom available, especially in case of newly produced electric vehicles. In this paper, vehicle inertia measurements, [...] Read more.
Accurate accident reconstruction requires the knowledge of the mass properties of vehicles, namely the centre of gravity location, the mass and the inertia tensor. Such data are seldom available, especially in case of newly produced electric vehicles. In this paper, vehicle inertia measurements, performed at Politecnico di Milano, refer to a number of electric vehicles. In addition to the “simple” measurement of vehicle inertia, measured mass properties are analysed to derive the proper empirical formulae for the estimation of the centre of gravity height and the moments of inertia. Both internal combustion and electric vehicles are considered. Data show a significant difference in the mass properties of the two types of vehicles. The proposed formulae can be effectively employed to quickly obtain a reasonable estimation of the mass properties of any vehicle. The results show that electric vehicles are characterised by higher values of mass with respect to internal combustion vehicles, but they present a lower centre of gravity location and proportionally lower values of the moments of inertia. Full article
(This article belongs to the Special Issue Electric Vehicle Crash Safety Design)
31 pages, 2188 KiB  
Article
Evaluation of Sustainable Behavior and Acceptance of Electric Public Transportation: A Perspective from the Philippines
by Jill Angela C. Buenavista, Ardvin Kester S. Ong, Princess Jane Servas, Zsaliyah Kathrine Ibrahim, Kyla Catherine Gemala, Tanya Jeimiel Base, Lanz Julian L. Buenaseda, Curt Denver G. Solano and Jamilla Raye C. Yagin
World Electr. Veh. J. 2024, 15(6), 265; https://doi.org/10.3390/wevj15060265 - 17 Jun 2024
Viewed by 256
Abstract
Rapid urbanization has exerted pressure for development on public transportation infrastructure. The rise in population has driven consumers to seek efficient, cost-effective, and environmentally sustainable transportation. The objective of this study was to assess the determinants influencing consumers’ behavioral intention and acceptance of [...] Read more.
Rapid urbanization has exerted pressure for development on public transportation infrastructure. The rise in population has driven consumers to seek efficient, cost-effective, and environmentally sustainable transportation. The objective of this study was to assess the determinants influencing consumers’ behavioral intention and acceptance of utilizing electric public transportation. The integrated UTAUT2 and sustainable theory of planned behavior underwent a higher-order construct using partial least squares structural equation modeling analysis to thoroughly evaluate key factors influencing the intention to accept electric public transportation. The study utilized a 55-item questionnaire distributed to 438 respondents. The findings indicated that the domains of UTAUT2 had the most significant effect, with hedonic motivation as the predominant variable, followed by effort expectancy and performance expectancy. This study indicated hedonic motivation as the primary factor influencing the intention to use electric public transportation, followed by effort expectancy. This study highlights the importance of ensuring user-friendly and convenient experience in the design and delivery of electric public transportation services. Substantial implications, both theoretical and practical, are also posited. Considering the impactful variables, this study deduced that the government, transportation sectors, and electric vehicle developers should place increased emphasis on enhancing customers’ intention to accept and use public transport in a sustainable manner. Full article
Show Figures

Figure 1

21 pages, 3578 KiB  
Article
Assessment of User Preferences for In-Car Display Combinations during Non-Driving Tasks: An Experimental Study Using a Virtual Reality Head-Mounted Display Prototype
by Liang Li, Chacon Quintero Juan Carlos, Zijiang Yang and Kenta Ono
World Electr. Veh. J. 2024, 15(6), 264; https://doi.org/10.3390/wevj15060264 - 17 Jun 2024
Viewed by 301
Abstract
The goal of vehicular automation is to enhance driver comfort by reducing the necessity for active engagement in driving. This allows for the performance of non-driving-related tasks (NDRTs), with attention shifted away from the driving process. Despite this, there exists a discrepancy between [...] Read more.
The goal of vehicular automation is to enhance driver comfort by reducing the necessity for active engagement in driving. This allows for the performance of non-driving-related tasks (NDRTs), with attention shifted away from the driving process. Despite this, there exists a discrepancy between current in-vehicle display configurations and the escalating demands of NDRTs. This study investigates drivers’ preferences for in-vehicle display configurations within highly automated driving contexts. Utilizing virtual reality head-mounted displays (VR-HMDs) to simulate autonomous driving scenarios, this research employs Unity 3D Shape for developing sophisticated head movement tracking software. This setup facilitates the creation of virtual driving environments and the gathering of data on visual attention distribution. Employing an orthogonal experiment, this experiment methodically analyses and categorizes the primary components of in-vehicle display configurations to determine their correlation with visual immersion metrics. Additionally, this study incorporates subjective questionnaires to ascertain the most immersive display configurations and to identify key factors impacting user experience. Statistical analysis reveals that a combination of Portrait displays with Windshield Head-Up Displays (W-HUDs) is favored under highly automated driving conditions, providing increased immersion during NDRTs. This finding underscores the importance of tailoring in-vehicle display configurations to individual needs to avoid distractions and enhance user engagement. Full article
20 pages, 6629 KiB  
Article
Estimation of Road Adhesion Coefficient Based on Camber Brush Model
by Shupei Zhang, Hongcheng Zhu, Haichao Zhou, Yixiang Chen and Yue Liu
World Electr. Veh. J. 2024, 15(6), 263; https://doi.org/10.3390/wevj15060263 - 17 Jun 2024
Viewed by 229
Abstract
Electric vehicles, with their distinct power systems, weight distribution, and power control strategies compared to traditional vehicles, influence the pressure distribution in the tire contact area, thereby affecting the estimation of road adhesion coefficient. In electric vehicle research, tire adhesion coefficient serves as [...] Read more.
Electric vehicles, with their distinct power systems, weight distribution, and power control strategies compared to traditional vehicles, influence the pressure distribution in the tire contact area, thereby affecting the estimation of road adhesion coefficient. In electric vehicle research, tire adhesion coefficient serves as a measure of the frictional force between the vehicle and the road surface, directly impacting the vehicle’s handling performance. The accurate estimation of the adhesion coefficient aids drivers in better understanding the vehicle’s driving state. However, the existing brush models neglect differences in ground pressure distribution along the width direction of tires during tire camber, potentially leading to inaccuracies in adhesion coefficient estimation. This study proposes a camber brush tire model that considers the width-direction pressure distribution characteristics, aiming to enhance the accuracy of adhesion coefficient estimation under camber conditions. Experimental comparisons between the improved and original models reveal a significant enhancement in estimation precision. Consequently, the findings of this study provide valuable insights for deepening our understanding of tire camber dynamics and for designing control systems for electric vehicles, thereby improving vehicle stability and safety. Full article
Show Figures

Figure 1

16 pages, 2122 KiB  
Review
Data and Energy Impacts of Intelligent Transportation—A Review
by Kaushik Rajashekara and Sharon Koppera
World Electr. Veh. J. 2024, 15(6), 262; https://doi.org/10.3390/wevj15060262 - 17 Jun 2024
Viewed by 319
Abstract
The deployment of intelligent transportation is still in its early stages and there are many challenges that need to be addressed before it can be widely adopted. Autonomous vehicles are a class of intelligent transportation that is rapidly developing, and they are being [...] Read more.
The deployment of intelligent transportation is still in its early stages and there are many challenges that need to be addressed before it can be widely adopted. Autonomous vehicles are a class of intelligent transportation that is rapidly developing, and they are being deployed in selected cities. A combination of advanced sensors, machine learning algorithms, and artificial intelligence are being used in these vehicles to perceive their environment, navigate, and make the right decisions. These vehicles leverage extensive data sourced from various sensors and computers integrated into the vehicle. Hence, massive computational power is required to process the information from various built-in sensors in milliseconds to make the right decision. The power required by the sensors and the use of additional computational power increases the energy consumption, and, hence, could reduce the range of the autonomous electric vehicle relative to a standard electric car and lead to additional emissions. A number of review papers have highlighted the environmental benefits of autonomous vehicles, focusing on aspects like optimized driving, improved route selection, fewer stops, and platooning. However, these reviews often overlook the significant energy demands of the hardware systems—such as sensors, computers, and cameras—necessary for full autonomy, which can decrease the driving range of electric autonomous vehicles. Additionally, previous studies have not thoroughly examined the data processing requirements in these vehicles. This paper provides a more detailed review of the volume of data and energy usage by various sensors and computers integral to autonomous features in electric vehicles. It also discusses the effects of these factors on vehicle range and emissions. Furthermore, the paper explores advanced technologies currently being developed by various industries to enhance processing speeds and reduce energy consumption in autonomous vehicles. Full article
Show Figures

Figure 1

18 pages, 11151 KiB  
Article
Lightweight Type-IV Hydrogen Storage Vessel Boss Based on Optimal Sealing Structure
by Weidong Shao, Jing Wang, Donghai Hu, Dagang Lu and Yinjie Xu
World Electr. Veh. J. 2024, 15(6), 261; https://doi.org/10.3390/wevj15060261 - 15 Jun 2024
Viewed by 309
Abstract
The seal and weight of the Type IV hydrogen storage vessel are the key problems restricting the safety and driving range of fuel cell vehicles. The boss, as a metal medium connecting the inner liner of the Type IV hydrogen storage vessel with [...] Read more.
The seal and weight of the Type IV hydrogen storage vessel are the key problems restricting the safety and driving range of fuel cell vehicles. The boss, as a metal medium connecting the inner liner of the Type IV hydrogen storage vessel with the external pipeline, affects the sealing performance of the Type IV hydrogen storage vessel, and there is no academic research on the weight of the boss. Therefore, according to the force characteristics of the boss, this paper divides the upper and lower areas (valve column and plate). The valve column with seal optimization and light weight is manufactured with a 3D printing additive, while the plate bearing and transferring the internal pressure load is manufactured by forging. Firstly, a two-dimensional axisymmetric simulation model of the sealing ring was established, and the effects of different compression rates on its seal performance were analyzed. Then, the size and position of the sealing groove were sampled, simulated, and optimized based on the Latin Hypercube method, and the reliability of the optimal seal structure was verified by experiments. Finally, the Solid Isotropic Material with Penalization (SIMP) topology method was used to optimize the weight of the boss with optimal sealing structure, and the reconstructed model was checked and analyzed. The results show that the weight of the optimized boss is reduced by 9.6%. Full article
Show Figures

Figure 1

16 pages, 1323 KiB  
Article
Global Patent Analysis of Battery Recycling Technologies: A Comparative Study of Korea, China, and the United States
by Chae-Hoon Lee
World Electr. Veh. J. 2024, 15(6), 260; https://doi.org/10.3390/wevj15060260 - 14 Jun 2024
Viewed by 1253
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 [...] Read more.
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. Full article
Show Figures

Figure 1

15 pages, 10922 KiB  
Article
An Automatic Emergency Braking Control Method for Improving Ride Comfort
by Fei Lai, Junbo Liu and Yuanzhi Hu
World Electr. Veh. J. 2024, 15(6), 259; https://doi.org/10.3390/wevj15060259 - 14 Jun 2024
Viewed by 319
Abstract
The contribution of this paper is to present an automatic emergency braking (AEB) optimized algorithm based on time to collision (TTC) and a professional driver fitting (PDF) braking pattern. When the TTC value is less than the given threshold, the PDF control algorithm [...] Read more.
The contribution of this paper is to present an automatic emergency braking (AEB) optimized algorithm based on time to collision (TTC) and a professional driver fitting (PDF) braking pattern. When the TTC value is less than the given threshold, the PDF control algorithm will be started, and vice versa. According to the standard test scenarios for passenger cars and commercial vehicles, the simulation analysis on the AEB systems using four different control algorithms, namely TTC, quadratic curve deceleration, PDF and proposed optimized control algorithm, is conducted, respectively. The results show that the proposed optimization algorithm can both meet the standard requirements and improve the ride comfort. While ensuring collision avoidance with the preceding vehicle, the control algorithm proposed in this study offers better braking comfort compared to the TTC algorithm and the quadratic curve deceleration algorithm. Additionally, it provides a more appropriate stopping distance compared to the PDF algorithm. Full article
Show Figures

Figure 1

18 pages, 931 KiB  
Article
Exploring User Attitudes and Behavioral Intentions towards Augmented Reality Automotive Assistants: A Mixed-Methods Approach
by Fucheng Wan, Jian Teng and Lisi Feng
World Electr. Veh. J. 2024, 15(6), 258; https://doi.org/10.3390/wevj15060258 - 12 Jun 2024
Viewed by 310
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 [...] Read more.
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. Full article
25 pages, 5301 KiB  
Article
Improved Model Predictive Control Path Tracking Approach Based on Online Updated Algorithm with Fuzzy Control and Variable Prediction Time Domain for Autonomous Vehicles
by Binshan Liu, Zhaoqiang Wang, Hui Guo and Guoxiang Zhang
World Electr. Veh. J. 2024, 15(6), 257; https://doi.org/10.3390/wevj15060257 - 12 Jun 2024
Viewed by 269
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Dynamics, Control and Simulation of Electrified Vehicles)
15 pages, 6494 KiB  
Article
Design and Construction of a Multipole Electric Motor Using an Axial Flux Configuration
by Adrián González-Parada, Francisco Moreno Del Valle and Ricard Bosch-Tous
World Electr. Veh. J. 2024, 15(6), 256; https://doi.org/10.3390/wevj15060256 - 12 Jun 2024
Viewed by 407
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 [...] Read more.
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. Full article
(This article belongs to the Topic Advanced Electrical Machine Design and Optimization Ⅱ)
Show Figures

Figure 1

19 pages, 2999 KiB  
Article
Novel Deep Learning Domain Adaptation Approach for Object Detection Using Semi-Self Building Dataset and Modified YOLOv4
by Ahmed Gomaa and Ahmad Abdalrazik
World Electr. Veh. J. 2024, 15(6), 255; https://doi.org/10.3390/wevj15060255 - 12 Jun 2024
Viewed by 339
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Electric Vehicle Autonomous Driving Based on Image Recognition)
Show Figures

Figure 1

14 pages, 2442 KiB  
Article
Research on Filtering Algorithm of Vehicle Dynamic Weighing Signal
by Lingcong Xiong, Tieyi Zhang, Anlu Yuan and Zhipeng Zhang
World Electr. Veh. J. 2024, 15(6), 254; https://doi.org/10.3390/wevj15060254 - 12 Jun 2024
Viewed by 341
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 [...] Read more.
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. Full article
Show Figures

Figure 1

22 pages, 1375 KiB  
Article
Multi-Cell Cooperative Resource Allocation and Performance Evaluation for Roadside-Assisted Automated Driving
by Shu Yang, Xuanhan Zhu, Yang Li, Quan Yuan and Lili Li
World Electr. Veh. J. 2024, 15(6), 253; https://doi.org/10.3390/wevj15060253 - 11 Jun 2024
Viewed by 424
Abstract
The proliferation of wireless technologies, particularly the advent of 5G networks, has ushered in transformative possibilities for enhancing vehicular communication systems, particularly in the context of autonomous driving. Leveraging sensory data and mapping information downloaded from base stations using I2V links, autonomous vehicles [...] Read more.
The proliferation of wireless technologies, particularly the advent of 5G networks, has ushered in transformative possibilities for enhancing vehicular communication systems, particularly in the context of autonomous driving. Leveraging sensory data and mapping information downloaded from base stations using I2V links, autonomous vehicles in these networks present the promise of enabling distant perceptual abilities essential to completing various tasks in a dynamic environment. However, the efficient down-link transmission of vehicular network data via base stations, often relying on spectrum sharing, presents a multifaceted challenge. This paper addresses the intricacies of spectrum allocation in vehicular networks, aiming to resolve the thorny issues of cross-station interference and coupling while adapting to the dynamic and evolving characteristics of the vehicular environment. A novel approach is suggested involving the utilization of a multi-agent option-critic reinforcement learning algorithm. This algorithm serves a dual purpose: firstly, it learns the most efficient way to allocate spectrum resources optimally. Secondly, it adapts to the ever-changing dynamics of the environment by learning various policy options tailored to different situations. Moreover, it identifies the conditions under which a switch between these policy options is warranted as the situation evolves. The proposed algorithm is structured in two layers, with the upper layer consisting of policy options that are shared across all agents, and the lower layer comprising intra-option policies executed in a distributed manner. Through experimentation, we showcase the superior spectrum efficiency and communication quality achieved by our approach. Specifically, our approach outperforms the baseline methods in terms of training average reward convergence stability and the transmission success rate. Control-variable experiments also reflect the better adaptability of the proposed method as the environmental conditions change, underscoring the significant potential of the proposed method in aiding successful down-link transmissions in vehicular networks. Full article
Show Figures

Figure 1

22 pages, 6301 KiB  
Article
Intelligent Vehicle Formation System Based on Information Interaction
by Peng Wang, Tao Ouyang, Shixin Zhao, Xuelin Wang, Zhewen Ni and Yuezhen Fan
World Electr. Veh. J. 2024, 15(6), 252; https://doi.org/10.3390/wevj15060252 - 11 Jun 2024
Viewed by 502
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 [...] Read more.
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. Full article
Show Figures

Figure 1

16 pages, 3821 KiB  
Article
State-Feedback and Nonsmooth Controller Design for Truck Platoon Subject to Uncertainties and Disturbances
by Jianbo Feng, Zepeng Gao and Bingying Guo
World Electr. Veh. J. 2024, 15(6), 251; https://doi.org/10.3390/wevj15060251 - 11 Jun 2024
Viewed by 422
Abstract
Intelligent truck platoons can benefit road transportation due to the short gap and better fuel economy, but they are also subject to dynamic uncertainties and external disturbances. Therefore, this paper develops a novel robust control algorithm for connected truck platoons. By introducing a [...] Read more.
Intelligent truck platoons can benefit road transportation due to the short gap and better fuel economy, but they are also subject to dynamic uncertainties and external disturbances. Therefore, this paper develops a novel robust control algorithm for connected truck platoons. By introducing a linearized expression method of platoon error dynamics based on state measurement, the state feedback mechanism combined with a nonsmooth controller for a truck platoon is proposed in the development of the distributed control method. The state-feedback controller can drive the nominal platoon system to the state of second-order consensus, and the nonsmooth controller counterparts the uncertainties and disturbances. The convergence and string stability of the proposed control algorithm are demonstrated both theoretically and experimentally, and the effectiveness and robustness are also verified by simulation tests. Full article
Show Figures

Figure 1

24 pages, 7565 KiB  
Article
Simulation and Testing of Self-Reconfigurable Battery Advanced Functions for Automotive Application
by Rémy Thomas, Nicolas Léto, Jérome Lachaize, Sylvain Bacquet, Yan Lopez and Leandro Cassarino
World Electr. Veh. J. 2024, 15(6), 250; https://doi.org/10.3390/wevj15060250 - 8 Jun 2024
Viewed by 437
Abstract
This article presents the design and production work carried out jointly by Vitesco Technologies and the CEA in order to build a Self-Reconfigurable Battery (SRB) demonstrator representative of an electric vehicle traction battery pack. The literature demonstrates that the use of an SRB [...] Read more.
This article presents the design and production work carried out jointly by Vitesco Technologies and the CEA in order to build a Self-Reconfigurable Battery (SRB) demonstrator representative of an electric vehicle traction battery pack. The literature demonstrates that the use of an SRB allows for individual bypassing or serialization of each cell in a battery pack, enabling control of the voltage output and dynamic balancing of the battery pack during all phases of vehicle use. The simulations and tests presented in this article confirm that the use of an SRB results in a 6% reduction in energy consumption compared to a Conventional Battery Pack (CBP) on a driving profile based on WLTP cycles. Additionally, an SRB enhances fast charging performance, with a charging time that is 22% faster than a CBP. Furthermore, it is shown that an SRB without a voltage inversion capability can still be connected directly to the AC grid for charging without the need for a dedicated converter, using only a single diode bridge rectifier for the whole system. Full article
Show Figures

Figure 1

26 pages, 1364 KiB  
Article
Joint Estimation of Driving State and Road Surface Adhesion Coefficient of a Four-Wheel Independent and Steering-Drive Electric Vehicle
by Zhixin Chen, Gang Li, Zhihua Zhang and Ruolan Fan
World Electr. Veh. J. 2024, 15(6), 249; https://doi.org/10.3390/wevj15060249 - 7 Jun 2024
Viewed by 371
Abstract
Vehicle running state parameters and road surface state are crucial to the stability of four-wheel independent drive and steering electric vehicle control. Therefore, this study explores the estimation of vehicle driving state parameters and road surface adhesion coefficients using a combination of federal [...] Read more.
Vehicle running state parameters and road surface state are crucial to the stability of four-wheel independent drive and steering electric vehicle control. Therefore, this study explores the estimation of vehicle driving state parameters and road surface adhesion coefficients using a combination of federal Kalman filtering and an intelligent bionic antlion optimization algorithm. Firstly, according to the research purpose of the paper and the focus on the accuracy of the establishment of the three degrees of freedom dynamics model, fully considering the road conditions, the paper adopts the Dugoff tire model and finally completes the establishment of the vehicle state estimation model. Secondly, the drive state estimation algorithm is developed utilizing the principles of federal Kalman filtering and volume Kalman filtering. At the same time, robust estimation theory is introduced into the sub-filter, and the antlion optimization module is designed at the lower layer of the main filter to enhance the accuracy of estimates. It is easy to see that the design of the Antlion federal Kalman travel state estimation algorithm has noticeably enhanced accuracy and traceability, according to the result. Thirdly, a joint estimation algorithm of state estimation and road surface adhesion coefficient has been devised to enhance the stability and precision of the estimation process. Finally, the results showed that the joint estimation algorithm has high accuracy in estimating vehicle driving state parameters such as the center of mass lateral deflection angle and road surface adhesion coefficient by simulation. Full article
12 pages, 3201 KiB  
Article
State of Health Prediction of Lithium-Ion Batteries Based on Multi-Kernel Relevance Vector Machine and Error Compensation
by Li Zhang, Chao Sun and Shilin Liu
World Electr. Veh. J. 2024, 15(6), 248; https://doi.org/10.3390/wevj15060248 - 6 Jun 2024
Viewed by 287
Abstract
Though lithium-ion batteries are extensively applied in electric vehicles as a power source due to their excellent advantages in recent years, the security risk has inarguably always existed. The state of health (SOH) of lithium-ion batteries is one of the most important indicators [...] Read more.
Though lithium-ion batteries are extensively applied in electric vehicles as a power source due to their excellent advantages in recent years, the security risk has inarguably always existed. The state of health (SOH) of lithium-ion batteries is one of the most important indicators related to security, the prediction of SOH is paid close attention spontaneously. To improve the prediction accuracy of SOH, this paper constructs an SOH prediction model based on a multi-kernel relevance vector machine and error compensation (EC-MKRVM). The provided model comprises a pre-estimation model and an error compensation model, both of which use the multi-kernel relevance vector machine (MKRVM) algorithm. The pre-estimation model takes the feature factors extracted in the charging segment as the input variable and the SOH pre-estimation value as the output. The error compensation model takes the pre-estimation error sequence as the input variable and the SOH prediction error as the output. Finally, the SOH prediction error is used to compensate for the SOH pre-estimation value of the pre-estimation model, and the final SOH prediction value is obtained. To verify the effectiveness and advancement of the model, the CACLE dataset is used for comparative experimental analysis. The results show that the proposed prediction model in this paper has higher prediction accuracy. Full article
Show Figures

Figure 1

18 pages, 8352 KiB  
Article
All-Wheel Steering Tracking Control Method for Virtual Rail Trains with Only Interoceptive Sensors
by Zhenpo Wang, Yi Zhang and Zhifu Wang
World Electr. Veh. J. 2024, 15(6), 247; https://doi.org/10.3390/wevj15060247 - 4 Jun 2024
Viewed by 451
Abstract
A virtual rail train (VRT) is a multi-articulated vehicle as well as a novel public transportation system due to its low economic cost, environmental friendliness and high transit capacity. Equipped with all-wheel steering (AWS) and a tracking control method, the super long VRT [...] Read more.
A virtual rail train (VRT) is a multi-articulated vehicle as well as a novel public transportation system due to its low economic cost, environmental friendliness and high transit capacity. Equipped with all-wheel steering (AWS) and a tracking control method, the super long VRT can travel on urban roads easily. This paper proposed a tracking control approach using only interoceptive sensors with high scene adaptivity. The kinematic model was established first under reasonable assumptions when the sensor configuration was completed simultaneously. A hierarchical controller consists of a front axle controller and a rear axle controller. The former applies virtual axles theory to avoid motion interference. The latter generates a first-axle reference path with path segmentation and a data updating method to improve storage and computational efficiency. Then, a fast curvature matching rear axles control method is developed with an actuator time delay considered. Finally, the proposed approach is verified in a hardware in loop (HIL) simulation under various situations with predefined evaluation standards, which shows better tracking performance and applicability. Full article
Show Figures

Figure 1

14 pages, 3752 KiB  
Article
A Comparative Study of Traffic Signal Control Based on Reinforcement Learning Algorithms
by Chen Ouyang, Zhenfei Zhan and Fengyao Lv
World Electr. Veh. J. 2024, 15(6), 246; https://doi.org/10.3390/wevj15060246 - 4 Jun 2024
Viewed by 501
Abstract
In recent years, the increasing production and sales of automobiles have led to a notable rise in congestion on urban road traffic systems, particularly at ramps and intersections with traffic signals. Intelligent traffic signal control represents an effective means of addressing traffic congestion. [...] Read more.
In recent years, the increasing production and sales of automobiles have led to a notable rise in congestion on urban road traffic systems, particularly at ramps and intersections with traffic signals. Intelligent traffic signal control represents an effective means of addressing traffic congestion. Reinforcement learning methods have demonstrated considerable potential for addressing complex traffic signal control problems with multidimensional states and actions. In this research, the team propose Q-learning and Deep Q-Network (DQN) based signal control frameworks that use variable phase sequences and cycle times to adjust the order and the duration of signal phases to obtain a stable traffic signal control strategy. Experiments are simulated using the traffic simulator Simulation of Urban Mobility (SUMO) to test the average speed and the lane occupancy rate of vehicles entering the ramp to evaluate its safety performance and test the vehicle’s traveling time to assess its stability. The simulation results show that both reinforcement learning algorithms are able to control cars in dynamic traffic environments with higher average speed and lower lane occupancy rate than the no-control method and that the DQN control model improves the average speed by about 10% and reduces the lane occupancy rate by about 30% compared to the Q-learning control model, providing a higher safety performance. Full article
(This article belongs to the Special Issue Development towards Vehicle Safety in Future Smart Traffic Systems)
Show Figures

Figure 1

Previous Issue
Next Issue
Back to TopTop