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Department of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
School of Automation Science and Engineering, South China University of Technology, Guangzhou, China
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Advanced Electric Vehicle Technology, 2nd Volume

Abstract submission deadline
closed (31 January 2025)
Manuscript submission deadline
closed (31 March 2025)
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37126

Topic Information

Dear Colleagues,

This Topic is a continuation of the previous successful Topic “Advanced Electric Vehicle Technology, 2nd Volume”. Electric vehicles are a very exciting topic of research and industrial development. In the last 10 years, rapid development in both electric vehicle technology and commercial activities has occurred. The number of research papers, webinars, tutorial courses and PhD graduates in this field has rapidly increased. Commercial electric vehicles have increased in terms of both their sales and models. Electric vehicles are also a hot topic in the news and internet media. Their batteries, energy storage, packaging and chargers still require a lot of research effort. Other associated technologies, such as Vehicle-to-X and new motors and actuators, are now replacing all the conventional mechanical and hydraulic systems in vehicles. Because of the demand for smart cities and robotic activities, new control methods and autonomous driving are now being applied to and developed in most vehicles. All automotive enterprises have gradually changed their models into electric versions. The associated infrastructure and government policy and standards are evolving, and we can see that this is an exciting topic of research. Today, electric vehicle technology has been extended to vessels, underwater vehicles, air transport and space vehicles. This technology is not only restricted to electrical, electronic and computer engineering but also extends to multi-disciplinary research.

We have initialized this Topic because we can see that the market development for electric vehicles is expanding rapidly. The next 50 years will be a transition period from fossil fuel vehicles to electric vehicles. The next 20 years are critical to electric vehicle development, and we now invite you to submit a paper to report, discuss and predict the research and development in this exciting field of science.

Prof. Dr. Eric Cheng
Prof. Dr. Junfeng Liu
Topic Editors

Keywords

  • electric vehicles
  • electric mass transit
  • energy storage
  • battery systems
  • fuel cells
  • wireless power transfer
  • V2X
  • connected vehicles
  • autonomous vehicles
  • vehicle standards
  • infrastructure of electric vehicles
  • government policy on electric vehicles
  • outer-space vehicles
  • modeling, simulation and control for vehicles
  • electric components for sea, submerged and air vehicles

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Batteries
batteries 		4.6 4.0 2015 19.7 Days CHF 2700
Designs
designs 		- 3.9 2017 21.7 Days CHF 1600
Energies
energies 		3.0 6.2 2008 16.8 Days CHF 2600
Sustainability
sustainability 		3.3 6.8 2009 19.7 Days CHF 2400
Vehicles
vehicles 		2.4 4.1 2019 19.9 Days CHF 1600
World Electric Vehicle Journal
wevj 		2.6 4.5 2007 16.2 Days CHF 1400

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Published Papers (22 papers)

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17 pages, 2821 KiB  
Article
Power Feasible Region Modeling and Voltage Support Control for V2G Charging Station Under Grid Fault Conditions
by Jinxin Ouyang, Ang Li, Yanbo Diao and Fei Huang
Sustainability 2025, 17(8), 3713; https://doi.org/10.3390/su17083713 - 19 Apr 2025
Viewed by 103
Abstract
The charging station (CS) is generally directly off-grid under a grid fault, which has become a key technical bottleneck that restricts the sustainable development of new energy transportation systems. During a grid fault, the CS under the vehicle-to-grid (V2G) mode experiences a reduction [...] Read more.
The charging station (CS) is generally directly off-grid under a grid fault, which has become a key technical bottleneck that restricts the sustainable development of new energy transportation systems. During a grid fault, the CS under the vehicle-to-grid (V2G) mode experiences a reduction in active power due to the current limitation of the voltage source converter (VSC), which may cause the DC voltage to exceed its limitations under unbalanced power. The effect of the active and reactive power of CS in low- and medium-voltage distribution networks on supporting the PCC voltage under the limitation of DC voltage and VSC current has not been analyzed, and a control method for PCC voltage support for CS has not been established. Therefore, a power boundary that avoids the DC overvoltage and AC overcurrent of the CS is defined. A power feasible region for the CS considering fault duration is established. The characteristic that the power feasible region shrinks with the increase in duration is found, and a calculation method for the critical clearing time of a fault to avoid DC overvoltage is proposed. The relationship between PCC voltage and power injected by the CS is analyzed. The property that the control point of maximum voltage support lies at the boundary of the power feasible region is revealed. A control method of PCC voltage support that considers the limitation of DC voltage and VSC current for the CS is proposed. Simulation verification shows that the support capability of CS for PCC voltage during a fault is significantly enhanced by the proposed method while securing the DC voltage. Full article
(This article belongs to the Topic Advanced Electric Vehicle Technology, 2nd Volume)
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23 pages, 4901 KiB  
Article
Multi-Objective Optimization Scheduling for Electric Vehicle Charging and Discharging: Peak-Load Shifting Strategy Based on Monte Carlo Sampling
by Jian Zheng, Jinglan Cui, Zhongmei Zhao, Guocheng Li, Cong Wang, Zeguang Lu, Xiaohu Yang and Zhengguang Liu
Designs 2025, 9(2), 51; https://doi.org/10.3390/designs9020051 - 17 Apr 2025
Viewed by 366
Abstract
The uncoordinated charging behaviors of electric vehicles (EVs) challenge the stable operation of the grid, e.g., increasing the peak-to-valley ratio of the grid and diminishing power supply reliability. A Monte Carlo sampling method is employed to develop a charging behavior model for EVs [...] Read more.
The uncoordinated charging behaviors of electric vehicles (EVs) challenge the stable operation of the grid, e.g., increasing the peak-to-valley ratio of the grid and diminishing power supply reliability. A Monte Carlo sampling method is employed to develop a charging behavior model for EVs to solve the problems raised by random charge mode. The probability densities of daily driving distance, initial charging time, charging power, and charging duration are incorporated and analyzed. The proposed model enables multiple random sample values for EVs, considering varying weather conditions and time-of-use electricity prices. For charge and discharge optimization, an EV charge and discharge scheduling model is constructed, aiming to balance multiple objective functions, including battery degradation costs, user charging costs, grid load fluctuations, and peak-to-valley differences. The weighting method is applied to transform the multi-objective framework into a single-objective comprehensive solution, facilitating the identification of optimal charge and discharge strategies. Results demonstrate that the Monte Carlo sampling can satisfactorily generate datasets with realistic characteristics on the driving range and charging initiation time of the EVs. Furthermore, the load results achieved through multi-objective optimization demonstrate that the proposed strategy effectively mitigates peak-to-valley disparities. The peak load reduction and trough load increment are 27.6% and 160.1%, respectively. Through post-peak load balancing, the average costs of each EV for daily charging and battery degradation are reduced to be 7.58 yuan and 15.68 yuan, respectively. This approach can significantly enhance the grid stability, simultaneously address the economic interests of users, and extend battery lifespan. Full article
(This article belongs to the Topic Advanced Electric Vehicle Technology, 2nd Volume)
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21 pages, 5512 KiB  
Article
Comparing the Effectiveness of Deep Learning Approaches for Charging Time Prediction in Electric Vehicles: Kocaeli Example
by Ayşe Tuğba Yapıcı, Nurettin Abut and Tarık Erfidan
Energies 2025, 18(8), 1961; https://doi.org/10.3390/en18081961 - 11 Apr 2025
Viewed by 473
Abstract
The aim of this study is to compare the performance of various deep learning models in predicting the arrival and charging time of an electric vehicle at a charging station. The objective is to identify the most precise model capable of predicting the [...] Read more.
The aim of this study is to compare the performance of various deep learning models in predicting the arrival and charging time of an electric vehicle at a charging station. The objective is to identify the most precise model capable of predicting the time from the driver’s location to the arrival at the charging station. Initially, an effort was made to ascertain which model type offers superior prediction accuracy, characterized by low error rates and high success scores. To this end, the study examined the prediction capabilities of the LSTM (Long Short-Term Memory), GRU (Gated Recurrent Unit), Prophet, and ARIMA (Autoregressive Integrated Moving Average) models, which were trained with historical data using various metrics. These metrics included the R2 (R-squared)success metric, MAE (Mean Absolute Error) and MSE (Mean Squared Error) error metrics, DTW (Dynamic Time Warping) metric scores, and model selection. In MAE metric scores, GRU has an error rate of 0.38, LSTM 0.50, Prophet 0.61, and ARIMA 2.31. For MSE metric scores, GRU has an error rate of 2.92, LSTM 3.05, Prophet 4.21, and ARIMA 65.54. In R2 metric scores, GRU has a success rate of 0.99, LSTM 0.99, Prophet 0.13, and ARIMA −2.19. In DTW metric scores, GRU has a distance ratio of 125.5, LSTM 126.9, Prophet 185.9, and ARIMA 454.9. Based on these score values, it was decided that the GRU model made the most accurate time estimation. After observing the superior performance of the GRU model, the time prediction capability of this model is demonstrated through an interface program for charging stations in the province of Kocaeli, which serves as the model’s real-world application area. The main contribution of this article is that LSTM, GRU, Prophet, and ARIMA deep learning approaches, which are preferred in many studies, are used for the first time in the process of estimating electric vehicle charging time. Full article
(This article belongs to the Topic Advanced Electric Vehicle Technology, 2nd Volume)
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15 pages, 1904 KiB  
Article
Design of a High-Voltage Insulation Resistance Detection System for Commercial Vehicles
by Feng Guo, Danping She, Xinfeng Zhang and Yue Han
Batteries 2025, 11(4), 143; https://doi.org/10.3390/batteries11040143 - 7 Apr 2025
Viewed by 305
Abstract
Based on the safety monitoring requirements of power batteries for new energy commercial vehicles, this study proposes a battery insulation detection method utilizing the bridge method in combination with existing insulation detection techniques. Through optimization and improvement of this methodology, an insulation detection [...] Read more.
Based on the safety monitoring requirements of power batteries for new energy commercial vehicles, this study proposes a battery insulation detection method utilizing the bridge method in combination with existing insulation detection techniques. Through optimization and improvement of this methodology, an insulation detection system for new energy commercial vehicle power batteries was developed, along with a dynamic online calculation method for insulation resistance. Comprehensive experimental testing under multiple operational conditions demonstrates that the proposed system achieves a measurement accuracy with errors below 5% for insulation resistance. Furthermore, the system exhibits significant advantages in dynamic real-time monitoring capabilities and operational reliability. Full article
(This article belongs to the Topic Advanced Electric Vehicle Technology, 2nd Volume)
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21 pages, 2653 KiB  
Article
The Potential of Thailand in Advancing the Classic Car EV Conversion Industry: A Transition Strategy
by Warit Thammasiriroj, Chedthawut Poompipatpong and Puchong Khumpunja
World Electr. Veh. J. 2025, 16(3), 122; https://doi.org/10.3390/wevj16030122 - 23 Feb 2025
Viewed by 850
Abstract
The adoption of electric vehicles (EVs) in Thailand has been growing steadily. This research study investigated the Thai automotive industry cluster and completed an analysis of the EV transition to create a domestic industry, its social and environmental impacts, the laws supporting EVs, [...] Read more.
The adoption of electric vehicles (EVs) in Thailand has been growing steadily. This research study investigated the Thai automotive industry cluster and completed an analysis of the EV transition to create a domestic industry, its social and environmental impacts, the laws supporting EVs, and consumer acceptance. The results of the study found that Thailand had 1.53 million EVs, accounting for 8.12% of all vehicles in 2023. This growing industry has a significant impact on Thailand’s GDP, highlighting the need for a strategic transition to support the development of the EV conversion industry. A particular focus is on the conversion of internal combustion engine vehicles that are over 10 years old. These debt-free vehicles, having simpler technology, present an ideal opportunity for modification as part of a broader strategy to prepare the domestic automotive sector for EV production and usage. A strong legal framework supports Thailand’s efforts by promoting the EV sector and EV conversion. The country is already a major automotive manufacturing hub, ranked 11th globally, with a robust automotive parts industry. Additionally, Thailand has a significant stock of older and classic cars, with 18.26% of its vehicles in 2023 being over 20 years old. The absence of laws restricting vehicle lifespan further facilitates the EV conversion process. Thailand’s legal measures also promote economic growth by supporting industries related to classic cars, with tax incentives designed to stimulate these sectors. The EV conversion business in Thailand attracted over USD 300 million in investment in 2023, with a survival rate of 97.33%, reflecting continuous year-on-year growth. These developments indicate that Thailand is well positioned to become a leading hub for EV conversion in Southeast Asia. If Thailand wants the EV conversion industry to grow without affecting stakeholders, those involved must consider the following issues or develop a transition strategy: (1) investment in the EV conversion industry; (2) environmental aspects of EV conversion; (3) laws related to EVs; and (4) consumers who are considering EV conversion. Countries with automotive industries similar to Thailand can consider using this model in their countries as well. Full article
(This article belongs to the Topic Advanced Electric Vehicle Technology, 2nd Volume)
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17 pages, 26724 KiB  
Article
Integrated Design and Dynamic Response Analysis of the EV Reducer Considering Mass Eccentricity
by Yuan Guan, Yao Li, Yue Deng, Gaoxiang Ni, Zifan Fang and Dong Huang
Energies 2025, 18(3), 530; https://doi.org/10.3390/en18030530 - 24 Jan 2025
Viewed by 664
Abstract
To meet the high-performance demands of electric vehicle reducers, the authors present a novel approach for parameter matching in electric drive systems for electric vehicles. Based on fuzzy evaluation, the method identifies the optimal performance parameters for the entire vehicle and determines the [...] Read more.
To meet the high-performance demands of electric vehicle reducers, the authors present a novel approach for parameter matching in electric drive systems for electric vehicles. Based on fuzzy evaluation, the method identifies the optimal performance parameters for the entire vehicle and determines the best transmission ratio scheme for the reducer. The gear geometrical parameters of the reducer are derived using the transmission ratio scheme as the constraint condition. An 18-degree-of-freedom dynamic system model, incorporating factors such as time-varying mesh stiffness, the backlash, time-varying transmission error and mass eccentricity, has been built using Matlab. The dynamic response of the gear system under the designed gear parameter scheme have been analyzed and compared with the gear parameter results obtained using KISSsoft, demonstrating the accuracy and rigour of the design. This research has practical implications for the design and performance optimization of electric vehicle reducers. Full article
(This article belongs to the Topic Advanced Electric Vehicle Technology, 2nd Volume)
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18 pages, 4398 KiB  
Article
Adaptive Second-Order Sliding Mode Wheel Slip Control for Electric Vehicles with In-Wheel Motors
by Jinghao Bi, Yaozhen Han, Mingdong Hou and Changshun Wang
World Electr. Veh. J. 2024, 15(11), 538; https://doi.org/10.3390/wevj15110538 - 20 Nov 2024
Viewed by 1035
Abstract
The influence of the external environment can reduce the braking performance of the electric vehicle (EV) with in-wheel motors (IWM). In this paper, an adaptive sliding mode wheel slip control method with a vehicle speed observer consideration is proposed, which enables the EV [...] Read more.
The influence of the external environment can reduce the braking performance of the electric vehicle (EV) with in-wheel motors (IWM). In this paper, an adaptive sliding mode wheel slip control method with a vehicle speed observer consideration is proposed, which enables the EV to accurately track the optimal slip ratio in various environments and improve braking performance. First, the braking system dynamics model is established by taking the EV with IWM as the study object. Second, a super-twisting sliding mode observer is used to estimate the vehicle speed, and a new adaptive second-order sliding mode controller is constructed to control the braking torque. Finally, co-simulation experiments are performed under different conditions based on Carsim and MATLAB/Simulink, and the proposed scheme is validated by comparison with three control methods. The experimental results show that the proposed scheme has better control performance, and both the safety and control quality of the EV is improved. Full article
(This article belongs to the Topic Advanced Electric Vehicle Technology, 2nd Volume)
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23 pages, 5900 KiB  
Review
Degradation Mechanism and Online Electrical Monitoring Techniques of Stator Winding Insulation in Inverter-Fed Machines: A Review
by Zihan Zou, Senyi Liu and Jinsong Kang
World Electr. Veh. J. 2024, 15(10), 444; https://doi.org/10.3390/wevj15100444 - 29 Sep 2024
Cited by 2 | Viewed by 1822
Abstract
Inverter-fed machines are widely used in electric vehicle drive systems and have shown a trend toward high voltage and frequency in recent years. They are subjected to multiple types of stress during operation, causing potential short-circuit fault damage to the stator winding insulation. [...] Read more.
Inverter-fed machines are widely used in electric vehicle drive systems and have shown a trend toward high voltage and frequency in recent years. They are subjected to multiple types of stress during operation, causing potential short-circuit fault damage to the stator winding insulation. Online condition monitoring of the insulation before or in the early stage of the short circuit fault can effectively reduce maintenance costs and ensure its health. This paper reviews and summarizes the deterioration mechanism and the recent online electrical monitoring techniques. First, four types of failure stress and each type’s failure factors and mechanisms are analyzed. The coupling effect and overall process of multi-physical fields on stator insulation failure are considered. Secondly, the latest online electrical monitoring technologies are summarized. Each technique’s principles, methods, advantages, and disadvantages are analyzed. Finally, existing problems and possible directions for improvement in current research are discussed, focusing on their feasibility and accuracy in practical applications. Full article
(This article belongs to the Topic Advanced Electric Vehicle Technology, 2nd Volume)
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13 pages, 9505 KiB  
Article
Research on Braking Characteristics of Hybrid Excitation Rotary Eddy Current Retarder
by Fei Wang, Wenguang Guo, Guijun Wu and Shi Li
World Electr. Veh. J. 2024, 15(10), 443; https://doi.org/10.3390/wevj15100443 - 28 Sep 2024
Viewed by 920
Abstract
According to the different excitation methods, automotive eddy current retarders (ECRs) can be divided into electrically excited retarders (EERs) and permanent magnet excited retarders (PMERs), and EERs and PMERs have certain complementarity in control and braking characteristics. Therefore, based on literature research, this [...] Read more.
According to the different excitation methods, automotive eddy current retarders (ECRs) can be divided into electrically excited retarders (EERs) and permanent magnet excited retarders (PMERs), and EERs and PMERs have certain complementarity in control and braking characteristics. Therefore, based on literature research, this article proposes a hybrid excitation rotary electromagnetic retarder (HERER) and conducts numerical simulation analysis and experimental research on the braking performance of the HERER. Firstly, the structure and working principle of the HERER are introduced. Secondly, based on the principles of electromagnetics, an equivalent magnetic circuit analysis model of the HERER is established. Then, a finite element analysis model of the HERER is established using Jmag 14 electromagnetic simulation software, and the braking performance of the HERER under different current and speed conditions is studied. Finally, bench tests are conducted on the air loss torque and eddy current braking performance of the HERER. The effectiveness of the finite element analysis model and equivalent magnetic circuit model of the HERER is verified. Full article
(This article belongs to the Topic Advanced Electric Vehicle Technology, 2nd Volume)
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20 pages, 6683 KiB  
Article
A Novel Estimating Algorithm of Critical Driving Parameters for Dual-Motor Electric Drive Tracked Vehicles Based on a Nonlinear Observer and an Adaptive Kalman Filter
by Zhaomeng Chen, Songhua Hu, Haoliang Lv and Yimeng Fu
Energies 2024, 17(18), 4625; https://doi.org/10.3390/en17184625 - 15 Sep 2024
Cited by 1 | Viewed by 997
Abstract
High-speed dual-motor electric drive tracked vehicles (DDTVs) have emerged as a research hotspot in the field of tracked vehicles in recent years due to their advantages in fuel economy and the scalability of electrical equipment. The emergency braking of a DDTV at high [...] Read more.
High-speed dual-motor electric drive tracked vehicles (DDTVs) have emerged as a research hotspot in the field of tracked vehicles in recent years due to their advantages in fuel economy and the scalability of electrical equipment. The emergency braking of a DDTV at high speed can lead to slipping or even yawing (which is caused by a large deviation of forces at each track directly), posing significant challenges to the vehicle’s stability and safety. Therefore, the accurate real-time acquisition of critical driving parameters, such as the longitudinal force and vehicle speed, is crucial for the stability control of a DDTV. This paper developed a novel estimating algorithm of critical driving parameters for DDTVs equipped with conventional sensors such as rotary transformers at PMSMs and onboard accelerometers on the basis of their dynamics models. The algorithm includes a sensor signal preprocessing module, a longitudinal force estimation method based on a nonlinear observer, and a speed estimation method based on an adaptive Kalman filter. Through hardware-in-loop experiments based on a Speedgoat real-time target machine, the proposed algorithm is proven to estimate the longitudinal force of the track and vehicle speed accurately, whether the vehicle has stability control functions or not, providing a foundation for the further development of vehicle stability control algorithms. Full article
(This article belongs to the Topic Advanced Electric Vehicle Technology, 2nd Volume)
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19 pages, 14049 KiB  
Article
Installation Design and Efficiency Evaluation of an EV Transform Powertrain and a 3.3 kW Multi-Charging System Driven by a 30 kW Permanent-Magnet Synchronous Motor
by Pataphiphat Techalimsakul and Arnon Niyomphol
Energies 2024, 17(18), 4584; https://doi.org/10.3390/en17184584 - 12 Sep 2024
Cited by 1 | Viewed by 1392
Abstract
This study focuses on the transformation of Jaguar XJ40 vehicles to electric power, with the main equipment being a permanent-magnet synchronous motor (PMSM), lithium iron phosphate (LFP) batteries, an on-board charger (OBC) system, and a battery management system (BMS). The process involves integrating [...] Read more.
This study focuses on the transformation of Jaguar XJ40 vehicles to electric power, with the main equipment being a permanent-magnet synchronous motor (PMSM), lithium iron phosphate (LFP) batteries, an on-board charger (OBC) system, and a battery management system (BMS). The process involves integrating the PMSM with the vehicle’s existing transmission system. This research compares the driving range of battery electric vehicles (BEVs) using different testing methods under the same conditions: simulation, dynamometer (dino), and actual on-road testing. Based on Raminthra’s public roads (RITA drive cycle), one drive cycle covers 7.64 km in 11.25 min. The simulation test by MATLAB/SIMULINK R2016a predicts a driving distance of up to 282.14 km. The dino test, using a chassis dynamometer to simulate driving conditions while the vehicle remains stationary, indicates a driving distance of 264.68 km. In contrast, actual on-road tests show a driving distance of 259.09 km, accounting for real-world driving conditions, including variations in speed, road types, weather, and traffic. The motor achieves 95% efficiency at 2400 rpm and 420 Nm torque. The simulated distance differs from the actual road distance by approximately 8.17%, suggesting reasonable accuracy of the model. Full article
(This article belongs to the Topic Advanced Electric Vehicle Technology, 2nd Volume)
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28 pages, 19988 KiB  
Article
Performance Improvement of Wireless Power Transfer System for Sustainable EV Charging Using Dead-Time Integrated Pulse Density Modulation Approach
by Franklin John, Pongiannan Rakkiya Goundar Komarasamy, Narayanamoorthi Rajamanickam, Lukas Vavra, Jan Petrov and Vladimir Kral
Sustainability 2024, 16(16), 7045; https://doi.org/10.3390/su16167045 - 16 Aug 2024
Cited by 5 | Viewed by 1463
Abstract
The recent developments in electric vehicle (EV) necessities the requirement of a human intervention free charging system for safe and reliable operation. Wireless power transfer (WPT) technology shows promising options to automate the charging process with user convenience. However, the operation of the [...] Read more.
The recent developments in electric vehicle (EV) necessities the requirement of a human intervention free charging system for safe and reliable operation. Wireless power transfer (WPT) technology shows promising options to automate the charging process with user convenience. However, the operation of the WPT system is designed to operate at a high-frequency (HF) range, which requires proper control and modulation technique to improve the performance of power electronic modules. This paper proposes a dead-time (DT) integrated Pulse Density Modulation (PDM) technique to provide better control with minimal voltage and current ripples at the switches. The proposed technique is investigated using a LCC-LCL compensated WPT system, which predominantly affects the high-frequency voltage and current ripples. The performance analysis is studied at different density conditions to explore the impact of the integrated PDM approach. Moreover, the PDM technique gives better control over the power transfer at different levels of load requirement. The simulation and experimental analysis was performed for a 3.7 kW WPT prototype test system under different modes of operation of the high-frequency power converters. Both the simulated and experimental results demonstrate that the proposed PDM technique effectively enhances the efficiency of the HF inverter while significantly reducing output current ripples, power dissipation and improving the overall WPT system efficiency to 92%, and leading to a reduction in the power loss in the range of 10% to 20%. This leads to improved overall system control and performance. Full article
(This article belongs to the Topic Advanced Electric Vehicle Technology, 2nd Volume)
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18 pages, 652 KiB  
Review
Vendor Partnerships in Sustainable Supply Chains in the Indian Electric Two-Wheeler Industry—A Systematic Review of the Literature
by D. K. Achal and G. S. Vijaya
Sustainability 2024, 16(15), 6603; https://doi.org/10.3390/su16156603 - 1 Aug 2024
Viewed by 2400
Abstract
The United Nations Convention on Climate Change 2015 mandates reducing the carbon footprint to reduce global warming. Considering environmental concerns, electric vehicles (EVs) spearhead the move towards green mobility. Niti Aayog (Indian Government) has envisaged an “EV only” scenario by 2030. Two wheelers, [...] Read more.
The United Nations Convention on Climate Change 2015 mandates reducing the carbon footprint to reduce global warming. Considering environmental concerns, electric vehicles (EVs) spearhead the move towards green mobility. Niti Aayog (Indian Government) has envisaged an “EV only” scenario by 2030. Two wheelers, with almost 80% of the market share of the Indian automobile industry, will provide the primary thrust for EVs. The holistic sustainability of the Indian EV two-wheeler industry will depend upon its vendor partnerships and processes, which are examined in this paper through a systematic review of the literature available from all known sources. This study, after reviewing over 165 papers apart from government and independent reports, also explores how sustainability and allied topics like green supply chain management in business decision making promotes efficiency, controls expenditure, enhances customer delight, increases sales and market share, optimizes risk management strategies and promotes profitability. Considering the restricted availability of the literature on the Indian automobile industry in general, and specifically on the Indian EV or EV two-wheeler industry, this work will help in bringing focus on this area of fast-burgeoning importance and will pave the way for the establishment of a conceptual framework for research. Full article
(This article belongs to the Topic Advanced Electric Vehicle Technology, 2nd Volume)
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23 pages, 2276 KiB  
Article
The Influence of Psychological Factors on Consumer Purchase Intention for Electric Vehicles: Case Study from China: Integrating the Necessary Condition Analysis Methodology from the Perspective of Self-Determination Theory
by Haipeng Zhao, Fumitaka Furuoka and Rajah Rasiah
World Electr. Veh. J. 2024, 15(8), 331; https://doi.org/10.3390/wevj15080331 - 24 Jul 2024
Cited by 3 | Viewed by 5666
Abstract
This paper examines the impact of psychological factors on consumer purchase intention for electric vehicles (EVs) through the lens of Self-Determination Theory (SDT). By integrating the three dimensions of autonomy, relatedness, and competence, this study addresses a research gap in consumer innovative consumption, [...] Read more.
This paper examines the impact of psychological factors on consumer purchase intention for electric vehicles (EVs) through the lens of Self-Determination Theory (SDT). By integrating the three dimensions of autonomy, relatedness, and competence, this study addresses a research gap in consumer innovative consumption, offering a deeper understanding of green transportation. The research reveals that psychological factors significantly influence innovative consumption and the purchase intention of EVs, aligning with the existing literature. In sustainable transportation, psychological factors such as motivation, attitude, and inner activities increasingly drive purchase decisions. This study examines the direct and indirect effects of psychological factors on purchase intention by employing Partial Least Squares Structural Equation Modeling (PLS-SEM) and Necessary Condition Analysis (NCA). It also considers the moderating role of driving experience in the relationship between psychological factors and innovative consumption. This combined data analysis approach provides a comprehensive understanding of the mechanisms influencing purchase intention, highlighting the intricate interplay between psychological determinants and consumer behavior in the adoption of electric vehicles. Full article
(This article belongs to the Topic Advanced Electric Vehicle Technology, 2nd Volume)
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23 pages, 5616 KiB  
Review
Advancing Electric Vehicle Infrastructure: A Review and Exploration of Battery-Assisted DC Fast Charging Stations
by Ahmet Aksoz, Burçak Asal, Emre Biçer, Saadin Oyucu, Merve Gençtürk and Saeed Golestan
Energies 2024, 17(13), 3117; https://doi.org/10.3390/en17133117 - 25 Jun 2024
Cited by 1 | Viewed by 2229
Abstract
Concerns over fossil fuel depletion, fluctuating fuel prices, and CO2 emissions have accelerated the development of electric vehicle (EV) technologies. This article reviews advancements in EV fast charging technology and explores the development of battery-assisted DC fast charging stations to address the [...] Read more.
Concerns over fossil fuel depletion, fluctuating fuel prices, and CO2 emissions have accelerated the development of electric vehicle (EV) technologies. This article reviews advancements in EV fast charging technology and explores the development of battery-assisted DC fast charging stations to address the limitations of traditional chargers. Our proposed approach integrates battery storage, allowing chargers to operate independently of the electric grid by storing electrical energy during off-peak hours and releasing it during peak times. This reduces dependence on grid power and enhances grid stability. Moreover, the transformer-less, modular design of the proposed solution offers greater flexibility, scalability, and reduced installation costs. Additionally, the use of smart energy management systems, incorporating artificial intelligence and machine learning techniques to dynamically adjust charging rates, will be discussed to optimize efficiency and cost-effectiveness. Full article
(This article belongs to the Topic Advanced Electric Vehicle Technology, 2nd Volume)
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19 pages, 3065 KiB  
Article
Research on Efficient Suspension Vibration Reduction Configuration for Effectively Reducing Energy Consumption
by Huixin Song, Mingming Dong and Liang Gu
Sustainability 2024, 16(10), 4208; https://doi.org/10.3390/su16104208 - 17 May 2024
Cited by 2 | Viewed by 1471
Abstract
Reducing vehicle energy consumption is crucial for sustainable development, especially in the context of energy crises and environmental pollution. Energy regenerative suspension offers a promising solution, yet its practical implementation faces challenges like inertial mass issues, cost, and reliability concerns. This study introduces [...] Read more.
Reducing vehicle energy consumption is crucial for sustainable development, especially in the context of energy crises and environmental pollution. Energy regenerative suspension offers a promising solution, yet its practical implementation faces challenges like inertial mass issues, cost, and reliability concerns. This study introduces a novel suspension configuration, optimizing shock absorber technology with energy regenerative principles. The objective is to drastically cut energy consumption. Through a frequency domain analysis, this study identifies the root causes of increased energy consumption and worsened vibration in traditional suspensions. This study presents a comparative analysis of the frequency-domain characteristics between the novel suspension configuration and the traditional one. This study reveals that the new configuration exhibits a low-pass filtering effect on the shock absorber’s velocity, effectively minimizing vibrations in the low-frequency range, while mitigating their impact in the high-frequency range. This approach mitigates the trade-off between increased energy consumption and worsened vibration in the high-frequency range, making it a promising solution. Simulations show that this configuration significantly reduces acceleration by 7.04% and suspension power consumption by 10.47% at 60 km/h on the D-level road, while maintaining handling stability. This makes it a promising candidate for future energy-efficient suspension systems. Full article
(This article belongs to the Topic Advanced Electric Vehicle Technology, 2nd Volume)
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20 pages, 13202 KiB  
Article
Efficiency Analysis of Hybrid Extreme Regenerative with Supercapacitor Battery and Harvesting Vibration Absorber System for Electric Vehicles Driven by Permanent Magnet Synchronous Motor 30 kW
by Pataphiphat Techalimsakul and Pakornkiat Sawetmethikul
World Electr. Veh. J. 2024, 15(5), 214; https://doi.org/10.3390/wevj15050214 - 12 May 2024
Cited by 2 | Viewed by 2038
Abstract
This research presents an approach to the hybrid energy harvesting paradigm (HEHP) based on suspended energy harvest. It uses a harvesting vibration absorber (HVA) with an SC/NMC-lithium battery hybrid energy storage paradigm (SCB-HESP) equipped regenerative braking system (SCB-HESP-RBS) for electric vehicles 2 tons [...] Read more.
This research presents an approach to the hybrid energy harvesting paradigm (HEHP) based on suspended energy harvest. It uses a harvesting vibration absorber (HVA) with an SC/NMC-lithium battery hybrid energy storage paradigm (SCB-HESP) equipped regenerative braking system (SCB-HESP-RBS) for electric vehicles 2 tons in gross weight (MEVs) driven by a 30 kW permanent magnet synchronous motor (PMSM). During regenerative braking, the ANN mechanism controls the RBS to adjust the switching waveform of the three-phase power inverter, and the braking energy transfers to the energy storage device. Additionally, a supercapacitor (SC) equipped with HVA can absorb energy from vehicle vibrations and convert it into electrical energy. The energy-harvesting efficiency of MEV based on SCB-HESP-RBS using HVA suspended energy harvesting enhances the efficiency maximum to 50.58% and 15.36% in comparison to MEV with only-HVA and SCB-HESP-RBS, respectively. Further, the MEV with SCB-HESP-RBS using HVA has a driving distance of up to 247.34 km (22.5 cycles) when compared with SCB-HESP-RBS (214.40 km, 19.5 cycles) and only-HVA (164.25 km, 15 cycles). Full article
(This article belongs to the Topic Advanced Electric Vehicle Technology, 2nd Volume)
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26 pages, 4807 KiB  
Review
Progress, Challenges and Opportunities of Electromobility in Mexico
by Lizbeth Salgado-Conrado, Carlos Álvarez-Macías, Rodrigo Loera-Palomo and C. Pamela García-Contreras
Sustainability 2024, 16(9), 3754; https://doi.org/10.3390/su16093754 - 30 Apr 2024
Cited by 6 | Viewed by 4024
Abstract
This paper highlights the attempts made by the government to integrate electromobility in Mexico, despite not having a well-defined National Electric Mobility Strategy, and compares the advances, challenges and future opportunities of electromobility with other countries with similar conditions in terms of the [...] Read more.
This paper highlights the attempts made by the government to integrate electromobility in Mexico, despite not having a well-defined National Electric Mobility Strategy, and compares the advances, challenges and future opportunities of electromobility with other countries with similar conditions in terms of the public policy, the evolution of the electric vehicles market, the charging infrastructure, incentives and legal framework, and diffusion channels. The results showed that Mexico has made partial advances in the infrastructure, production and exportation of electric vehicles, consumer incentives and project implementation. However, the country requires strengthening strategies on the economic incentives for the user and industry, homologation of chargers, training of personnel specialised in electric vehicles, handling and destination of batteries, and defining its National Electric Mobility Strategy. As a way forward, our study suggests comparing the electromobility strategies of other countries and understanding the key aspects that might enable the successful introduction of electric vehicles. Full article
(This article belongs to the Topic Advanced Electric Vehicle Technology, 2nd Volume)
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24 pages, 5743 KiB  
Article
Design of a Modularization-Based Automation Performance Simulation Framework for Multi-Vehicle Interaction System
by Qifeng Qian, Ronghui Xiang, Xiaohua Zeng, Dafeng Song and Xuanming Zhang
World Electr. Veh. J. 2024, 15(4), 138; https://doi.org/10.3390/wevj15040138 - 28 Mar 2024
Viewed by 1494
Abstract
With the electrification and connectivity of vehicles in transportation, traditional vehicles with single drivetrains are being replaced by pure electric or hybrid electric vehicles (HEVs). This evolution has given rise to diverse electromechanical coupling drivetrains. There is a pressing need to update simulation [...] Read more.
With the electrification and connectivity of vehicles in transportation, traditional vehicles with single drivetrains are being replaced by pure electric or hybrid electric vehicles (HEVs). This evolution has given rise to diverse electromechanical coupling drivetrains. There is a pressing need to update simulation software to assess the economic performance of vehicles in various environments, and promote sustainable development and energy conservation. This paper presents a unified framework for the construction and automated operation of large-scale automated vehicle simulations with multiple drivetrain types, facilitating synchronous information exchange among vehicles. Central to the framework is the development of a plug-and-play vehicle model based on a modular component design, facilitating the rapid assembly of vehicles with varied drivetrain configurations and standardizing simulation file management. Additionally, a standardized simulation process construction is established to accommodate the automated operation of simulations. Furthermore, a data scheduling method among vehicles is introduced to achieve multi-vehicle interconnection simulation. Finally, the effectiveness of the framework is demonstrated through a case study involving queue-following control for HEVs. This framework aims to provide a comprehensive solution for quickly establishing automated simulation environments for multi-vehicle interaction, enhancing model reusability and scalability. Full article
(This article belongs to the Topic Advanced Electric Vehicle Technology, 2nd Volume)
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27 pages, 7920 KiB  
Article
Fast Finite-Time Composite Controller for Vehicle Steer-by-Wire Systems with Communication Delays
by Kamal Rsetam, Jasim Khawwaf, Yusai Zheng, Zhenwei Cao and Zhihong Man
World Electr. Veh. J. 2024, 15(4), 132; https://doi.org/10.3390/wevj15040132 - 26 Mar 2024
Cited by 3 | Viewed by 1683
Abstract
The modern steer-by-wire (SBW) systems represent a revolutionary departure from traditional automotive designs, replacing mechanical linkages with electronic control mechanisms. However, the integration of such cutting-edge technologies is not without its challenges, and one critical aspect that demands thorough consideration is the presence [...] Read more.
The modern steer-by-wire (SBW) systems represent a revolutionary departure from traditional automotive designs, replacing mechanical linkages with electronic control mechanisms. However, the integration of such cutting-edge technologies is not without its challenges, and one critical aspect that demands thorough consideration is the presence of nonlinear dynamics and communication network time delays. Therefore, to handle the tracking error caused by the challenge of time delays and to overcome the parameter uncertainties and external perturbations, a robust fast finite-time composite controller (FFTCC) is proposed for improving the performance and safety of the SBW systems in the present article. By lumping the uncertainties, parameter variations, and exterior disturbance with input and output time delays as the generalized state, a scaling finite-time extended state observer (SFTESO) is constructed with a scaling gain for quickly estimating the unmeasured velocity and the generalized disturbances within a finite time. With the aid of the SFTESO, the robust FFTCC with the scaling gain is designed not only for ensuring finite-time convergence and strong robustness against time delays and disturbances but also for improving the speed of the convergence as a main novelty. Based on the Lyapunov theorem, the closed-loop stability of the overall SBW system is proven as a global uniform finite-time. Through examination across three specific scenarios, a comprehensive evaluation is aimed to assess the efficiency of the suggested controller strategy, compared with active disturbance rejection control (ADRC) and scaling ADRC (SADRC) methods across these three distinct driving scenarios. The simulated results have confirmed the merits of the proposed control in terms of a fast-tracking rate, small tracking error, and strong system robustness. Full article
(This article belongs to the Topic Advanced Electric Vehicle Technology, 2nd Volume)
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21 pages, 7116 KiB  
Article
An Investigation of Representative Customer Load Collectives in the Development of Electric Vehicle Drivetrain Durability
by Mingfei Li, Fabian Kai-Dietrich Noering, Yekta Öngün, Michael Appelt and Roman Henze
World Electr. Veh. J. 2024, 15(3), 112; https://doi.org/10.3390/wevj15030112 - 15 Mar 2024
Cited by 1 | Viewed by 1942
Abstract
To ensure the precise dimensioning and effective testing of drivetrain components, it is crucial to have a thorough understanding of customer requirements, with a particular emphasis on customer stress on these components. An accurate interpretation of customer data is essential for determining representative [...] Read more.
To ensure the precise dimensioning and effective testing of drivetrain components, it is crucial to have a thorough understanding of customer requirements, with a particular emphasis on customer stress on these components. An accurate interpretation of customer data is essential for determining representative customer requirements, such as load collectives. The automobile industry has faced challenges in analyzing large amounts of customer driving data to obtain representative load collectives as target values in durability design. However, due to technical limitations and cost constraints, collecting data from a large sample size is not feasible. The ongoing digitalization of the automotive industry, driven by an increasing number of connected vehicles, enhances data-based and customer-oriented development. This paper investigates representative customer load collectives using cloud data from over 40,000 customer vehicles to lay the groundwork for realizing robust requirement engineering. A systematic method for analyzing big data on the cloud was introduced. The derived component-specific damage distribution from these collectives adopts a unique approach, utilizing the 1% vehicle term instead of the common 1% customer term to represent typical customer stress. This study shows that the driven mileage and the number of vehicles are crucial factors in 1% vehicle analysis. An analysis of the characteristics of the 1% vehicle is conducted, followed by an exploration to determine the required vehicle quantity for obtaining stable results. The shape parameter of the damage distribution determines the necessary number of vehicles for a reliable conclusion. Additionally, a comparative analysis of market-specific customer requirements between the US and Europe is presented, and real usage differences in customer operations are explained using an operating point frequency heatmap. The information presented in this paper provides valuable input for optimizing durability design and conducting efficient, customer-oriented tests, resulting in significant reductions in development time and costs. Full article
(This article belongs to the Topic Advanced Electric Vehicle Technology, 2nd Volume)
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26 pages, 15329 KiB  
Article
Research on Vehicle Frame Optimization Methods Based on the Combination of Size Optimization and Topology Optimization
by Qun He, Xinning Li, Wenjie Mao, Xianhai Yang and Hu Wu
World Electr. Veh. J. 2024, 15(3), 107; https://doi.org/10.3390/wevj15030107 - 9 Mar 2024
Cited by 8 | Viewed by 2643
Abstract
The efficient development of electric vehicles is essential to drive society towards sustainable development. Designing a lightweight frame is a key strategy to improve the economy and environment, increase energy efficiency, and reduce carbon emissions. Taking an automatic loading and unloading mixer truck [...] Read more.
The efficient development of electric vehicles is essential to drive society towards sustainable development. Designing a lightweight frame is a key strategy to improve the economy and environment, increase energy efficiency, and reduce carbon emissions. Taking an automatic loading and unloading mixer truck as the research object, a force analysis of its frame was conducted under six typical working conditions. A size optimization method based on a hybrid model of the Kriging model and the analytic hierarchy process (AHP) is proposed. An approximate model of the mass and maximum stress of the frame was established using the Kriging model, and the Kriging model was optimized by using the multi-objective genetic optimization algorithm and the AHP method. Meanwhile, topology optimization was introduced to improve the structural performance of the frame and reduce its weight. The optimization results show that the overall weight of the frame is reduced by 11.96% compared to the pre-optimization period, though it still meets the material performance specifications. By comparing the iterative curves of the single Kriging model with those of the AHP model, it can be seen that the initial optimization efficiency of the hybrid model is about twice as much as that of the AHP model, and the final optimization result is improved by about 3.6% compared with the Kriging model. This validates the hybrid model as an effective tool for the multi-objective optimization of electric vehicle frames, providing more efficient and accurate optimization results for frame design. Full article
(This article belongs to the Topic Advanced Electric Vehicle Technology, 2nd Volume)
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