Advanced Electric Vehicle Technology, 2nd Volume

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

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Batteries batteries	4.0	5.4	2015	17.7 Days	CHF 2700	Submit
Designs designs	-	3.2	2017	16.4 Days	CHF 1600	Submit
Energies energies	3.2	5.5	2008	16.1 Days	CHF 2600	Submit
Sustainability sustainability	3.9	5.8	2009	18.8 Days	CHF 2400	Submit
Vehicles vehicles	2.2	2.9	2019	22.2 Days	CHF 1600	Submit
World Electric Vehicle Journal wevj	2.3	3.7	2007	14.1 Days	CHF 1400	Submit

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Published Papers (5 papers)

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All Batteries Designs Energies Sustainability Vehicles WEVJ

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26 pages, 4807 KiB  

Open AccessReview

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

Viewed by 418

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  

Open AccessArticle

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 637

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  

Open AccessArticle

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

Viewed by 708

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  

Open AccessArticle

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

Viewed by 969

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  

Open AccessArticle

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 - 09 Mar 2024

Viewed by 1117

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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