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WEVJ
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Vehicle Control and Drive Systems for Electric Vehicles
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Vehicle Control and Drive Systems for Electric Vehicles

A special issue of World Electric Vehicle Journal (ISSN 2032-6653).

Deadline for manuscript submissions: 31 December 2024 | Viewed by 10337

Special Issue Editors

Dr. Dejun Yin

E-Mail Website
Guest Editor
School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, China
Interests: design and development of electronic and electrical systems for vehicles; software and hardware for vehicle control systems
Dr. Jianhu Yan

E-Mail Website
Guest Editor
School of Automation, Nanjing University of Science and Technology, Nanjing, Jiangsu, China
Interests: electrical machine design and control for EVs

Special Issue Information

Dear Colleagues,

With the advantages of zero emissions and no dependence on oil resources, electric vehicles have been unanimously favored by the public, and are the main direction of the future development of the automobile industry. As the demands of people on the move are increasingly enhanced, the requirements for vehicle quality and function are also increasing. The study of vehicle control and drive systems has long been an important method for achieving this goal. Vehicle automation offers new opportunities for designing vehicle control systems by applying the fusion of diverse information channels and incorporating intelligent and adaptive decision-making algorithms in the control logic. In comparison with conventional vehicle powertrains, electric drive systems require higher integration, higher speed, and higher power density. Therefore, innovations regarding the design, control, and optimization of electric drive systems, as well as their core components such as motors and control, have become a hot topic in the automotive field.

Aimed at spreading the latest research in the field widely, we are pleased to announce a Special Issue on "Vehicle Control and Drive Systems for Electric Vehicles". This Special Issue will bring together original and high-quality articles through an international standard peer-review process on the following main topics (but not limited to only these):

  • Control and automation systems in automobiles.
  • Specific problems of designing vehicle dynamics control systems for electric vehicles.
  • Specific problems of vehicle dynamics.
  • Active and passive vehicle safety.
  • Energy efficiency and rational use of energy in electric vehicles.
  • Design and development of drive systems for electric vehicles.
  • Design, control, and optimization of in-wheel motors.
  • Control and calibration of powertrains.
  • Distributed generation and renewable energy systems.
  • Energy-efficient motor drives and controllers.

Dr. Dejun Yin
Dr. Jianhu Yan
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. World Electric Vehicle Journal is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • electric vehicle
  • vehicle dynamics and control
  • in-wheel motor
  • motor design
  • motor control
  • renewable energy system
  • electrified components for EV

Published Papers (7 papers)

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Research

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17 pages, 4698 KiB  
Article
Optimization of the Electronic Control Unit of Electric-Powered Agricultural Vehicles
by Ionuț Vasile, Emil Tudor, Ion-Cătălin Sburlan, Mihai-Gabriel Matache and Mario Cristea
World Electr. Veh. J. 2023, 14(10), 267; https://doi.org/10.3390/wevj14100267 - 22 Sep 2023
Cited by 1 | Viewed by 1232
Abstract
Agricultural vehicles, such as tractors, combines, and harvesters, are following the trend of commercial vehicles with a transition from diesel to electric propulsion. Seen as an integrated system, a full-electric tractor is a complex machine with many systems that have to be interconnected [...] Read more.
Agricultural vehicles, such as tractors, combines, and harvesters, are following the trend of commercial vehicles with a transition from diesel to electric propulsion. Seen as an integrated system, a full-electric tractor is a complex machine with many systems that have to be interconnected for efficient functionality; thus, the need for a central control unit arises. The purpose of this article is to present an electronic control unit that interconnects the powertrain, the hydraulic systems, and the auxiliary systems of a full-electric tractor, with an emphasis on optimization through software design. The article describes the hardware of the electronic control unit and the software state diagrams necessary to implement the functions required by the electric tractor. The results of this article show how, through software optimization, the performances of the tractor can be improved, with parameters such as the response time of the various equipment being a useful indicator of such an improvement. Furthermore, the implementation of trip memory and an easy-to-use human–machine interface allows for easy diagnostic of the electric tractor. Full article
(This article belongs to the Special Issue Vehicle Control and Drive Systems for Electric Vehicles)
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17 pages, 15278 KiB  
Article
Research on Control Strategy of APSO-Optimized Fuzzy PID for Series Hybrid Tractors
by Liyou Xu, Yiting Wang, Yanying Li, Jinghui Zhao and Mengnan Liu
World Electr. Veh. J. 2023, 14(9), 258; https://doi.org/10.3390/wevj14090258 - 11 Sep 2023
Viewed by 1015
Abstract
Energy management strategies are crucial for improving fuel economy and reducing the exhaust emissions of hybrid tractors. The authors study a series diesel-electric hybrid tractor (SDEHT) and propose a multi-operating point Fuzzy PID control strategy (MOPFPCS) aimed to achieve better fuel economy and [...] Read more.
Energy management strategies are crucial for improving fuel economy and reducing the exhaust emissions of hybrid tractors. The authors study a series diesel-electric hybrid tractor (SDEHT) and propose a multi-operating point Fuzzy PID control strategy (MOPFPCS) aimed to achieve better fuel economy and improved control. To further improve the vehicle economy, the adaptive particle swarm optimization method is used to optimize the key parameters of the Fuzzy PID controller. A co-simulation model in AVL-Cruise and Matlab/Simulink environment is developed for plowing mode and transportation mode. The simulation results show that under the two operation modes, the equivalent fuel consumption of the adaptive particle swarm optimization multi-operating points Fuzzy PID control strategy (APSO-MOPFPCS) is reduced by 18.3% and 15.0%, respectively, compared to the engine single-operating point control strategy (ESOPCS). Also, it was found to be reduced by 9.5% and 4.6%, respectively, compared to the MOPFPCS. Full article
(This article belongs to the Special Issue Vehicle Control and Drive Systems for Electric Vehicles)
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30 pages, 22412 KiB  
Article
An Economic Velocity Planning Strategy Based on Driving Style and Improved Dynamic Programming for a Hybrid Electric Truck
by Yuting Li, Rong Yang, Zhengteng Wu, Wei Huang and Minmin Xu
World Electr. Veh. J. 2023, 14(7), 194; https://doi.org/10.3390/wevj14070194 - 21 Jul 2023
Viewed by 1107
Abstract
The power coupling equation and energy consumption model for enhancing the fuel economy and power performance of plug-in hybrid electric trucks (PHETs) are proposed based on the economic velocity planning strategy (EVPS-DSIDP), which takes into account the driving style and an improved dynamic [...] Read more.
The power coupling equation and energy consumption model for enhancing the fuel economy and power performance of plug-in hybrid electric trucks (PHETs) are proposed based on the economic velocity planning strategy (EVPS-DSIDP), which takes into account the driving style and an improved dynamic programming (IDP) algorithm. This strategy employs a fuzzy controller to identify the driving style, and optimizes the efficiency and accuracy of the conventional dynamic programming (DP) algorithm by associating decision variables, dynamically adjusting the discretization step size, and restricting the state space. Additionally, a penalty function is introduced to enhance the robustness of the DP algorithm. Under our EVPS-DSIDP, the variation of velocity is liberated from the constraints of fixed driving conditions, and directly correlates with road information and driving styles, which is of significant importance for addressing energy management issues in real-time traffic conditions. Moreover, the proposed IDP algorithm can improve computational efficiency while ensuring calculation accuracy, thereby greatly enhancing the potential for the practical application of this algorithm in real-world vehicle scenarios. The simulation results demonstrate that compared to the rule-based control strategy, the application of the proposed EVPS-DSIDP in the economy velocity planning strategy can achieve an average reduction of 2.88% in economic costs and 10.6% in travel time across different driving styles. This approach offers a more comprehensive optimization of both fuel economy and power performance. Full article
(This article belongs to the Special Issue Vehicle Control and Drive Systems for Electric Vehicles)
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13 pages, 13884 KiB  
Article
Thermal Design and Analysis of Oil-Spray-Cooled In-Wheel Motor Using a Two-Phase Computational Fluid Dynamics Method
by Chao Huang, Lu Xiong, Liang Hu and Yu Gong
World Electr. Veh. J. 2023, 14(7), 184; https://doi.org/10.3390/wevj14070184 - 13 Jul 2023
Viewed by 1768
Abstract
In-wheel motors for new energy vehicles are close to the brake, which results in a high ambient temperature. Thus, there is a high demand for cooling systems. This paper designs an oil-spray-cooled system based on the flat structural characteristics of an in-wheel motor. [...] Read more.
In-wheel motors for new energy vehicles are close to the brake, which results in a high ambient temperature. Thus, there is a high demand for cooling systems. This paper designs an oil-spray-cooled system based on the flat structural characteristics of an in-wheel motor. A computational fluid dynamics method with a two-phase volume-of-fluid model is applied to simulate the transient process of oil spraying from nozzles onto the stator carrier and then dripping to the end windings. The spatially distributed fluid interfaces with location and shape fidelity are derived. Considering the big difference of thermal inertia between the motor solid and oil fluid, the mixed timescale method is applied to calculate the temperature fields of the fluid and solid. Finally, a prototype is fabricated and tested to verify the proposed oil-cooling system and simulation method. Full article
(This article belongs to the Special Issue Vehicle Control and Drive Systems for Electric Vehicles)
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16 pages, 3397 KiB  
Article
Design of Auto-Tuning Nonlinear PID Tracking Speed Control for Electric Vehicle with Uncertainty Consideration
by Mohamed A. Shamseldin
World Electr. Veh. J. 2023, 14(4), 78; https://doi.org/10.3390/wevj14040078 - 23 Mar 2023
Cited by 6 | Viewed by 1472
Abstract
This study presents a new auto-tuning nonlinear PID controller for a nonlinear electric vehicle (EV) model. The purpose of the proposed control was to achieve two aims. The first aim was to enhance the dynamic performance of the EV regarding internal and external [...] Read more.
This study presents a new auto-tuning nonlinear PID controller for a nonlinear electric vehicle (EV) model. The purpose of the proposed control was to achieve two aims. The first aim was to enhance the dynamic performance of the EV regarding internal and external disturbances. The second aim was to minimize the power consumption of the EV. To ensure that these aims were achieved, two famous controllers were implemented. The first was the PID controller based on the COVID-19 optimization. The second was the nonlinear PID (NPID) optimized controller, also using the COVID-19 optimization. Several driving cycles were executed to compare their dynamic performance and the power consumption. The results showed that the auto-tuning NPID had a smooth dynamic response, with a minimum rise and settling time compared to other control techniques (PID and NPID controllers). Moreover, it achieved low continuous power consumption throughout the driving cycles. Full article
(This article belongs to the Special Issue Vehicle Control and Drive Systems for Electric Vehicles)
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18 pages, 4395 KiB  
Article
An Anti-Skid Control System Based on the Energy Method for Decentralized Electric Vehicles
by Longtao Ci, Yan Zhou and Dejun Yin
World Electr. Veh. J. 2023, 14(2), 49; https://doi.org/10.3390/wevj14020049 - 10 Feb 2023
Cited by 2 | Viewed by 1635
Abstract
Anti-slip control, as a fundamental technique of vehicle stability control, prevents loss of control of vehicles, especially under extreme driving conditions. However, current control methods fail to suppress vehicle slippage when steering. Therefore, a new anti-slip control approach for four-wheel independent-drive electric vehicles [...] Read more.
Anti-slip control, as a fundamental technique of vehicle stability control, prevents loss of control of vehicles, especially under extreme driving conditions. However, current control methods fail to suppress vehicle slippage when steering. Therefore, a new anti-slip control approach for four-wheel independent-drive electric vehicles (EVs) based on the energy method is proposed. This approach makes full use of the distribution of motor energy between the body and the wheels during vehicle turning, being able to adjust the driving torque of each wheel. Simulation results validate that the proposed approach can prevent wheel slip when the vehicle steers on slippery roads. Furthermore, simulations also show that the proposed control strategy can maintain high control performance when the motor flux linkage varies. Full article
(This article belongs to the Special Issue Vehicle Control and Drive Systems for Electric Vehicles)
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Review

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29 pages, 3179 KiB  
Review
An Overview of Diagnosis Methods of Stator Winding Inter-Turn Short Faults in Permanent-Magnet Synchronous Motors for Electric Vehicles
by Yutao Jiang, Baojian Ji, Jin Zhang, Jianhu Yan and Wenlong Li
World Electr. Veh. J. 2024, 15(4), 165; https://doi.org/10.3390/wevj15040165 - 15 Apr 2024
Viewed by 490
Abstract
This article provides a comprehensive overview of state-of-the-art techniques for detecting and diagnosing stator winding inter-turn short faults (ITSFs) in permanent-magnet synchronous motors (PMSMs) for electric vehicles (EVs). The review focuses on the following three main categories of diagnostic approaches: motor model-based, signal [...] Read more.
This article provides a comprehensive overview of state-of-the-art techniques for detecting and diagnosing stator winding inter-turn short faults (ITSFs) in permanent-magnet synchronous motors (PMSMs) for electric vehicles (EVs). The review focuses on the following three main categories of diagnostic approaches: motor model-based, signal processing-based, and artificial intelligence (AI)-based fault detection and diagnosis methods. Motor model-based methods utilize motor state estimation and motor parameter estimation as the primary strategies for ITSF diagnosis. Signal processing-based techniques extract fault signatures from motor measured data across time, frequency, or time-frequency domains. In contrast, AI-based methods automatically extract higher-order fault signatures from large volumes of preprocessed data, thereby enhancing the effectiveness of fault diagnosis. The strengths and limitations of each approach are thoroughly examined, providing valuable insights into the advancements in ITSF detection and diagnosis techniques for PMSMs in EV applications. The emphasis is placed on the application of signal processing methods and deep learning techniques in the diagnosis of ITSF in PMSMs in EV applications. Full article
(This article belongs to the Special Issue Vehicle Control and Drive Systems for Electric Vehicles)
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