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Electronics
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Fault Diagnosis and Control Technology of Electric Vehicle
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Fault Diagnosis and Control Technology of Electric Vehicle

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Electrical and Autonomous Vehicles".

Deadline for manuscript submissions: closed (20 August 2023) | Viewed by 11188

Special Issue Editors

Prof. Dr. Qinghua Meng

E-Mail Website
Guest Editor
School of Mechanical Engineering, Hangzhou Dianzi University, Hangzhou 310018, China
Interests: vehicle dynamics and control; in-wheel motor electric vehicle; automotive electronics; nonlinear system control; fault diagnosis
Dr. Longchuan Guo

E-Mail Website
Guest Editor
School of Mechanical Engineering, Hangzhou Dianzi University, Hangzhou 310018, China
Interests: marine electronic equipment; nonlinear control systems and applications; power electronics technology; underwater robot technology; industrial internet technology
Dr. Zhenlong Xu

E-Mail Website
Guest Editor
School of Mechanical Engineering, Hangzhou Dianzi University, Hangzhou 310018, China
Interests: energy harvesting and intelligent sensing based on piezoelectric/electromagnetic/triboelectric mechanisms; self-powered system; electromechanical system design and dynamic analysis; intelligent materials and structures
Dr. Ying Yang

E-Mail Website
Guest Editor
School of Mechanical Engineering, Hangzhou Dianzi University, Hangzhou 310018, China
Interests: nonlinear dynamics; stochastic dynamics; vibration control

Special Issue Information

Dear Colleagues,

We are inviting you to submit a paper to the Special Issue “Fault Diagnosis and Control Technology of Electric Vehicle” in Electronics.  Recent research in automotive engineering has focused on control technology as one of the core technologies of  electric vehicles (EVs), being involved in stability, lateral stability, the power system, battery management system, vehicle energy management system, braking system, energy recovery system, and ride comfort.  EVs are becoming increasingly complex with the additions of high-voltage batteries, motors, electronic control systems,  entertainment equipment, and other auxiliary equipment. It is thus necessary to develop fault diagnosis technology for EVs.

The proposed Special Issue will focus on fault diagnosis and control technology for electric vehicles. We are calling for authors around the world to share their innovative results with other researchers and related industries.

Topics of interest include, but are not limited to the following:

  • Vehicle dynamics and control for EVs;
  • Handling stability control for EVs;
  • Lateral stability control for EVs;
  • Power system control for EVs;
  • Vehicle energy management system control for EVs;
  • Battery state monitoring and control of EVs;
  • Trajectory planning for automated EVs;
  • Coordinate control for connected and automated EVs;
  • Braking and energy recovery control of EVs;
  • Fault-tolerant control for Evs;
  • Fault detection and location in EVAs by means of current, flux, vibration, temperature, and other electrical, mechanical, and chemical variables;
  • Tools for fault diagnosis: neural networks, fuzzy logic, artificial intelligence, genetic algorithms, expert systems, estimation/identification, observers, data analysis, and signal processing techniques.

Prof. Dr. Qinghua Meng
Dr. Longchuan Guo
Dr. Zhenlong Xu
Dr. Ying Yang
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. Electronics is an international peer-reviewed open access semimonthly 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 2400 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 control
  • fault diagnosis
  • automated vehicle
  • driverless vehicle

Published Papers (7 papers)

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Research

19 pages, 5167 KiB  
Article
Research on Rolling Bearing Fault Diagnosis Based on Variational Modal Decomposition Parameter Optimization and an Improved Support Vector Machine
by Lin Li, Weilun Meng, Xiaodong Liu and Jiyou Fei
Electronics 2023, 12(6), 1290; https://doi.org/10.3390/electronics12061290 - 08 Mar 2023
Cited by 9 | Viewed by 1157
Abstract
Aiming at the problems of modal aliasing and poor noise resistance when processing the vibration acceleration signal of rolling bearings by empirical modal decomposition (EMD), a variational modal decomposition (VMD) method based on parameter optimization is proposed. Combined with the improved particle swarm [...] Read more.
Aiming at the problems of modal aliasing and poor noise resistance when processing the vibration acceleration signal of rolling bearings by empirical modal decomposition (EMD), a variational modal decomposition (VMD) method based on parameter optimization is proposed. Combined with the improved particle swarm optimization algorithm (IPSO) and improved envelope entropy, the VMD decomposition layers and penalty parameters were optimized. The components with high correlation coefficients with the original signal were screened out, and the fault characteristics were extracted by combining the sample entropy. Aiming at the low classification accuracy of the support vector machine with fixed parameters in the fault diagnosis stage and the defects of the gray wolf algorithm, such as insufficient population diversity and large influence of the initial population on the optimization effect, an improved gray wolf algorithm (IGWO) based on multistrategy improvement is proposed. The IGWO was combined with the support vector machine to obtain an improved gray wolf algorithm optimization support vector machine (IGWO-SVM). The rolling bearing fault diagnosis test bench is established to collect the vibration acceleration signals of rolling bearing under different states. The experimental results show that the fault diagnosis of rolling bearings with strong noise can be effectively realized by applying the above methods, and the average fault diagnosis accuracy rate reaches 98.875%. Full article
(This article belongs to the Special Issue Fault Diagnosis and Control Technology of Electric Vehicle)
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10 pages, 422 KiB  
Article
Global Regulation by Integral Feedback for Lower-Triangular Nonlinear Systems with Actuator Failures and Limited Delays
by Xiandong Chen, Dajun Wei, Guoteng Zhang and Jinbao Li
Electronics 2023, 12(5), 1127; https://doi.org/10.3390/electronics12051127 - 25 Feb 2023
Viewed by 885
Abstract
This paper studies the global asymptotic regulation problem for a class of lower-triangular nonlinear systems with actuator failures and limited delays. New integral controllers consisting of an integral dynamic are constructed to make all system states bounded and asymptotically convergent to zero. First, [...] Read more.
This paper studies the global asymptotic regulation problem for a class of lower-triangular nonlinear systems with actuator failures and limited delays. New integral controllers consisting of an integral dynamic are constructed to make all system states bounded and asymptotically convergent to zero. First, an integral dynamic is constructed and a novel state transformation is introduced, which ensures that the involved systems with actuator failures are converted into a class of auxiliary nonlinear systems without actuator failures. Second, by introducing the static high-gain technique, the problem of designing integral controllers for auxiliary nonlinear systems is converted into that of designing the gain parameter and determining the limit of the actuator delay. At last, with the help of the Lyapunov stability theorem, the gain parameter and the limit of the actuator delay are determined, and the stabilization of the auxiliary nonlinear systems yields the global asymptotic regulation of the involved systems. A physical system example is given to demonstrate the effectiveness of the proposed integral controllers. Full article
(This article belongs to the Special Issue Fault Diagnosis and Control Technology of Electric Vehicle)
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20 pages, 7463 KiB  
Article
Low-Cost Hardware in the Loop for Intelligent Neural Predictive Control of Hybrid Electric Vehicle
by Mohamed El-Sayed M. Essa, Joseph Victor W. Lotfy, M. Essam K. Abd-Elwahed, Khaled Rabie, Basem M. ElHalawany and Mahmoud Elsisi
Electronics 2023, 12(4), 971; https://doi.org/10.3390/electronics12040971 - 15 Feb 2023
Cited by 6 | Viewed by 1586
Abstract
The design and investigation of an intelligent controller for hardware-in-the-loop (HIL) implementation of hybrid electric vehicles (HEVs) are proposed in this article. The proposed intelligent controller is adopted based on the enhancement of a model predictive controller (MPC) by an artificial neural network [...] Read more.
The design and investigation of an intelligent controller for hardware-in-the-loop (HIL) implementation of hybrid electric vehicles (HEVs) are proposed in this article. The proposed intelligent controller is adopted based on the enhancement of a model predictive controller (MPC) by an artificial neural network (ANN) approach. The MPC-based ANN (NNMPC) is proposed to control the speed of HEVs for a simulation system model and experimental HIL test systems. The HIL is established to assess the performance of the NNMPC to control the velocity of HEVs in an experimental environment. The real-time environment of HIL is implemented through a low-cost approach such as the integration of an Arduino Mega 2560 and a host Lenovo PC with a Core i7 @ 3.4 GHz processor. The NNMPC is compared with a proportional–integral (PI) controller, a classical MPC, and two different settings of the ANN methodology to verify the efficiency of the proposed intelligent NNMPC. The obtained results show a distinct behavior of the proposed NNMPC to control the speed of HEVs with good performance based on the distinct transient response, minimum error steady state, and system robustness against parameter perturbation. Full article
(This article belongs to the Special Issue Fault Diagnosis and Control Technology of Electric Vehicle)
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20 pages, 7532 KiB  
Article
Design of an Adaptive Distributed Drive Control Strategy for a Wheel-Side Rear-Drive Electric Bus
by Huipeng Chen, Weiyang Wang, Shaopeng Zhu, Sen Chen, Jian Gao, Rougang Zhou and Wei Wei
Electronics 2022, 11(24), 4223; https://doi.org/10.3390/electronics11244223 - 18 Dec 2022
Viewed by 1179
Abstract
A wheel motor simplifies the chassis structure of an electric bus, greatly improving its response speed and controllability. How to improve the lateral stability of the vehicle under complex and changeable driving conditions is a major problem in the motion control of electric [...] Read more.
A wheel motor simplifies the chassis structure of an electric bus, greatly improving its response speed and controllability. How to improve the lateral stability of the vehicle under complex and changeable driving conditions is a major problem in the motion control of electric buses. This study proposed an adaptive distributed drive control strategy for a rear-wheel drive electric bus. An adaptive fuzzy controller was designed to obtain the additional yaw moment of the vehicle and then combined with a rule distribution method to modify the steering characteristics of the vehicle to obtain the optimal driving torque distribution. Hardware-in-the-loop test results showed that under adaptive fuzzy control, the yaw rate deviations under low- and high-speed conditions were reduced from 18% and 42% without control to 10% and 23% with control, respectively. Under sine wave conditions, the deviation of the yaw rate and the vehicle’s sideslip angle were reduced from 83% and 852% without control to 12% and 15% with control, respectively. It was verified that the electric bus with adaptive fuzzy control could maintain good vehicle stability at full speed. Full article
(This article belongs to the Special Issue Fault Diagnosis and Control Technology of Electric Vehicle)
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21 pages, 3820 KiB  
Article
Design of a Wheel-Side Rear-Drive Distributed Electric Bus Control Strategy Based on Self-Correcting Fuzzy Control
by Wenhua Luo, Huipeng Chen, Shaopeng Zhu, Sen Chen, Jian Gao, Weiyang Wang and Rougang Zhou
Electronics 2022, 11(24), 4219; https://doi.org/10.3390/electronics11244219 - 17 Dec 2022
Cited by 2 | Viewed by 1380
Abstract
A suitable and effective control strategy is a prerequisite for achieving the stable driving of a distributed drive electric bus. In order to effectively utilize the advantage of the independent controllability of each rear wheel, this paper designs and compares two direct transverse [...] Read more.
A suitable and effective control strategy is a prerequisite for achieving the stable driving of a distributed drive electric bus. In order to effectively utilize the advantage of the independent controllability of each rear wheel, this paper designs and compares two direct transverse moment control strategies of sliding mode control and self-correcting fuzzy control and distributes the drive torque in combination with the vehicle steering torque constraint. Moreover, based on the established seven-degrees-of-freedom vehicle model, the simulation was verified in the MATLAB/Simulink and TruckSim co-simulation platforms. The simulation results show that, compared with the sliding mode control, the self-correcting fuzzy control strategy can reduce the maximum sideslip angle deviation by 19%, 6% and 9.7%, respectively, under the double shift line condition, the high-speed small steering angle step condition and the sinusoidal line shift condition and can more effectively reduce the vehicle lateral acceleration and improve the vehicle yaw rate tracking ability, significantly improving the lateral stability of the vehicle. Full article
(This article belongs to the Special Issue Fault Diagnosis and Control Technology of Electric Vehicle)
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Graphical abstract

25 pages, 7128 KiB  
Article
A Dynamics Coordinated Control System for 4WD-4WS Electric Vehicles
by Shaopeng Zhu, Bangxuan Wei, Dong Liu, Huipeng Chen, Xiaoyan Huang, Yingjie Zheng and Wei Wei
Electronics 2022, 11(22), 3731; https://doi.org/10.3390/electronics11223731 - 14 Nov 2022
Cited by 4 | Viewed by 2187
Abstract
With the aggravation of the energy crisis and environmental problems, the new energy electric vehicle industry has ushered in vigorous development. However, with the continuous increase in car ownership, traffic accidents and other issues have gradually attracted widespread attention. Some existing stability coordination [...] Read more.
With the aggravation of the energy crisis and environmental problems, the new energy electric vehicle industry has ushered in vigorous development. However, with the continuous increase in car ownership, traffic accidents and other issues have gradually attracted widespread attention. Some existing stability coordination control systems often have problems, such as single stability judgment method and strong coupling between different subsystems. Therefore, based on previous research, it is necessary to further optimize the method of judging the vehicle’s stability state, establish clear coordination rules, and reasonably solve the coupling problem between subsystems. This is of great significance for promoting the further development of the electric vehicle industry. Due to four-wheel-distributed driving and four-wheel-distributed steering electric vehicles having the characteristics of integrated driving, flexible steering, and easy fault-tolerant control, it has unique advantages in improving vehicle stability and is a good carrier for designing and constructing the stability coordination control system. In this paper, four-wheel-distributed driving and four-wheel-distributed steering (4WD-4WS) electric vehicles are taken as the research object, and a coordinated control strategy of four-wheel steering and four-wheel drive is proposed. Firstly, in order to realize the accurate judgment of vehicle stability, based on the vehicle two-degree-of-freedom two-track model and magic tire model, this paper uses the phase plane law to divide the phase plane stability region of the vehicle and introduces the stability quantification index PPS-region for the evaluation of vehicle stability. Secondly, a fuzzy variable parameter active rear-wheel steering controller and a compensated yaw moment controller are designed. Then, for the coupling problem between the two controllers, a coordination rule is proposed based on the stability index PPS-region of the phase plane stability region. Finally, a hardware-in-the-loop testbed is built to verify the feasibility of the coordination control strategy proposed in this paper. Experimental results show that: When the vehicle is in different stable states, according to the divided steady state, the control strategy can be correctly switched to the corresponding control strategy, and the work of each subsystem can be reasonably coordinated. Under the continuous gain sine condition, the control algorithm can reduce the maximum amplitude of the yaw rate error response curve by 73% and the side slip angle error response curve by 85%. Compared with a single stability control system, the coordinated stability control algorithm can improve the control effect of yaw rate and side slip angle by 20% and 62.5%. In the case of double lane-change, the control algorithm can reduce the maximum amplitude of the yaw rate error response curve by 68.5% and the side slip angle error response curve by 57.4%. Compared with a single stability control system, the coordinated stability control algorithm can improve the control effect of yaw rate and side slip angle by 40.6% and 44.7%. Full article
(This article belongs to the Special Issue Fault Diagnosis and Control Technology of Electric Vehicle)
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Graphical abstract

15 pages, 2842 KiB  
Article
Research on the Torque Control Strategy of a Distributed 4WD Electric Vehicle Based on Economy and Stability Control
by Lei Qiu, Shaopeng Zhu, Dong Liu, Zhiwei Xiang, Hong Fu and Huipeng Chen
Electronics 2022, 11(21), 3546; https://doi.org/10.3390/electronics11213546 - 30 Oct 2022
Cited by 2 | Viewed by 1655
Abstract
To improve the comprehensive performance of the distributed wheel-side four-wheel-drive electric bus, the problem of optimal distribution of the driving torque of the four wheel-side motors is studied. Aiming at the poor economy and failure of switching control due to the consideration of [...] Read more.
To improve the comprehensive performance of the distributed wheel-side four-wheel-drive electric bus, the problem of optimal distribution of the driving torque of the four wheel-side motors is studied. Aiming at the poor economy and failure of switching control due to the consideration of both straight and steering conditions, this paper proposes a fuzzy yaw moment control strategy based on the golden section search algorithm. Under full working conditions, according to the efficiency characteristics of the front and rear axle drive motors, the golden section search algorithm is used to determine the best front and rear axle motor torque distribution coefficient K to distribute the front and rear axle motor torques. Given the stability problems existing in the steering conditions, based on the optimal torque distribution of the front and rear axles, fuzzy control is used to calculate the expected yaw moment, and the left and right wheel torques are adjusted in real time. The simulation is carried out through TruckSim and MATLAB/Simulink, and a hardware-in-the-loop platform is built for experimentation under step steering conditions and sine wave steering conditions. The results show that the proposed torque optimal distribution strategy can optimally distribute the torque of the four drive motors through the real-time identification of working conditions. Compared with the four-wheel equal distribution, under two different steering conditions, the torque distribution efficiency of the torque distribution strategy using the golden section search algorithm increased by 4.35% and 3.83%, respectively. The energy utilization rate of the whole vehicle is improved under all of the working conditions. Under steering conditions, compared with the four-wheel equal distribution and the torque distribution strategy using the golden section search algorithm under all of the conditions, the yaw rate deviation and the slip angle deviation can be reduced, and the yaw stability has been improved. Full article
(This article belongs to the Special Issue Fault Diagnosis and Control Technology of Electric Vehicle)
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