Search Advanced

Mathematical Biosciences and Engineering

2023, Volume 20, Issue 7: 13334-13355. doi: 10.3934/mbe.2023594
Previous Article Next Article
Research article Special Issues

Direct yaw-moment control of electric vehicles based on adaptive sliding mode

  • 1.
    School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China
  • 2.
    Zhejiang JIALIFT Warehouse Equipment Co., Ltd., Huzhou 313104, China

  • Academic Editor: Xiaodi Li
  • Received: 20 April 2023 Revised: 08 May 2023 Accepted: 15 May 2023 Published: 09 June 2023

  • The direct yaw-moment control (DYC) system consisting of an upper controller and a lower controller is developed on the basis of sliding mode theory and adaptive control technique. First, the two-degree of freedom (2-DOF) model is utilized to calculate the ideal yaw rate. Then, the seven-degree of freedom (7-DOF) electric vehicle model is given to design the upper controller by employing first-order sliding mode (FOSM) method, which is constructed to guarantee the actual yaw rate to approach the ideal value and gain the additional yaw moment. On this basis, an adaptive first-order sliding mode (AFOSM) controller is designed to enhance the system robustness against probable modelling error and parametric uncertainties. In order to mitigate the chattering issue present in the FOSM controller, a novel adaptive super-twisting sliding mode (ASTSM) controller is proposed for the design of DYC. Furthermore, the lower controller converting the additional yaw moment into driving or braking torque acting on each wheel is also developed. Finally, The simulation results indicate that the proposed DYC system can improve the electric vehicle driving stability effectively.

    Citation: Li Ma, Chang Cheng, Jianfeng Guo, Binhua Shi, Shihong Ding, Keqi Mei. Direct yaw-moment control of electric vehicles based on adaptive sliding mode[J]. Mathematical Biosciences and Engineering, 2023, 20(7): 13334-13355. doi: 10.3934/mbe.2023594

    Related Papers:

  • The direct yaw-moment control (DYC) system consisting of an upper controller and a lower controller is developed on the basis of sliding mode theory and adaptive control technique. First, the two-degree of freedom (2-DOF) model is utilized to calculate the ideal yaw rate. Then, the seven-degree of freedom (7-DOF) electric vehicle model is given to design the upper controller by employing first-order sliding mode (FOSM) method, which is constructed to guarantee the actual yaw rate to approach the ideal value and gain the additional yaw moment. On this basis, an adaptive first-order sliding mode (AFOSM) controller is designed to enhance the system robustness against probable modelling error and parametric uncertainties. In order to mitigate the chattering issue present in the FOSM controller, a novel adaptive super-twisting sliding mode (ASTSM) controller is proposed for the design of DYC. Furthermore, the lower controller converting the additional yaw moment into driving or braking torque acting on each wheel is also developed. Finally, The simulation results indicate that the proposed DYC system can improve the electric vehicle driving stability effectively.


    加载中


    [1] L. Ma, K. Mei, S. Ding, T. Pan, Design of adaptive fuzzy fixed-time HOSM controller subject to asymmetric output constraints, IEEE Trans. Fuzzy Syst., 2023 (2023). https://doi.org/10.1109/TFUZZ.2023.3241147 doi: 10.1109/TFUZZ.2023.3241147
    [2] Y. Tang, X. Wu, P. Shi, F. Qian, Input-to-state stability for nonlinear systems with stochastic impulses, Automatica, 113 (2020), 108766. https://doi.org/10.1016/j.automatica.2019.108766 doi: 10.1016/j.automatica.2019.108766
    [3] B. Xu, Q. Jiang, W. Ji, S. Ding, An improved three-vector-based model predictive current control method for surface-mounted PMSM drives, IEEE Trans. Transp. Electrif., 8 (2022), 4418–4430. https://doi.org/10.1109/TTE.2022.3169515 doi: 10.1109/TTE.2022.3169515
    [4] Q. K. Hou, S. H. Ding, X. H. Yu, Composite super-twisting sliding mode control design for PMSM speed regulation problem based on a novel disturbance observer, IEEE Trans. Energy Convers., 36 (2021), 2591–2599. https://doi.org/10.1109/tec.2020.2985054 doi: 10.1109/tec.2020.2985054
    [5] Y. Wu, L. F. Wang, J. Z. Zhang, F. Li, Robust vehicle yaw stability controlby active front steering with active disturbance rejection controller, in Proceedings of the Institution of Mechanical Engineers Part Ⅰ Journal of Systems and Control Engineering, (2018). https://doi.org/10.1177/0959651818813515
    [6] J. Zhang, H. Wang, M. Ma, M. Yu, A. Yazdani, Active front steering-based electronic stability control for steer-by-wire vehicles via terminal sliding mode and extreme learning machine, IEEE Trans. Veh. Technol., 69 (2020), 14713–14726. https://doi.org/10.1109/TVT.2020.3036400 doi: 10.1109/TVT.2020.3036400
    [7] Y. C. Zhu, L. Ma, Composite chattering-free discrete-time sliding mode controller design for active front steering system of electric vehicles, Nonlinear Dyn., 105 (2021), 301–313. https://doi.org/10.1007/s11071-021-06465-5 doi: 10.1007/s11071-021-06465-5
    [8] A. Aksjonov, K. Augsburg, V. Vodovozov, Design and Simulation of the Robust ABS and ESP Fuzzy Logic Controller on the Complex Braking Maneuvers, Appl. Sci., 6 (2016). https://doi.org/10.3390/app6120382 doi: 10.3390/app6120382
    [9] J. H. Guo, Y. G. Luo, C. Hu, C. Tao, K. Q. Li, Robust combined lane keeping and direct yaw moment control for intelligent electric vehicles with time delay, Int. J. Autom. Technol., 20 (2019), 289–296. https://doi.org/10.1007/s12239-019-0028-5 doi: 10.1007/s12239-019-0028-5
    [10] S. H. Ding, J. L. Sun, Direct yaw-moment control for 4WID electric vehicle via finite-time control technique, Nonlinear Dyn., 88 (2016), 239–254. https://doi.org/10.1007/s11071-016-3240-0 doi: 10.1007/s11071-016-3240-0
    [11] B. Xu, X. Cui, W. Ji, H. Yuan, J. Wang, Apple grading method design and implementation for automatic grader based on improved YOLOv5, Agriculture, 13 (2023), 124. https://doi.org/10.3390/agriculture13010124 doi: 10.3390/agriculture13010124
    [12] B. Xu, L. Zhang, W. Ji, Improved non-singular fast terminal sliding mode control with disturbance observer for PMSM drives, IEEE Trans. Transp. Electrification, 7 (2021), 2753–2762. https://doi.org/10.1109/TTE.2021.3083925 doi: 10.1109/TTE.2021.3083925
    [13] J. Sun, J. Yi, Z. Pu, Fixed-time adaptive fuzzy control for uncertain nonstrict-feedback systems with time-varying constraints and input saturations, IEEE Trans. Fuzzy Syst., 30 (2022), 1114–1128. https://doi.org/10.1109/TFUZZ.2021.3052610 doi: 10.1109/TFUZZ.2021.3052610
    [14] X. Li, D. W. C. Ho, J. Cao, Finite-time stability and settling-time estimation of nonlinear impulsive systems, Automatica, 99 (2019), 361–368. https://doi.org/10.1016/j.automatica.2018.10.024 doi: 10.1016/j.automatica.2018.10.024
    [15] K. Mei, C. Qian, S. Ding, Design of adaptive SOSM controller subject to disturbances with unknown magnitudes, IEEE Trans. Circuits Syst. Ⅰ, 70 (2023), 2133–2142. https://doi.org/10.1109/TCSI.2023.3241291 doi: 10.1109/TCSI.2023.3241291
    [16] K. Mei, S. Ding, X. Yu, A generalized supertwisting algorithm, IEEE Trans. Cybern., 2022 (2022). https://doi.org/10.1109/TCYB.2022.3188877 doi: 10.1109/TCYB.2022.3188877
    [17] S. Ding, B. Zhang, K. Mei, J. Park, Adaptive fuzzy SOSM controller design with output constraints, IEEE Trans. Fuzzy Syst., 30 (2022), 2300–2311. https://doi.org/10.1109/TFUZZ.2021.3079506. doi: 10.1109/TFUZZ.2021.3079506
    [18] X. Li, X. Yang, S. Song, Lyapunov conditions for finite-time stability of time-varying time-delay systems, Automatica, 103 (2019), 135–140. https://doi.org/10.1016/j.automatica.2019.01.031 doi: 10.1016/j.automatica.2019.01.031
    [19] X. Li, X. Yan, J. Cao, Event-triggered impulsive control for nonlinear delay systems, Automatica, 117 (2020), 108981. https://doi.org/10.1016/j.automatica.2020.108981 doi: 10.1016/j.automatica.2020.108981
    [20] J. H. Guo, J. Y. Wang, Y. G. Luo, K. Q. Li, Takagi–Sugeno fuzzy-based robust $H_{\infty}$ integrated lane-keeping and direct yaw moment controller of unmanned electric vehicles, IEEE/ASME Trans. Mech., 26 (2020), 2151–2162. https://doi.org/10.1109/TMECH.2020.3032998 doi: 10.1109/TMECH.2020.3032998
    [21] K. Mei, S. Ding, W. X. Zheng, Fuzzy adaptive SOSM based control of a type of nonlinear systems, IEEE Trans. Circuits Syst. Ⅱ, 69 (2022), 1342–1346. https://doi.org/10.1109/TCSII.2021.3116812 doi: 10.1109/TCSII.2021.3116812
    [22] X. K. He, K. M. Yang, Y. L. Liu, X. W. Ji, A novel direct yaw moment control system for autonomous vehicle, SAE Tech. Paper, 2018 (2018). https://doi.org/10.4271/2018-01-1594 doi: 10.4271/2018-01-1594
    [23] S. Ding, Q. Hou, H. Wang, Disturbance-observer-based second-order sliding mode controller for speed control of PMSM drives, IEEE Trans. Energy Convers., 38 (2023), 100–110. https://doi.org/10.1109/TEC.2022.3188630 doi: 10.1109/TEC.2022.3188630
    [24] L. Hind, D. Moustapha, T. Reine, C. Ali, Yaw moment Lyapunov based control for in-wheel-motor-drive electric vehicle, IFAC-PapersOnLine, 50 (2017), 13828–13833. https://doi.org/10.1016/j.ifacol.2017.08.2189 doi: 10.1016/j.ifacol.2017.08.2189
    [25] J. Song, W. X. Zheng, Y. G. Niu, Self-triggered sliding mode control for networked PMSM speed regulation system: A PSO-optimized super-twisting algorithm, IEEE Trans. Ind. Electron., 69 (2021), 763–773. https://doi.org/10.1109/TIE.2021.3050348 doi: 10.1109/TIE.2021.3050348
    [26] S. H. Ding, B. B. Zhang, K. Q. Mei, J. H. Park, Adaptive fuzzy SOSM controller design with output constraints, IEEE Trans. Fuzzy Syst., 30 (2021), 2300–2311. https://doi.org/10.1109/TFUZZ.2021.3079506 doi: 10.1109/TFUZZ.2021.3079506
    [27] S. H. Ding, K. Q. Mei, X. H. Yu, Adaptive second-order sliding mode control: A Lyapunov approach, IEEE Trans. Autom. Control, 67 (2021), 5392–5399. https://doi.org/10.1109/TAC.2021.3115447 doi: 10.1109/TAC.2021.3115447
    [28] S. H. Ding, L. Liu, W. X. Zheng, Sliding mode direct yaw-moment control design for in-wheel electric vehicles, IEEE Trans. Ind. Electron., 64 (2017), 6752–6762. https://doi.org/10.1109/tie.2017.2682024 doi: 10.1109/tie.2017.2682024
    [29] B. Lenzo, M. Zanchetta, A. Sorniotti, P. Gruber, W. D. Nijs, Yaw rate and sideslip angle control through single input single output direct yaw moment control, IEEE Trans. Control Syst. Technol., 29 (2021), 124–139. https://doi.org/10.1109/TCST.2019.2949539 doi: 10.1109/TCST.2019.2949539
    [30] C. Y. Fu, H. Reza, K. N. Li, M. H. Hu, A novel adaptive sliding mode control approach for electric vehicle direct yaw-moment control, Adv. Mech. Eng., 10 (2018), 1–12. https://doi.org/10.1177/1687814018803179 doi: 10.1177/1687814018803179
    [31] W. Qi, H. Su, A Cybertwin based multimodal network for ECG patterns monitoring using deep learning, IEEE Trans. Ind. Inf., 18 (2022), 6663–6670. https://doi.org/10.1109/TII.2022.3159583 doi: 10.1109/TII.2022.3159583
    [32] Y. Shi, L. Li, J. Yang, Y. Wang, S. Hao, Center-based transfer feature learning with classifier adaptation for surface defect recognition, Mech. Syst. Signal Process., 188 (2023), 110001. https://doi.org/10.1016/j.ymssp.2022.110001 doi: 10.1016/j.ymssp.2022.110001
    [33] S. Roy, S. Baldi, L. M. Fridman, On adaptive sliding mode control without a priori bounded uncertainty, Automatica, 111 (2020), 108650. https://doi.org/10.1016/j.automatica.2019.108650 doi: 10.1016/j.automatica.2019.108650
    [34] Z. Lv, Y. Wu, X. Sun, Q. Wang, Fixed-time control for a quadrotor with a cable-suspended load, IEEE Trans. Intell. Trans. Syst., 23 (2022), 21932–21943. https://doi.org/10.1109/TITS.2022.3180733 doi: 10.1109/TITS.2022.3180733
    [35] Q. Hou, S. Ding, GPIO based super-twisting sliding mode control for PMSM, IEEE Trans. Circuits Syst. Ⅱ, 68 (2021), 747–751. https://doi.org/10.1109/TCSII.2020.3008188 doi: 10.1109/TCSII.2020.3008188
    [36] Z. Lv, Q. Zhao, S. Li, Y. Wu, Finite-time control design for a quadrotor transporting a slung load, Control Eng. Prac., 122 (2022), 105082. https://doi.org/10.1016/j.conengprac.2022.105082 doi: 10.1016/j.conengprac.2022.105082
    [37] Y. Tang, X. Jin, Y. Shi, W. Du, Event-triggered attitude synchronization of multiple rigid body systems with velocity-free measurements, Automatica, 143 (2022), 110460. https://doi.org/10.1016/j.automatica.2022.110460 doi: 10.1016/j.automatica.2022.110460
    [38] Y. Tang, D. Zhang, P. Shi, W. Zhang, F. Qian, Event-based formation control for nonlinear multiagent systems under DoS attacks, IEEE Trans. Autom. Control, 66 (2021), 452–459. https://doi.org/10.1109/TAC.2020.2979936 doi: 10.1109/TAC.2020.2979936
    [39] W. W. Chen, X. T. Liang, Q. D. Wang, L. F. Zhao, X. Wang, Extension coordinated control of four wheel independent drive electric vehicles by AFS and DYC, Control Eng. Prac., 101 (2020), 1242–1258. https://doi.org/10.1016/j.conengprac.2020.104504 doi: 10.1016/j.conengprac.2020.104504
    [40] S. B. Zheng, H. J. Tang, J. Hou, Z. Z. Han, Y. Zhang, Controller design for vehicle stability enhancement, Control Eng. Prac., 14 (2006), 1413–1421. https://doi.org/10.1016/j.conengprac.2005.10.005 doi: 10.1016/j.conengprac.2005.10.005
    [41] R. Rajesh, Vehicle Dynamics and Control, Springer Science & Business Media, 2011.
    [42] L. Arie, Sliding order and sliding accuracy in sliding mode control, Int. J. Control, 58 (1993), 1247–1263. https://doi.org/10.1080/00207179308923053 doi: 10.1080/00207179308923053
    [43] D. L. Liang, J. Li, R. H. Qu, W. B. Kong, Adaptive second-order sliding-mode observer for PMSM sensorless control considering VSI nonlinearity, IEEE Trans. Power Electron., 33 (2017), 8994–9004. https://doi.org/10.1109/TPEL.2017.2783920 doi: 10.1109/TPEL.2017.2783920
    [44] Q. K Hou, S. H. Ding, X. H. Yu, K. Q. Mei, A super-twisting-like fractional controller for SPMSM drive system, IEEE Trans. Ind. Electron., 69 (2021), 9376–9384. https://doi.org/10.1109/TIE.2021.3116585 doi: 10.1109/TIE.2021.3116585
    [45] K. Q. Mei, S. H. Ding, C. C. Chen, Fixed-time stabilization for a class of output-constrained nonlinear systems, IEEE Trans. Syst. Man Cybern. Syst., 52 (2022), 6498–6510. https://doi.org/10.1109/tsmc.2022.3146011 doi: 10.1109/tsmc.2022.3146011
    [46] G. Gandikota, D. K. Das, Terminal sliding mode disturbance observer based adaptive super twisting sliding mode controller design for a class of nonlinear system, Eur. J. Control, 57 (2021), 232–241. https://doi.org/10.1016/j.ejcon.2020.05.004 doi: 10.1016/j.ejcon.2020.05.004
    [47] B. B. Yan, P. Dai, R. F. Liu, M. Z. Xing, S. X. Liu, Adaptive super-twisting sliding mode control of variable sweep morphing aircraft, Aerosp. Sci. Technol., 92 (2019), 198–210. https://doi.org/10.1016/j.ast.2019.05.063 doi: 10.1016/j.ast.2019.05.063
    [48] S. Yuri, T. Mohammed, P. Franck, A novel adaptive-gain supertwisting sliding mode controller: Methodology and application, Automatica, 48 (2012), 759–769. https://doi.org/10.1016/j.automatica.2012.02.024 doi: 10.1016/j.automatica.2012.02.024
    [49] L. Zhai, T. M. Sun, J. Wang, Electronic stability control based on motor driving and braking torque distribution for a four in-wheel motor drive electric vehicle, IEEE Trans. Veh. Technol., 65 (2016), 4726–4739. https://doi.org/10.1109/TVT.2016.2526663 doi: 10.1109/TVT.2016.2526663
  • Reader Comments
  • © 2023 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索
Mathematical Biosciences and Engineering
3.9

Metrics

Article views(1784) PDF downloads(188) Cited by(49)

Preview PDF
Download XML
Export Citation
Article outline

Figures and Tables

Figures(12)  /  Tables(3)

Other Articles By Authors

Related pages

Tools

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog