Volume 26 Issue 4
Apr.  2026
Turn off MathJax
Article Contents
Article Navigation >  Journal of Traffic and Transportation Engineering  > 2026  >  26(4): 286-302
Next Previous
YANG Bing, FU Rui, SUN Qin-yu, JIANG Si-yang, WANG Chang. Adaptive sliding mode acceleration slip regulation control based on road identification for distributed electric drive buses[J]. Journal of Traffic and Transportation Engineering, 2026, 26(4): 286-302. doi: 10.19818/j.cnki.1671-1637.2026.020
Citation: YANG Bing, FU Rui, SUN Qin-yu, JIANG Si-yang, WANG Chang. Adaptive sliding mode acceleration slip regulation control based on road identification for distributed electric drive buses[J]. Journal of Traffic and Transportation Engineering, 2026, 26(4): 286-302. doi: 10.19818/j.cnki.1671-1637.2026.020
shu

Adaptive sliding mode acceleration slip regulation control based on road identification for distributed electric drive buses

doi: 10.19818/j.cnki.1671-1637.2026.020

  • School of Automobile, Chang'an University, Xi'an 710064, Shaanxi, China

Funds:

National Natural Science Foundation of China 52272412

Key R&D Program of Shaanxi Province 2024CY2-GJHX-87

Fundamental Research Funds for the Central Universities 300102224205

Fundamental Research Funds for the Central Universities 300102224501

Fundamental Research Funds for the Central Universities 300102224302

More Information
  • Corresponding author: FU Rui, professor, PhD, E-mail: furui@chd.edu.cn
  • Received Date: 2025-04-07
  • Accepted Date: 2025-08-25
  • Rev Recd Date: 2025-06-06
  • Publish Date: 2026-04-28
    Abstract
  • To solve the problem of excessive slippage of the driving wheels when distributed electric drive buses start on low-adhesion roads, an acceleration slip regulation (ASR) control strategy based on road identification and adaptive sliding mode control (ASMC) was proposed. A nonlinear vehicle dynamics model and a Dugoff tire model were established. A road adhesion coefficient estimation method was designed based on the high-degree cubature Kalman filter algorithm with singular value decomposition. Combined with the tire parameters of the target vehicle model, the tire test module in TruckSim was utilized to test tire characteristics and determine the optimal slip ratios under different road surfaces, based on which an ASR trigger and exit mechanism was designed. An anti-slip control algorithm based on ASMC was designed, into the reaching law of which an exponential adaptive gain was introduced to adaptively adjust the control force according to the error size, accelerate the slip ratio tracking speed, and suppress overshoot. Test maneuvers were set combined with the collected real-vehicle starting data. Based on the joint simulation platform of MATLAB/Simulink and TruckSim, the performance of the proposed ASR control strategy was verified under different starting maneuvers and loads and compared with the traditional model predictive control (MPC), first-order sliding mode control (FOSMC), and integral sliding mode control (ISMC) methods. Analysis results indicate that under four typical test maneuvers, the ASR control strategy based on ASMC minimizes both the average absolute error and root mean square error of slip ratio tracking; it increases the bus speed by 30.45%, 10.01%, 24.55%, and 13.45% compared with MPC, by 5.62%, 5.08%, 5.38%, and 6.35% compared with FOSMC, and by 4.09%, 2.74%, 3.21%, and 4.64% compared with ISMC, respectively. The proposed ASR control strategy can improve the longitudinal stability and driving performance of distributed electric drive buses, providing an important reference for the torque control system design of distributed electric drive buses.

     

    • FullText(HTML)
  • loading
    • References(35)
  • [1]
    WANG Zhi-zhong, YU Rong-jie, QIU Bin. Review and prospect on management of transportation and vehicle engineering discipline under NSFC in 2024[J]. Journal of Traffic and Transportation Engineering, 2025, 25(1): 1-7. doi: 10.19818/j.cnki.1671-1637.2025.01.001
    [2]
    YUE M, SHANGGUAN J Y, GUO L, et al. All-in-one control framework for distributed drive electric buses path tracking subject to uncertain crosswind and varied passenger mass[J]. IEEE Transactions on Vehicular Technology, 2023, 72 (7): 8342-8353. doi: 10.1109/TVT.2023.3244980
    [3]
    MESQUITA H C, LAGANÁ A A M, ANGÉLICO B A. An algebraic estimation-based model-free control for acceleration slip regulation of electric vehicles[J]. Journal of Control, Automation and Electrical Systems, 2024, 35 (6): 1097-1107. doi: 10.1007/s40313-024-01126-5
    [4]
    DEGEL W, LUPBERGER S, ODENTHAL D, et al. Scalable slip control with torque vectoring including input-to-state stability analysis[J]. IEEE Transactions on Control Systems Technology, 2023, 31 (3): 1250-1265. doi: 10.1109/TCST.2022.3224839
    [5]
    HORI Y. Future vehicle driven by electricity and control-research on four-wheel-motored "UOT electric march Ⅱ"[J]. IEEE Transactions on Industrial Electronics, 2004, 51 (5): 954-962. doi: 10.1109/TIE.2004.834944
    [6]
    YIN D, OH S, HORI Y. A novel traction control for EV based on maximum transmissible torque estimation[J]. IEEE Transactions on Industrial Electronics, 2009, 56 (6): 2086-2094. doi: 10.1109/TIE.2009.2016507
    [7]
    NGUYEN B M, HARA S, FUJIMOTO H, et al. Slip control for IWM vehicles based on hierarchical LQR[J]. Control Engineering Practice, 2019, 93: 104179. doi: 10.1016/j.conengprac.2019.104179
    [8]
    SHI K, YUAN X F, LIU L. Model predictive controller-based multi-model control system for longitudinal stability of distributed drive electric vehicle[J]. ISA Transactions, 2018, 72: 44-55. doi: 10.1016/j.isatra.2017.10.013
    [9]
    DING X L, WANG Z P, ZHANG L. Hybrid control-based acceleration slip regulation for four-wheel-independent-actuated electric vehicles[J]. IEEE Transactions on Transportation Electrification, 2021, 7 (3): 1976-1989. doi: 10.1109/TTE.2020.3048405
    [10]
    ZHANG H Z, QI Y Y, SI W J, et al. An improved adaptive sliding mode control approach for anti-slip regulation of electric vehicles based on optimal slip ratio[J]. Machines, 2024, 12 (11): 769. doi: 10.3390/machines12110769
    [11]
    LI B, E W J, FENG T L, et al. Road adhesion coefficient estimation based on LiDAR reflectance intensity[J]. IEEE Sensors Journal, 2024, 24 (18): 29135-29148. doi: 10.1109/JSEN.2024.3436897
    [12]
    CHEN L, QIN Z B, BIAN Y G, et al. Data-driven tire-road friction estimation for electric-wheel vehicle with data category selection and uncertainty evaluation[J]. IEEE Transactions on Industrial Electronics, 2025, 72 (3): 3048-3060. doi: 10.1109/TIE.2024.3440510
    [13]
    ZHAO S Y, ZHANG J Z, JIANG Y H, et al. Tire-road friction coefficients adaptive estimation through image and vehicle dynamics integration[J]. Mechanical Systems and Signal Processing, 2025, 224: 112039. doi: 10.1016/j.ymssp.2024.112039
    [14]
    WANG Y, HU J Y, WANG F A, et al. Tire road friction coefficient estimation: Review and research perspectives[J]. Chinese Journal of Mechanical Engineering, 2022, 35(1): 6. doi: 10.1186/s10033-021-00675-z
    [15]
    LENG B, TIAN C, HOU X C, et al. Tire-road peak adhesion coefficient estimation based on multisource information assessment[J]. IEEE Transactions on Intelligent Vehicles, 2023, 8 (7): 3854-3870. doi: 10.1109/TIV.2023.3271867
    [16]
    KANG S, CHEN J J, QIU G Q, et al. Slip ratio adaptive control based on wheel angular velocity for distributed drive electric vehicles[J]. World Electric Vehicle Journal, 2023, 14(5): 119. doi: 10.3390/wevj14050119
    [17]
    LIU Y H, LI T, YANG Y Y, et al. Estimation of tire-road friction coefficient based on combined APF-IEKF and iteration algorithm[J]. Mechanical Systems and Signal Processing, 2017, 88: 25-35. doi: 10.1016/j.ymssp.2016.07.024
    [18]
    WANG X D, RAN M P, ZHOU X L. Integration of in-wheel motor sensorless systems and hierarchical direct yaw moment control for distributed drive electric vehicles[J]. Engineering Applications of Artificial Intelligence, 2025, 139: 109600. doi: 10.1016/j.engappai.2024.109600
    [19]
    ZHANG R Y, FENG Y. L, SHI P C, et al. Tire-road friction coefficient estimation for distributed drive electric vehicles using PMSM sensorless control[J]. IEEE Transactions on Vehicular Technology, 2023, 72 (7): 8672-8685. doi: 10.1109/TVT.2023.3248866
    [20]
    SUN X M, XIAO Z H, WANG Z, et al. Acceleration slip regulation control method for distributed electric drive vehicles under icy and snowy road conditions[J]. Applied Sciences, 2024, 14 (15): 6803. doi: 10.3390/app14156803
    [21]
    ATAEI M, KHAJEPOUR A, JEON S. Model predictive control for integrated lateral stability, traction/braking control, and rollover prevention of electric vehicles[J]. Vehicle System Dynamics, 2020, 58 (1): 49-73. doi: 10.1080/00423114.2019.1585557
    [22]
    LI Q X, LIU L J, YUAN X F. Model predictive controller-based optimal slip ratio control system for distributed driver electric vehicle[J]. Mathematical Problems in Engineering, 2020: 8086590.
    [23]
    SAVITSKI D, IVANOV V, AUGSBURG K, et al. Wheel slip control for the electric vehicle with in-wheel motors: Variable structure and sliding mode methods[J]. IEEE Transactions on Industrial Electronics, 2020, 67 (10): 8535-8544. doi: 10.1109/TIE.2019.2942537
    [24]
    ZHANG Li-peng, LIU Xin, LIU Shuai-shuai, et al. Driving stability control of a dual-mode coupling drive intelligent electric vehicle on bisectional slopes[J]. China Journal of Highway and Transport, 2024, 37 (3): 204-215.
    [25]
    LI Z X, PAN S J, MAO K, et al. Combined acceleration slip regulation for multi-wheel distributed electric drive vehicles considering torque loss factor[J]. Control Engineering Practice, 2024, 146: 105893. doi: 10.1016/j.conengprac.2024.105893
    [26]
    YUAN S X, SHI Q, HE Z J, et al. Acceleration slip regulation by electric motor torque of battery electric vehicle with nonlinear model predictive control approach[J]. Vehicle System Dynamics, 2023, 61 (8): 1937-1953. doi: 10.1080/00423114.2022.2093758
    [27]
    WU Bo-fu, XU Xiao, CHEN Zi-qiang, et al. Acceleration slip regulation of electric racing cars based on nonlinear MPC[J]. Journal of Hefei University of Technology (Natural Science), 2024, 47 (2): 182-188.
    [28]
    ZHANG Rong-yun, FENG Yong-le, SHI Pei-cheng, et al. Estimation on road adhesion coefficient of distributed drive electric vehicles[J]. Mechanical Science and Technology for Aerospace Engineering, 2025, 44 (1): 187-198.
    [29]
    WANG Hong-bo, WANG Chun-yang, GAO Han, et al. Vehicle traction force control based on the road adhesion coefficient estimation by FFUKF[J]. Chinese Journal of Theoretical and Applied Mechanics, 2022, 54 (7): 1866-1879.
    [30]
    CHEN T, CAI Y F, CHEN L, et al. Sideslip angle fusion estimation method of three-axis autonomous vehicle based on composite model and adaptive cubature Kalman filter[J]. IEEE Transactions on Transportation Electrification, 2024, 10 (1): 316-330. doi: 10.1109/TTE.2023.3263592
    [31]
    JIA B, XIN M, CHENG Y. High-degree cubature Kalman filter[J]. Automatica, 2013, 49 (2): 510-518. doi: 10.1016/j.automatica.2012.11.014
    [32]
    WU Jian-yang, WANG Zhen-po, ZHANG Lei, et al. Coordination stability control strategy for four-wheel-independent-actuated electric vehicles[J]. Journal of Mechanical Engineering, 2023, 59 (04): 163-172.
    [33]
    FU R, YANG B, ZHANG H L, et al. Lateral stability control of buses: A framework considering the steering hysteresis response using interleaved predictive control[J]. IEEE Transactions on Vehicular Technology, 2024, 73 (1): 216-231. doi: 10.1109/TVT.2023.3306800
    [34]
    HU Hai-lin, YU Shi-yan, HUANG Wei-yi, et al. Speed sensorless MPTC of linear induction motors for rail transit based on improved SMO[J]. Journal of Traffic and Transportation Engineering, 2025, 25 (2): 94-107. doi: 10.19818/j.cnki.1671-1637.2025.02.006
    [35]
    FU Qi-tao. Stability control system design for distributed drive electric bus[D]. Hangzhou: Zhejiang University, 2021.
    • Relative Articles
    • Supplements(0)
    • Cited By

Catalog

    Get Citation
    PDF
    XML

    Article Metrics

    Article views (88) PDF downloads(10) Cited by()
    Related

    Website copyright Journal of Traffic and Transportation Engineering Editorial Department陕ICP备05001904号-1

    Address ：Editorial Department of Journal of Traffic and Transportation Engineering, Chang'an University, Middle Section of South 2nd Ring Road, Xi'an, China（710064） Tel：029-82334388 Email：jygc@chd.edu.cn

    All visit:Today's visit:

    Supported by: Beijing Renhe Information Technology Co. Ltd    

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return