A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation
Volume 7 Issue 6
Oct.  2020

IEEE/CAA Journal of Automatica Sinica

  • JCR Impact Factor: 11.8, Top 4% (SCI Q1)
    CiteScore: 17.6, Top 3% (Q1)
    Google Scholar h5-index: 77, TOP 5
Turn off MathJax
Article Contents
Yantao Tian, Xuanhao Cao, Xiaoyu Wang and Yanbo Zhao, "Four Wheel Independent Drive Electric Vehicle Lateral Stability Control Strategy," IEEE/CAA J. Autom. Sinica, vol. 7, no. 6, pp. 1542-1554, Nov. 2020. doi: 10.1109/JAS.2019.1911729
Citation: Yantao Tian, Xuanhao Cao, Xiaoyu Wang and Yanbo Zhao, "Four Wheel Independent Drive Electric Vehicle Lateral Stability Control Strategy," IEEE/CAA J. Autom. Sinica, vol. 7, no. 6, pp. 1542-1554, Nov. 2020. doi: 10.1109/JAS.2019.1911729

Four Wheel Independent Drive Electric Vehicle Lateral Stability Control Strategy

doi: 10.1109/JAS.2019.1911729
Funds:  This work was supported by the National Nature Science Foundation (U1664263), and National Key R&D Program of China (2016YFB0101102)
More Information
  • In this paper, a kind of lateral stability control strategy is put forward about the four wheel independent drive electric vehicle. The design of control system adopts hierarchical structure. Unlike the previous control strategy, this paper introduces a method which is the combination of sliding mode control and optimal allocation algorithm. According to the driver’s operation commands (steering angle and speed), the steady state responses of the sideslip angle and yaw rate are obtained. Based on this, the reference model is built. Upper controller adopts the sliding mode control principle to obtain the desired yawing moment demand. Lower controller is designed to satisfy the desired yawing moment demand by optimal allocation of the tire longitudinal forces. Firstly, the optimization goal is built to minimize the actuator cost. Secondly, the weighted least-square method is used to design the tire longitudinal forces optimization distribution strategy under the constraint conditions of actuator and the friction oval. Beyond that, when the optimal allocation algorithm is not applied, a method of axial load ratio distribution is adopted. Finally, CarSim associated with Simulink simulation experiments are designed under the conditions of different velocities and different pavements. The simulation results show that the control strategy designed in this paper has a good following effect comparing with the reference model and the sideslip angle $\,\beta$ is controlled within a small rang at the same time. Beyond that, based on the optimal distribution mode, the electromagnetic torque phase of each wheel can follow the trend of the vertical force of the tire, which shows the effectiveness of the optimal distribution algorithm.


  • loading
  • [1]
    F.-Y. Wang, N. N. Zheng, D. P. Cao, C. M. Martinez, L. Li, and T. Liu, “Parallel driving in CPSS: A unified approach for transport automation and vehicle intelligence,” IEEE/CAA J. Autom. Sinica, vol. 4, no. 4, pp. 577–587, Sept. 2017. doi: 10.1109/JAS.2017.7510598
    C. Lv, D. P. Cao, Y. F. Zhao, D. J. Auger, M. Sullman, H. J. Wang, L. M. Dutka, L. Skrypchuk, and A. Mouzakitis, “Analysis of autopilot disengagements occurring during autonomous vehicle testing,” IEEE/CAA J. Autom. Sinica, vol. 5, no. 1, pp. 58–68, Jan. 2018. doi: 10.1109/JAS.2017.7510745
    C. Lv, X. S. Hu, A. Sangiovanni-Vincentelli, Y. T. Li, C. M. Martinez, and D. P. Cao, “Driving-style-based codesign optimization of an automated electric vehicle: A cyber-physical system approach,” IEEE Trans. Ind. Electron., vol. 66, no. 4, pp. 2965–2975, Apr. 2019. doi: 10.1109/TIE.2018.2850031
    C. Lv, Y. H. Liu, X. S. Hu, H. Y. Guo, D. P. Cao, and F.-Y. Wang, “Simultaneous observation of hybrid states for cyber-physical systems: A case study of electric vehicle powertrain,” IEEE Trans. Cybernet., vol. 48, no. 8, pp. 2357–2367, Aug. 2018. doi: 10.1109/TCYB.2017.2738003
    C. Lv, Y. Xing, C. Lu, Y. H. Liu, H. Y. Guo, H. B. Gao, and D. P. Cao, “Hybrid-learning-based classification and quantitative inference of driver braking intensity of an electrified vehicle,” IEEE Trans. Veh. Technol., vol. 67, no. 7, pp. 5718–5729, Jul. 2018.
    D. Kim, S. Hwang, and H. Kim, “Vehicle stability enhancement of four-wheel-drive hybrid electric vehicle using rear motor control,” IEEE Trans. Veh. Technol., vol. 57, no. 2, pp. 727–735, Mar. 2008. doi: 10.1109/TVT.2007.907016
    X. Y. Huang, H. Zhang, G. G. Zhang, et al., “Robust weighted gain-scheduling H vehicle lateral motion control with considerations of steering system backlash-type hysteresis,” IEEE Trans. Control Systems Technology, vol. 22, no. 5, pp. 1740–1753, Sept. 2014.
    C. Zhou and J. Xiao, “Improved strong track filter and its application to vehicle state estimation,” Acta Autom. Sinica, vol. 38, no. 9, pp. 1520–1527, Sept. 2012. doi: 10.3724/SP.J.1004.2012.01520
    K. Tabti, M. Bourahla, and L. Mostefai, “Hybrid control of electric vehicle lateral dynamics stabilization,” J. Electr. Eng., vol. 64, no. 1, pp. 50–54, Mar. 2013.
    H. Ohara and T. Murakami, “A stability control by active angle control of front-wheel in a vehicle system,” IEEE Trans. Ind. Electron., vol. 55, no. 3, pp. 1277–1285, Mar. 2008. doi: 10.1109/TIE.2007.909051
    M. Canale, L. Fagiano, A. Ferrara, and C. Vecchio, “Vehicle yaw control via second-order sliding-mode technique,” IEEE Trans. Ind. Electron., vol. 55, no. 11, pp. 3908–3916, Nov. 2008. doi: 10.1109/TIE.2008.2003200
    M. H. B. Peeie, “Skid control of small electric vehicles (direct yaw moment control using tire steer angle),” Proc. Schl. Eng. Tokai Univ. Ser. E, vol. 39, no. 11, pp. 73–80, Nov. 2014.
    A. Nasri, B. Gasbaoui, and B. M. Fayssal, “Sliding mode control for four wheels electric vehicle drive,” Procedia Technol., vol. 22, pp. 518–526, Jan. 2016. doi: 10.1016/j.protcy.2016.01.111
    K. Nam, H. Fujimoto, and Y. Hori, “Lateral stability control of in-wheel-motor-driven electric vehicles based on sideslip angle estimation using lateral tire force sensors,” IEEE Trans. Veh. Technol., vol. 61, no. 5, pp. 1972–1985, Jun. 2012. doi: 10.1109/TVT.2012.2191627
    A. Nahidi, A. Kasaiezadeh, S. Khosravani, A. Khajepour, S. K. Chen, and B. Litkouhi, “Modular integrated longitudinal and lateral vehicle stability control for electric vehicles,” Mechatronics, vol. 44, pp. 60–70, Jun. 2017. doi: 10.1016/j.mechatronics.2017.04.001
    L. J. Zhang, J. Sun, and G. Orosz, “Hierarchical design of connected cruise control in the presence of information delays and uncertain vehicle dynamics,” IEEE Trans. Control Syst. Technol., vol. 26, no. 1, pp. 139–150, Jan. 2018. doi: 10.1109/TCST.2017.2664721
    Y. Q. Xia, F. Pu, S. F. Li, and Y. Gao, “Lateral path tracking control of autonomous land vehicle based on ADRC and differential flatness,” IEEE Trans. Ind. Electron., vol. 63, no. 5, pp. 3091–3099, May 2016. doi: 10.1109/TIE.2016.2531021
    S. Khosravani, M. Jalali, A. Khajepour, A. Kasaiezadeh, S. K. Chen, and B. Litkouhi, “Application of lexicographic optimization method to integrated vehicle control systems,” IEEE Trans. Ind. Electron., vol. 65, no. 12, pp. 9677–9686, Dec. 2018. doi: 10.1109/TIE.2018.2821625
    R. C. Rafaila, C. F. Caruntu, and G. Livint, “Nonlinear model predictive control using lyapunov functions for vehicle lateral dynamics,” IFAC-Papersonline, vol. 49, no. 3, pp. 135–140, Jul. 2016. doi: 10.1016/j.ifacol.2016.07.023
    Y. Yamaguchi and T. Murakami, “Adaptive control for virtual steering characteristics on electric vehicle using steer-by-wire system,” IEEE Trans. Ind. Electron., vol. 56, no. 5, pp. 1585–1594, May 2009. doi: 10.1109/TIE.2008.2010171
    C. Geng, L. Mostefai, M. Denai, and Y. Hori, “Direct yaw-moment control of an in-wheel-motored electric vehicle based on body slip angle fuzzy observer,” IEEE Trans. Ind. Electron., vol. 56, no. 5, pp. 1411–1419, May 2009. doi: 10.1109/TIE.2009.2013737
    H. Imine, N. K. M’Sirdi, and Y. Delanne, “Sliding-mode observers for systems with unknown inputs: Application to estimating the road profile,” Proc. Inst. Mech. Eng.,Part D:J. Autom. Eng., vol. 219, no. 8, pp. 989–997, Aug. 2005. doi: 10.1243/095440705X34658
    H. B. Pacejka, Tire and Vehicle Dynamics. 3rd ed. Oxford, UK: Butterworth-Heinemann, 2012.
    J. Ahmadi, A. K. Sedigh, and M. Kabganian, “Adaptive vehicle lateral-plane motion control using optimal tire friction forces with saturation limits consideration,” IEEE Trans. Veh. Technol., vol. 58, no. 8, pp. 4098–4107, Oct. 2009. doi: 10.1109/TVT.2009.2023660
    R. Rajamani, Vehicle Dynamics and Control. Austin, US: Springer, 2006.
    S. H. Ding, L. Liu, and W. X. Zheng, “Sliding mode direct yaw-moment control design for in-wheel electric vehicles,” IEEE Trans. Ind. Electron., vol. 64, no. 8, pp. 6752–6762, Aug. 2017. doi: 10.1109/TIE.2017.2682024
    L. Zhai, T. M. Sun, and 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., vol. 65, no. 6, pp. 4726–4739, Jun. 2016. doi: 10.1109/TVT.2016.2526663
    O. Mokhiamar and M. Abe, “Simultaneous optimal distribution of lateral and longitudinal tire forces for the model following control,” J. Dyn. Syst.,Meas.,Control, vol. 126, no. 4, pp. 753–763, Dec. 2004. doi: 10.1115/1.1850533
    B. X. Duan, “Study on electronic stability control of in-wheel motor EV,” M.S. thesis, Jilin Univ., Changchun, China, 2013.


    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

    Figures(12)  / Tables(2)

    Article Metrics

    Article views (1899) PDF downloads(115) Cited by()


    • Design a kind of vehicle tire longitudinal forces optimization distribution strategy, which increases the utilization rate of each wheel.
    • Proposed a kind of compensation allocation strategy based on the axle load distribution method, which considers the tire longitudinal force constraint. And the effectiveness of actuators can be guaranteed.
    • Adopt the hierarchical control structure for controller design, which effectively improves the performance of automotive active safety.


    DownLoad:  Full-Size Img  PowerPoint