Using Integrated Predictive Model Control in the Simulation of Stability and Traction Control of an Electric Vehicle

Document Type : Research Article

Authors

1 Department of Mechanical Engineering/Yazd University/Yazd/Iran

2 Department of Mechanical Engineering, Yazd University, Yazd, Iran

Abstract

Two of the main challenges of electric vehicles are ensuring stability and preventing wheel slippage. In the electric vehicle in this article, each wheel has an independent electric motor, and this conventional vehicle is at a lower level than the autonomous and self-driving types. The body of this car has three degrees of freedom, and the wheel has three too, which is suitable for moving on a flat road surface. The governing differential equations are obtained using the Newton-Euler method. After mathematical modeling and determining the nonlinear state space for the vehicle and wheel, the equations are verified by comparison with the CarSim software. Furthermore, both the control or ensuring of vehicle stability and the control of traction or avoiding slippage are carried out with the help of an integrated predictive model controller, in which there is no interference or failure to the controller. In similar articles, separate controllers have been used, or they have been implemented in a hierarchical and cascaded manner, which will be subject to interference and disruption. In addition, in this controller, a cost function is considered to minimize the desired indicators and optimize them to satisfy the constraints of the problem. Simulation results show that this controller has been successful in both stability control and traction control based on the European automotive standard, and the results obtained are reliable.

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Main Subjects

References

[1] H.Z. Li, L. Li, L. He, M.X. Kang, J. Song, L.Y. Yu, C. Wu, H.Z. Li, L. Li, L. He, M.X. Kang, J. Song, L.Y. Yu, C. Wu, PID plus fuzzy logic method for torque control in traction control system, International Journal of Automotive Technology, 13(3) (2012) 441-450.
[2] Model predictive control based vehicle stability control via active front steering, Chinese Automation Congress (CAC),  (2017).
[3] G. Liu, L. Jin, A Study of Coordinated Vehicle Traction Control System Based on Optimal Slip Ratio Algorithm, Mathematical Problems in Engineering,  (2016).
[4] N. Behrouz, M. Mehdi, T. Amin, Design of optimal torque vectoring control system with predictive approach for improvement of stability and energy consumption in electric vehicle, Journal of Mechanical Engineering, 49(4) (2019) 257-267.
[5] A. Bagheri, S. Azadi, A. Soltani, Vehicle yaw stability improvement via active braking system using adaptive sliding mode control, Journal of Solid and Fluid Mechanics, 7(1) (2017).
[6] J. Sharifi, A. Amirjamshidi, Fuzzy Electronic Stability Control System for Electric Vehicle with Four Motor in Wheel, Journal of Control, 9(4 ) (2016) 41-53.
[7] M.A. Saeedi, Nonlinear Active Steering Controller for Improvement of Vehicle Lateral Stability, Young Researchers and Elite Club,,  (2017).
[8] M. Jalali, A. Khajepour, S.-K. Chen, B. Litkouhi, Integrated stability and traction control for electric vehicles using model predictive control, Control Engineering Practice, 54 (2016) 256-266.
[9] D. Dogan, P. Boyraz, Smart Traction Control Systems for Electric Vehicles Using Acoustic Road-type Estimation,  (2019).
[10] H. Wu, Z. Li, Z. Si, Trajectory tracking control for four-wheel independent drive intelligent vehicle based on model predictive control and sliding mode control, Advances in Mechanical Engineering, 13(9) (2021).
[11] S. Vaskov, R. Quirynen, M. Menner, K. Berntorp, Friction-Adaptive Stochastic Nonlinear Model Predictive Control for Autonomous Vehicles,  (2023).
[12] J. Feng, J. Liang, Y. Lu, W. Zhuang, D. Pi, G. Yin, L. Xu, P. Peng, C. Zhou, J. Feng, J. Liang, Y. Lu, W. Zhuang, D. Pi, G. Yin, L. Xu, P. Peng, C. Zhou, An Integrated Control Framework for Torque Vectoring and Active Suspension System, Chinese Journal of Mechanical Engineering, 37(1) (2024).
[13] K. Kahraman, M. Senturk, M.T. Emirler, I.M.C. Uygan, B. Aksun-Guvenc, L. Guvenc, B. Efendioglu, Yaw Stability Control System Development and Implementation for a Fully Electric Vehicle,  (2020).
[14] G. Tavolo, K.M. So, D. Tavernini, P. Perlo, A. Sorniotti, Nonlinear Model Predictive Control for Preview-Based Traction Control,  (2024).
[15] R.N. Jazar, Vehicle Dynamics: Theory and application,  (2025).
[16] R. Rajamani, Vehicle Dynamics and Control, Mechanical Engineering Series,  (2012).
[17] J. Tuma, Torque Vectoring Predictive Control for Electric Vehicles, 2018.
[18] M.S. corp., Tire Models (Casim help from Mechanical Simulation), in, 2017.
[19] K. Baarath, M.A. Zakaria, N.A. Zainal, An Investigation on the Effect of Lateral Motion on Normal Forces Acti,  (2018).
[20] G. Nunes, Design and analysis of multivariable predictive control applied to an oil-water-gas separator: A polynomial approach,  (2001).
[21] J.A.E. Andersson, J. Gillis, G. Horn, J.B. Rawlings, M. Diehl, CasADi: a software framework for nonlinear optimization and optimal control, Mathematical Programming Computation, 11(1) (2018).
[22] Regulation No 140 of the Economic Commission for Europe of the United Nations (UN/ECE) — Uniform provisions concerning the approval of passenger cars with regard to Electronic Stability Control (ESC) Systems [2018/1592], in, 2018, pp. 17-35.
[23] T. Koller, F. Berkenkamp, M. Turchetta, J. Boedecker, A. Krause, Learning-based Model Predictive Control for Safe Exploration and Reinforcement Learning,  (2019).
Amirkabir Journal of Mechanical Engineering
Volume 57, Issue 5
August 2025
Pages 611-632

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