Acceleration slip regulation by electric motor torque of battery electric vehicle with nonlinear model predictive control approach

References

• He Z, Shi Q, Wei Y, et al. A torque demand model predictive control approach for driving energy optimization of battery electric vehicle. IEEE Trans Veh Technol. 2021;PP(99):1–1.
   Google Scholar
• Osinenko P, Streif S. Optimal traction control for heavy-duty vehicles. Control Eng Pract. 2017;69:99–111.
   Web of Science ®Google Scholar
• Guo N, Zhang X, Zou Y, et al. A fast model predictive control allocation of distributed drive electric vehicles for tire slip energy saving with stability constraints. Control Eng Pract. 2020;102:Article ID 104554.
   Web of Science ®Google Scholar
• Shi K, Yuan X, Liu L. Model predictive controller-based multi-model control system for longitudinal stability of distributed drive electric vehicle. ISA Trans. 2018;72:44–55.
   PubMed Web of Science ®Google Scholar
• Savitski D, Schleinin D, Ivanov V, et al. Improvement of traction performance and off-road mobility for a vehicle with four individual electric motors: driving over icy road. J Terramech. 2017;69(Feb.):33–43.
   Web of Science ®Google Scholar
• Davide T, Mathias M, Patrick G, et al. Explicit nonlinear model predictive control for electric vehicle traction control. IEEE Trans Control Syst Technol. 2018;PP:1–14.
   Google Scholar
• Pinto SD, Chatzikomis C, Sorniotti A, et al. Comparison of traction controllers for electric vehicles with on-board drivetrains. IEEE Trans Veh Technol. 2017;66(8):6715–6727.
   Web of Science ®Google Scholar
• Ran X, Zhao X, Chen J, et al. Novel coordinated algorithm for traction control system on split friction and slope road. Int J Autom Technol. 2016;17(5):817–827.
   Web of Science ®Google Scholar
• Young J-S, Kuan-Jung C. A feasible approach for the force control of traction wheels driven by electric motors. Asian Journal of Control: Affiliated with ACPA, the Asian Control Professors' Association. 2016;18(1):112–121.
   Google Scholar
• Song P, Tomizuka M, Zong C. A novel integrated chassis controller for full drive-by-wire vehicles. Veh Syst Dyn. 2015;53(2):215–236.
   Web of Science ®Google Scholar
• Shi K, Yuan X, Huang G, et al. MPC-based compensation control system for the yaw stability of distributed drive electric vehicle. Int J Syst Sci. 2018;49:1795–1808.
   Web of Science ®Google Scholar
• Peng B, Zhang H, Zhao P. Research on the stability control strategy of four-wheel independent driving electric vehicle. Engineering. 2017;9(3):338–350.
   Google Scholar
• Zhang Y, Zeng T, Zhang Y, et al. Model adaptive torque control and distribution with error reconstruction strategy for RWID EVs. IET Intell Transp Syst. 2019;14(5):382–391.
   Web of Science ®Google Scholar
• Yin D, Sun N, Hu J-S. A wheel slip control approach integrated with electronic stability control for decentralized drive electric vehicles. IEEE Trans Ind Inform. 2020;15(4):2244–2252.
   Web of Science ®Google Scholar
• Jalali M, Khajepour A, Chen SK, et al. Integrated stability and traction control for electric vehicles using model predictive control. Control Eng Pract. 2016;54:256–266.
   Web of Science ®Google Scholar
• Li B, Goodarzi A, Khajepour A, et al. An optimal torque distribution control strategy for four-independent wheel drive electric vehicles. Veh Syst Dyn. 2015;53(8):1172–1189.
   Web of Science ®Google Scholar
• Shi Q, Wang M, He Z, et al. A fuzzy-algorithm-based sliding mode control approach for acceleration slip regulation of battery electric vehicle. Chin J Mech Eng. 2022;35(72).
   Google Scholar
• Shi K, Yuan X, Huang G, et al. DLMPCS-based improved yaw stability control strategy for DDEV. IET Intell Transp Syst. 2019;13(9):1329–1339.
   Web of Science ®Google Scholar
• Yue M, Lu Y, Sun X, et al. Stability control for FWID-EVs with supervision mechanism in critical cornering situations. IEEE Trans Veh Technol. 2018;PP:1–1.
   Google Scholar
• Aligia DA, Magallan GA, De Angelo CH. EV traction control based on nonlinear observers considering longitudinal and lateral tire forces. IEEE Trans Intell Transp Syst. 2017;19(8):2558–2571.
   Web of Science ®Google Scholar
• Eto R, Sakata K, Yamakawa J. Driving force distribution based on tyre energy for independent wheel-drive vehicle on rough ground. J Terramechanics. 2018;76:29–38.
   Web of Science ®Google Scholar
• Kobayashi T, Katsuyama E, Sugiura H, et al. Efficient direct yaw moment control: tyre slip power loss minimisation for four-independent wheel drive vehicle. Veh Syst Dyn. 2018;56(5):719–733.
   Web of Science ®Google Scholar
• Fuchun S. Research and development on theory and algorithms of sliding mode control. Control Theory Appl. 2007;24(3):407–418.
   Google Scholar
• He L, Shen T, Yu L, et al. A model-predictive-control-based torque demand control approach for parallel hybrid powertrains. IEEE Trans Veh Technol. 2013;62(3):1041–1052.
   Web of Science ®Google Scholar
• Hoseinnezhad R, Bab-Hadiashar A. Efficient antilock braking by direct maximization of tire CRoad frictions. IEEE Trans Ind Electron. 2011;58(8):3593–3600.
   Web of Science ®Google Scholar
• Guan H, Wang B, Lu P, et al. Identification of maximum road friction coefficient and optimal slip ratio based on road type recognition. Chin J Mech Eng. 2014;27(5):1018–1026.
   Web of Science ®Google Scholar
• He Z, Shi Q, Wei Y, et al. A model predictive control approach with slip ratio estimation for electric motor anti-lock braking of battery electric vehicle. IEEE Trans Ind Electron. 2022;10. doi:10.1109/TIE.2021.3112966
   Web of Science ®Google Scholar
• He L, Ye W, He Z, et al. A combining sliding mode control approach for electric motor anti-lock braking system of battery electric vehicle. Control Eng Pract. 2020;102:Article ID 104520.
   Web of Science ®Google Scholar
• Shaoyi B, Bo L, Yanyan Z. Adhesion state estimation based on improved tire brush model. Adv Mech Eng. 2018;10(1):Article ID 168781401774770.
   Web of Science ®Google Scholar
• Castillo JJ, Cabrera JA, Guerra AJ, et al. A novel electrohydraulic brake system with tire-road friction estimation and continuous brake pressure control. IEEE Trans Ind Electron. 2016;63(3):1863–1875.
   Web of Science ®Google Scholar
• Albinsson A, Bruzelius F, Jacobson B, et al. Design of tyre force excitation for tire-road friction estimation. Veh Syst Dyn. 2016;55(2):208–230.
   Web of Science ®Google Scholar
• Zhao YQ, Li HQ, Lin F, et al. Estimation of road friction coefficient in different road conditions based on vehicle braking dynamics. Chin J Mech Eng. 2017;30(4):982–990.
   Web of Science ®Google Scholar
• Chen C, Jia Y, Wang Y, et al. Non-linear velocity observer for vehicles with tire-road friction estimation. Int J Syst Sci. 2018;49(5–8):1–16.
   Google Scholar
• Xia X, Xiong L, Sun K, et al. Estimation of maximum road friction coefficient based on Lyapunov method. Int J Autom Technol. 2016;17(6):991–1002.
   Web of Science ®Google Scholar
• Unsal C, Kachroo P. Sliding mode measurement feedback control for antilock braking systems. IEEE Trans Control Syst Technol. 2002;7(2):271–281.
   Web of Science ®Google Scholar
• Wong JY. Theory of ground vehicles. J Autom Eng. 2002;216(7):629–629.
   Google Scholar