Adaptive Anti-slip Regulation Method for Electric Vehicle with In-wheel Motors Considering the Road Slope

Anti-slip regulation (ASR) is one of the research focus in the field of active safety of electric vehicle. An ASR algorithm adaptive to road condition is proposed in this paper based on 4WD electric vehicle with in-wheel motors. The controller based on anti-windup sliding mode control is robust to wheel parameter uncertainty. The longitudinal velocity estimator based on the fusion of dynamics method and kinematics method is adopted to reduce the velocity estimation error. The road slope is estimated using recursive least square with forgetting factor and the longitudinal acceleration sensor information is calibrated by the road slope estimation for slope adaptive velocity estimation. At the same time, a road coefficient estimator is adopted to estimate road condition using improved Burckhardt model, so the optimal reference slip ratio is selected according to the estimated road adhesion coefficient for the maximum driving efficiency and the realization of adaptive anti-slip regulation. Multi-condition simulations show that the controller is adaptive to road changes, and it can suppress wheel slip ratio and ensure the vehicle stability.

[1]  Hassan K. Khalil,et al.  Universal controllers with nonlinear integrators , 2002, Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301).

[2]  K. Hedrick,et al.  Real-time slip-based estimation of maximum tire-road friction coefficient , 2004, IEEE/ASME Transactions on Mechatronics.

[3]  Dihua Sun,et al.  Real-time road slope estimation based on adaptive extended Kalman filter algorithm with in-vehicle data , 2017, 2017 29th Chinese Control And Decision Conference (CCDC).

[4]  Qi Zhang,et al.  An investigation of calculation method of wheel angular acceleration in anti-lock braking system , 2008, 2008 International Conference on Information and Automation.

[5]  Hiroyuki Yamaguchi,et al.  Development of Vehicle Stability Control System Based on Vehicle Sideslip Angle Estimation , 2001 .

[6]  Karl Hedrick,et al.  Estimation of the Maximum Tire-Road Friction Coefficient , 2003 .

[7]  Yoichi Hori Future vehicle driven by electricity and control-research on four wheel motored "UOT Electric March II" , 2002, 7th International Workshop on Advanced Motion Control. Proceedings (Cat. No.02TH8623).

[8]  Shuzhi Sam Ge,et al.  Sliding-Mode-Observer-Based Adaptive Slip Ratio Control for Electric and Hybrid Vehicles , 2012, IEEE Transactions on Intelligent Transportation Systems.

[9]  Zhuoping Yu,et al.  Path Following Control for Skid Steering Vehicles with Vehicle Speed Adaption , 2014 .

[10]  Rajesh Rajamani,et al.  Development and experimental evaluation of a slip angle estimator for vehicle stability control , 2006 .

[11]  Håvard Fjær Grip,et al.  Topics in State and Parameter Estimation for Nonlinear and Uncertain Systems , 2010 .

[12]  J. Christian Gerdes,et al.  ROAD GRADE AND VEHICLE PARAMETER ESTIMATION FOR LOGITUDINAL CONTROL USING GPS. , 2001 .

[13]  Zhuoping Yu,et al.  Estimation of maximum road friction coefficient based on Lyapunov method , 2016 .

[14]  Yugong Luo,et al.  Vehicle mass and road slope estimates for electric vehicles , 2015 .