Yaw Stability Control of 4WD Vehicles Based on Model Predictive Torque Vectoring with Physical Constraints

Abstract

This paper describes a yaw stability control algorithm of 4WD vehicles based on model predictive torque vectoring with physical constraints. A vehicle planar model based predictive rear and all-wheel torque vectoring algorithms were developed for 4WD vehicles by considering predictive states and driver's steering wheel angle. The physical constraints applied to the model predictive control consist of three types: limitation on magnitude of tire force, change rate of tire force, and output torque of transfer case. Two types of torque vectoring algorithms, rear-wheel and all-wheel, were constructed for comparative analysis. The steady state yaw rate was derived and applied as a desired value for yaw stability of the vehicle. The algorithm was constructed in a MATLAB/Simulink environment and the performance evaluation was conducted under various test scenarios, such as step steering and double lane change, using the CarSim software. The evaluation results of the predictive torque vectoring showed sound performance based on the prediction of states and driver's steering angle.