Vehicle Motion Control with Jerk Constraint by Nonlinear Model Predictive Control

In this paper, a nonlinear model predictive control considering vehicle jerk dynamics is proposed for improving ride comfort of passengers. Since the vehicle model in prediction phase requires high accuracy dynamics in order to handle the jerk motion, the approximated wheel load transfer dynamics is introduced. Also, to obtain the control capability for not only jerk but also acceleration, velocity and position, the expanded state space model including these dimensions into the one has been developed. It improves the utility as autonomous vehicle controller. By numerical simulation in assuming cornering driving scene, the effectiveness that jerk and other vehicle states enable to constraint simultaneously by individual torque distribution by electric power train is validated. Further, the principle of the optimized torque distribution by proposed method is analyzed.