Model predictive control of a semi-active suspension with a shift delay compensation using preview road information

Abstract

This paper presents a model predictive control of a semi-active suspension with a shift delay compensation using preview road information. A Model Predictive Control (MPC) methodology has been developed to optimize both ride comfort and road handling performance, where suspension states have been estimated through a model-based Kalman filter. The use of MPC in semi-active suspension control has proven to be suitable due to its ability to consider constraints when optimizing the objective function. A feasible region for the control inputs into the semi-active suspension has been determined from its mechanical limitations. However, the proposed Model Predictive Controller carries a sizeable computational load. Occurrences of “shift time delays” have been observed from the vehicle’s Electronic Control Unit processing the algorithm. To combat this, a model prediction system, in which a full-car dynamic model and road preview information are utilized to predict vehicle suspension states, has been further proposed to compensate for the shift time delay. Preview road information has been obtain through the computation of relative vehicle motion and a temporal–spatial conversion. The overall algorithm has been evaluated via computer simulation studies. Simulation results have shown that the shift compensation algorithm provides considerable improvements with regards to ride comfort. A noteworthy section of this study is the successful implementation of the proposed algorithms into an actual vehicle, where the real world performance of the proposed algorithms have been assessed. It has been shown via vehicle tests that significant improvement in ride comfort can be obtained by the proposed MPC damping control.