Abstract:

On board sensors provide rich environment information for intelligent vehicles. However， in the electronically controlled suspension control algorithm， the road information perceived by vehicles has not been fully utilized， resulting in poor vehicle dynamics control effect. In this paper， a variable step length model predictive control （VSL-MPC） algorithm is proposed based on the high-performance preview control of semi-active suspension. The VSL-MPC algorithm determines the step length of preview control by real-time vehicle velocity and the road information collected by the binocular camera， so that the road perception information included in the control algorithm can reflect the road features more accurately， which is helpful for the semi-active suspension to adjust the damping characteristics of the suspension at a more appropriate time to realize a more ideal suspension decision-making control. The road profile information is collected by the binocular camera first. Then the optimal performance limit of semi-active suspension system is introduced as the performance evaluation benchmark， and four different semi-active suspension simulation models based on model predictive control are established. The results of simulation show that under the typical urban road conditions such as continuous deceleration belts and manhole cover impact， the performance gap between the VSL-MPC algorithm and the benchmark is only 0.72 and 2.33 dB， which are much smaller than 4.31 and 4.46 dB of traditional preview MPC algorithm， and 4.04 and 4.74 dB of non-preview MPC algorithm， when taking the vertical acceleration of sprung mass as the indicator. The VSL-MPC algorithm can enhance the dynamic performance of semi-active suspension effectively.

Key words: semi-active suspension, preview control, VSL-MPC, transient impact, continuous damping control damper