Vibration analysis and adaptive model predictive control of active suspension for vehicles equipped with non-pneumatic wheels

In this paper, an adaptive controller is proposed for an active suspension system to achieve optimal compromise performance for vehicles equipped with non-pneumatic wheels under different road conditions. Firstly, the effective vertical stiffness of the non-pneumatic wheel (NPW) was identified through the static force-deflection tests. Then, the effect of the variations in NPW stiffness and mass on the vibration responses was investigated using a quarter-vehicle model. In order to coordinate the ride comfort and handling performance of the vehicle for different road excitations, an adaptive controller was synthesized using the model predictive control (MPC) theory together with an H ∞ state observer. The control gains for different control objectives were determined using a genetic algorithm (GA). Simulations indicate that the proposed controller can adapt to different road excitations and effectively enhance the dynamic performance of the vehicle. Specifically, by applying adaptive control, the root-mean-square (RMS) value of sprung mass acceleration (SMA) and the dynamic wheel load (DWL) coefficient are reduced by 19.4% and −9.3% on Class B roads and 12.4% and 3.8% on Class C roads, respectively, which is superior to the modified skyhook control (19.4% and −11.8% on Class B roads, and 19.3% and −12.3% on Class C roads). The effectiveness of simulation results was subsequently verified through hardware-in-the-loop experiments.