Hybrid damping control of magnetorheological semi-active suspension based on feedback linearization Kalman observer

Abstract

To improve the dynamic performances of nonlinear magnetorheological (MR) semi-active suspension, a hybrid damping control (HDC) based on Kalman observer of nonlinear suspension system is proposed. Firstly, the mechanical test of MR damper is carried out, and the mechanical model of MR damper and suspension system model are established. On this basis, a feedback linearization Kalman observer (FLKO) based on differential geometry theory is designed. Then, the working modes of the MR suspension system are divided according to different driving roads. HDC is proposed to achieve the dynamic control objectives under different working modes, and genetic algorithm is used to optimize the coefficients of skyhook, groundhook and distribution. The simulation results show that the estimation accuracy of FLKO is more than 85%. Compared with passive suspension, the tire dynamic load is optimized by 15.53% on A class road, improving the road holding. On B class road, the body acceleration, suspension deflection and tire dynamic load are optimized by 2.22%, 23.76% and 1.47% respectively, optimizing the dynamic performances comprehensively. On C class road, the body acceleration is optimized by 17.69%, improving the ride comfort effectively. Finally, a test bench is built, and the test results are basically consistent with simulation, which verifies the effectiveness of the designed FLKO and HDC.