Study of ride comfort of active suspension based on model reference neural network control system

In order to study the ride comfort of active suspension vehicle, a detailed virtual prototype vehicle was established by using SIMPACK software, and a seven-degree freedom mathematical model for the active suspension automotive system was also built. A model reference adaptive control based on neural network was designed for active suspension system. The SIMPACK-MATLAB co-simulation method was used to analyze the ride comfort of active suspension. The result showed that, comparing with passive suspension, when the vehicle speed reached to 60km/h on grade C road, the neural network controller could reduce the mean square roots(RMS) of the vertical acceleration, the roll angular acceleration and the pitch angular acceleration by 38.75%, 44.12% and 36.99%. When the speed of vehicle achieved 120km/h, the mean square roots reduced by 33.88%, 41.97% and 25.50%. It showed that the model reference adaptive control based on neural network could reduce the vehicle body vibration and improve the ride comfort.