Seven-degree-of-freedom-based electric wheel sampled-data active shimmy control method considering unknown sensor measurement error

The active shimmy control methods for electric vehicle driven by in-wheel motors (EV-DIM) have been proposed in the recent years. However, these methods assume that data obtained from sensors are accurate, despite the fact that sensor measurements are prone to error. This unknown measurement error can make shimmy control difficult. Additionally, current shimmy models are low degree-of-freedom, which simplifies control but decreases accuracy. In this paper, we address these issues using a sampled-data output control method based on a higher seven-degree-of-freedom (7DOF) shimmy model which includes the steering system, suspension, and electric wheel. We first construct a 7DOF electric wheel shimmy model and use Lagrange's theorem to derive the electric wheel shimmy dynamic equations. We then obtain system state equations that account for unknown sensor measurement error based on the 7DOF shimmy model. A sampled-data observer and controller are designed to attenuate or eliminate the shimmy phenomenon via a domination gain. Finally, we conduct numerical simulations and experiments to verify the effectiveness of our proposed method.