Brake Pressure Estimation of the Integrated Braking System Considering Vehicle Dynamics

Abstract

The integrated braking control system (IBC) has become one of the most popular brake-by-wire (BBW) solutions due to its compactness and versatility. Accurate monitoring of wheel cylinder pressure in real time is the basis for brake pressure control, and pressure estimation is a low-cost and reliable method. However, the IBC is an electromechanical hydraulic coupling system that has significant nonlinear behaviors; moreover, vehicle dynamics also have a critical impact on the accuracy of pressure estimation. To solve this problem, this paper proposes a novel adaptive extended Kalman filter (EKF) approach that combines a hydraulic model and a single-wheel model. This novel strategy has better estimation than the hydraulic model when the pressure is accurately estimated by the single-wheel model, while when the single-wheel model is not accurate, the EKF degrades to the hydraulic model. Finally, vehicle experimental data under high- and low-mu braking are collected. The pressure estimation error of the EKF is within 0.4 MPa in the low-mu road and 2 MPa in the high-mu road. It is proven that the proposed pressure estimation strategy is highly effective.

Keywords

• brake pressure estimation
• integrated braking control system
• Kalman filter
• single-wheel model
• hydraulic model
• apply valve