Wheel Pressure Estimation of Hydraulic Integrated Braking System by Fusion Model

The precise wheel pressure acquisition is the pre-requisite for the sensor diagnosis, pressure regulation and subsequent vehicle dynamics control. Limited by environmental per-turbations, model mismatch, and other reasons, the stability and convergence of pure hydraulic model-based estimation methods are not well guaranteed. To mitigate the estimation error, the key perturbation, coil winding temperature, is estimated in this research, and the Kalman Filter is adopted to fuse the hydraulic model and the vehicle dynamics information. To further consider the effect of model mismatch in the low and high pressure region of the hydraulic braking system, this research presents two kinds of hydraulic models depending on the valve dynamics, and an interacting multiple model (IMM) filter is presented to fuse different hydraulic models to suit various control inputs. The filter developed in this paper is verified in typical driving conditions, and the results show that the proposed filter presents better pressure estimation compared to a single Kalman Filter and pure hydraulic model-based methods.