A Integrated Estimation Scheme for Tire Road Friction Coefficient Using EKHF and AUKF

The tire-road friction coefficient (TRFC) is essential for vehicle stability control and motion planning, particularly in four-wheel distributed drive electric vehicles. Estimating the TRFC typically requires obtaining the tire force first. However, onboard sensors usually do not directly measure tire force, making it common practice to use a tire model for calculation. The accuracy of tire force calculation is affected by time-varying sensor noise, which in turn impacts the TRFC estimation. To address this, we propose a method that combines the extended H-infinity Kalman filter (EHKF) with the adaptive Unscented Kalman filter (AUKF). The EHKF is used to obtain the tire force, and then the AUKF, along with the vehicle model, estimates the TRFC. Empirical data reveal that the Suggested algorithm surpasses the traditional UKF in terms of estimation accuracy and has lower volatility.