Extended-Kalman-filter-based regenerative and friction blended braking control for electric vehicle equipped with axle motor considering damping and elastic properties of electric powertrain

Because of the damping and elastic properties of an electrified powertrain, the regenerative brake of an electric vehicle (EV) is very different from a conventional friction brake with respect to the system dynamics. The flexibility of an electric drivetrain would have a negative effect on the blended brake control performance. In this study, models of the powertrain system of an electric car equipped with an axle motor are developed. Based on these models, the transfer characteristics of the motor torque in the driveline and its effect on blended braking control performance are analysed. To further enhance a vehicle's brake performance and energy efficiency, blended braking control algorithms with compensation for the powertrain flexibility are proposed using an extended Kalman filter. These algorithms are simulated under normal deceleration braking. The results show that the brake performance and blended braking control accuracy of the vehicle are significantly enhanced by the newly proposed algorithms.