Robust Control of Regenerative and Hydraulic Brakes for Enhancing Directional Stability of an Electric Vehicle during Straight-Line Braking

Thanks to the actuation flexibility of their systems, electric vehicles with individual powertrains, including in-wheel and on-board motors, are a very popular research topic amongst various types of electrified powertrain architectures. The introduction of the individual electric powertrain provides great capacity for improvement of the vehicle's energy efficiency and control performance. However, it also poses tremendous challenges concerning vehicle safety, due to the complex system dynamics and cooperation mechanisms between multiactuators. For an electric vehicle with independently controlled motors, because of design and manufacturing factors, the steady-state error of each motor output torque, and the flexibilities and nonlinear backlash of left and right drivetrains, can be different. This results in asymmetrical output characteristics of electric powertrain systems on the same axle. Therefore, during a normal straight-line deceleration, an unexpected yaw moment would be generated, affecting vehicle's directional stability. In this study, a novel method of directional stability enhancement through robust control of blended braking of an electric vehicle equipped with four individual on-board motors during normal straight-line deceleration are studied. System models, including the vehicle dynamics, tire, electric powertrain, and hydraulic brake models, are developed. Mechanisms of directional instability of the electric vehicle during straight-line braking are analyzed. To further improve the electric vehicle's safety and performance, robust control algorithm of blended braking is developed using nonlinear sliding mode approach. Simulations of the proposed control strategy is carried out under straight-line braking. The results demonstrate that the developed approach is advantageous over the baseline, with respect to both the directional stability and regeneration efficiency, thus validating the feasibility and effectiveness of the controller synthesis.