Robust Adaptive Autonomous Braking Control for Intelligent Electric Vehicles*

Abstract

This paper presents a two-stage autonomous braking control for electric vehicles with preview information acquired by intelligent transportation systems (ITS) or connected and autonomous vehicle (CAV) technologies. The goal of the control method is firstly to plan a speed profile to comply with a target speed and a target residual distance to an upcoming deceleration event and then to track the planned speed profile by generating tracking-driven braking control torques, which maximally employ regenerative braking. Once deceleration circumstances are perceived, the intelligent reference speed planner computes a smooth speed profile by using a current vehicle speed, a target speed, and a target residual distance. For the braking control to robustly track the planned speed profile, a chattering-free sliding mode controller is designed on the interconnected vehicle and braking system model with braking system uncertainties and external disturbances, and a sufficient condition for the sliding mode gain is introduced. Also, adaptive update laws to compensate for the braking system uncertainties provide feed-forward control efforts for the tracking control inputs. To verify the effectiveness of the proposed control approach, the control methods are applied to a real commercial vehicle and the consecutive driving experiments with various deceleration circumstances illustrate a successful tracking-driven cooperative braking performance.