Iterative learning control of antilock braking of electric and hybrid vehicles

Hybrid electric vehicles (HEVs) use multiple sources of power for propulsion which provides great ease and flexibility to achieve advanced controllability and additional driving performance. In this paper, the electric motor in HEV and electric vehicle (EV) propulsion systems is used to achieve antilock braking performance without a conventional antilock braking system (ABS). The paper illustrates that the antilock braking of HEV can be easily achieved using iterative learning control for various road conditions. A vehicle model, a slip ratio model, and a vehicle speed observer were developed to control the antilock performance of HEV during braking. Through iterative learning process, the motor torque is optimized to keep the tire slip ratio corresponding to the peak traction coefficient during braking. Simulations were performed on a compact size vehicle to validate the proposed control method. The control algorithm proposed in this paper may also be used for the ABS control of conventional vehicles.