Finding optimal deceleration with serial regenerative braking of electric vehicle using a multi-objective genetic algorithm

To improve the fuel economy and range of an electric vehicle, as much as energy regeneration during braking is important. It was observed that driving harshness has a great impact on the regeneration efficiency during vehicle deceleration. On the other hand, to reduce the trip time as well as to avoid accident, the deceleration duration needs to be kept short. By realizing these conflicting objectives, in the present work an optimal deceleration is find out for a speed change using a genetic algorithm. The concerned multi-objective optimization problem (MOOP) was solved based on two approaches: considering a constant deceleration, and variable decelerations during braking. Comparative results of both the approaches are presented for a representative speed change in four driving cycles. Results of both approaches in solving the MOOP including under certain constraints, such as a desired comfort journey and maintaining a safe braking distance, suggest that multiple decelerations should be used during planned braking, where as either a constant or multiple deceleration may be taken during braking for high comfort journey and under emergency braking demand.