An effective regenerative braking strategy based on the combination algorithm of particle swarm optimization and ant colony optimization for electrical vehicle

Regenerative braking method is one of the core technologies to improve the economy of electric vehicles. Considering the characteristics of regenerative braking system and pneumatic braking system, designing the optimal regenerative braking control strategy to improve the economy as much as possible under the premise of ensuring the safety of vehicle is still a challenge. An effective regenerative braking strategy based on the combination of particle swarm optimization and ant colony optimization is proposed to solve this problem in the paper. Firstly, the configuration of regenerative braking system and pneumatic braking system are described in detail. Then, considering the high nonlinear and multi-objective characteristics of the system, the proposed strategy is designed based on the hybrid braking system. Finally, simulation experiments are carried out based on the model, and the experimental results shows that the braking stability is guaranteed in the emergency braking condition, and the recovery braking energy is improved 16.04% compared with the rule-based regenerative braking strategy in the driving cycle in city.