TY - GEN
T1 - An effective regenerative braking strategy based on the combination algorithm of particle swarm optimization and ant colony optimization for electrical vehicle
AU - Zhang, Yuanbo
AU - Wang, Weida
AU - Yang, Chao
AU - Han, Lijin
AU - Zhang, Zhongguo
AU - Liu, Jingang
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/6
Y1 - 2019/6
N2 - 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.
AB - 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.
KW - ant colony optimization
KW - electric vehicle
KW - particle swarm optimization
KW - predictive control (key words)
KW - regenerative braking control
UR - http://www.scopus.com/inward/record.url?scp=85070599949&partnerID=8YFLogxK
U2 - 10.1109/ISIE.2019.8781183
DO - 10.1109/ISIE.2019.8781183
M3 - Conference contribution
AN - SCOPUS:85070599949
T3 - IEEE International Symposium on Industrial Electronics
SP - 1905
EP - 1910
BT - Proceedings - 2019 IEEE 28th International Symposium on Industrial Electronics, ISIE 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 28th IEEE International Symposium on Industrial Electronics, ISIE 2019
Y2 - 12 June 2019 through 14 June 2019
ER -