TY - GEN
T1 - Design and Implementation of Braking Control for Hybrid Electric Vehicles
AU - Mei, Peng
AU - Yang, Shichun
AU - Xu, Bin
AU - Sun, Kangkang
AU - Zhang, Chao
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Regenerative braking can effectively improve fuel consumption for hybrid electric vehicles, and it is a critical technology related to the multi-objective control situation, which is used to realize vehicle braking safety, the energy of braking recovery, and braking stability. Therefore, this paper put forward an adaptive fuzzy control (AFC) method for energy recovery in electric vehicles, mainly for a regenerative braking system. In particular, adaptive control is designed for estimating the road condition. The fuzzy logic control is proposed based on the braking strength of the vehicle, the battery state of charge, and vehicle speed. Combine the mentioned methods, an electric vehicle model is established in the Simulink environment to verify the applicability of the proposed control algorithm.
AB - Regenerative braking can effectively improve fuel consumption for hybrid electric vehicles, and it is a critical technology related to the multi-objective control situation, which is used to realize vehicle braking safety, the energy of braking recovery, and braking stability. Therefore, this paper put forward an adaptive fuzzy control (AFC) method for energy recovery in electric vehicles, mainly for a regenerative braking system. In particular, adaptive control is designed for estimating the road condition. The fuzzy logic control is proposed based on the braking strength of the vehicle, the battery state of charge, and vehicle speed. Combine the mentioned methods, an electric vehicle model is established in the Simulink environment to verify the applicability of the proposed control algorithm.
KW - adaptive control
KW - fuzzy logic control
KW - hybrid electric vehicles
KW - torque allocate strategy
UR - https://www.scopus.com/pages/publications/85123848380
U2 - 10.1109/ICICIP53388.2021.9642191
DO - 10.1109/ICICIP53388.2021.9642191
M3 - 会议稿件
AN - SCOPUS:85123848380
T3 - 11th International Conference on Intelligent Control and Information Processing, ICICIP 2021
SP - 160
EP - 164
BT - 11th International Conference on Intelligent Control and Information Processing, ICICIP 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 11th International Conference on Intelligent Control and Information Processing, ICICIP 2021
Y2 - 3 December 2021 through 7 December 2021
ER -