@inproceedings{760b391ed93949919426577c3c69c341,
title = "A Fuzzy Sliding-Mode Control for Regenerative Braking System of Electric Vehicle",
abstract = "This paper presents a novel sliding-mode control scheme with fuzzy logic control approach for the energy management of electric vehicles subject to a regenerative braking system. Based on the μ-slip curve, the road friction coefficient can be estimated. A fuzzy logic controller is designed to adjust the sliding mode parameters according to the slip ratio tracking error between the optimal slip ratio and the actual slip ratio. The proposed torque distribution strategy can integrate the best battery condition and energy recovery efficiency through this control method by determining the hydraulic braking torque and regenerative braking torque, which consider related constraints. The simulations have been conducted in the Simulink environment based on an electric vehicle model to verify the proposed controller.",
keywords = "electric vehicle, fuzzy logic control, regenerative braking system, sliding-mode control",
author = "Peng Mei and Shichun Yang and Bin Xu and Kangkang Sun",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 7th International Conference on Control, Automation and Robotics, ICCAR 2021 ; Conference date: 23-04-2021 Through 26-04-2021",
year = "2021",
month = apr,
day = "23",
doi = "10.1109/ICCAR52225.2021.9463463",
language = "英语",
series = "2021 7th International Conference on Control, Automation and Robotics, ICCAR 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "397--401",
booktitle = "2021 7th International Conference on Control, Automation and Robotics, ICCAR 2021",
address = "美国",
}