Regenerative Braking Algorithm for Parallel Hydraulic Hybrid Vehicles Based on Fuzzy Q-Learning-Reference-Cited by-同舟云学术

Regenerative Braking Algorithm for Parallel Hydraulic Hybrid Vehicles Based on Fuzzy Q-Learning

Published:2023-02-14 Issue:4 Volume:16 Page:1895
ISSN:1996-1073
Container-title:Energies
language:en
Short-container-title:Energies

Author:

Ning Xiaobin¹^ORCID,Wang Jiazheng¹,Yin Yuming¹,Shangguan Jiarong¹,Bao Nanxin¹,Li Ning²

Affiliation:

1. College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310014, China

2. School of Intelligent Manufacturing, Taizhou University, Taizhou 318000, China

Abstract

The use of regenerative braking systems is an important approach for improving the travel mileage of electric vehicles, and the use of an auxiliary hydraulic braking energy recovery system can improve the efficiency of the braking energy recovery process. In this paper, we present an algorithm for optimizing the energy recovery efficiency of a hydraulic regenerative braking system (HRBS) based on fuzzy Q-Learning (FQL). First, we built a test bench, which was used to verify the accuracy of the hydraulic regenerative braking simulation model. Second, we combined the HRBS with the electric vehicle in ADVISOR. Third, we modified the regenerative braking control strategy by introducing the FQL algorithm and comparing it with a fuzzy-control-based energy recovery strategy. The simulation results showed that the power savings of the vehicle optimized by the FQL algorithm were improved by about 9.62% and 8.91% after 1015 cycles and under urban dynamometer driving schedule (UDDS) cycle conditions compared with a vehicle based on fuzzy control and the dynamic programming (DP) algorithm. The regenerative braking control strategy optimized by the fuzzy reinforcement learning method is more efficient in terms of energy recovery than the fuzzy control strategy.

Funder

Basic Public Welfare Research Program of Zhejiang Province

National Natural Science Foundation of China

Publisher

MDPI AG

Subject

Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction

Link

https://www.mdpi.com/1996-1073/16/4/1895/pdf

Reference32 articles.

1. A review on hybrid electric vehicles architecture and energy management strategies;Sabri;Renew. Sustain. Energy Rev.,2016

2. Li, N., Jiang, J.P., Sun, F.L., Ye, M.R., Ning, X.B., and Chen, P.Z. (2022). A cooperative control strategy for a hydraulic regenerative braking system based on chassis domain control. Electronics, 11.

3. Braking energy optimization control for four in-wheel motors electric vehicles considering battery life;Xu;Control Theory Appl.,2019

4. Design strategy for improving the energy efficiency in series hydraulic/electric synergy system;Ramakrishnan;Energy,2014

5. Optimal brake torque distribution for a four-wheel-drive hybrid electric vehicle stability enhancement;Kim;Proc. Inst. Mech. Eng. Part D—J. Automob. Eng.,2007

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