Next Article in Journal
Cost Benefit Analysis of Using Clean Energy Supplies to Reduce Greenhouse Gas Emissions of Global Automotive Manufacturing
Next Article in Special Issue
Battery Management Systems in Electric and Hybrid Vehicles
Previous Article in Journal
Designing an Energy Storage System Fuzzy PID Controller for Microgrid Islanded Operation
Previous Article in Special Issue
Model Predictive Control-Based Fast Charging for Vehicular Batteries
Open AccessArticle

An Intelligent Regenerative Braking Strategy for Electric Vehicles

by Guoqing Xu 1,2, Weimin Li 3,*, Kun Xu 3 and Zhibin Song 3
Department of Electrical Engineering, Tongji University, Shanghai 200092, China
Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong, China
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
Author to whom correspondence should be addressed.
Energies 2011, 4(9), 1461-1477;
Received: 12 May 2011 / Revised: 2 September 2011 / Accepted: 6 September 2011 / Published: 22 September 2011
(This article belongs to the Special Issue Electric and Hybrid Vehicles)
Regenerative braking is an effective approach for electric vehicles (EVs) to extend their driving range. A fuzzy-logic-based regenerative braking strategy (RBS) integrated with series regenerative braking is developed in this paper to advance the level of energy-savings. From the viewpoint of securing car stability in braking operations, the braking force distribution between the front and rear wheels so as to accord with the ideal distribution curve are considered to prevent vehicles from experiencing wheel lock and slip phenomena during braking. Then, a fuzzy RBS using the driver’s braking force command, vehicle speed, battery SOC, battery temperature are designed to determine the distribution between friction braking force and regenerative braking force to improve the energy recuperation efficiency. The experimental results on an “LF620” prototype EV validated the feasibility and effectiveness of regenerative braking and showed that the proposed fuzzy RBS was endowed with good control performance. The maximum driving range of LF620 EV was improved by 25.7% compared with non-RBS conditions. View Full-Text
Keywords: regenerative braking; fuzzy logic; braking force distribution regenerative braking; fuzzy logic; braking force distribution
Show Figures

Figure 1

MDPI and ACS Style

Xu, G.; Li, W.; Xu, K.; Song, Z. An Intelligent Regenerative Braking Strategy for Electric Vehicles. Energies 2011, 4, 1461-1477.

Show more citation formats Show less citations formats

Article Access Map by Country/Region

Only visits after 24 November 2015 are recorded.
Back to TopTop