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Energies 2017, 10(11), 1875; https://doi.org/10.3390/en10111875

Enhanced Regenerative Braking Strategies for Electric Vehicles: Dynamic Performance and Potential Analysis

1
College of Engineering, South China Agricultural University, Guangzhou 510640, China
2
Guangdong Academy of Agricultural Sciences, Guangzhou 510640, China
3
University of Technology Sydney, 15 Broadway, Ultimo, NSW 2007, Australia
*
Author to whom correspondence should be addressed.
Received: 13 October 2017 / Revised: 7 November 2017 / Accepted: 13 November 2017 / Published: 15 November 2017
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Abstract

A regenerative braking system and hydraulic braking system are used in conjunction in the majority of electric vehicles worldwide. We propose a new regenerative braking distribution strategy that is based on multi-input fuzzy control logic while considering the influences of the battery’s state of charge, the brake strength and the motor speed. To verify the braking performance and recovery economy, this strategy was applied to a battery electric vehicle model and compared with two other improved regenerative braking strategies. The performance simulation was performed using standard driving cycles (NEDC, LA92, and JP1015) and a real-world-based urban cycle in China. The tested braking strategies satisfied the general safety requirements of Europe (as specified in ECE-13H), and the emergency braking scenario and economic potential were tested. The simulation results demonstrated the differences in the braking force distribution performance of these three regenerative braking strategies, the feasibility of the braking methods for the proposed driving cycles and the energy economic potential of the three strategies. View Full-Text
Keywords: regenerative braking strategy; energy flow; fuzzy control; battery electric vehicle; driving cycle construction regenerative braking strategy; energy flow; fuzzy control; battery electric vehicle; driving cycle construction
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Xiao, B.; Lu, H.; Wang, H.; Ruan, J.; Zhang, N. Enhanced Regenerative Braking Strategies for Electric Vehicles: Dynamic Performance and Potential Analysis. Energies 2017, 10, 1875.

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