Particle Swarm Optimization Algorithm for Regenerative Braking Fuzzy Control of Electric Vehicle

DOI

10.2991/icismme-15.2015.153How to use a DOI?

Keywords

Regenerative braking; fuzzy controller; particle swarm optimization; electric vehicle.

Abstract

Improving raking energy regeneration efficiency is a vital problem of electric vehicle. Particle swarm optimization is introduced for regenerative braking fore distribution fuzzy controller, using membership functions and rules of fuzzy controller as optimization object and using limit of input as constraint condition. In this article, based on the front and rear braking force distribution strategy, a traditional fuzzy controller is designed. Then we show how to use particle swarm optimization algorithm to optimize it. Compared to the traditional one, we carry on some simulations in ADVISOR software. The results show that, the braking torque is improved and the braking energy regeneration efficiency raises by 7.19 percent, which indicates the validity of the proposed fuzzy controller.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Liao Qin
PY  - 2015/07
DA  - 2015/07
TI  - Particle Swarm Optimization Algorithm for Regenerative Braking Fuzzy Control of Electric Vehicle
BT  - Proceedings of the First International Conference on Information Sciences, Machinery, Materials and Energy
PB  - Atlantis Press
SP  - 738
EP  - 742
SN  - 1951-6851
UR  - https://doi.org/10.2991/icismme-15.2015.153
DO  - 10.2991/icismme-15.2015.153
ID  - Qin2015/07
ER  -