Energy Management Strategy for a Fuel Cell E-REV Based on Minimum Power Loss Algorithm

Author:

Hu Jin Yu1,Song Ke1,Zhang Tong1

Affiliation:

1. Tongji University

Abstract

Aim at the different characteristics from general fuel-cell vehicles of extended-range electric vehicles (E-REVs) with a fuel-cell stack as the Range Extender (RE), an energy management strategy based on minimum power loss algorithm is presented, which considers the efficiency of the fuel-cell stack and the charging and discharging efficiency of battery. The strategy is realized by neural network, simulated with the E-REV model, which is set up with ADVISOR. And a longer driving range is obtained.

Publisher

Trans Tech Publications, Ltd.

Subject

General Engineering

Reference6 articles.

1. Guohui Ren, HEV Energy Management Control Strategies, Science & Technology Information, 2010, (24), pp.26-28.

2. Ke Song, Jing Zhang and Tong Zang, Design and Development of a Pluggable PEMFC Extended Range Electric Vehicle, Mechanic Automation and Control Engineering (MACE), 2011 Second International Conference, 2011, pp.1144-1147.

3. Xing Xie, Su Zhou, Tinghong Wang and Fengxiang Chen, A Simulation on Energy Management Strategy for the Power System of a Fuel Cell/Battery HEV Based on Cruise/Simulink, Automotive Engineering, 2010, 32(5), pp.373-378.

4. Jian Wu, Chenghui Zhang and Naxin Cui, Real-time Energy Management of Parallel Hybrid Electric Vehicle based on BP Neural Network, Electric Machines and Control, 2008, 12(5), pp.610-614.

5. Shuang Cong, Neural Network Theory and Applications with MATLAB Toolboxes, 3rd Version, Press of University of Science and Technology of China, 2009. 4.

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