Design of genetic-fuzzy control strategy for parallel Hybrid Electric Vehicles

被引：158

作者：

Poursamad, Amir ^{[1
]}

Montazeri, Morteza ^{[1
]}

机构：

[1] Iran Univ Sci & Technol, Dept Mech Engn, Tehran 16844, Iran

来源：

CONTROL ENGINEERING PRACTICE | 2008年 / 16卷 / 07期

关键词：

hybrid electric vehicle; control strategy; FUZZY logic; genetic algorithms;

D O I：

10.1016/j.conengprac.2007.10.003

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Hybrid Electric Vehicles (HEVs) generate the power required to drive the vehicle via a combination of internal combustion engines and electric generators. To make HEVs as efficient as possible, proper management of the different energy elements is essential. This task is performed using the HEV control strategy. The HEV control strategy is the algorithm according to which energy is produced, used and saved. This paper describes a genetic-fuzzy control strategy for parallel HEVs. The genetic-fuzzy control strategy is a fuzzy logic controller that is tuned by a genetic algorithm. The objective is to minimize fuel consumption and emissions, while enhancing or maintaining the driving performance characteristics of the vehicle. The tuning process is performed over three different driving cycles including NEDC, FTP and TEH-CAR. Results from the computer simulation demonstrate the effectiveness of this approach in reducing fuel consumption and emissions without sacrificing vehicle performance. (C) 2007 Elsevier Ltd. All rights reserved.

引用

页码：861 / 873

页数：13

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