A fuzzy - genetic algorithm approach for finding a new HEV control strategy idea

Arash Zargham nejhad, B. Asaei
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引用次数: 7

Abstract

In this paper, a novel control strategy for hybrid electric vehicles (HEVs) is presented. The proposed method is based on global optimization for energy management system of a conventional parallel HEV. A rule based fuzzy control strategy is considered for optimization of the system. The fuzzy membership function boundaries are kept constant and the fuzzy rule table is optimized by using genetic algorithm for different types of cycles. The results of the proposed optimization method suggest that fixing the internal combustion engine (ICE) torque constant is prior to keeping the state of charge (SOC) of the batteries constant. It confirms that the electric machine should provide dynamic power of the load and static power should be supplied by the ICE.
用模糊遗传算法寻找新的混合动力汽车控制策略思想
提出了一种新的混合动力汽车控制策略。该方法基于对传统并联混合动力汽车能量管理系统的全局优化。采用基于规则的模糊控制策略对系统进行优化。针对不同类型的循环,采用遗传算法优化模糊规则表,并保持模糊隶属函数边界不变。优化结果表明,保持内燃机(ICE)扭矩恒定优先于保持电池的荷电状态(SOC)恒定。确认负载的动电源由电机提供,静电源由ICE提供。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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