Design of Energy Management Strategy in Hybrid Electric Vehicles by Evolutionary Fuzzy System Part II: Tuning Fuzzy Controller by Genetic Algorithms

Aihua Wang, Weizi Yang
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引用次数: 22

Abstract

This paper presents the second part of a two-part paper on development of an evolutionary fuzzy energy management strategy for parallel hybrid vehicles. In this part, we utilized genetic algorithms (GA) to optimize the parameters of the fuzzy controller. In addition, we employed a novel method to cope with the difficulties often encountered in designing a fitness function of GA. The simulation study reveals that the proposed "evolutionary fuzzy system" based energy management strategy provide a platform of new energy management system and gives improved performance of a parallel hybrid vehicle
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基于进化模糊系统的混合动力汽车能量管理策略设计第二部分:基于遗传算法的模糊控制器整定
本文是关于并联混合动力汽车演化模糊能量管理策略研究的第二部分。在这一部分中,我们利用遗传算法(GA)来优化模糊控制器的参数。此外,我们采用了一种新颖的方法来解决遗传算法在设计适应度函数时经常遇到的困难。仿真研究表明,提出的基于“进化模糊系统”的能量管理策略为新型能量管理系统提供了平台,提高了并联式混合动力汽车的性能
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