Particle Swarm Optimization of a Fuzzy Controlled Hybrid Energy Storage System - HESS

Lenon Diniz Seixas, Hilkija Gaïus Tosso, F. C. Corrêa, J. Eckert
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引用次数: 8

Abstract

With the increase in transportation electrification, one of the biggest challenges is to improve battery performance and its autonomy. One promising alternative is the hybrid energy storage system (HESS), composed of a battery associated with supercapacitors (SC). In this work, a fuzzy logic power management control for the HESS is developed aiming to increase the overall system autonomy. When batteries an SC are associated, the power management complexity increases considerably. Therefore, it is necessary to determine the correct power distribution between the storage devices, in order to enhance the system efficiency, by saving the battery of excessive efforts. To reach these objectives, a particle swarm optimization was applied to tune the fuzzy controller in a Matlab simulation system. Finally, the optimized fuzzy controlled HESS was capable to extend the autonomy by 66.67%, as compared to a single battery-powered system, under the same operating conditions.
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模糊控制混合储能系统的粒子群优化
随着交通运输电气化程度的提高,提高电池性能及其自主性是最大的挑战之一。一种很有前途的替代方案是混合能源存储系统(HESS),它由与超级电容器(SC)相关的电池组成。本文提出了一种基于模糊逻辑的HESS电源管理控制方法,以提高系统的整体自主性。当电池和SC相关联时,电源管理的复杂性大大增加。因此,有必要确定正确的存储设备之间的功率分配,以提高系统效率,通过节省电池的过度努力。为了达到这些目标,在Matlab仿真系统中应用粒子群算法对模糊控制器进行整定。最后,在相同的运行条件下,优化后的模糊控制HESS与单一电池供电系统相比,自主性提高了66.67%。
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