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Hybrid Swarm Intelligence-Based Optimization for Charging Plug-in Hybrid Electric Vehicle

机译:基于混合群的充电插件混合动力电动汽车的混合体群优化

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Plug-in hybrid electric vehicle (PHEV) has the potential to facilitate the energy and environmental aspects of personal transportation, but face a hurdle of access to charging system. The charging infrastructure has its own complexities when it is compared with petrol stations because of the involvement of the different charging alternatives. As a result, the topic related to optimization of Plug-in hybrid electric vehicle charging infrastructure has attracted the attention of researchers from different communities in the past few years. Recently introduced smart grid technology has brought new challenges and opportunities for the development of electric vehicle charging facilities. This paper presents Hybrid particle swarm optimization Gravitational Search Algorithm (PSOGSA)-based approach for state-of-charge (SoC) maximization of plug-in hybrid electric vehicles hence optimize the overall smart charging.
机译:插入式混合动力电动车(PHEV)有可能促进个人运输的能源和环境方面,但面临着充电系统的障碍。由于不同的充电替代方案的参与,充电基础设施在与汽油站进行比较时具有自己的复杂性。因此,与插件混合动力电动车充电基础设施的优化有关的话题引起了过去几年来自不同社区的研究人员的注意。最近推出的智能电网技术为电动汽车充电设施的开发带来了新的挑战和机遇。本文介绍了混合粒子群优化重力搜索算法(PSOGSA)基本的充电状态(SOC)最大化的插件混合动力电动车辆的最大化,因此优化了整体智能充电。

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