Using PV Fuzzy Tracking Algorithm to Charge Electric Vehicles

Yao Lung Chuang, Miguel Herrera, Afshin Balal
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引用次数: 5

Abstract

Due to the possible shortage of oil and gas, increasing the number of cars, global warming, air pollution, and outages, there is a special need for renewable energy sources and electric vehicles (EVs). The new battery-electric vehicles BEVs can be charged by the power grid. However, the existing fossil fuel power plant cannot provide enough power for this purpose, and the only choice is renewable energy sources (RECs). Comparing RECs, solar energy is abundant and accessible in any part of the world. Needless to state that a maximum power point tracking (MPPT) system is required in order to extract maximum power from solar modules. In this paper, a charging strategy is proposed via using a solar system, a boost converter, and a fuzzy tracking algorithm. The main research contribution of the presented paper is to charge an EV without putting stress on the power grid. The effectiveness of this approach is demonstrated by the MATLAB Simulink and LTSPICE results.
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基于PV模糊跟踪算法的电动汽车充电
由于石油和天然气可能短缺、汽车数量增加、全球变暖、空气污染和停电,对可再生能源和电动汽车(ev)的需求特别大。新型纯电动汽车可以通过电网充电。然而,现有的化石燃料发电厂无法提供足够的电力,唯一的选择是可再生能源(RECs)。与RECs相比,太阳能在世界任何地方都是丰富和可获得的。不用说,为了从太阳能模块中提取最大功率,需要最大功率点跟踪(MPPT)系统。本文提出了一种利用太阳能系统、升压变换器和模糊跟踪算法的充电策略。本文的主要研究贡献是在不对电网施加压力的情况下为电动汽车充电。MATLAB Simulink和LTSPICE实验结果验证了该方法的有效性。
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