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PSO Based PI Controller Design for a Solar Charger System

机译:基于PO的PI控制器设计用于太阳能充电器系统

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Due to global energy crisis and severe environmental pollution, the photovoltaic (PV) system has become one of the most important renewable energy sources. Many previous studies on solar charger integrated system only focus on load charge control or switching Maximum Power Point Tracking (MPPT) and charge control modes. This study used two-stage system, which allows the overall portable solar energy charging system to implement MPPT and optimal charge control of Li-ion battery simultaneously. First, this study designs a DC/DC boost converter of solar power generation, which uses variable step size incremental conductance method (VSINC) to enable the solar cell to track the maximum power point at any time. The voltage was exported from the DC/DC boost converter to the DC/DC buck converter, so that the voltage dropped to proper voltage for charging the battery. The charging system uses constant current/constant voltage (CC/CV) method to charge the lithium battery. In order to obtain the optimum PI charge controller parameters, this study used intelligent algorithm to determine the optimum parameters. According to the simulation and experimental results, the control parameters resulted from PSO have better performance than genetic algorithms (GAs).
机译:由于全球能源危机和严重的环境污染,光伏(PV)系统已成为最重要的可再生能源之一。许多先前关于太阳能充电器集成系统的研究只关注负载电荷控制或切换最大功率点跟踪(MPPT)和充电控制模式。本研究采用了两级系统,允许整体便携式太阳能充电系统同时实现MPPT和Li离子电池的最佳充电控制。首先,本研究设计了太阳能发电的DC / DC升压转换器,它使用可变步长增量电导方法(VSINC)来使得太阳能电池随时跟踪最大功率点。电压从DC / DC Boost转换器导出到DC / DC降压转换器,使电压降至适当的电压,用于对电池充电。充电系统使用恒流/恒压(CC / CV)方法来对锂电池充电。为了获得最佳PI充电控制器参数,本研究使用智能算法来确定最佳参数。根据仿真和实验结果,PSO引导的控制参数比遗传算法(气体)具有更好的性能。

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