SOC Control of Lithium–Ion Battery Using Fuzzy Logic Controller and PID Controller Employed in DC Micro Grid

Priyanka A. Wagh, Sushil Karvekar
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Abstract

Integrating solar panels in DC micro grid is a big task, since it involves a battery for power storage and battery controller. The most tedious task is enhancement of battery life and efficiency. This paper introduces two separate models of DC micro grid, one regulated by fuzzy logic controller and the other one by a conventional PID controller. The fuzzy logic controller is implemented in MATLAB Simulink based upon Mamdani inference system. MPPT, fuzzy logic controller, lithium-ion battery and DC load are all integrated in one Simulink model. Best possible rule base is developed to regulate power flow through the DC micro grid, thus simultaneously enhancing the performance of lithium-ion battery. The fuzzy logic controller facilitates maintenance of SOC of lithium-ion battery within desired limits, which results in prevention of overcharging and over discharging. Also, conventional PID controller is implemented in MATLAB Simulink for maintaining SOC of lithium-ion battery within desired limits. This model involves integration of PID controller, MPPT, bi-directional DC-DC converter and lithium-ion battery. Based upon the obtained performance and results of both Simulink models, a comparison between the two controllers is deduced and corresponding results are analyzed. Transient response analysis is performed to compare the two controllers.
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基于模糊控制器和PID控制器的直流微电网锂离子电池SOC控制
将太阳能电池板集成到直流微电网中是一项艰巨的任务,因为它涉及到用于储能的电池和电池控制器。最乏味的任务是提高电池寿命和效率。本文介绍了两种独立的直流微电网模型,一种是由模糊控制器控制的,另一种是由传统的PID控制器控制的。基于Mamdani推理系统,在MATLAB Simulink中实现了模糊逻辑控制器。MPPT、模糊控制器、锂离子电池和直流负载都集成在一个Simulink模型中。开发最佳规则库来调节直流微电网的潮流,从而同时提高锂离子电池的性能。模糊控制器使锂离子电池的SOC保持在理想的范围内,从而防止过充过放。此外,在MATLAB Simulink中实现了传统的PID控制器,使锂离子电池的SOC保持在期望的范围内。该模型集成了PID控制器、MPPT、双向DC-DC变换器和锂离子电池。根据两种Simulink模型所获得的性能和结果,推导了两种控制器的比较,并对相应的结果进行了分析。对两种控制器进行了暂态响应分析比较。
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