Parallel Balancing Battery using Adaptive Power Sharing and ANN SOC Estimator

Mokhamad Zuhal Muflih, Gilang Andaru Trinandana, Eka Prasetyono, D. O. Anggriawan
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引用次数: 0

Abstract

The battery balancing method is commonly used in cell circuits and battery circuits to maintain the power continuity on the DC Bus. The power continuity on the DC Bus is guaranteed if the load continues to get a power source, even if either the battery or power supply malfunctions. Besides, the battery balancing method is also used to protect the battery from excessive charging current pliers flowing into the battery. Therefore, the State-of-Charge (SoC) should be concern in balancing the maintained battery condition on both systems and avoiding overcharging. Artificial Neural Network (ANN) is used in this paper to determine the value of battery SoC. Based on simulations using MATLAB 2018, SoC values with ANN showed accurate results with error values below 0.1%. Based on the simulation results, the two batteries, which are arranged to have a difference of SoC value of 0.3%, will achieve a balanced SoC value for 28.45 seconds from the simulation.
基于自适应功率共享和ANN SOC估计器的并联平衡电池
电池平衡方法通常用于电池电路和电池电路,以保持直流母线上的电源连续性。如果负载继续获得电源,即使电池或电源出现故障,直流母线上的电源连续性也会得到保证。此外,电池平衡方法还用于保护电池免受过大的充电电流钳子流入电池的影响。因此,在平衡两个系统上保持的电池状态并避免过度充电时,应考虑充电状态(SoC)。本文使用人工神经网络(ANN)来确定电池SoC的值。基于MATLAB 2018的仿真,使用ANN的SoC值显示出准确的结果,误差值低于0.1%。根据仿真结果,SoC值相差0.3%的两个电池将在28.45秒内实现SoC值的平衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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