一种改进的主动锂离子电池均衡方案,提高近零能耗建筑和电动汽车微电网的性能

M. Koseoglou, E. Tsioumas, N. Jabbour, C. Mademlis
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引用次数: 2

摘要

本文提出了一种改进的电池管理系统(BMS),该系统在电池单元中提供主动均衡,以减少总充电时间,提高系统性能。所提出的控制方案可应用于近零能耗建筑(nZEB)和电动汽车(EV)微电网中使用的锂离子电池储能系统。所提出的BMS更适合上述应用,因为需要电池系统的可重复和高动态性能。通过并联的MOSFET栅极电压适当调节每个电池的充电电流,可以改善电池的运行,从而提高整个微电网的性能。提出了一种老化估计模糊逻辑控制器(AEFLC),通过对每个电池的内阻增长和容量衰减因子进行适当的评估,可以在线估计每个电池堆的健康电池。因此,该算法基于更健康的电池,控制MOSFET电流以实现电池均衡。具体来说,均衡器模糊逻辑控制器(EFLC)评估单元的电压,并在每个MOSFET上施加适当的栅极源电压($V _{GS}$)。通过MATLAB/Simulink程序的仿真模型,验证了所提出的BMS在nZEB和EV微电网中的功能和有效性。给出了选择性仿真结果,以验证新BMS技术可以提供的操作改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Improved Active Li-ion Battery Equalization Scheme for Enhancing the Performance of a nearly Zero Energy Building and Electric Vehicle Microgrid
This paper proposes an improved Battery Management System (BMS) that provides active equalization in the battery cells to reduce the total charging time and enhance the system performance. The suggested control scheme can be applied to energy storage systems with Li-ion batteries that are utilized in nearly zero energy building (nZEB) and electric vehicle (EV) microgrids. The proposed BMS is more suitable for the above applications, since repeatable and high dynamic performance from the battery system are required. The improvement in the battery operation and therefore, the enhancement of the whole microgrid performance can be accomplished by properly regulating the charging current of each battery cell through the gate voltage of a parallel connected MOSFET. An Aging Estimator Fuzzy Logic Controller (AEFLC) is also proposed that can online estimates the healthier cell of each battery stack by properly evaluating the internal resistance growth and the capacity fade factor of each cell. Thus, based on the healthier cell, the proposed algorithm controls the MOSFET current in order to achieve the cell equalization. Specifically, an Equalizer Fuzzy Logic Controller (EFLC) evaluates the cells’ voltages and applies the appropriate gate-source voltage ($V _{GS}$) at each MOSFET. The functionality and the effectiveness of the proposed BMS are verified both for nZEB and EV microgrids via simulation models using the MATLAB/Simulink program. Selective simulation results are presented to validate the operating improvements that the new BMS technique can provide.
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