模型预测控制
荷电状态
电池(电)
储能
参数统计
电容器
电压
控制理论(社会学)
H桥
计算机科学
工程类
渲染(计算机图形)
功率(物理)
转换器
电子工程
控制(管理)
电气工程
脉冲宽度调制
量子力学
计算机图形学(图像)
统计
数学
人工智能
物理
作者
Gaowen Liang,Ezequiel Rodríguez,Glen G. Farivar,Enrique Nunes,Georgios Konstantinou,Christopher D. Townsend,Ramon Leyva,Josep Pou
标识
DOI:10.1109/tie.2023.3290249
摘要
In the operation of battery energy storage systems based on the cascaded H-bridge converter, it is beneficial to balance the state of charge of batteries in different submodules within the converter phase-arm. This is achieved by distributing the active power among the submodules. Although multiple methods have been proposed for this purpose, they face the challenge of rendering optimal active power distributions that maximize balancing speed while meeting power constraints in the battery energy storage system. To overcome this challenge, a model predictive control scheme is developed in this paper. The proposed method is remarkably robust against parametric uncertainties (battery voltage, capacity, etc.), as evidenced by its ability to tolerate a substantial 50% uncertainty in the parameters, resulting in a mere 0.05% steady-state error. Furthermore, because the predictive control can be executed at a low frequency, the computational burden is comparable to other existing methods.
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