基于模糊模型预测控制的电池均衡研究
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国家自然科学基金(52207233)


Research on battery balancing based on fuzzy model predictive control
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    摘要:

    为了提升锂离子电池组均衡系统的性能,提出了一种基于模糊自适应模型预测控制(fuzzy adaptive model predictive control,FAMPC)的模块化均衡系统。首先,由改进的buck-boost电路和反激变压器组成双层均衡拓扑结构;其次,以不同电池剩余容量(state of charge,SOC)的状态作为模糊逻辑算法的输入,对均衡电流的约束条件进行调节;再次,基于FAMPC均衡控制方法,直接利用开关管的占空比作为系统输入;最后,在改变电池组状态并不使用额外电流控制机制的情况下进行仿真实验。结果表明,与传统的模糊控制方法相比,所提系统在正常条件下均衡速度提高了约24.51%,在电池低SOC的极端条件下均衡速度可以进一步提高至34.48%。所提系统将模糊算法提供的稳定性与模型预测控制算法的快速性相结合,保证了电池组更安全稳定的运行,可为电池组性能提升研究提供参考。

    Abstract:

    To improve the performance of lithium-ion battery pack balancing system, a modular balancing system based on fuzzy adaptive model predictive control (FAMPC) was proposed. Firstly, a dual-layer balancing topology structure was composed of an improved buck-boost circuit and a flyback transformer. Secondly, using the state of charge (SOC) at different levels of battery remaining capacities as inputs for the fuzzy logic algorithm, the constraints on the balancing current were adjusted. Then, based on FAMPC balancing control method, the duty cycle of the switching transistor was directly used as the system input. Finally, simulation experiments were conducted without employing additional current control mechanisms to change the battery pack state. The results show that compared with traditional fuzzy control methods, the proposed system increase the balancing speed by approximately 24.51% under normal conditions and can further increase the balancing speed to 34.48% under extreme conditions with low battery SOC. The proposed system combines the stability provided by fuzzy algorithms with the rapid response of model predictive control algorithms, ensuring safer and more stable operation of the battery pack, which can provide reference for the research of enhancing battery pack performance.

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刘光军,王宇涛,马黎阳,吴铁洲,田爱娜.基于模糊模型预测控制的电池均衡研究[J].河北科技大学学报,2025,46(1):21-29

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  • 收稿日期:2024-08-23
  • 最后修改日期:2024-09-19
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  • 在线发布日期: 2025-01-17
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