锂(药物)
计算机科学
离子
国家(计算机科学)
功率(物理)
汽车工程
化学
生物
物理
工程类
算法
热力学
内分泌学
有机化学
作者
Shreasth Shreasth,Chia Ai Ooi,Neha Khan,Mohd Khairunaz Mat Desa,Mohamad Khairi Ishak,Khalid Ammar
标识
DOI:10.1038/s41598-025-96581-8
摘要
In series and parallel strings connected Lithium-ion (Li-ion) battery modules or packs, it is essential to equalise each Li-ion cell to enhance the power delivery performance and usable capacity, otherwise, it is restricted by the worst cell in the string. An active cell balancing algorithm based on Charging State-of-Power (CSoP) and Discharging State-of-Power (DSoP) derived from the dynamically estimated State-of-Charge (SoC) or State-of-Health (SoH) is proposed to handle the problem of cell imbalance during both charging and discharging operation. Compared with the voltage-based and SoC-based cell equalization algorithms, the proposed algorithm determines cell imbalance using State-of-Power (SoP) invariance among cells in the battery pack, which allows the Battery Management System (BMS) to regulate the power flow of the Electric Vehicle (EV) with minimum balancing efforts and fully charge/discharge each cell in the battery pack. This ensures the better performance of the proposed cell balancing as compared to other (Voltage/SoC-based) balancing in maximizing the battery pack capacity and minimizing balancing losses. To validate the efficacy of the novel SoP-based cell equalization algorithm, a simulation is conducted in which a Li-ion battery model is built in MATLAB/Simulink platform. The simulation results show that the usable capacity using the proposed SoP-based method is improved by 16% as compared to the usable capacity of the battery pack without-balancing. An experimental setup using four Li-ion cells is also executed to explore the stability, robustness, and precision of the proposed cell balancing algorithm. The parameters of cells differ in capacity and initial SoC from each other to resemble the imbalance among the cells in the battery pack.
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