A novel active lithium-ion cell balancing method based on charging and discharging state of power in electric vehicles

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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Publication Details

Journal
Scientific Reports
Published
2025-05-06
DOI
https://doi.org/10.1038/s41598-025-96581-8
Citations
5
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
3.41

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article

A novel active lithium-ion cell balancing method based on charging and discharging state of power in electric vehicles

Khalid Ammar, Neha Khan, Chia Ai Ooi, Mohd Khairunaz Mat Desa et al.
5 citations
Scientific Reports
Advanced Battery Technologies Research
3.41
article

A novel active lithium-ion cell balancing method based on charging and discharging state of power in electric vehicles

Khalid Ammar, Neha Khan, Chia Ai Ooi, Mohd Khairunaz Mat Desa, Mohamad Khairi Ishak, Shreasth Shreasth
article en
5 citations

Abstract

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.

Scientific ReportsVol. 15(1)
Universiti Sains Malaysia (MY), Ajman University (AE)
Universiti Sains Malaysia, Ajman University
Affordable and clean energy
Openalex Percentile: Top 8%
Advanced Battery Technologies Research
3.41
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