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All Journal Journal of Applied Smart Electrical Network and System (JASENS)
Tiara Erly Syah Putri
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Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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the Estimation of State of Charge for 4S2P Lithium-Ion Battery Using Kalman Filter and Coulomb Counting Tiara Erly Syah Putri; Mat Syai’in; Ii Munadhif
Journal of Applied Smart Electrical Network and Systems Vol 6 No 01 (2025): Vol 06, No. 01 June 2025
Publisher : Indonesian Society of Applied Science (ISAS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52158/jasens.v6i01.1166

Abstract

State of Charge (SoC) estimation is crucial for the performance and safety of Battery Management Systems (BMS). This study evaluates and compares two SoC estimation methods—Kalman Filter and Coulomb Counting—based on numerical simulation of a 4S2P lithium-ion battery charging process using MATLAB. The methods are assessed using statistical metrics: RMSE, MAE, MAPE, and R², and are compared against both current-based reference calculations and normalized actual voltage. Kalman Filter consistently demonstrates superior performance, achieving lower RMSE (0.00067) and MAE (0.00045) against SoC reference, and RMSE (0.0376), MAE (0.0312), R² (0.978) against voltage reference. In contrast, Coulomb Counting shows increased error accumulation and lower correlation with system behavior. This confirms Kalman Filter's robustness in dynamic conditions, owing to its real-time correction mechanism and noise tolerance. The study highlights Kalman Filter as a more accurate and reliable method for modern BMS applications. Recommendations for future development include real-world testing and hybrid algorithm implementation.
Co-Authors Ii Munadhif Mat Syai’in