MATLAB - Simulink Based Analysis of Lithium-Ion Battery Charging, Discharging and SOC Estimation

Abstract

Lithium-ion batteries are widely used in electric vehicles and energy storage systems due to their high energy density, long cycle life, and stable performance. Accurate analysis of charging, discharging, and State of Charge (SOC) estimation is essential for reliable Battery Management Systems (BMS). This research presents a complete MATLAB–Simulink based simulation framework that models the dynamic behavior of a single lithium-ion cell using CC–CV charging and controlled discharging. The model integrates electrical, thermal, and SOC estimation subsystems to evaluate overall battery performance. Charging and discharging energy were computed using time-domain voltage and current data, yielding 8.078 Wh during charging and 6.710 Wh during discharging. The round-trip energy efficiency was found to be 83.10%, which closely aligns with real lithium-ion cell characteristics. SOC estimation using the Coulomb Counting method achieved high accuracy during charging (RMSE 0.40%) and acceptable behavior during discharging (RMSE 11.41%). The results validate the developed model and demonstrate its suitability for BMS algorithm development, EV battery testing, and educational research applications.

Introduction

This work presents an integrated MATLAB–Simulink framework for modeling, analyzing, and validating the charging, discharging, State of Charge (SOC) estimation, and energy efficiency of lithium-ion batteries. Lithium-ion cells are widely used in EVs, electronics, and renewable systems, making accurate battery modeling and SOC estimation essential for Battery Management System (BMS) design and battery health assessment.

The study uses Simscape Battery libraries to simulate a realistic 18650 lithium-ion cell, avoiding the cost, time, and safety risks of experimental testing. Charging is modeled using the standard Constant Current–Constant Voltage (CC–CV) method, while discharging is performed under controlled constant load conditions. SOC is estimated using the Coulomb Counting method and compared with the SOC computed internally by Simscape based on OCV–SOC characteristics.

The simulation framework integrates electrical, thermal, SOC estimation, and energy computation subsystems within a single environment. Charging and discharging energies are calculated using voltage–current integration, and round-trip efficiency is evaluated. Simulation results show accurate CC–CV charging behavior, realistic discharge characteristics, stable temperature operation, and an energy efficiency of 83.10%, which aligns with typical commercial lithium-ion cells.

SOC comparison results indicate high accuracy of Coulomb Counting during charging (RMSE 0.40%), while moderate deviation occurs during long discharging cycles (RMSE 11.41%) due to integration drift. Overall, the proposed unified simulation model provides a reliable and practical foundation for lithium-ion battery research, SOC validation, energy efficiency analysis, and advanced BMS development.

Conclusion

This work presented a comprehensive MATLAB–Simulink based simulation framework for analyzing lithium-ion battery charging, discharging, SOC estimation, and round-trip energy efficiency. The CC–CV charging model and constant current discharging conditions produced realistic electrical and thermal responses. SOC estimation using the Coulomb Counting method showed excellent accuracy during charging with an RMSE of 0.40%, while a higher deviation of 11.41% was observed during discharging due to integration drift. Charging and discharging energy values of 8.078 Wh and 6.710 Wh, respectively, resulted in a round-trip efficiency of 83.10%, which aligns well with typical commercial lithium-ion cells. The developed framework is reliable, computationally efficient, and can serve as a foundation for BMS development, EV battery studies, and academic training.

References

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Copyright

Copyright © 2025 Sahil ., Vikas Sindhu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.