Performance Analysis of Time Capacity and Coulomb Methods for SoC Estimation in VRLA Batteries
DOI:
https://doi.org/10.35814/asiimetrik.v7i2.8774Keywords:
state of charge, VRLA battery, time capacity, coulomb counting, arduinoAbstract
The climate crisis and limited energy availability in remote areas encourage the use of VRLA battery-based off-grid solar energy systems, where accurate state-of-charge (SoC) evaluation is essential for system efficiency. At middle SoC ranges, the VRLA voltage curve's flatness makes voltage-based methods less effective. This research investigates the efficacy of two practical methods, Time Capacity and Coulomb Counting, in estimating the SoC of 12V 10Ah VRLA batteries at varying discharge rates (C20 to C1) using a system that incorporates Arduino Uno and ACS712 sensors. The experimental findings show that Time Capacity is the best strategy, with an inaccuracy of 0-12%. Due to sensor error and temperature sensitivity, Coulomb Counting's error is 30-38.4%. Heatmap imaging proved Time Capacity's stability across all C-rates, making it suitable for remote monitoring. These findings lay the groundwork for reliable and cost-effective renewable energy systems and encourage further research on hybrid algorithms and environmental optimisation.
Downloads
References
Afif, A.R., Aprillia, B.S. and Priharti, W. (2020) ‘Design and Implementation of Battery Management System for Portable Solar Panel with Coulomb Counting Method’, in IOP Conference Series: Materials Science and Engineering. 2nd International Conference on Engineering and Applied Sciences (2nd InCEAS), Yogyakarta, Indonesia: IOP Publishing Ltd, p. 012005. Available at: https://doi.org/10.1088/1757-899X/771/1/012005.
de Almeida, A.T., Moura, P. and Quaresma, N. (2020) ‘Off-Grid Sustainable Energy Systems for Rural Electrification’, in Affordable and Clean Energy. Springer, Cham, pp. 1–22. Available at: https://doi.org/10.1007/978-3-319-71057-0_68-1.
Alshabib, Khalid.R. and Tural, T. (2022) ‘Temperature Effect on Performance Parameters of Valve Regulated Lead Acid (VRLA) Batteries: An Experimental Study for Off-Grid System’, in 2022 Saudi Arabia Smart Grid (SASG). 2022 Saudi Arabia Smart Grid (SASG), Riyadh, Saudi Arabia: IEEE, pp. 1–5. Available at: https://doi.org/10.1109/SASG57022.2022.10199474.
Azis, N.A., Joelianto, E. and Widyotriatmo, A. (2019) ‘State of Charge (SoC) and State of Health (SoH) Estimation of Lithium-Ion Battery Using Dual Extended Kalman Filter Based on Polynomial Battery Model’, in 2019 6th International Conference on Instrumentation, Control, and Automation (ICA). 2019 6th International Conference on Instrumentation, Control, and Automation (ICA), Bandung, Indonesia: IEEE, pp. 88–93. Available at: https://doi.org/10.1109/ICA.2019.8916734.
Bose, D. et al. (2024) ‘Reliability analysis of VRLA Batteries Using Failure Mode and Effects Analysis (FMEA) Technique for hot and Semi-Arid Indian Climatic Condition’, in 2024 IEEE Third International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES). 2024 IEEE Third International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES), Delhi, India: IEEE, pp. 773–778. Available at: https://doi.org/10.1109/ICPEICES62430.2024.10719348.
Bouchareb, H. et al. (2024) ‘Lithium-Ion Battery Health Management and State of Charge (SOC) Estimation Using Adaptive Modelling Techniques’, Energies, 17(22), p. 5746. Available at: https://doi.org/10.3390/en17225746.
Catenaro, E. and Onori, S. (2021) ‘Experimental Data Of Lithium-Ion Batteries Under Galvanostatic Discharge Tests At Different Rates And Temperatures Of Operation’, Data in Brief, 35, p. 106894. Available at: https://doi.org/10.1016/j.dib.2021.106894.
Conde, H.J.C., Demition, C.M. and Honra, J. (2025) ‘Storage Is the New Black: A Review of Energy Storage System Applications to Resolve Intermittency in Renewable Energy Systems’, Energies, 18(2), p. 354. Available at: https://doi.org/10.3390/en18020354.
Hassan, M.U. et al. (2022) ‘A Comprehensive Review Of Battery State Of Charge Estimation Techniques’, Sustainable Energy Technologies and Assessments, 54, p. 102801. Available at: https://doi.org/10.1016/j.seta.2022.102801.
Hassanzadeh, M.E. et al. (2022) ‘Intelligent Fuzzy Control Strategy For Battery Energy Storage System Considering Frequency Support, SoC Management, And C-Rate Protection’, Journal of Energy Storage, 52, p. 104851. Available at: https://doi.org/10.1016/j.est.2022.104851.
Kondaveeti, H.K. et al. (2021) ‘A Systematic Literature Review On Prototyping With Arduino: Applications, challenges, advantages, and limitations’, Computer Science Review, 40, p. 100364. Available at: https://doi.org/10.1016/j.cosrev.2021.100364.
Lee, J. and Won, J. (2023) ‘Enhanced Coulomb Counting Method for SoC and SoH Estimation Based on Coulombic Efficiency’, IEEE Access, 11, pp. 15449–15459. Available at: https://doi.org/10.1109/ACCESS.2023.3244801.
Madhusudanan, G. and Padhmanabhaiyappan, S. (2024) ‘Solar Power Fluctuation Smoothing Through Battery Energy Storage System Using AVOA-SAGAN Approach’, Journal of Energy Storage, 101, p. 113610. Available at: https://doi.org/10.1016/j.est.2024.113610.
Maltezo, M.R.C. et al. (2021) ‘Arduino-Based Battery Monitoring System With State Of Charge And Remaining Useful Time Estimation’, International Journal of Advanced Technology and Engineering Exploration, 8(76), pp. 432–444. Available at: https://doi.org/10.19101/IJATEE.2021.874023.
Movassagh, K. et al. (2021) ‘A Critical Look at Coulomb Counting Approach for State of Charge Estimation in Batteries’, Energies, 14(14), p. 4074. Available at: https://doi.org/10.3390/en14144074.
Oloyede, M.O. et al. (2025) ‘Correction: Oloyede et al. A Review on State-of-Charge Estimation Methods, Energy Storage Technologies and State-of-the-Art Simulators: Recent Developments and Challenges’, World Electric Vehicle Journal, 16(8), p. 414. Available at: https://doi.org/10.3390/wevj16080414.
Qian, D. et al. (2019) ‘Research on Calculation Method of Internal Resistance of Lithium Battery Based on Capacity Increment Curve’, in 2019 2nd World Conference on Mechanical Engineering and Intelligent Manufacturing (WCMEIM). 2019 2nd World Conference on Mechanical Engineering and Intelligent Manufacturing (WCMEIM), Shanghai, China: IEEE, pp. 343–346. Available at: https://doi.org/10.1109/WCMEIM48965.2019.00074.
Rawal, A. et al. (2019) ‘A Critical Review On The Absorptive Glass Mat (AGM) Separators Synergistically Designed Via Fiber And Structural Parameters’, Journal of Power Sources, 430, pp. 175–192. Available at: https://doi.org/10.1016/j.jpowsour.2019.04.108.
Sharma, S. and Panigrahi, B.K. (2024) ‘Aging Responsive State of Charge Prediction of Lithium-Ion Battery Using Attention Mechanism Based Convolutional Neural Networks’, IEEE Transactions on Industry Applications, 60(5), pp. 7342–7355. Available at: https://doi.org/10.1109/TIA.2024.3405431.
Simanjuntak, I.U.V. et al. (2021) ‘Performance Analysis of VRLA Battery for DC Load at Telecommunication Base Station’, ELKHA : Jurnal Teknik Elektro, 13(2), pp. 148–154. Available at: https://doi.org/10.26418/elkha.v13i2.49202.
Skyllas-Kazacos, M. (2010) ‘10 - Electro-Chemical Energy Storage Technologies For Wind Energy Systems’, in J.K. Kaldellis (ed.) Stand-Alone and Hybrid Wind Energy Systems. Woodhead Publishing (Woodhead Publishing Series in Energy), pp. 323–365. Available at: https://doi.org/10.1533/9781845699628.2.323.
Soyoye, B.D. et al. (2025) ‘State of Charge and State of Health Estimation in Electric Vehicles: Challenges, Approaches and Future Directions’, Batteries, 11(1), p. 32. Available at: https://doi.org/10.3390/batteries11010032.
Triawan, M.A., Yolanda, D. and Humam, F. (2024) ‘Estimating SoC and SoH of Li-ion Battery Using Coulomb Counting Method in IoT Node Application’, in 2024 2nd International Symposium on Information Technology and Digital Innovation (ISITDI). 2024 2nd International Symposium on Information Technology and Digital Innovation (ISITDI), Bukittinggi, Indonesia: IEEE, pp. 96–101. Available at: https://doi.org/10.1109/ISITDI62380.2024.10795992.
Victoria, M. et al. (2021) ‘Solar Photovoltaics Is Ready To Power A Sustainable Future’, Joule, 5(5), pp. 1041–1056. Available at: https://doi.org/10.1016/j.joule.2021.03.005.
Xu, B. and Wen, G. (2021) ‘Experimental Study to Investigate the Effects of Temperature Rise during Discharge on Li-ion Battery Degradation’, IOP Conference Series: Earth and Environmental Science, 844(1), p. 012010. Available at: https://doi.org/10.1088/1755-1315/844/1/012010.
Yang, C. et al. (2020) ‘An Online SOC And Capacity Estimation Method For Aged Lithium-Ion Battery Pack Considering Cell Inconsistency’, Journal of Energy Storage, 29, p. 101250. Available at: https://doi.org/10.1016/j.est.2020.101250.
Zhao, X. et al. (2024) ‘Error Theory Study On EKF-Based SOC And Effective Error Estimation Strategy For Li-Ion Batteries’, Applied Energy, 353, p. 121992. Available at: https://doi.org/10.1016/j.apenergy.2023.121992.
Zine, B. et al. (2022) ‘Experimentally Validated Coulomb Counting Method for Battery State-of-Charge Estimation under Variable Current Profiles’, Energies, 15(21), p. 8172. Available at: https://doi.org/10.3390/en15218172.

Downloads
Published
Issue
Section
License
Copyright (c) 2025 Jurnal Asiimetrik: Jurnal Ilmiah Rekayasa & Inovasi

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.