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Abstract This paper presents the design, modeling, and validation of an experimental LiFePO4 battery cycling system applied to stand-alone and on-grid photovoltaic (PV) scenarios. A comprehensive analysis of battery behaviour -including key parameters such as SOC, SOH, DOD, and internal resistance- is conducted to highlight the advantages of LiFePO4 chemistry in terms of safety, thermal stability, and cycle life. The charge/discharge dynamics are governed by the CCCV protocol, with detailed insights into voltage plateau behaviour, degradation mechanisms, and second-life reuse potential. The proposed experimental platform integrates a programmable power supply, active load, and full monitoring system to simulate real irradiance and consumption profiles with high temporal resolution. Results from the test-bench validate the accurate tracking of SOC, power flow optimization, and effective battery cycling under fluctuating PV conditions. Colour-map diagrams and hourly data analyses demonstrate the system’s capacity to balance generation, storage, and consumption, ensuring reliability and autonomy. The setup also enables the modeling of thermal and electrical behaviour at minute-level resolution, offering a valuable tool for the simulation and development of distributed PV-battery storage systems. The energy balance analysis, based on minutely power data, confirms the model’s accuracy in simulating real-world PV-battery interactions. Key words: Battery Cycling System, LiFePO4 Battery, Battery charge/discharge, SOC/SOH estimation, BMS, stand-alone/on-grid Photovoltaic Power System.
References [1] Dufo-López, R.; Lujano-Rojas, J.M.; Artal-Sevil, J.S.; Bernal-Agustín, J.L. "Optimising Grid-Connected PV-Battery Systems for Energy Arbitrage and Frequency Containment Reserve". Batteries, MDPI Journals. Open Access. 2024, Vol. 10, issue: 12; pp.: 1–29. [2] J.S. Artal-Sevil, V. Ballestín-Bernad, J.M. Lujano-Rojas, R. Dufo-López, J.L. Bernal-Agustín. "Modeling of a stand-alone solar photovoltaic water pumping system for irrigation". Renewable Energy and Power Quality Journal (RE&PQJ). July 2023, Vol. 21; pp.: 662–667. [3] Huang, S.-C., Tseng, K.-H., Liang, J.-W., Chang, C.-L., & Pecht, M. G. (2017). "An Online SOC and SOH Estimation Model for Lithium-Ion Batteries". Energies, MDPI Open Access. 2017, vol. 10(4), 512. Pp: 1-18.
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