Intelligent Modular Energy Hub: Advanced Optimization of Second-Life Lithium-Based Batteries for Sustainable Power Utilization

Year 2025, Volume: 13 Issue: 2, 219 - 229, 30.06.2025

Abdulkadir Gozuoglu

https://doi.org/10.17694/bajece.1641971

Abstract

The Intelligent Modular Energy Hub (IMEH) introduces a cost-effective and scalable energy storage solution by repurposing second-life lithium-based batteries, including Li-ion, LiPo, and LiFePO₄ cells, sourced from discarded consumer electronics, power tools, and electric vehicles. This study develops an STM32- and ESP32-based battery testing system, integrating an electronic dummy load and a custom battery management system (BMS) to accurately assess the state-of-charge and state-of-health (SoH) of various battery chemistries. A 7S and variable parallel battery pack configuration ensures adaptability to diverse residential and off-grid applications. The proposed system features real-time IoT monitoring, extending battery lifespan while optimizing charging cycles through grid, solar, or wind energy sources. Experimental results demonstrate that the Samsung 25R battery exhibited the highest SoH (92%) and energy efficiency (95%), making it the most viable for second-life applications. The Turnigy Graphene LiPo battery, while displaying the highest efficiency (97%), showed a slightly lower capacity retention (89%), indicating potential limitations for long-term storage. Voltage drop analysis confirmed that lower internal resistance leads to better performance, with the Turnigy Graphene battery maintaining the lowest voltage drop (160mV) under discharge conditions. Additionally, the IMEH system achieved an average energy efficiency of 94.75%, outperforming commercial BMS solutions, which averaged 92% efficiency. IoT-based predictive maintenance enhanced battery longevity, ensuring better cycle count retention and charge-discharge stability. This research contributes to affordable energy solutions, supports the circular economy, and enhances sustainable power utilization by integrating modular and intelligent energy management strategies into next-generation smart grids.

Keywords

Intelligent energy hub , modular energy storage , second-life lithium-based batteries , Li-ion , LiPo , LiFePO₄ , IoT-based battery management , electronic dummy load , energy optimization , sustainable power utilization , STM32 , ESP32 , smart grid

References

• [1] C. Liu, N. Gao, X. Cai, and R. Li, "Differentiation Power Control of Modules in Second-Life Battery Energy Storage System Based on Cascaded H-Bridge Converter," IEEE Transactions on Power Electronics, vol. 35, pp. 6609-6624, 2020.
• [2] S. Chai, N. Z. Xu, M. Niu, K. W. Chan, C. Y. Chung, H. Jiang, et al., "An Evaluation Framework for Second-Life EV/PHEV Battery Application in Power Systems," IEEE Access, vol. 9, pp. 152430-152441, 2021.
• [3] M. H. S. M. Haram, M. T. Sarker, G. Ramasamy, and E. E. Ngu, "Second Life EV Batteries: Technical Evaluation, Design Framework, and Case Analysis," IEEE Access, vol. 11, pp. 138799-138812, 2023.
• [4] A. Hassan, S. A. Khan, R. Li, W. Su, X. Zhou, M. Wang, et al., "Second-Life Batteries: A Review on Power Grid Applications, Degradation Mechanisms, and Power Electronics Interface Architectures," Batteries, vol. 9, p. 571, 2023.
• [5] X. Cui, A. Ramyar, P. Mohtat, V. Contreras, J. B. Siegel, A. G. Stefanopoulou, et al., "Lite-Sparse Hierarchical Partial Power Processing for Second-Use Battery Energy Storage Systems," IEEE Access, vol. 10, pp. 90761-90777, 2022.
• [6] J. Lin, J. Qiu, Y. Yang, and W. Lin, "Planning of Electric Vehicle Charging Stations Considering Fuzzy Selection of Second Life Batteries," IEEE Transactions on Power Systems, vol. 39, pp. 5062-5076, 2024.
• [7] H. Song, H. Chen, Y. Wang, and X.-E. Sun, "An Overview About Second-Life Battery Utilization for Energy Storage: Key Challenges and Solutions," Energies, vol. 17, p. 6163, 2024.
• [8] M. Terkes, A. Demirci, E. Gokalp, and U. Cali, "Battery Passport for Second-Life Batteries: Potential Applications and Challenges," IEEE Access, vol. 12, pp. 128424-128467, 2024.
• [9] A. Burgio, D. Cimmino, A. Nappo, L. Smarrazzo, and G. Donatiello, "An IoT-Based Solution for Monitoring and Controlling Battery Energy Storage Systems at Residential and Commercial Levels," Energies, vol. 16, p. 3140, 2023.
• [10] R. R. Irshad, S. Hussain, I. Hussain, I. Ahmad, A. Yousif, I. M. Alwayle, et al., "An Intelligent Buffalo-Based Secure Edge-Enabled Computing Platform for Heterogeneous IoT Network in Smart Cities," IEEE Access, vol. 11, pp. 69282-69294, 2023.
• [11] X. Cui, M. A. Khan, G. Pozzato, S. Singh, R. Sharma, and S. Onori, "Taking second-life batteries from exhausted to empowered using experiments, data analysis, and health estimation," Cell Reports Physical Science, vol. 5, 2024.
• [12] M. S. H. Lipu, M. S. Miah, T. Jamal, T. Rahman, S. Ansari, M. S. Rahman, et al., "Artificial Intelligence Approaches for Advanced Battery Management System in Electric Vehicle Applications: A Statistical Analysis towards Future Research Opportunities," Vehicles, vol. 6, pp. 22-70, 2024.
• [13] Z. Shi, "MambaLithium: Selective state space model for remaining-useful-life, state-of-health, and state-of-charge estimation of lithium-ion batteries," arXiv preprint arXiv:2403.05430, 2024.
• [14] M. Gharebaghi, O. Rezaei, C. Li, Z. Wang, and Y. Tang, "A Survey on Using Second-Life Batteries in Stationary Energy Storage Applications," Energies, vol. 18, p. 42, 2025.
• [15] Y. Jiang, Y. Ke, F. Yang, J. Ji, and W. Peng, "State of Health Estimation for Second-Life Lithium-Ion Batteries in Energy Storage System With Partial Charging-Discharging Workloads," IEEE Transactions on Industrial Electronics, vol. 71, pp. 13178-13188, 2024.
• [16] F. Basic, C. R. Laube, P. Stratznig, C. Steger, and R. Kofler, "Wireless BMS Architecture for Secure Readout in Vehicle and Second life Applications," in 2023 8th International Conference on Smart and Sustainable Technologies (SpliTech), 2023, pp. 1-6.
• [17] X. Gu, H. Bai, X. Cui, J. Zhu, W. Zhuang, Z. Li, et al., "Challenges and opportunities for second-life batteries: a review of key technologies and economy," arXiv preprint arXiv:2308.06786, 2023.
• [18] A. N. Patel, L. Lander, J. Ahuja, J. Bulman, J. K. H. Lum, J. O. D. Pople, et al., "Lithium-ion battery second life: pathways, challenges and outlook," Front Chem, vol. 12, p. 1358417, 2024.
• [19] H. Fu, Z. Liu, K. Cui, Q. Du, J. Wang, and D. Shi, "Physics-Informed Neural Network for Spacecraft Lithium-Ion Battery Modeling and Health Diagnosis," IEEE/ASME Transactions on Mechatronics, vol. 29, pp. 3546-3555, 2024.
• [20] X. Liu, Z. Hu, X. Wang, and M. Xie, "Capacity Degradation Assessment of Lithium-Ion Battery Considering Coupling Effects of Calendar and Cycling Aging," IEEE Transactions on Automation Science and Engineering, vol. 21, pp. 3052-3064, 2024.
• [21] R. Suganya, L. L. Joseph, and S. Kollem, "Understanding lithium-ion battery management systems in electric vehicles: Environmental and health impacts, comparative study, and future trends: A review," Results in Engineering, vol. 24, p. 103047, 2024.
• [22] X. Hu, X. Deng, F. Wang, Z. Deng, X. Lin, R. Teodorescu, et al., "A Review of Second-Life Lithium-Ion Batteries for Stationary Energy Storage Applications," Proceedings of the IEEE, vol. 110, pp. 735-753, 2022.
• [23] M. N. Akram and W. Abdul-Kader, "Repurposing Second-Life EV Batteries to Advance Sustainable Development: A Comprehensive Review," Batteries, vol. 10, p. 452, 2024.
• [24] J. John, G. Kudva, and N. S. Jayalakshmi, "Secondary Life of Electric Vehicle Batteries: Degradation, State of Health Estimation Using Incremental Capacity Analysis, Applications and Challenges," IEEE Access, vol. 12, pp. 63735-63753, 2024.
• [25] E. Michelini, P. Höschele, C. Ellersdorfer, and J. Moser, "Impact of Prolonged Electrochemical Cycling on Health Indicators of Aged Lithium-Ion Batteries for a Second-Life Use," IEEE Access, vol. 12, pp. 193707-193716, 2024.