STATE OF HEALTH (SOH) ESTIMATION FOR EMBEDDED BATTERY MANAGEMENT SYSTEMS: A COMPARATIVE ANALYSIS OF COMPUTATIONALLY EFFICIENT METHODS

• Datum: 2026
• Hauptverfasser: Sorochynskyi , Ya., Bosak , Al., Dubovyk , V., Kulakovskyi , L., Bosak , An.
• Format: Artikel
• Sprache: Englisch
• Veröffentlicht: Institute of Renewable Energy National Academy of Sciences of Ukraine 2026
• Schlagworte: Keywords: State of Health; SOH; battery management system; BMS; Battery Energy Storage Systems (BESS); renewable energy; distributed generation; microgrids; lithium-ion batteries; machine learning; embedded systems; Support Vector Regression; Random Forest; computational efficiency.
• Online Zugang: https://ve.org.ua/index.php/journal/article/view/599
• Назва журналу: Vidnovluvana energetika

Accurate State of Health (SOH) estimation is critically important for the safe and long-term operation of lithium-ion batteries. However, the implementation of estimation algorithms in embedded Battery Management Systems (BMS) is significantly limited by available computational resources. This paper...