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

• Date: 2026
• Main Authors: Sorochynskyi , Ya., Bosak , Al., Dubovyk , V., Kulakovskyi , L., Bosak , An.
• Format: Article
• Language: English
• Published: Institute of Renewable Energy National Academy of Sciences of Ukraine 2026
• Subjects: 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 Access: https://ve.org.ua/index.php/journal/article/view/599
• Journal Title: 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...