Real-time battery SoC estimation using machine learning with raspberry Pi and OPAL-RT validation

Key Points

• Battery state of charge estimation achieved using machine learning algorithms, improving accuracy.
• The approach utilizes raspberry pi and opal-rt for real-time validation of the model.
• Real-time data processing allows for effective monitoring of battery performance issues.
• The findings highlight the potential for advanced battery management solutions in various applications.