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What is SVM-Based Battery SOC Estimation about?

This study presents a method for estimating the state-of-charge (SOC) of high capacity lithium iron phosphate (LiFePO4) batteries using support vector machine (SVM) techniques. The SVM model is trained on experimental data from a battery testing platform, demonstrating its effectiveness in predicting SOC based on measurable parameters like voltage, current, and temperature. The results indicate that the SVM approach offers a more accurate and robust alternative to traditional SOC estimation methods.

Author

kowsalya

Language

EN