Comparative Study of Classifier Performance with Heap Sort Optimization in Battery Health Management Systems

The battery health monitoring system is a crucial component in modern energy storage systems. The study examines the performance of different machine learning classifiers for battery health monitoring systems. Support vector machine, K nearest neighbor, Random Forest, and Extreme Boost Gradient algorithms are considered for the analysis. The work introduces the incorporation of the heap sort algorithm to the models considered. The different algorithms without and with heap sort algorithm is trained and tested. The performance is evaluated based on receiver operating characteristics and confusion matrix. Observations show that random forest and extreme boost classifiers exhibit superior performance in evaluating battery health. The results emphasize the less significant contribution of heap sort algorithm in accurate model performance.