Remaining Useful Life Prediction of Aviation Lithium-ion Battery Based on SVR-MC

Aiming at the problem that the accuracy of the remaining useful life (RUL) of aviation lithium-ion batteries is not high, this paper proposes a method for predicting the remaining useful life of aviation lithium-ion batteries based on the combination of Support Vector Regression (SVR) and Markov Chain (MC). First, use NASA lithium-ion battery aging data set, design and use SVR network model to predict the RUL of aviation lithium-ion battery. Second, use MC to correct the prediction results of the SVR network model. Finally, the proposed life prediction method based on SVR-MC is tested and verified. The results show that the life prediction method of aviation lithium-ion battery proposed in this paper can achieve the prediction performance of the remaining useful life of aviation lithium-ion battery, has good prediction accuracy, and has good application prospects.