Remaining Useful Life Estimation of Lithium-Ion Batteries Based on Optimal Time Series Health Indicator

Abstract

The evaluation of lithium battery performance is a complex and very important issue. Generally, manufacturers perform battery burn-in tests and evaluate the performance of lithium batteries based on capacity, internal resistance, voltage, and other parameters in the cycle. However, due to the complexity of practical applications and the difficulty of parameter measurement, it is necessary to evaluate the status of health (SOH) of lithium-ion batteries from the side. Analysis of battery charge and discharge data found that using the charge and discharge time to evaluate the health of the battery is effective and feasible, especially the time during the discharge/charge platform period, and the parameter measurement is more convenient. In this paper, three time-health indicators are constructed and analyzed in detail, and then the health of the battery is evaluated using a simple Bayesian Monte Carlo theory. The experimental results of four batteries show that the scheme is simple and convenient, and can effectively evaluate the SOH of lithium-ion batteries.

Keywords

• Optimal health indicator
• lithium-ion battery
• correlation analysis
• time difference
• Bayesian Monte Carlo
• state of health