A state of health estimation method for full lifetime of lithium-ion batteries

Abstract:

To solve the problem that the state of health(SOH) of lithium-ion batteries is difficult to be estimated accurately under dynamic working conditions and full life cycle, a method based on fixed charging voltage segment was proposed. Firstly, the charging capacity in a fixed voltage segment during the charging process was treated as the equivalent health factor of battery capacity estimation. Secondly, the optimal charging voltage segment was selected by using genetic algorithm. Finally, eight verification numerical examples based on the aging experiment data of two types of lithium battery were designed, which were different in discharging current and SOH interval. Experimental results show that the value of MAE and RMSE that comes from the estimated SOH of training set batteries and testing set batteries in eight numerical examples were less than 1.55%. The proposed method can accurately estimate the SOH of lithium batteries under full lifetime(SOH between 100% and 60%) for different discharging rates and materials, which means this method is good applicable in practice.