Abstract：Aiming at the problem that it is difficult to directly measure the capacity of the lithium-ion battery when the remaining useful life(RUL)of the battery is predicted and the prediction result is inaccurate, an indirect prediction method was proposed. First, after fully analyzing the parameters of battery life sates, the equivalent voltage drop discharge time was chosen as the indirect health index of the battery. Secondly, genetic algorithm was introduced to optimize the extreme learning machine parameters to establish an indirect RUL prediction model for lithium-ion battery. Finally, the correctness of the GA-ELM method was verified based on NASA data and independent experimental data. The results showed, compared with the ELM method and Gaussian process regression method, this new method is accurate and effective, with high predicting speed, and its output is stable.
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2020, Vol. 41 
