For the instability of the extreme learning machine in predicting the remaining useful life of lithiumion batteries, this paper proposes a hybrid particle swarm optimization algorithm to optimize the prediction model of extreme learning machines.The optimized particle swarm optimization algorithm is used to optimize the input of the extreme learning machine, which not only can significantly improve the prediction accuracy of the model, but also greatly increase the credibility of the single prediction result of the remaining useful life lithiumion battery.In this paper, the lithiumion battery data published by NASA PcoE is used to carry out simulation experiments and evaluate the prediction performance of the model, and compare it with the prediction results of standard extreme learning machine prediction model.The statistical results show that the prediction error is controlled by about 2%.