Battery aging-aware energy management strategy with dual-state feedback for improving life cycle economy by using multi-neural networks learning algorithm

•The offline optimal control results considering battery life are obtained by an improved Pontryagin's minimum principle.•The determination coefficient is introduced to determine the train data for neural network learning.•Dual-state feedback control is applied to the energy management strategy.•The adaptability and effectiveness of the proposed strategy are assessed by random driving cycles.