As the number of charge and discharge cycles of a lithium-ion battery increases,its state-of-health(SOH)will degrade to some degree accordingly.Aimed at this problem,a method for estimating the SOH of lithium-ion battery based on an improved multi-objective Cuckoo search(IMOCS)-BP neural network is designed,which adaptively changes the update probability and search step size of the Cuckoo search(CS)algorithm while avoiding the algorithm from falling into the local optimum,thereby solving the problems of slow convergence speed and low solution accuracy in the CS algorithm.The IMOCS algorithm is combined with BP neural network to conduct a global search in the node space,reduce the influence of initial values of weight and threshold on BP neural network,and realize the parameter optimiza-tion.Through Matlab simulations,it is verified that the SOH estimation algorithm based on IMOCS-BP neural network has a low error and a strong performance,thus realizing an accurate SOH prediction of lithium-ion battery.
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