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The battery capacity is the key characteristic which determines the performance of battery. The estimation of zinc silver battery state of charge is the key research point. Using battery discharge time of whole discharge process, the discharge current and battery voltage as radial basis function (RBF) neural network input parameters, battery status of charge as the output parameter, this paper establishes RBF neural network model of battery discharge. In order to overcome the shortcoming of the RBF neural network with low convergence accuracy and easy to fall into local minimum, the hybrid algorithm, which is based on differential evolution algorithm and particle swarm optimization, optimizes the RBF neural network. After Simulating with MATLAB, results display that, RBF neural network optimized by hybrid optimization algorithm possesses higher estimation accuracy and less estimation error compared with RBF neural network optimized by particle swarm optimization algorithm.