The parameter identification method for the equivalent circuit model of lithium-ion battery has a great impact on the model accuracy.To solve the problems of low convergence accuracy and slow convergence speed in a satin bowerbird optimization(SBO)algorithm,an improved satin bowerbird optimization(ISBO)algorithm is proposed.The inertial weights,Cauchy mutation,Gaussian mutation and greedy selection strategies are used to improve the convergence accuracy of the ISBO algorithm,and its convergence performance is verified by standard test functions.Based on the battery charging and discharging data,the proposed ISBO algorithm is applied to the parameter identification of the equivalent circuit model of lithium-ion battery.Experimental results show that compared with the SBO and adaptive weight particle swarm optimization algorithms,the ISBO algorithm has a higher accuracy when it is used in identifying the model parameters and the identification accuracy is not affected by the working conditions of battery.
维普
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