Battery parameters identification is crucial for accurate prediction of battery life in electric vehicles. In order to optimize battery parameter identification, an improved PSO (particle swarm optimization) algorithm was proposed based on the use of Thevenin battery model to abstract the problem into an optimization problem. The experimental results show that the computational accuracy of the improved PSO algorithm is higher than that of the genetic algorithm and the original PSO algorithm, and the battery parameters calculated by the improved PSO algorithm are also more accurate.