Abstract: Accurate and efficient identification of the magnetostriction model parameters of electrical steel sheet is the premise of the model's application in the vibration analysis of the transformer core. Aiming at the problem that the existing parameters identification method based on the single-objective optimization algorithm cannot take into account the accuracy and speed, in this paper, based on the magnetostriction model of combining the improved Jiles-Atherton-Sablik and Energetic models, the parameters identification of the model is transformed into a multi-objective optimization problem. Taking the root mean square error of hysteresis loop and magnetostriction curve as two optimization objectives, a multi-objective optimization mathematical model for parameters identification is established. Based on this model, the multi-objective differential evolution algorithm is improved from three aspects: control parameters adaptation technology, mutation operator improvement strategy and selection operator improvement strategy; thus a parameters identification method of magnetostriction model by using the improved multi-objective differential evolution algorithm is proposed. Compared with the existing method, the solution accuracy of hysteresis loop of the proposed method is improved by 17.84%, the solution accuracy of magnetostriction curve is improved by 13.60%, and the identification speed is improved by 41.57%.