This paper aims to propose an improved parameter identification method for the inverse play model to reduce the error in hysteresis simulation.
This paper proposes an improved parameter identification method for the inverse play model, which selects a portion of the data from numerically generated first-order reversal curves to identify the shape function, thereby avoiding simulation errors caused by repeated hysteresis operators. The proposed method is then combined with an optimization algorithm to derive the optimal parameter solution for the model, enabling hysteresis simulation.
By using the proposed method to identify the parameters of the inverse play model and simulate hysteresis loops, it is demonstrated that the global error in hysteresis loss calculation is controlled within approximately 5%. This indicates a significant improvement in the accuracy of hysteresis simulation and also addresses the issue of non-smooth hysteresis loops.
The proposed method significantly improved the accuracy of hysteresis simulation with the inverse play model after parameter identification. Meanwhile, due to the reduced amount of data used for identifying the shape function, the efficiency of obtaining the optimal solution was increased, thereby shortening the computation time.
