Abstract：Tire is an important part of the vehicle. The behaviour of the tire is of basic importance to the vehicle dynamics, and plays a vital role in vehicle's performance, so the precision of a tire model affects the simulation reliability of the whole vehicle model. Partical swarm optimization algorithm is used to identify the tire model parameters in this paper. According to the organic evolution in nature, the multi-population with a variation threshold partical swarm optimization algorithm is proposed to keep the population diversity and improve the reliability of holistic convergence. The variation threshold is to avoid the problem of converging to a part-optimum. Comparing the simulation results with the test results, it is shown that the simulation data from the multi-population with a variation threshold partical swarm optimization algorithm would fit the test data better than those from other optimization algorithms, the identification accuracy is slightly higher. The multi-population with variation threshold optimization algorithm has a good application prospect in tire parameter identification.