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基于群体与适应度的概念，应用改进的PSO算法，从随机解出发，提出了基于PSO 算法的本构模型参数识别方法. 该方法解决了橡胶类材料大应变时硬化现象的本构模型参数 的确定这一难题. 首先通过单轴拉伸本构模型实验，在针对硬化实验曲线存在拐点的情 况下，应用PSO算法进行拟合，最后利用简单剪切实验进行验证. 结果表明该方法科学可行， 且具有速度快、精度高、易于收敛等优点. 并且有效地解决了本构模型参数识别的困难，可 广泛应用于各种复杂材料.

PARAMETER IDENTIFICATION FOR CONSTITUTIVE MODEL BASED ON PARTICLE SWARM OPTIMIZATION ALGORITHM

On basis of concepts of population and adaptive degree,a new method is proposed to identify parameters in the constitutive model used to improve Particle Swarm Optimization Algorithm starting from a stochastic solution.This method can solve difficult problems of identifying parameters in a constitutive model for hardening rubber-like materials with large strain.Firstly,by a constitutive model test of uniaxial tension, a point of inflexion in the experimental curve is obtained,the PSO is used to identify the parameter,and then the result is testified by a simple shearing test.The result shows that the PSO method enjoys efficiency,high precision and quick convergence,in identifying constitutive parameters and it can be widely used for various complex materials.