The invention discloses a self-adaptive agent model optimization method based on a complex form and an application of the self-adaptive agent model optimization method in battery module optimization design. Due to the fact that a traditional optimization method is high in cost, long in period and complex in operation when solving a black box problem or an engineering problem with a complex performance function, the self-adaptive agent model optimization method based on the complex form is provided and applied to optimization design of a battery module. The method comprises the following steps:firstly, constructing an ANSYS geometric optimization model of the air cooling battery module; secondly, performing CFD calculation according to the ANSYS geometric optimization model; then, establishing an agent model by utilizing a test design method and an approximation technology, and finally, optimizing the air cooling battery module by the self-adaptive agent model optimization method basedon the complex form. The complex form method is applied to sequence point-adding iteration of the agent model. Compared with a traditional sequence point-adding optimization method, the method has the advantages of being few in added samples, high in convergence speed, high in local precision, high in optimization efficiency and the like, and the wide application prospect is achieved.