Application method of self-adaptive agent model in battery module optimization design based on complex form

Abstract

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.

Description

technical field [0001] The invention belongs to the technical field of engineering optimization design, and in particular relates to an application method of a complex shape-based self-adaptive agent model in battery module optimization design. Background technique [0002] Black-box problems and optimization problems with complex performance functions in the engineering field are usually difficult to optimize directly. Surrogate-Based Optimization (SBO) has been used to solve implicit functions and complex and time-consuming expensive model optimization problems, such as aerospace systems involving aerodynamics, structural optimization, turbine blades, etc. Proven to be a proven method. The surrogate model was proposed by Kleijnen in 1975. Sacks et al. realized the stochastic process of deterministic output based on computer experiments, so that it is more convenient to predict. This work is considered to be the beginning of approximate optimization research. After years ...

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Problems solved by technology

[0007] The purpose of the present invention is: in order to solve the problem that the traditional proxy model-based optimization method has a complicated process, a large number of adaptive points, and a high optimization cost, the present invention proposes a compound-based self-adaptive proxy model in the battery module Applied methods in optimal design

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