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

An adaptive agent and battery module technology, applied in special data processing applications, computing, electrical digital data processing, etc., can solve problems such as high optimization cost, large number of adaptive points, complex process, etc., to reduce the total number and shorten the design The effect of cycle, broad application prospects

Active Publication Date: 2019-08-09
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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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

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

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[0043] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0044] Such as figure 1 As shown in FIG. 1 , it is a schematic flow chart of an application method of a compound-based adaptive proxy model in battery pack optimization design of the present invention. An application of a compound-based self-adaptive proxy model optimization method in the optimal design of battery packs, comprising the following steps:

[0045] A. Establish the geometric optimization model of the air-cooled battery module;

[0046] B. Perform CFD simulation on the geometric optimization model of the air-cooled battery module;

[0047] C. Use the experimental design technology to...

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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 ...

Claims

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Application Information

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IPC IPC(8): G06F17/50
CPCG06F30/20
Inventor 许焕卫刘椋文张淼
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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