An electromagnetic mechanism static characteristic optimization method

Abstract

The invention relates to an electromagnetic mechanism static characteristic optimization method based on an adaptive weight multi-objective differential evolution algorithm, which comprises the following steps: S1, determining parameters to be optimized and static characteristic related indexes of an electromagnetic system; S2, determining the upper limit and the lower limit of each static characteristic optimization parameter according to the product material and the processing technology of the electromagnetic mechanism, and simultaneously determining an additional constraint index related to the static characteristic optimization parameter; S3, obtaining an initial population; S4: obtaining the Pareto solution set distribution of the optimization objective function; S5, selecting different mutation strategies and crossing strategies according to the number of iteration times of the current optimization parameter population and the Pareto dominance relationship of each optimization parameter, generating a progeny population, repeating the operation of step 4 to the whole population, and adopting a selection strategy considering the niche sorting result to control the population size; S6, obtaining the Pareto solution set distribution of the optimization objective function; S7, selecting a group of optimization parameters from the obtained groups of optimization parameters, and taking the group of optimization parameters as the optimization design parameters of the electromagnetic mechanism.

Description

technical field [0001] The invention relates to the technical field of static characteristic optimization of an electromagnetic mechanism, in particular to a static characteristic optimization method of an electromagnetic mechanism based on an adaptive weight multi-objective differential evolution algorithm. Background technique [0002] With the development of computer technology, the method of converting practical engineering problems into mathematical problems for solving is more and more widely used, which greatly shortens the development cycle and improves the development efficiency. The optimization of the static characteristics of the relay electromagnetic mechanism often requires the optimization of multiple parameters. Due to the limitations of the product material and processing technology of the electromagnetic mechanism, there are upper and lower limits for each parameter and there are corresponding constraint indicators between them. At the same time, the optimiz...

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Problems solved by technology

However, for multi-objective problems, there are conflicting and mutually constrained relationships among the various objective functions, so the traditional differential evolution algorithm cannot directly deal with multi-objective optimization problems.

In order to enable the existing differential evolution algorithm to be used in multi-objective optimization problems, most scholars at home and abroad adjust the selection operation and propose various selection operators with different strategies, but they often cannot take into account the convergence speed and convergence

[0004] At present, there are many research results on the optimization of the relay electromagnetic mechanism, but the use of multi-objective differential evolution algorithm to optimize the relay electromagnetic mechanism and improve the static characteristics of the relay has not been reported. Most of the literature is used to solve the static characteristics of the electromagnetic mechanism. The multi-objective optimization algorithm still has problems such as slow convergence speed, poor convergence accuracy, and uneven optimal solution set.

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