In order to conduct an in-depth analysis of the electromagnetic force generated during the operation of high-speed and low-vacuum maglev trains and realize the optimization of the electromagnetic force on this basis, taking linear induction motor as the research object, a method combining parametric processing and evolutionary algorithms (EA) multi-objective optimization was proposed to optimize the electromagnetic force. Firstly, the finite element model of transient field was established based on the structure of linear induction motor used in maglev train. Then the characteristic curve of electromagnetic force was analyzed. The relationship between the secondary thickness and the electromagnetic force was predicted by parameterizing the secondary thickness. The optimal electromagnetic thrust and normal force were obtained by using EA multi-objective optimization method which took the velocity, the thickness of the secondary aluminum plate and the thickness of the secondary steel plate as variables and the electromagnetic thrust and normal force as targets. The results show that with the increase of secondary thickness, the value of electromagnetic thrust decreases, the normal force changes from positive to negative and the absolute value decreases, and the normal force changes from attractive to repulsive. When the speed is 0.001 m/s, the thickness of the secondary aluminum plate is 2.895 mm, and the thickness of the secondary steel plate is 5.789 mm, the electromagnetic thrust and normal force at steady state are increased by 3.62 N and 2.503 N, respectively, compared with before optimization. The optimization effect is remarkable. The method combining parametric processing and EA multi-objective optimization can effectively optimize the electromagnetic force, which is suitable for the multi-objective optimization design of linear induction motor. It provides an important basis for the improvement of the structure and performance of linear induction motor design.
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