Research On Multi-objective Performance Optimization Of Linear Induction Motors Based On Genetic Algorithm

With the development of urban rail transit,medium-low-speed maglev trains have received extensive attention.It is driven by a single-sided linear induction motor and uses electromagnets to suspend the train to achieve no contact between the wheelset and the rail.It has the advantages of simple structure,low noise,low friction loss,strong climbing ability,and easy maintenance.These advantages make the operation of the linear induction motor not only beneficial to energy conservation and environmental protection,but also meet people’s requirements for speed.Therefore,linear induction motors have good development prospects in medium-low-speed maglev trains systems.In actual operation,it was found that the linear induction motor as the core of the low-and medium-speed maglev train drive system,the large air gap and the end effect caused by the iron core interruption weaken the motor thrust and reduce the motor efficiency and power factor.In order to achieve the purpose of improving the performance of the motor,this paper optimizes the motor designs by studying the effect of the linear induction design parameters on the motor performances.Firstly,in this paper the working principle and end effect of linear induction motor is explained.A T-type equivalent circuit model considering the end effect and the half-filled slot effect of linear induction motors is established.Derivation of electromagnetic thrust,efficiency,and power factor mathematical expressions based on equivalent circuit model.Using the theory of multilayer traveling wave electromagnetic field to analyze the normal force of linear induction motor.And the effects of motor design parameters on electromagnetic thrust,normal force,efficiency,power factor are studied.Secondly,this paper uses genetic algorithm to automatically optimize the motor parameters.The genetic algorithm is tested to verify its suitability for multi-variable and multi-objective optimization problems.Selecting design parameters such as slot width,tooth width,primary core height,secondary guide plate thickness,and slip frequency that have a large effect on motor performance as optimization variables,and building an optimization objective function to obtain multi-objective optimization model.Finally,according to the actual needs and constraints,a series of optimization design results are obtained to achieve the purpose of improving the motor performance.Comparison and analysis of the difference in optimization results when different optimization goals are selected.The finite element software is used to simulate and analyze the linear induction motor before and after optimization to verify the correctness and effectiveness of the optimization results.