Multi-objective optimization of motor shaft based on response-surface method and particle-swarm algorithm
In this article,a multi-objective optimization method based on the response-surface method and the particle-swarm algorithm is proposed for the lightweight design of the new-energy vehicle's motor shaft.With the motor shaft's inner diameter as the design variable and the strength constraints taken into account,the multi-objective optimization model is set up by taking the motor shaft's mass,the equivalent stress at multiple dangerous sections and the first-order critical speed as the design objectives.The Box-Behnken test is conducted to obtain the finite-element analytical scheme of 4 factors and 3 levels,and the least-square method is used to fit the high-precision response-surface equation of each sub-objective.Besides,according to the importance of each sub-objective,the influence factor is introduced,and the unified global optimization objective function is worked out.Final-ly,the global optimization objective function is optimized by means of the particle-swarm optimization algorithm with the linear-de-creasing inertia weight.The optimization results show that the motor shaft's mass decreases by 4.8％,the first-order critical speed increases by 8％,and the equivalent stress at two dangerous sections decreases by 2.9％and 2.5％respectively.
motor shaftmulti-objective optimizationresponse-surface methodparticle-swarm algorithm
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