Engineering Application of Pareto Sorting Genetic Algorithm in Parameter Design of Battery Case of Pure Electric Car
To solve the problems of massive and stress concentration of ternary lithium battery case.The parameters after the variable density topology optimization were sampled using the Latin hypercube method,and the Pareto ranking multi-objective genetic algorithm was utilized to select stresses,etc.as the objective function for iterative calculation.The paper used Kriging space interpolation to obtain each response profile and a preliminary predicted optimization scheme.Based on the above results,a 62-group response surface mathematical model was established using Design-Expert,and the calculated Pareto optimum was 70%,with the p-value≤0.000 1.This proves the accuracy of the response surface model,and the performance of the optimized structure after simulation has been improved in all aspects compared to the original model,with better reliability.
pure electric vehiclemulti-objective genetic algorithmresponse surface optimization
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