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基于Simulink运动仿真与改进自适应遗传算法的曲轴优化设计.docx

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基于Simulink运动仿真与改进自适应遗传算法的曲轴优化设计 Introduction: Intheautomotiveindustry,optimizingenginedesignisofutmostimportanceasitenablestheproductionofhigh-performanceengineswithbetterfuelefficiencyandreducedemissions.Oneofthevitalcomponentsoftheengineisthecrankshaft,whichconvertsthelinearmotionofthepistonintorotationalmotiontodrivethewheels.Awell-designedcrankshafthasanimportantinfluenceontheengineperformanceanddurability.Inthispaper,weproposeacombinationofSimulink-basedmotionsimulationandanimprovedadaptivegeneticalgorithmforoptimizingthecrankshaftdesign. Simulink-basedMotionSimulation: Simulinkisapowerfultoolusedformodeling,simulating,andanalyzingdynamicsystems.Ithasbeenwidelyusedintheautomotiveindustrytosimulatethemotionofenginesandtheircomponents.Inthisstudy,Simulinkwasusedtosimulatethemotionofthecrankshaftandanalyzeitsperformance. ThefirststepwastocreateaSimulinkmodelofthecrankshaft.Themodelwascomposedofthefollowingcomponents:theengineblock,theconnectingrod,thepiston,andthecrankshaft.Thesimulationsoftwarewasusedtosimulatethemotionofthepistonandconnectingrod,andhencethemotionofthecrankshaft. Thesimulationmodelwasevaluatedforvariousdesignparametersofthecrankshaft,suchascrankradius,throw,andphaseangle.Themotionsimulationwasevaluatedforvariousperformanceparameterssuchascrankshafttorque,angularacceleration,andvelocity. ImprovedAdaptiveGeneticAlgorithm: Thegeneticalgorithmisaheuristicoptimizationmethodbasedontheprincipleofnaturalselectionandgeneticinheritance.However,ithassomelimitationsliketrappingatalocalminimumandslowconvergence. So,weproposedanimprovedadaptivegeneticalgorithmthatovercomestheselimitations.Theadaptivealgorithmintroducesamutationoperatorthatusesanon-uniformdistributionprobabilitytoenhancetheexplorationcapabilityofthealgorithm.Also,acrossoveroperatorwasintroducedbasedontheparentselectiontoensurethequalityoftheoffspring.Theadaptivealgorithmusesanadaptivemutationratecontrolledbythefitnessofthepopulation. CrankshaftOptimization: Theoptimizeddesignofthecrankshaftwasa