Evidence-based Reliability Design Optimization And Its Application In Automobile Lightweight

Uncertainties are everywhere in practical engineering problems.Uncertainties such as external loads,material properties,structural dimensions,boundary conditions,etc.,although small in value,may cause engineering products to deviate significantly from expected objectives or even cause product failure under coupling,so at the design stage,Accurately measuring uncertainty and controlling it within the expected range is the key to ensuring product quality and reliability.Uncertainty can be considered as the difference caused by the sufficient degree of information mastery.Based on this viewpoint,the uncertainty is divided into random uncertainty and cognitive uncertainty.Probabilistic methods are often used to deal with stochastic uncertainty,while nonprobability methods are used to deal with cognitive uncertainty.The modeling theories include convex model theory,interval theory and evidence theory.Because the framework of evidence theory is more flexible and has obvious advantages in describing and dealing with cognitive uncertainty,Evidence-based Reliability Design Optimization(EBDO)has attracted much attention and emerged.A series of important results.At present,EBDO is still in its infancy,and there are still a series of theoretical and technical problems to be solved in terms of computational efficiency,mathematical modeling of complex problems,and engineering applications.In response to the above issues,this paper carries out and completes the following work:(1)An EBDO solving method based on approximate motion vector is studied.Under the premise of no additional information,firstly construct the probability variable corresponding to the evidence variable by the equal area method,then use SORA method to solve the design point of RBDO based on probability theory,and analyze the reliability of the design point,and then pass the probability variable.Calculate the reliability of the design point,use the gradient of reliability as the approximate gradient of the credibility of the evidence theory,as the moving direction of the constraint in the next iteration step,continue to solve until convergence,and finally use a numerical example and an engineering example The computational efficiency of the method was verified.(2)Evidence-based reliability design optimization for vehicle lightweighting.In the vehicle lightweight design problem based on vehicle crashworthiness,considering the imperfect information in the design stage,using the evidence theory to process the design variables into evidence variables,and establishing the EBDO model,and then the key to the frontal collision of vehicles such as anti-collision beams The design is optimized and verified by simulation to provide a basis for the design of the front structural parameters of the car.