Research On Optimization Design Method And Application Of Crash Safety For An Electric Vehicle

Electric vehicle has become an important development direction of automobile industry,and many road accidents caused by it bring more and more stringent requirements for its safety performance.Body structure as an important factor affecting vehicle crash safety,its crashworthiness is directly related to the injury degree of occupants,so the optimization design of it is of great significance.However,the traditional optimization design mainly focused on deterministic optimization,in which all design inputs are assumed to be invariant and does not take into account the influence of the uncertainty of the design variables.When a large number of uncertainties in engineering practice cause the design variables to fluctuate,the design scheme of deterministic optimization cannot be guaranteed,so the uncertainty optimization design is needed.Based on the above reasons,this paper adopts deterministic optimization and uncertainty optimization(including reliability optimization and robust optimization)to optimize the crash safety of an electric vehicle.Firstly,the research status of the body structure crashworthiness is analyzed.Then the simulation model of 40% offset deformable barrier crash of an electric vehicle is established.After that,the model is verified by physical test,corresponding results show that the simulation results are in good agreement with the test results,thus the model can be used instead of the physical test for subsequent optimization process.Based on the established model,the deterministic optimization of structural crashworthiness is carried out in this paper.In order to improve the prediction accuracy of the approximation model,the least squares support vector regression(LSSVR)model is employed to fit the relations between design variables and the output response.Meanwhile,the particle swarm optimization(PSO)algorithm is used to optimize the parameters of the LSSVR model.Then,this paper using non-dominated sorting genetic algorithm II(NSGA-II)to implement optimization process.The optimization results show that,compared with the initial design,the mass of the key components is reduced by 10.44% and energy absorption is increased by 3.84%,while the peak deceleration of the body and firewall intrusion also meet the design requirements.Based on the deterministic optimization,this paper further discusses the influence of the uncertainty of the design variables on the optimization results.In order to improve the reliability and robustness of the system,the method of reliability optimization and robust optimization is adopted to implement the uncertainty optimization design of the body.By comparing different reliability / robustness requirements and different types of robust optimization models,the most suitable design scheme is chosen for engineering application and it is verified by finite element simulation.The results show that,although the uncertainty optimization decreases slightly on the optimization objectives compared with deterministic optimization,but the optimized body performance still meets the needs of engineering exploitation,and the reliability and robustness of the system are effectively guaranteed.