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Crashworthiness Analysis And Multi-objective Optimization Design Of A Novel Negative Poisson’s Ratio Battery Protection System

Posted on:2021-06-02Degree:MasterType:Thesis
Country:ChinaCandidate:K J ShenFull Text:PDF
GTID:2492306479462294Subject:Master of Engineering
Abstract/Summary:PDF Full Text Request
For the crashworthiness safety of electric vehicles,it is not only necessary to meet the collision safety standards of traditional fuel-powered vehicles,but also necessary to consider that the battery modules of electric vehicles are prone to fire and even explosion due to their high density energy and large volume.The negative Poisson’s ratio structure has good energy absorption capacity and impact resistance,which can be applied to the battery protection suspension of electric vehicles to enhance the protection performance of battery modules,so as to improve the collision safety of electric vehicles.Its lightweight quality is in line with the lightweight design of electric vehicles.Firstly,the finite element model of the traditional battery system is established.Firstly,the geometric model of the battery system is built in CATIA software,and then the finite element model is built by importing it into the pretreatment software for geometric cleaning and meshing.To improve the protection performance of the battery protection system in the case of electric vehicle collision,the negative Poisson’s ratio structure finite element model is firstly established,and a new negative Poisson’s ratio battery protection system is proposed by combining the traditional protection structure of battery with the double-arrow negative Poisson’s ratio structure.According to the relevant requirements of FMVSS208 regulation,the feasibility of the model was verified.Secondly,by comparing the acceleration curve,energy absorption curve and collision force curve of the traditional battery protection structure with the novel negative Poisson’s ratio battery protection system,the crashworthiness of the electric vehicles was analyzed.The result shows that the negative Poisson’s ratio battery protection system can protect the battery modules of electric vehicles better.Considering the negative Poisson’s ratio inner core increase the total mass of the battery protection system,so this article choose the long cell wall thickness,the short cell wall thickness and the negative Poisson’s ratio filling materials of the double-arrow negative Poisson’s ratio witch have a significant impact on quality.The influence of three factors on the crashworthiness of the novel negative Poisson’s ratio battery protection system was studied by changing the thickness of the long cell wall,the short cell wall and the material of the negative Poisson’s ratio structure.Finally,the addition of negative Poisson’s ratio filling core increases the mass of electric vehicles,so it is necessary to optimize the design of the new negative Poisson’s ratio battery protection system to achieve further lightweight.Latin hypercube sampling technique is combined with the response surface method.The thickness of the long cell wall and the short cell wall of the double-arrow negative Poisson’s ratio structure the thickness of the front suspension of the battery protection system were chosen as the optimization variables,the quality is firstly taken as the optimization objective,and the nonlinear quadratic programming algorithm(NLPQL)and adaptive simulated annealing(ASA)algorithm are used to optimize the negative Poisson’s ratio battery protection system.Then the total mass and total energy absorption of the novel battery protection system are selected as the optimization objectives,and the intrusion displacement of the front suspension of the battery protection system is set as a constraint,then the approximate model is established.The Pareto optimal frontier of multi-objective optimization was obtained by combining the forth-order response surface function with the genetic algorithm.In this paper,two optimization algorithms,the second-generation non-inferiority sequencing genetic algorithm(NSGA-II)and the neighborhood cultivation genetic algorithm(NCGA),are applied to optimize the battery protection system,and the effects of different optimization algorithms on the crashworthiness performance were compared.
Keywords/Search Tags:crashworthiness analysis, Multi-objective optimization design, Negative Poisson’s ratio structure, Electric vehicles, Battery protection
PDF Full Text Request
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