Research and Simulation Design of Lightweight Technology Approaches for Integrated Forming of New Energy Vehicles,ERICDATA高等教育知識庫
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篇名
Research and Simulation Design of Lightweight Technology Approaches for Integrated Forming of New Energy Vehicles
並列篇名
Research and Simulation Design of Lightweight Technology Approaches for Integrated Forming of New Energy Vehicles
作者 Zhi ZhangWen-Tao LiXiao-Bo DongXiang-Yun YiYan-Chao SunLiang-Gui Zhang
英文摘要

Electric vehicle lightweighting is a new method for car molding. This article establishes an integrated molding model for car doors. The lightweight technology for car doors requires special structures and optimized parameters. The optimized parameters include inner plate thickness, outer plate thickness, door and window frame thickness, door lock installation surface thickness, door hinge installation surface thickness as design variables, first-order free mode frequency as the optimization function, second-order free mode frequency as the optimization function, sinking stiffness working condition displacement, torsional stiffness working condition displacement as the optimization object, and increasing the weight of the car door as the optimization object. To this end, a car door optimization model and finite element analysis model were constructed. In order to solve the optimal optimization parameters, this paper uses an improved Bayesian optimization algorithm and TabNet deep learning algorithm to solve, and finally obtains the optimal parameters for lightweight car doors. After analysis, it is found that the car doors can achieve significant weight reduction while improving stiffness.

 

起訖頁 327-343
關鍵詞 new energy vehicleslightweight technologytopological optimizationdeep learning
刊名 電腦學刊  
期數 202406 (35:3期)
DOI 10.53106/199115992024063503022   複製DOI
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