Digital Intelligent Material Selection For New Energy Vehicles Simulation Design Software

Since the 21 st century,A wide variety of new materials have emerged.It’s not only creating information redundancy but also make manage and retrieve information of materials more difficul.In order to cope with this problem,it is necessary to select the appropriate selection method.Material selection methods can by broadly classified as traditional,semi-empirical and modern selection by time.Most of the current industries still use traditional or semi-empirical material selection methods.Designers obtain the required materials relying on their own practical experience and extensive testing,which require a lot of manpower and material resources and have high requirements in the level of knowledge of the practitioners in the material.With the development of computer technology,based on the practical experience accumulated in long-term traditional selection of materials,modern material selection methods have emerged combining database technology with powerful storage capabilities and efficient query processing capabilities.Modern selection methods mainly combine databases,artificial intelligence-related technologies and advanced value engineering methods,comprehensive evaluation methods,etc.In the process of material selection,it can help to simplify the material selection process and reduce the reliance on manual experience in the material selection process and improve the efficiency of material selection,which can bring great help to relevant practitioners and help effectively reduce enterprise costs by incorporating database technology and artificial intelligence technology,combining specific material selection algorithms and setting corresponding material selection evaluation criteria.Specifically,based on material database,this paper implements an intelligent material selection system and the main research elements are as follows.(1)The research progress and development status of material selection at home and abroad is studied from the perspective of the problems of traditional selection methods.The corresponding material data storage format is set according to the actual needs.And we established the material database in order to collect relevant material information and provide custom functions such as material information inquiry,addition and deletion which can be the support of intelligent material selection system.(2)This paper’s research object is shaft parts in new energy vehicles,In order to simplify the study,specifically for drive shafts.Intelligent material selection recommendation system not only combines material database but also incorporates BP neural network and expert s ystem technology which can recommend eligible materials for the relevant practitioners in the design process basing on the corresponding condition input.(3)CAE-aided design is used to verify the material availability and provide reference for subsequent material evaluation.The finite element model material data is updated after obtaining the initial set of materials through the intelligent selection reasoning module.And the CAE software is automatically invoked to calculate and generate the corresponding calculation results which can verify the material performance and facilitate the subsequent material evaluation.(4)The corresponding material evaluation system is e stablished.The calculation results of different material models are generated using CAE software.Combined with CAE simulation results,expert can use the hierarchical analysis method to evaluate the material in four aspects of functionality,economy,process and environmental protection and then the final recommendation results are generated.