Research On Front Face Design Of Electric Vehicle Driven By User Image

In recent years,the modeling design of electric vehicle has become a matching problem with its technology iteration.In order to ensure the success of the electric vehicle modeling design scheme in the market,the perceptual image styling theory based on "analyzing user’s emotional factors to produce design features" is applied to establish the relationship between the design features of the electric vehicle front face and the user’s image,enhance the influence weight of user factors in the front face modeling design activities of electric vehicles,and realize the front face modeling design of electric vehicles driven by user image.Research methods,research process and research conclusions mainly include:(1)Sorting out the underlying theories: sorting out the perceptual image styling theory,according to the expected conclusions and results of the research,and based on the goal of "user factor leading generation of design features ",artificial neural network(hereinafter referred to as "ANN")and genetic algorithm(hereinafter referred to as "GA ")are selected as the key technology to realize user image driving electric vehicle front face modeling design.(2)Modeling design elements of electric vehicle’s front face: analyze the traditional automobile modeling theory,understand the electric vehicle front face modeling from the perspective of "features",determine the key modeling features,and describe it from two aspects,shape and proportion.According to the hierarchical relationship of "feature-attribute-design elements",the design elements are obtained.A parameterized model and mapping rules for the front face of electric vehicle are established;Through the design elements,the transformation from visual language to data language is completed,which is the pre work of building ANN model and running GA.(3)The modeling image of electric vehicle’s front face: find the common adjectives that users describe the front face of electric vehicles,and screen them by frequency analysis and cluster analysis,so that the adjectives are general;The perceptual adjectives obtained are used to establish semantic difference scale to quantify the user emotion.The quantitative data of user emotion is the front work of establishing ANN model.(4)Modeling design of front face driven by user image: the results of semantic difference scale form ANN model training data;The fitness function needed to run genetic algorithm is established through ANN model,and then the multi-objective image optimization of electric vehicle front face modeling is realized based on genetic algorithm,and the optimal solution of electric vehicle front face modeling based on specific design objectives is obtained(5)Practice and verification of electric vehicle front face modeling design: the multi-objective image optimization results form a prototype scheme,which is combined with different electric vehicle body modeling platforms to produce a design practice scheme.The evaluation system is constructed based on image adjectives.The verification results show that the multi-objective image optimization results of electric vehicle front face modeling based on perceptual image theory can be used to guide the actual design activities,and the modeling design process of electric vehicle front face driven by user image based on ANN and GA is feasible.