In the face of the rapid growth of China's car ownership, the variety of vehicle types, and the increasingly complex structure and use conditions of modern cars, the majority of car manufacturers urgently need to further control the performance of cars in the process of car design and production, and effectively measure the performance of cars and analyse and process the results so that they have high practicality and economic benefits. The purpose of this paper is to study the vehicle performance evaluation and testing system based on multi-objective genetic algorithm. The indicators for the evaluation of the vehicle performance are determined, including vehicle dynamics, fuel economy, braking, handling stability and environmental friendliness. The fuzzy comprehensive evaluation method is used to establish the subordinate degree function of each factor, so as to obtain the scores of the vehicle performance evaluation, select the appropriate input and output parameters, and establish the evaluation model using the neural network of multi-objective genetic algorithm. As a result, the overall vehicle performance scores after the two sets of real-world tests were 79 and 80 respectively.


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    Title :

    The Evaluation and Testing System of Automobile Performance Based on Multi-Objective Genetic Algorithm


    Contributors:
    Wen, Yanling (author) / Tan, Kecheng (author)


    Publication date :

    2023-11-24


    Size :

    287588 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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