Urban standard cyclic working condition constructing method based on genetic algorithm optimization

Abstract

The invention discloses an urban standard cyclic working condition constructing method based on genetic algorithm optimization. The urban standard cyclic working condition constructing method includes the following steps of testing vehicle working conditions, dividing a micro stroke, calculating micro stroke characteristic parameters, analyzing a main component, K-clustering of the micro stroke, optimizing a working condition segment genetic algorithm and synthesizing all kinds of optimized representative working condition segments into one standard cyclic working condition. Based on practical driving working condition test data in a certain city, the micro stroke is divided, K-clustering is carried out, the optimal cluster number is determined through variance analysis, the genetic algorithm is used for fitting and modifying all kinds of working condition segments, the error between the working condition segments and a cluster center is reduced, and the accuracy of the constructed urban standard cyclic working condition is improved.

Description

technical field [0001] The invention belongs to the field of urban standard cyclic working condition construction, and in particular relates to a method for constructing urban standard cyclic working condition based on genetic algorithm optimization. Background technique [0002] Standard cycle conditions have a wide range of applications in the field of vehicle engineering, such as for the detection of vehicle pollutant emissions and fuel consumption, as the verification and calibration of new models, and the inspection of new technology achievements. The standard cycle conditions (regulatory conditions) of the United States, Japan, and the European Union are relatively well established, and China is currently equivalent to the European ECE regulatory conditions. However, since the roads, traffic and driving conditions of Chinese cities are very different from those of EU countries, it is of great significance to construct a standard cycle condition that is suitable for the...

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Problems solved by technology

However, it is difficult to determine the optimal number of clusters for this method, and when the sample size is insufficient, there is a large error between the characteristic parameters of the representative working condition and its cluster center, resulting in poor consistency between the synthetic working condition characteristics and the total sample working condition characteristics, and the synthesized The accuracy of the standard working conditions is poor and cannot meet the engineering requirements

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