基于模拟退火算法优化的城市标准行驶工况构建

Hang Zhang, Siwen Lv, Yu Zhang, S. Zhang
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引用次数: 0

摘要

为了评估车辆在实际行驶中的排放和能耗,准确的车辆行驶周期是非常必要的。本文的创新之处在于在前人驾驶工况构建方法的基础上,提出了一种基于模拟退火算法的城市驾驶工况构建方法。主要任务是数据处理和优化。在数据处理方面,根据微行程分析理论选取微行程特征参数,进行主成分分析降维运动特征参数,并采用k均值聚类方法对运动段进行分类。在片段的选择上,本文采用模拟退火算法进行优化。最终的分析结果表明,误差大大减小,进一步提高了工况的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Construction of urban standard driving cycle based on simulated annealing algorithm optimization
In order to assess the vehicle emissions and energy consumption in actual driving, the accurate vehicle driving cycles are extremely necessary. On the basis of the previous driving cycle's construction methods, the innovation of this paper is proposing a method for constructing urban driving cycle based on simulated annealing algorithm. The major task is the data processing and optimizing. For data processing, the characteristic parameter of the micro-trips is selected according to the theory of micro-trips analysis, then this paper performs principal component analysis to reduce the dimensions of motion characteristic parameters and the K-means clustering method is used to classify kinematics segments. In the selection of fragments, this paper adopts the simulated annealing algorithm to optimize. The final analysis results show that the error is largely reduced and the accuracy of the operating conditions is further improved.
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