一种结合变参数马尔可夫链和蒙特卡罗的驱动循环构造方法

Jiaming Xing, Yuanjian Zhang, Chong Guo, Zhuoran Hou, Peng Liu, Shibo Li
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引用次数: 0

摘要

在比较不同汽车的环保性和经济性时,有必要让汽车在相同的行驶循环中运行,以获得污染物排放和燃油消耗。然而,在实际驾驶过程中,车辆的性能可能与测试周期中的性能存在明显差异。为了生成能够代表实际行驶过程的行驶循环,本文采用特定行驶路线的快运货车行驶数据,结合马尔可夫链和蒙特卡洛随机抽样,构建城市的典型行驶循环。在施工过程中加入随机响应,利用变异参数模拟突发交通情况。设置CCPV和CPV参数,评估产生的行驶周期。通过Simulink仿真,验证了生成的驱动循环的可靠性,并确定了不同统计特性的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A driving cycle construction methodology combining Markov chain with variation parameters and Monte Carlo
When comparing the environmental protection and economy of different cars, it is necessary for cars to run in the same driving cycle to obtain the pollutant emission and fuel consumption. However, in the actual driving process, the performance of the vehicle may be markedly different from the performance in test cycle. In order to generate the driving cycle that can represent the actual driving process, this paper adopts the driving data of an express truck with specific driving routes to construct the typical driving cycle of a city by combining Markov chain with Monte Carlo random sampling. The random response is added in the construction process, and the variation parameter is used to simulate the sudden traffic situation. CCPV and CPV parameters are set to evaluate the generated driving cycle. Through Simulink simulation, the reliability of the generated driving cycle is verified and the influence of different statistical characteristics is determined.
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