Development of a representative driving cycle for evaluating exhaust emission and fuel consumption for Chinese switcher locomotives

Siyou Tao, Ke Ding, Zhuoyun Li and Hui Zhang

Applied Energy, 2022, vol. 322, issue C, No S0306261922008212

Abstract: This paper aims to develop a representative driving cycle which can be applied to emission and fuel consumption testing for Chinese switcher locomotives. Considerable raw driving data is collected by on-board recorder. After analyzing the working features of recorder and switcher locomotives, a data preprocessing which includes interpolation, re-sampling, and filtering is implemented to generate valid data. Switcher locomotives generally work in two modes (in-yard mode and transfer mode) with apparently different traits. For the purpose of developing a representative driving cycle with controllable length for the two working modes, we develop two parts of driving cycle for the two modes based on moving fragments and snippets. For the in-yard part, a dimensional reduction method based on auto-encoding and density based clustering method are applied to cluster moving fragments. Then, several fragments with minimum key parameters deviation in each cluster are picked up. For the transfer part, a series of candidate fragments are synthesized by randomly selected snippets and the one with minimum deviation is chosen as representative fragment. The duration of idling fragments is equal to the mean value of each cumulative probability interval. Finally, the moving fragments of two parts and idling fragments are synthesized into the representative driving cycle.

Keywords: Switcher locomotives; Driving cycle; Working modes; Minimum component; Auto-encoding (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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DOI: 10.1016/j.apenergy.2022.119499

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