Development of a representative urban driving cycle construction methodology for electric vehicles: A case study in Xi'an

This paper develops a systematic and practical construction methodology of a representative urban driving cycle for electric vehicles, taking Xi'an as a case study. The methodology tackles four major tasks: test route selection, vehicle operation data collection, data processing, and driving cycle construction. A qualitative and quantitative comprehensive analysis method is proposed based on a sampling survey and an analytic hierarchy process to design test routes. A hybrid method using a chase car and on-board measurement techniques is employed to collect data. For data processing, the principal component analysis algorithm is used to reduce the dimensions of motion characteristic parameters, and the K-means and support vector machine hybrid algorithm is used to classify the driving segments. The proposed driving cycle construction method is based on the Markov and Monte Carlo simulation method. In this study, relative error, performance value, and speed-acceleration probability distribution are used as decision criteria for selecting the most representative driving cycle. Finally, characteristic parameters, driving range, and energy consumption are compared under different driving cycles.