Study on Driving Cycle Synthesis Method for City Buses considering Random Passenger Load

This paper proposes a novel driving cycle construction method in consideration of velocity, road slope, and passenger load, based on a real-world bus route with a plug-in hybrid electric bus (PHEB). The main purpose is to address the disadvantage that an inaccurate reflection of the real-world drivi...

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Main Authors: Xiaodong Liu, Jian Ma, Xuan Zhao, Juan Du, Yanfeng Xiong
Format: Article
Language:English
Published: Wiley 2020-01-01
Series:Journal of Advanced Transportation
Online Access:http://dx.doi.org/10.1155/2020/3871703
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author Xiaodong Liu
Jian Ma
Xuan Zhao
Juan Du
Yanfeng Xiong
author_facet Xiaodong Liu
Jian Ma
Xuan Zhao
Juan Du
Yanfeng Xiong
author_sort Xiaodong Liu
collection DOAJ
description This paper proposes a novel driving cycle construction method in consideration of velocity, road slope, and passenger load, based on a real-world bus route with a plug-in hybrid electric bus (PHEB). The main purpose is to address the disadvantage that an inaccurate reflection of the real-world driving characteristics for city buses will be caused when ignoring the passenger load in the course of a driving cycle synthesis. Two contributions are supplemented to distinguish from the previous research. Firstly, a novel station-based method is proposed aiming at developing a driving cycle with high accuracy. The kinematic segments are partitioned according to the distance of adjacent bus stops, while a two-dimensional Markov chain Monte Carlo method is employed to synthesize driving cycle between each interval of adjacent bus stops. Secondly, the random passenger load for different bus stops is treated as a discrete Markov chain model, according to the correlation analysis of the measured passenger data which are distinguished for off-peak and peak hours. Meanwhile, Monte Carlo simulation and maximum likelihood estimation are utilized to determine the most likely number of passengers for each bus stop. At last, the fuel consumption of the PHEB is simulated with the best-synthesized driving cycle and contrasted to the mean fuel consumption of the later measured data which is composed of the velocity, road slope, and the passenger load. The results demonstrate that the synthesized driving cycle has a higher accuracy on fuel consumption estimation.
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institution Kabale University
issn 0197-6729
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language English
publishDate 2020-01-01
publisher Wiley
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series Journal of Advanced Transportation
spelling doaj-art-db9c74dafee34e5486bc1a7875e443262025-08-20T03:24:21ZengWileyJournal of Advanced Transportation0197-67292042-31952020-01-01202010.1155/2020/38717033871703Study on Driving Cycle Synthesis Method for City Buses considering Random Passenger LoadXiaodong Liu0Jian Ma1Xuan Zhao2Juan Du3Yanfeng Xiong4School of Automobile, Chang’an University, Xi’an, Shaanxi 710064, ChinaSchool of Automobile, Chang’an University, Xi’an, Shaanxi 710064, ChinaSchool of Automobile, Chang’an University, Xi’an, Shaanxi 710064, ChinaSchool of Mechanical & Automotive Engineering, Liaocheng University, Liaocheng, Shandong 252059, ChinaSchool of Automobile, Chang’an University, Xi’an, Shaanxi 710064, ChinaThis paper proposes a novel driving cycle construction method in consideration of velocity, road slope, and passenger load, based on a real-world bus route with a plug-in hybrid electric bus (PHEB). The main purpose is to address the disadvantage that an inaccurate reflection of the real-world driving characteristics for city buses will be caused when ignoring the passenger load in the course of a driving cycle synthesis. Two contributions are supplemented to distinguish from the previous research. Firstly, a novel station-based method is proposed aiming at developing a driving cycle with high accuracy. The kinematic segments are partitioned according to the distance of adjacent bus stops, while a two-dimensional Markov chain Monte Carlo method is employed to synthesize driving cycle between each interval of adjacent bus stops. Secondly, the random passenger load for different bus stops is treated as a discrete Markov chain model, according to the correlation analysis of the measured passenger data which are distinguished for off-peak and peak hours. Meanwhile, Monte Carlo simulation and maximum likelihood estimation are utilized to determine the most likely number of passengers for each bus stop. At last, the fuel consumption of the PHEB is simulated with the best-synthesized driving cycle and contrasted to the mean fuel consumption of the later measured data which is composed of the velocity, road slope, and the passenger load. The results demonstrate that the synthesized driving cycle has a higher accuracy on fuel consumption estimation.http://dx.doi.org/10.1155/2020/3871703
spellingShingle Xiaodong Liu
Jian Ma
Xuan Zhao
Juan Du
Yanfeng Xiong
Study on Driving Cycle Synthesis Method for City Buses considering Random Passenger Load
Journal of Advanced Transportation
title Study on Driving Cycle Synthesis Method for City Buses considering Random Passenger Load
title_full Study on Driving Cycle Synthesis Method for City Buses considering Random Passenger Load
title_fullStr Study on Driving Cycle Synthesis Method for City Buses considering Random Passenger Load
title_full_unstemmed Study on Driving Cycle Synthesis Method for City Buses considering Random Passenger Load
title_short Study on Driving Cycle Synthesis Method for City Buses considering Random Passenger Load
title_sort study on driving cycle synthesis method for city buses considering random passenger load
url http://dx.doi.org/10.1155/2020/3871703
work_keys_str_mv AT xiaodongliu studyondrivingcyclesynthesismethodforcitybusesconsideringrandompassengerload
AT jianma studyondrivingcyclesynthesismethodforcitybusesconsideringrandompassengerload
AT xuanzhao studyondrivingcyclesynthesismethodforcitybusesconsideringrandompassengerload
AT juandu studyondrivingcyclesynthesismethodforcitybusesconsideringrandompassengerload
AT yanfengxiong studyondrivingcyclesynthesismethodforcitybusesconsideringrandompassengerload