Development of a City Bus Driving Cycle in Seoul Based on the Actual Patterns of Urban Bus Driving

Wi, Hyoseong; Park, Jinil; Lee, Jong-Hwa; Kim, Woo Seok; Kim, Yukyeom

doi:10.4271/2009-01-2914

Cited by 14 publications

(6 citation statements)

References 6 publications

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“…A common example of a legislative certification driving cycle for type approval for light-duty vehicles in Europe is the new european driving cycle (NEDC) and the FTP-75. The reason for the elementary role of driving cycles is that they provide constraints that vehicles have to entertain and where the cost, fuel consumption, and the pollutant emissions are all dependent on the driving cycle [14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

myBas driving cycle for Kuala Terengganu city

Norbakyah

Nordiyana

Anida

et al. 2021

IJECE

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Driving cycles are series of data points that represent vehicle speed versus time sequenced profile developed for specific road, route, city or certain location. It is widely utilized in the application of vehicle manufacturers, environmentalists and traffic engineers. Since the vehicles are one of the higher air pollution sources, driving cycle is needed to evaluate the fuel consumption and exhaust emissions. The main objectives in this study are to develop and characterize the driving cycle for myBAS in Kuala Terengganu city using established k-means clustering method and to analyse the fuel consumption and emissions using advanced vehicle simulator (ADVISOR). Operation of myBAS offers 7 trunk routes and one feeder route. The research covered on two operation routes of myBAS which is Kuala Terengganu city-feeder and from Kuala Terengganu to Jeti Merang where the speed-time data is collected using on-board measurement method. In general, driving cycle is made up of a few micro-trips, defined as the trip made between two idling periods. These micro-trips cluster by using the k-means clustering method and matrix laboratory software (MATLAB) is used in developing myBAS driving cycle. Typically, developing the driving cycle based on the real-world in resulting improved the fuel economy and emissions of myBAS.

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Section: Introductionmentioning

confidence: 99%

myBas driving cycle for Kuala Terengganu city

Norbakyah

Nordiyana

Anida

et al. 2021

IJECE

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show abstract

“…Previous studies have revealed that each city and region possess driving cycles with unique characteristics such as the Hong Kong driving cycle, 8 Seoul city bus driving cycle, 9 Singapore driving cycle, 10 and Chennai driving cycle for passenger cars. 11 Numerous studies have served to shed light on the construction of vehicle driving cycles for different regions, as well as prediction of the driving cycles for EVs and PHEVs in the development of power management strategies.…”

Section: Introductionmentioning

confidence: 99%

“…1 Furthermore, a global driving cycle based on real-time traffic conditions has been proposed to improve the fuel consumption and performance of real-time control for plug-in hybrid electric vehicle (PHEV) 2,3 Also, driving cycle is generally utilized in evaluating the energy consumption of electric vehicles (EVs), 4,5 developing the methodology of regenerative braking, 6 and water and thermal management of fuel cell hybrid vehicles. 7 Previous studies have revealed that each city and region possess driving cycles with unique characteristics such as the Hong Kong driving cycle, 8 Seoul city bus driving cycle, 9 Singapore driving cycle, 10 and Chennai driving cycle for passenger cars. 11 Numerous studies have served to shed light on the construction of vehicle driving cycles for different regions, as well as prediction of the driving cycles for EVs and PHEVs in the development of power management strategies.…”

Section: Introductionmentioning

confidence: 99%

A driving cycle construction methodology combining k-means clustering and Markov model for urban mixed roads

Peng

Yuan

Yang

2019

Proceedings of the Institution of Mechanical Engineers, Part D:

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With the rapid urban expansion in China, there is considerable development of road networks, mainly comprising arterial roads, expressways, and loop-lines in urban regions. In addition to typical short trips, certain number of long trips are also included in the driving behavior for urban areas. In view of the new characteristics of urban mixed roads, a driving cycle construction methodology combining k-means clustering and Markov model method is proposed based on about 2.4 million seconds of driving data collected from seven passenger cars without route planning. In order to cluster micro trips into appropriate categories corresponding to different types of roads, the Silhouette equation is introduced to determine the appropriate clustering strategy and the error of artificial factors is restrained. The constructed driving cycle, comprising a 1200 s speed-time series, is developed based on the assessment of speed–acceleration frequency distribution and estimation of six characteristic parameters. According to the results, the average difference rate of six characteristic parameters is only 4.31%, which demonstrates the effectiveness of the proposed method.

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“…Furthermore, in cases where a vehicle platform is unavailable during the earlier development phase, manufacturers conduct engine validations on a test bench using the drive-cycles as the testing conditions to provide an understanding of fuel economy under actual driving conditions. However, drive-cycles are known to have discrepancies in the fuel economy and emission results compared to actual driving conditions [7][8][9][10]. Some of the main reasons for these discrepancies are the generalization of drive-cycles to cover a wide range of driving conditions and the evolution of other factors such as technologies and infrastructures.…”

Section: Introductionmentioning

confidence: 99%

Simulation of Fuel Economy for Malaysian Urban Driving

Abas

Said

Abidin

et al. 2015

Int. J. Automot. Mech. Eng.

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By understanding the implications of real-world driving conditions, improved fuel economy via a strategy of key technologies can be implemented to assist fuel economy validation during development programs. Vehicles in real-world driving conditions regularly travel at idle, low and medium speeds, particularly for urban driving, and this has a crucial weight in overall vehicle fuel economy, given the residencies at the lower engine speed and load region. This paper presents the validation of the derived engine conditions representing Malaysian actual urban driving in an attempt to formulate representative fuel economy data. The measurements were conducted through on-road urban driving within Kuala Lumpur to establish representative driving conditions. The effectiveness of the proposed conditions was then validated in terms of fuel economy using a simulation. The discrepancy between the fuel economy in the proposed conditions and the real-world measurements has improved, falling to 11.9% compared to 43.1% reported by the NEDC.

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Development of a City Bus Driving Cycle in Seoul Based on the Actual Patterns of Urban Bus Driving

Cited by 14 publications

References 6 publications

myBas driving cycle for Kuala Terengganu city

myBas driving cycle for Kuala Terengganu city

A driving cycle construction methodology combining k-means clustering and Markov model for urban mixed roads

Simulation of Fuel Economy for Malaysian Urban Driving

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