Road type-based driving cycle development and application to estimate vehicle emissions for passenger cars in Guangzhou

Zhang, Lihang; Huang, Zhijiong; Yu, Fei; Liao, Shaowei; Luo, Hao; Zhong, Zhuangmin; Zhu, Manni; Li, Zhen; Cui, Xiaozhen; Yan, Min; Zheng, Junyu

doi:10.1016/j.apr.2021.101138

Cited by 14 publications

(6 citation statements)

References 55 publications

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“…Unfortunately, the author did not specify which software they used to analyse and filter all the data. In addition, in Guangzhou, China, four handheld Global Positioning System (GPS) devices were used to collect the second-by-second vehicle velocity and location information (longitude and latitude), and Portable Emission Measurement System (PEMS) was used to collect instantaneous exhaust emission, which applied to calibrate emission estimates by local driving cycles [42]. In order to improve the construction of driving cycles, the original driving data were pre-processed.…”

Section: On-board Measurement Methodsmentioning

confidence: 99%

Data Collection and Data Management Approach for Developing a Driving Cycle: A Review

Nurru Anida Ibrahim,

Arunkumar Subramaniam,

Siti Norbakyah Jabar

et al. 2024

ARASET

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Driving cycles were first proposed and developed for standard emission measurements used by legislative bodies to approve newly developed vehicles. There are many driving cycles that have been developed over the past few years. Most of the research on driving cycles is based on the condition of the vehicle in a specific location, such as the United States FTP75, European ECE 15, Japan 10115, and others. A driving cycle is a representative speed-time profile that reflects the typical driving pattern of a given city or region. A driving cycle consists of a sequence of vehicle operating conditions (idle, acceleration, cruise, and deceleration). The basic methodologies to construct a driving cycle are route selection, data collection, and the development of the driving cycle. However, as far as we know, detailed reviews and in-depth discussions of data collection instruments and data management are rarely present. As a result, this paper reviews and discusses the recent data collection approach, as well as providing a thorough analysis of the mechanisms that they employ. Furthermore, the disadvantages and advantages of the reviewed mechanisms have also been discussed.

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Section: On-board Measurement Methodsmentioning

confidence: 99%

Data Collection and Data Management Approach for Developing a Driving Cycle: A Review

Nurru Anida Ibrahim,

Arunkumar Subramaniam,

Siti Norbakyah Jabar

et al. 2024

ARASET

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“…When constructing vehicle driving cycles, selecting a relevant test route that can capture real-world traffic circumstances in a city or region is crucial. The test route should take into account all local traffic factors, such as the distribution of road types, average velocity, traffic flow, topography, and so on [20].…”

Section: Methodsmentioning

confidence: 99%

Driving cycle development methods: case study in Malaysia

Ibrahim

Jabar²,

Subramaniam³

et al. 2023

TELKOMNIKA

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Over the years, many models have been created to estimate pollution inventories and fuel usage. These models can be divided into two types: travel-based and fuel-based. One of the most used travel-based models for estimating emission inventories is driving cycles. It can be used for a variety of different things, such as establishing pollution regulations, traffic control, and calculating journey time. For these goals, researchers have previously attempted to use easily available, well-established driving cycles. In many ways, however, the local environment differs greatly from that of the driving cycle's genesis. As a result, these cycles' applications have failed to provide high-quality results. This research aims to analyse the various approaches utilised for driving cycle construction in various locations of Malaysia under varied operational situations.

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“…They showed that the İstanbul cycles resulted in lower CO 2 emission factors than those of the WLTC for segments of rural, urban, and highway. Similarly, Zhang et al [17] developed road-type-based driving cycles for Guangzhou city to compare to the standard cycles in terms of emissions and fuel consumption of passenger cars. It was reported that the obtained fuel consumption and emission factors from the city-level driving cycle of Guangzhou were quite different from those under the standard cycles.…”

Section: Introductionmentioning

confidence: 99%

A Data-Driven Framework for Driving Cycle Generation and Analysis

Keskin,

Yıldız,

Arslannur

2023

Preprint

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This paper presents a methodology for generating realistic driving cycles using Markov chain modelling, Monte Carlo simulation and dynamic time warping. The study focuses on the construction of a representative driving cycle for the city of Igdir, taking into account its unique traffic characteristics. The methodology involves segmenting the original driving datasets based on traffic conditions and road types, creating a detailed representation of driving behaviour. Dynamic time warping is used to identify reference segments for each group of segments, ensuring accurate matching with the generated driving cycles. The integration of Markov chain-Monte Carlo simulation introduces variability and randomness. The proposed methodology provides an advanced algorithm for generating highly accurate representative driving cycles, which can contribute to energy consumption analysis, vehicle performance and emission evaluation. The comprehensive approach provided by the methodology enables an accurate understanding of driving patterns, promoting the development of sustainable mobility solutions and advancing transport research.

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Road type-based driving cycle development and application to estimate vehicle emissions for passenger cars in Guangzhou

Cited by 14 publications

References 55 publications

Data Collection and Data Management Approach for Developing a Driving Cycle: A Review

Data Collection and Data Management Approach for Developing a Driving Cycle: A Review

Driving cycle development methods: case study in Malaysia

A Data-Driven Framework for Driving Cycle Generation and Analysis

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