Fuel consumption and exhaust emissions of diesel vehicles in worldwide harmonized light vehicles test cycles and their sensitivities to eco-driving factors

Gao, Jianbing; Chen, Haibo; Liu, Ying; Chen, Junyan; Zhang, Hongjie; Dave, Kaushali; Huang, Yue

doi:10.1016/j.enconman.2019.06.038

Cited by 83 publications

(30 citation statements)

References 46 publications

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“…The maximum speed for truck 2 is ∼10 km/h higher than truck 1, which causes higher overall level of fuel consumption rates in road segment 1 for truck 2. As indicated by Gao et al, 37 the fuel economy of the light-duty vehicle increased from 5.6 to 7.5 L/100 km when the vehicle average speed increased from 18.75 to 91.88 km/h, and the optimal speed for the fuel economy is around 60 km/h. In the process of acceleration, the trucks’ fuel consumption rate is even higher than high speed and uphill situations.…”

Section: Resultsmentioning

confidence: 83%

Analysis of driving behaviours of truck drivers using motorway tests

Gao

Chen

Dave

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part D:

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Road transportations still play a dominant role in goods delivery, and driving behaviours significantly affect the fuel economy of heavy-duty trucks. Plenty of fossil fuel is wasted as a result of unreasonable driving behaviours even in the case of highly experienced drivers. The objective of this paper is to analyse drivers’ behaviours over two segments of motorways and estimate the potential benefits of fuel saving caused by a change in driving habits during national and international goods delivery. Drivers’ habits on motorways change depending on the road situations. In the acceleration process, the fuel consumption rates are huge even under low-speed conditions. The truck fuel consumption rates are exaggerated by positive road slopes, but still dominated by acceleration. Accelerations are generally in normal distributions, with the median value being approximately 0.5 m/s2. The speed ranges corresponding to each gear enlarge with the increase in gear number. The potentials of annual fuel saving for parts of European Union countries are nearly 2 × 106 m3 by adopting proper driving behaviours.

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Section: Resultsmentioning

confidence: 83%

Analysis of driving behaviours of truck drivers using motorway tests

Gao

Chen

Dave

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part D:

Self Cite

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“…Fuel consumption and safe driving of heavy-duty vehicles are also of great interest not only to transport and environment but also to asset management. In the actual driving cycle of vehicle, many variables affect fuel consumption and exhaust emissions [20]. Currently, the main factors used to analyze the fuel consumption of heavy-duty vehicles include speed and road gradient [21], driving style [22] [23], driving enthusiasm [24] [25], and driving conditions [26] [27].…”

Section: Introductionmentioning

confidence: 99%

Study of Driving Cycle of City Tour Bus Based on Coupled GA-K-Means and HMM Algorithms: A Case Study in Beijing

et al. 2021

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Driving cycle is an important indicator to evaluate vehicle performance and to measure fuel consumption. Its impact is not only on pollution emissions but also on asset management. Based on the real life detailed data from the city tour buses in Beijing, this paper proposes to couple a genetic algorithm based GA-K-means clustering with the Hidden Markov Model (HMM) to construct a city tour bus urban road driving cycle in Beijing. Compared to the standard driving cycle C-WTVC used for heavy commercial vehicle fuel consumption certification in China, our driving cycle model can reflect the real life situation more accurately. With our model, the influence of driving state and driving behavior on fuel consumption is also analyzed, and the fuel consumption estimation model under the corresponding driving cycle is constructed. To gain deeper insight and better fuel consumption, we further segment and construct the driving sub-cycles of peak and off-peak periods according to the difference in fuel consumption at different time periods in Beijing in September 2019. Through this fine-grain driving cycle, we can further improve the accuracy of the fuel consumption estimation model.

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“…Each new passenger car must meet exhaust gas toxicity standards before it is introduced to the market [35][36][37]. The test conditions depend on the vehicle class and the country of destination [38][39][40].…”

Section: Introductionmentioning

confidence: 99%

A Computer Tool for Modelling CO2 Emissions in Driving Cycles for Spark Ignition Engines Powered by Biofuels

Tucki¹

2021

Energies

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A driving cycle is a record intended to reflect the regular use of a given type of vehicle, presented as a speed profile recorded over a certain period of time. It is used for the assessment of engine pollutant emissions, fuel consumption analysis and environmental certification procedures. Different driving cycles are used, depending on the region of the world. In addition, drive cycles are used by car manufacturers to optimize vehicle drivelines. The basis of the work presented in the manuscript was a developed computer tool using tests on the Toyota Camry LE 2018 chassis dynamometer, the results of the optimization process of neural network structures and the properties of fuels and biofuels. As a result of the work of the computer tool, the consumption of petrol 95, ethanol, methanol, DME, CNG, LPG and CO2 emissions for the vehicle in question were analyzed in the following driving tests: Environmental Protection Agency (EPA US06 and EPA USSC03); Supplemental Federal Test Procedure (SFTP); Highway Fuel Economy Driving Schedule (HWFET); Federal Test Procedure (FTP-75–EPA); New European Driving Cycle (NEDC); Random Cycle Low (×05); Random Cycle High (×95); Mobile Air Conditioning Test Procedure (MAC TP); Common Artemis Driving Cycles (CADC–Artemis); Worldwide Harmonized Light-Duty Vehicle Test Procedure (WLTP).

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Fuel consumption and exhaust emissions of diesel vehicles in worldwide harmonized light vehicles test cycles and their sensitivities to eco-driving factors

Cited by 83 publications

References 46 publications

Analysis of driving behaviours of truck drivers using motorway tests

Analysis of driving behaviours of truck drivers using motorway tests

Study of Driving Cycle of City Tour Bus Based on Coupled GA-K-Means and HMM Algorithms: A Case Study in Beijing

A Computer Tool for Modelling CO2 Emissions in Driving Cycles for Spark Ignition Engines Powered by Biofuels

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