Comparative study of real-world driving cycles, energy consumption, and CO2 emissions of electric and gasoline motorcycles driving in a congested urban corridor

Koossalapeerom, Triluck; Satiennam, Thaned; Satiennam, Wichuda; Leelapatra, Watis; Seedam, Atthapol; Rakpukdee, Thana

doi:10.1016/j.scs.2018.12.031

Cited by 42 publications

(42 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…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]. Such tests, carried out in laboratory conditions, enable the repeatability and comparability of the obtained results [41][42][43].…”

Section: Introductionmentioning

confidence: 99%

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

Tucki¹

2021

Energies

View full text Add to dashboard Cite

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).

show abstract

Section: Introductionmentioning

confidence: 99%

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

Tucki¹

2021

Energies

View full text Add to dashboard Cite

show abstract

“…In those countries, the use of motorcycles is motivated by the poor quality of transit, traffic congestion, and their advantageous cost of acquisition and operation, together with a higher average speed. On the other hand, motorcycle accidents are accountable for economic and social impacts (Koossalapeerom et al, 2019). The conflict between advantages and disadvantages addresses the relevance of the metric analyzed when evaluating traffic, which can be an individual one, such as travel time and direct costs; or a collective one, such as indirect costs with road infrastructure and accidents, flow of vehicles, fuel production, and CO 2 emissions (Tranter, 2012).…”

Section: Introductionmentioning

confidence: 99%

“…Individual vehicle owners tend to purchase their vehicle based on flexibility and convenience. For motorcycles, low purchase and running costs are essential for the lower income population who acquire them (Koossalapeerom et al, 2019). There is also a growing concern about the global climate change, and CO 2 emissions from the transportation sector is a frequently addressed subject (Ehsani, Ahmadi, and Fadai, 2016).…”

Section: Introductionmentioning

confidence: 99%

Multimetric Analysis of a Simulated Mixed Traffic of Motorcycles and Automobiles: Flow, Energy, CO2 and Costs

et al. 2021

View full text Add to dashboard Cite

The fleet of developing countries consists of motorcycles and cars. This heterogeneous traffic condition has its advantages and disadvantages, which results in conflicting points of view (e.g., motorcyclists enjoying a higher mobility while car drivers resent their decreased speed). In this paper, we corroborated the notion that traffic evaluation depends on the chosen metric (e.g., vehicle flow, fuel consumption, monthly costs) and the point of view (driver, rider, and policy makers). To this effect, we studied a mixed traffic condition, considering that the vehicle performance is affected by three scales: engine, vehicle, and traffic. We modeled the engine using empirical correlations of power and energy efficiency, the vehicle based on a balance of propulsive and resistive forces, and traffic with a cellular automata model. We simulated 189 traffic conditions and evaluated vehicle flow, average energy consumption, total CO2 emission of the road, and monthly costs. We also discussed the results from the point of view of the driver, rider, and society. We concluded that the optimal condition depends both on the choice of metric and point of view, and that is not appropriate to use results from homogeneous traffic to analyze heterogeneous traffic conditions, even if both scenarios present the same total vehicle flow.

show abstract

“…The most widely used definition of a microtrip is the sequence between two successive stops ( 7 ). That definition was used among others in recent studies conducted by ( 9 , 10 ) and ( 11 ). However, this segmentation method is not appropriate for urban areas where traffic and urban roads cause stop-and-go driving behaviors, which create very short and biased microtrips ( 8 , 12 ).…”

Section: Introductionmentioning

confidence: 99%

Comparing Driving Cycle Development Methods Based on Markov Chains

Roy

Morency

2020

Transportation Research Record

View full text Add to dashboard Cite

The transportation sector is a major contributor to greenhouse gas (GHG) emissions, accounting for 14% of global emissions in 2010 according to the United States Environmental Protection Agency. In Quebec, this share amounts to 43%, of which 80% is caused by road transport according to the MinistÉre de l’Environnement et de la Lutte contre les changements climatiques of QuÅbec. It is therefore essential to support the actions taken to reduce GHGs emissions from this sector and to quantify the impact of these actions. To do so, accurate and reliable emission models are needed. Driving cycles are defined as speed profiles over time and they are a key element of emission models. They represent driving behaviors specific to various road types in each region. The most widely used method to construct driving cycles is based on Markov chains and consists of concatenating small sections of speed profiles, called microtrips, following a transition matrix. Two of the main steps involved in the development of driving cycles are microtrip segmentation and microtrip classification. In this study, several combinations of segmentation and clustering methods are compared to generate the most reliable driving cycle. Results show that segmentation of microtrips with a fixed distance of 250 m and clustering of the microtrips by applying a principal component analysis on many key parameters related to their speed and acceleration provide the most accurate driving cycles.

show abstract

Comparative study of real-world driving cycles, energy consumption, and CO2 emissions of electric and gasoline motorcycles driving in a congested urban corridor

Cited by 42 publications

References 12 publications

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

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

Multimetric Analysis of a Simulated Mixed Traffic of Motorcycles and Automobiles: Flow, Energy, CO2 and Costs

Comparing Driving Cycle Development Methods Based on Markov Chains

Contact Info

Product

Resources

About