An Experimental Methodology for Measuring Resistance Forces of Light-Duty Vehicles under Real-World Conditions and the Impact on Fuel Consumption

2020 ◽  
Author(s):  
Dimitrios Komnos ◽  
Georgios Fontaras ◽  
Leonidas Ntziachristos ◽  
Jelica Pavlovic ◽  
Biagio Ciuffo
Keyword(s):  
Fuel Consumption ◽  
Real World ◽  
Experimental Methodology ◽  
Light Duty ◽  
Light Duty Vehicles ◽  
The Impact ◽  
Resistance Forces

scholarly journals Estimation of Real-world Fuel Consumption Rate of Light-duty Vehicles Based on Big Data

2021 ◽  
Author(s):  
Isabella Yunfei Zeng ◽  
Shiqi Tan ◽  
Jianliang Xiong ◽  
Xuesong Ding ◽  
Yawen Li ◽  
...  
Keyword(s):  
Fuel Consumption ◽  
Real World ◽  
Consumption Rate ◽  
Effective Control ◽  
Fuel Consumption Rate ◽  
Light Duty ◽  
Light Duty Vehicle ◽  
Light Duty Vehicles ◽  
The Impact ◽  
Engine Power

Private vehicle travel is the most basic mode of transportation, and the effective control of the real-world fuel consumption rate of light-duty vehicles plays a vital role in promoting sustainable economic development as well as achieving a green low-carbon society. Therefore, the impact factors of individual carbon emission must be elucidated. This study builds five different models to estimate real-world fuel consumption rate of light-duty vehicles in China. The results reveal that the Light Gradient Boosting Machine (LightGBM) model performs better than the linear regression, Naïve Bayes regression, Neural Network regression, and Decision Tree regression models, with mean absolute error of 0.911 L/100 km, mean absolute percentage error of 10.4%, mean square error of 1.536, and R squared (R2) of 0.642. This study also assesses a large number of factors, from which three most important factors are extracted, namely, reference fuel consumption rate value, engine power and light-duty vehicle brand. Furthermore, a comparative analysis reveals that the vehicle factors with greater impact on real-world fuel consumption rate are vehicle brand, engine power, and engine displacement. Average air pressure, average temperature, and sunshine time are the three most important climate factors.

Analysis of Driving Cycles for Emission Test of Light-Duty Vehicles in China

2012 ◽  
Vol 616-618 ◽  
pp. 1154-1160
Author(s):  
Jin Lin Xue
Keyword(s):  
Real World ◽  
Gasoline Engine ◽  
The Real ◽  
Driving Behaviors ◽  
Traffic Conditions ◽  
Driving Cycles ◽  
Driving Pattern ◽  
Light Duty ◽  
Light Duty Vehicles ◽  
The Impact

The driving cycles employed to measure the emissions from automotive vehicles should adequately represent the real-world driving pattern of the vehicle to provide the most realistic estimation of emissions levels. The driving cycles used for light-duty gasoline engine vehicles in China were reviewed in this paper firstly. Then the impact of various factors, such as driving behaviors, driving conditions, road conditions, traffic conditions, on real-world emission levels were analyzed. Finally, the shortages of the existing driving cycles were pointed out. It can be concluded that the emissions levels from automotive vehicles are underestimated because of the characteristics of the existing drive cycles, so it is urgent to research and develop new driving cycles to fit the situation of China.

scholarly journals Estimation of Real-World Fuel Consumption Rate of Light-Duty Vehicles Based on the Records Reported by Vehicle Owners

Energies ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 7915
Author(s):  
Isabella Yunfei Zeng ◽  
Shiqi Tan ◽  
Jianliang Xiong ◽  
Xuesong Ding ◽  
Yawen Li ◽  
...  
Keyword(s):  
Fuel Consumption ◽  
Real World ◽  
Consumption Rate ◽  
The Real ◽  
Fuel Consumption Rate ◽  
Light Gradient ◽  
Light Duty ◽  
Light Duty Vehicle ◽  
Light Duty Vehicles ◽  
Engine Power

Private vehicle travel is the most basic mode of transportation, so that an effective way to control the real-world fuel consumption rate of light-duty vehicles plays a vital role in promoting sustainable economic growth as well as achieving a green low-carbon society. Therefore, the factors impacting individual carbon emissions must be elucidated. This study builds five different models to estimate the real-world fuel consumption rate of light-duty vehicles in China. The results reveal that the light gradient boosting machine (LightGBM) model performs better than the linear regression, naïve Bayes regression, neural network regression, and decision tree regression models, with a mean absolute error of 0.911 L/100 km, a mean absolute percentage error of 10.4%, a mean square error of 1.536, and an R-squared (R2) value of 0.642. This study also assesses a large pool of potential factors affecting real-world fuel consumption, from which the three most important factors are extracted, namely, reference fuel-consumption-rate value, engine power, and light-duty vehicle brand. Furthermore, a comparative analysis reveals that the vehicle factors with the greatest impact are the vehicle brand, engine power, and engine displacement. The average air pressure, average temperature, and sunshine time are the three most important climate factors.

Real-world emissions and fuel consumption of gasoline and hybrid light duty vehicles under local and regulatory drive cycles

2022 ◽  
Vol 805 ◽  
pp. 150407
Author(s):  
Ran Tu ◽  
Junshi Xu ◽  
An Wang ◽  
Mingqian Zhang ◽  
Zhiqiang Zhai ◽  
...  
Keyword(s):  
Fuel Consumption ◽  
Real World ◽  
Light Duty ◽  
Light Duty Vehicles

Impact factors of the real-world fuel consumption rate of light duty vehicles in China

Energy ◽  
2020 ◽  
Vol 190 ◽  
pp. 116388 ◽  
Author(s):  
Tian Wu ◽  
Xiao Han ◽  
M. Mocarlo Zheng ◽  
Xunmin Ou ◽  
Hongbo Sun ◽  
...  
Keyword(s):  
Fuel Consumption ◽  
Real World ◽  
Consumption Rate ◽  
Impact Factors ◽  
The Real ◽  
Fuel Consumption Rate ◽  
Light Duty ◽  
Light Duty Vehicles

scholarly journals Multilayer Perceptron Method to Estimate Real-World Fuel Consumption Rate of Light Duty Vehicles

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 63395-63402 ◽  
Author(s):  
Yawen Li ◽  
Guangcan Tang ◽  
Jiameng Du ◽  
Nan Zhou ◽  
Yue Zhao ◽  
...  
Keyword(s):  
Fuel Consumption ◽  
Real World ◽  
Multilayer Perceptron ◽  
Consumption Rate ◽  
Fuel Consumption Rate ◽  
Light Duty ◽  
Light Duty Vehicles

Dealing with the Gap between Type-Approval and In-Use Light Duty Vehicles Fuel Consumption and CO2 Emissions: Present Situation and Future Perspective

2018 ◽  
Vol 2672 (2) ◽  
pp. 23-32 ◽  
Author(s):  
Jelica Pavlovic ◽  
Konstantinos Anagnostopoulos ◽  
Michael Clairotte ◽  
Vincenzo Arcidiacono ◽  
Georgios Fontaras ◽  
...  
Keyword(s):  
Fuel Consumption ◽  
Real World ◽  
Test Procedure ◽  
Present Situation ◽  
Future Perspective ◽  
Type Approval ◽  
Real Driving Emission ◽  
Light Duty ◽  
The Difference ◽  
Light Duty Vehicles

There is increasing evidence suggesting that real-world fuel consumption and CO2 improvements in the last decade have been much less than those measured during type-approval tests. Scientific studies have found that the offset between officially reported values and real-world vehicle CO2 emissions in Europe has constantly increased over the last years. The difference between officially reported and actual CO2 emissions of vehicles has three main implications: (i) it undermines the effectiveness of CO2 regulations in reducing greenhouse gas emissions in Europe; (ii) it distorts competition between vehicle manufacturers; (iii) it undermines innovation. As a fundamental step to deal with this issue, the European Commission has already replaced the old and outdated test procedure used so far in the emission type-approval of vehicles with the worldwide harmonized light vehicles test procedure (WLTP). Being a lab-based test procedure, the WLTP, by its nature, can only cover part of the CO2 gap. There is therefore increasing pressure to integrate the current type-approval system with additional measures based on real-world measurements. One of the options under discussion is to use the CO2 emissions measured during the real driving emission test. The objective of the present paper is to assess the validity of this proposal and to propose other possible ways to deal with the CO2/fuel consumption gap. In particular, the paper presents experimental evidence on the variability of the CO2/fuel consumption of a vehicle, questioning the idea that a single central estimate of these quantities may be sufficient.

scholarly journals Monte Carlo Simulation Methodology to Assess the Impact of Ambient Wind on Emissions from a Light-Commercial Vehicle Running on the Worldwide-Harmonized Light-Duty Vehicles Test Cycle (WLTC)

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 661
Author(s):  
Alexandros T. Zachiotis ◽  
Evangelos G. Giakoumis
Keyword(s):  
Monte Carlo Simulation ◽  
Energy Consumption ◽  
Commercial Vehicle ◽  
Ambient Wind ◽  
Simulation Methodology ◽  
Road Load ◽  
Light Duty ◽  
Light Commercial Vehicle ◽  
Light Duty Vehicles ◽  
The Impact

A Monte Carlo simulation methodology is suggested in order to assess the impact of ambient wind on a vehicle’s performance and emissions. A large number of random wind profiles is generated by implementing the Weibull and uniform statistical distributions for wind speed and direction, respectively. Wind speed data are drawn from eight cities across Europe. The vehicle considered is a diesel-powered, turbocharged, light-commercial vehicle and the baseline trip is the worldwide harmonized light-duty vehicles WLTC cycle. A detailed engine-mapping approach is used as the basis for the results, complemented with experimentally derived correction coefficients to account for engine transients. The properties of interest are (engine-out) NO and soot emissions, as well as fuel and energy consumption and CO2 emissions. Results from this study show that there is an aggregate increase in all properties, vis-à-vis the reference case (i.e., zero wind), if ambient wind is to be accounted for in road load calculation. Mean wind speeds for the different sites examined range from 14.6 km/h to 24.2 km/h. The average increase in the properties studied, across all sites, ranges from 0.22% up to 2.52% depending on the trip and the property (CO2, soot, NO, energy consumption) examined. Based on individual trip assessment, it was found that especially at high vehicle speeds where wind drag becomes the major road load force, CO2 emissions may increase by 28%, NO emissions by 22%, and soot emissions by 13% in the presence of strong headwinds. Moreover, it is demonstrated that the adverse effect of headwinds far exceeds the positive effect of tailwinds, thus explaining the overall increase in fuel/energy consumption as well as emissions, while also highlighting the shortcomings of the current certification procedure, which neglects ambient wind effects.

Powertrain Waste Heat Recovery: A Systems Approach to Maximize Drivetrain Efficiency

2012 ◽  
Author(s):  
Kevin Laboe ◽  
Marcello Canova
Keyword(s):  
Fuel Consumption ◽  
Waste Heat Recovery ◽  
Systems Approach ◽  
Waste Heat ◽  
Combustion Engine ◽  
Heat Energy ◽  
Engine Oils ◽  
Engine Cooling ◽  
Light Duty ◽  
Light Duty Vehicles

Up to 65% of the energy produced in an internal combustion engine is dissipated to the engine cooling circuit and exhaust gases [1]. Therefore, recovering a portion of this heat energy is a highly effective solution to improve engine and drivetrain efficiency and to reduce CO2 emissions, with existing vehicle and powertrain technologies [2,3]. This paper details a practical approach to the utilization of powertrain waste heat for light vehicle engines to reduce fuel consumption. The “Systems Approach” as described in this paper recovers useful energy from what would otherwise be heat energy wasted into the environment, and effectively distributes this energy to the transmission and engine oils thus reducing the oil viscosities. The focus is on how to effectively distribute the available powertrain heat energy to optimize drivetrain efficiency for light duty vehicles, minimizing fuel consumption during various drive cycles. To accomplish this, it is necessary to identify the available powertrain heat energy during any drive cycle and cold start conditions, and to distribute this energy in such a way to maximize the overall efficiency of the drivetrain.

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