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.

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.

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

Measurement and Evaluation of Real-World Speed and Acceleration Activity Envelopes for Light-Duty Vehicles

2015 ◽  
Vol 2503 (1) ◽  
pp. 128-136 ◽  
Author(s):  
Bin Liu ◽  
H. Christopher Frey
Keyword(s):  
Real World ◽  
Test Procedure ◽  
Accurate Estimation ◽  
Vehicle Type ◽  
Light Duty ◽  
Road Grade ◽  
Light Duty Vehicle ◽  
Curb Weight ◽  
Vehicle Activity ◽  
Light Duty Vehicles

Accurate estimation of vehicle activity is critically important for the accurate estimation of emissions. To provide a benchmark for estimation of vehicle speed trajectories such as those from traffic simulation models, this paper demonstrates a method for quantifying light-duty vehicle activity envelopes based on real-world activity data for 100 light-duty vehicles, including conventional passenger cars, passenger trucks, and hybrid electric vehicles. The vehicle activity envelope was quanti-fied in the 95% frequency range of acceleration for each of 15 speed bins with intervals of 5 mph and a speed bin for greater than 75 mph. Potential factors affecting the activity envelope were evaluated; these factors included vehicle type, transmission type, road grade, engine displacement, engine horsepower, curb weight, and ratio of horsepower to curb weight. The activity envelope was wider for speeds ranging from 5 to 20 mph and narrowed as speed increased. The latter was consistent with a constraint on maximum achievable engine power demand. The envelope was weakly sensitive to factors such as type of vehicle, type of transmission, road grade, and engine horsepower. The effect of road grade on cycle average emissions rates was evaluated for selected real-word cycles. The measured activity envelope was compared with those of dynamometer driving cycles, such as the federal test procedure, highway fuel economy test, SC03, and US06 cycles. The effect of intervehicle variability on the activity envelope was minor; this factor implied that the envelope could be quantified based on a smaller vehicle sample than used for this study.

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.

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

Experimental Investigation to Fuel Consumption Characteristics of Light-Duty Passenger Vehicle under Sliding Condition

2012 ◽  
Vol 433-440 ◽  
pp. 2142-2148
Author(s):  
Hong Liang Lin ◽  
Qiang Yu ◽  
Xuan Meng Cui ◽  
Xue Li Zhang
Keyword(s):  
Fuel Consumption ◽  
Consumption Rate ◽  
Operation Mode ◽  
Practical Significance ◽  
Exhaust Emission ◽  
Passenger Vehicle ◽  
Sliding Speed ◽  
Fuel Consumption Rate ◽  
Light Duty ◽  
Proper Operation

Technical level of driving behavior has run as high as 20% impact on vehicle’s fuel consumption, so choosing proper operation mode is one effective way to improve the vehicle’s running fuel economy. Vehicle sliding on level road is often used by driver, and analyzing vehicle’s fuel consumption characteristics during sliding condition has practical significance on realizing the reasonable driving and lowering fuel consumption. Taking some light-duty diesel passenger vehicle as experimental object, this paper discussed the variation discipline and curves involving sliding speed, sliding time and fuel consumption rate based on various sliding tests, especially analyzed the fuel consumption difference of sliding in neutral and sliding in different gears. Finally, following conclusions are achieved: the average fuel consumption rate while vehicle sliding in different gears is similar, which is about to 1/50 of sliding in neutral’. While sliding, the vehicle’s fuel consumption rate basically maintains at a low level. But once the sliding speed decreases too low, the fuel consumption rate increases dramatically. Therefore, aiming at lowing fuel consumption and reducing emission discharge, vehicle sliding in gear should have priority to sliding in neutral and choosing a reasonable sliding speed range is important for reducing vehicle’s running fuel consumption and exhaust emission.

On-Road Portable Emission Measurement Systems Test Data Analysis and Light-Duty Vehicle In-Use Emissions Development

2020 ◽  
Vol 9 (2) ◽  
pp. 111-131
Author(s):  
SoDuk Lee ◽  
◽  
Carl R Fulper ◽  
Daniel Cullen ◽  
Joseph McDonald ◽  
...  
Keyword(s):  
Test Data ◽  
Real World ◽  
Environmental Protection Agency ◽  
Emission Measurement ◽  
Mobile Source ◽  
Measurement Systems ◽  
Light Duty ◽  
Light Duty Vehicle ◽  
Inventory Development ◽  
Light Duty Vehicles

Portable emission measurement systems (PEMS) [1] are used by the US Environmental Protection Agency (EPA) to measure gaseous and particulate matter mass emissions from vehicles in normal, in-use, on-the-road, and “real-world” operations to support many of its programs. These programs include vehicle modeling, emissions compliance, regulatory development, emissions inventory development, and investigations of the effects of real, in-use driving conditions on NOx, CO2, and other regulated pollutants. This article discusses EPA’s analytical methodology for evaluating light-duty vehicle energy and EU Real Driving Emissions (RDE). A simple, data-driven model was developed and validated using measured PEMS emissions test data. The work also included application of the EU RDE procedures and comparison to the PEMS test methodologies and FTP and other chassis dynamometer test data used by EPA for characterizing in-use light- and heavy-duty vehicle emissions. This work was conducted as part of EPA’s participation in the development of UNECE Global Technical Regulations and also supports EPA mobile source emission inventory development. This article discusses the real-world emissions of light-duty vehicles with 12V Start-Stop technology and light-duty vehicles using both gasoline and diesel fuels.

scholarly journals Investigation of Driving Behavior on Performance and Fuel Consumption of Light-Duty Vehicle

2020 ◽  
Vol 13 (4) ◽  
pp. 102-113
Author(s):  
Loay M. Mubarak ◽  
Ahmed Al-Samari
Keyword(s):  
Fuel Consumption ◽  
Real World ◽  
Driving Behavior ◽  
Driving Cycle ◽  
Aggressive Driving ◽  
Data Logger ◽  
Passenger Cars ◽  
Driving Cycles ◽  
Light Duty ◽  
Light Duty Vehicle

This manuscript instrumented two light-duty passenger cars to construct real-world driving cycles for the Baghdad-Basrah highway road in Iraq using a data logger. The recorded data is conducted to obtain typical speed profiles for each vehicle. Each of the recruited vehicles is modelized using Advanced Vehicle Simulator and conducted on the associated created driving cycle to investigate fuel economy and analyze performance. Moreover, to inspect the influence of driving behavior on fuel consumption and emissions, the simulation process is re-implemented by substituting the conducted real-world driving cycle. The analyses are done for the first and second stages of simulation predictions to explore the fuel-penalty of aggressive driving behavior. The analysis for substitution predictions showed that fuel consumption could be reduced by 12.8% due to conducting vehicle under the more consistent real-world driving cycle. However, conducting vehicle under the more aggressive one would increase fuel consumption by 14.6%. The associated emissions change prediction due to the substitution is also achieved and presented.

Development of Operating Mode Distribution Models for Light-Duty Vehicles on Unrestricted Access Roadways

2020 ◽  
Vol 2674 (10) ◽  
pp. 416-428
Author(s):  
Jia Li ◽  
Hanhui He ◽  
Bo Peng
Keyword(s):  
Real World ◽  
Operating Mode ◽  
Specific Power ◽  
Trajectory Data ◽  
Average Speed ◽  
The Real ◽  
Light Duty ◽  
Unrestricted Access ◽  
Data Points ◽  
Light Duty Vehicles

The key correlating traffic variable for modeling vehicle emissions has evolved from average speed to vehicle-specific power (VSP), and recently to operating mode as defined in Motor Vehicle Emission Simulator (MOVES). The analysis of operating mode and its distribution, however, requires a large amount of data and is time consuming and challenging. This paper attempts to build models between the operating mode distributions and the common traffic variable—average speed—to facilitate the emission estimation. Focusing on light-duty vehicles and unrestricted access roadways, a floating car survey was conducted separately on arterials and collectors in Shaoshan, China. The trajectory data were processed to reveal the characteristics of operating mode distributions. A key finding is that, when the data points of the operating mode of idle are excluded, the VSP distributions of the remaining data points follow logistic distributions and the parameters can be linearly regressed with the average speed. Arterials and collectors feature different operating mode distributions even at the same average speed, and therefore different models were developed. The models were then applied to generate operating mode distributions, which were validated with the real-world data from the test bed and which, when compared with the default values generated by MOVES, fit the real-world condition better.

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