Real-World Freeway and Ramp Activity and Emissions for Light-Duty Gasoline Vehicles

2017 ◽  
Vol 2627 (1) ◽  
pp. 17-25 ◽  
Author(s):  
H. Christopher Frey ◽  
Maryam Delavarrafiee ◽  
Sanjam Singh
Keyword(s):  
Study Design ◽  
Real World ◽  
Time Of Day ◽  
Specific Power ◽  
Peak Time ◽  
Oxides Of Nitrogen ◽  
Design Quality ◽  
Light Duty ◽  
Gasoline Vehicles ◽  
Vehicle Activity

There are few data on differences in real-world emissions by in-use vehicles when they operate on freeway ramps compared with operations on the freeway itself. The objective of this paper is to quantify the variability in link-based emissions rates for on-ramps and off-ramps in comparison to rates on freeways. Real-world measurements were made with the use of a portable emissions measurement system (PEMS) for selected vehicles, ramps, and freeway segments. The methodology included development of a study design for field data collection of vehicle activity and emissions, execution of the study design, quality assurance of the raw data, and analysis of the quality-assured data. Four light-duty gasoline vehicles were driven on two routes, each composed of on-ramp, freeway, and off-ramp links. Data were collected for morning peak, evening peak, and off-peak time periods. A PEMS test was used to measure exhaust emissions of oxides of nitrogen (NOx), hydrocarbon (HC), and carbon monoxide (CO). The emissions rates for on-ramps were shown to be substantially higher than rates on freeways for NOx, HC, and CO. Some of this variability in emissions rates can be explained by link average vehicle specific power, which can vary by time of day and from one location to another. The variability in emissions rates by route and time of day indicates that there can be complex interactions between traffic flow, road geometry, and emissions rates. Recommendations are offered for additional study and regarding how these results can be used by researchers and practitioners.

Analysis of emissions from various driving cycles based on real driving measurements obtained in a high-altitude city

2020 ◽  
Vol 234 (6) ◽  
pp. 1563-1571 ◽  
Author(s):  
Meng Lyu ◽  
Xiaofeng Bao ◽  
Yunjing Wang ◽  
Ronald Matthews
Keyword(s):  
High Altitude ◽  
Real World ◽  
Vehicle Emissions ◽  
Control Strategies ◽  
Driving Cycle ◽  
Specific Power ◽  
Test Cycle ◽  
Light Duty ◽  
And Control ◽  
Light Duty Vehicles

Vehicle emissions standards and regulations remain weak in high-altitude regions. In this study, vehicle emissions from both the New European Driving Cycle and the Worldwide harmonized Light-duty driving Test Cycle were analyzed by employing on-road test data collected from typical roads in a high-altitude city. On-road measurements were conducted on five light-duty vehicles using a portable emissions measurement system. The certification cycle parameters were synthesized from real-world driving data using the vehicle specific power methodology. The analysis revealed that under real-world driving conditions, all emissions were generally higher than the estimated values for both the New European Driving Cycle and Worldwide harmonized Light-duty driving Test Cycle. Concerning emissions standards, more CO, NOx, and hydrocarbons were emitted by China 3 vehicles than by China 4 vehicles, whereas the CO2 emissions exhibited interesting trends with vehicle displacement and emissions standards. These results have potential implications for policymakers in regard to vehicle emissions management and control strategies aimed at emissions reduction, fleet inspection, and maintenance programs.

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.

Geospatial Variation of Real-World Tailpipe Emission Rates for Light-Duty Gasoline Vehicles

2020 ◽  
Vol 54 (14) ◽  
pp. 8968-8979
Author(s):  
Tanzila Khan ◽  
H. Christopher Frey ◽  
Nikhil Rastogi ◽  
Tongchuan Wei
Keyword(s):  
Real World ◽  
Emission Rates ◽  
Light Duty ◽  
Gasoline Vehicles

Evaluation of the Precision and Accuracy of Cycle-Average Light Duty Gasoline Vehicles Tailpipe Emission Rates Predicted by Modal Models

2020 ◽  
Vol 2674 (7) ◽  
pp. 566-584
Author(s):  
Tongchuan Wei ◽  
H. Christopher Frey
Keyword(s):  
Goodness Of Fit ◽  
Motor Vehicle ◽  
Vehicle Group ◽  
Specific Power ◽  
Emission Measurement ◽  
Emission Rates ◽  
Light Duty ◽  
Wide Range ◽  
Gasoline Vehicles ◽  
Precision And Accuracy

A vehicle specific power (VSP) modal model and the MOtor Vehicle Emission Simulator (MOVES) Operating Mode (OpMode) model have been used to evaluate and quantify the fuel use and emission rates (FUERs) for on-road vehicles. These models bin second-by-second FUERs based on factors such as VSP, speed, and others. The validity of binning approaches depends on their precision and accuracy in predicting variability in cycle-average emission rates (CAERs). The objective is to quantify the precision and accuracy of the two modeling methods. Since 2008, North Carolina State University has used portable emission measurement systems to measure tailpipe emission rates for 214 light duty gasoline vehicles on 1,677 driving cycles, including 839 outbound cycles and 838 inbound cycles on the same routes. These vehicles represent a wide range of characteristics and emission standards. For each vehicle, the models were calibrated based on outbound cycles and were validated based on inbound cycles. The goodness-of-fit of the calibrated models was assessed using linear least squares regression without intercept between model-predicted versus empirical CAERs for individual vehicles. Based on model calibration and validation, the coefficients of determination ( R2) typically range from 0.60 to 0.97 depending on the vehicle group and pollutant, indicating moderate to high precision, with precision typically higher for higher-emitting vehicle groups. The slopes of parity plots for each vehicle group and all vehicles typically range from 0.90 to 1.10, indicating good accuracy. The two modeling approaches are similar to each other at the microscopic and macroscopic levels.

Evaluating real-world emissions of light-duty gasoline vehicles with deactivated three-way catalyst converters

2018 ◽  
Vol 9 (1) ◽  
pp. 126-132 ◽  
Author(s):  
Xuan Zheng ◽  
Ye Wu ◽  
Shaojun Zhang ◽  
Liqiang He ◽  
Jiming Hao
Keyword(s):  
Real World ◽  
Light Duty ◽  
Gasoline Vehicles ◽  
Three Way Catalyst

How Many Trajectories Are Needed to Develop Facility- and Speed-Specific Vehicle-Specific Power Distributions for Emission Estimation? Case Study in Beijing

2019 ◽  
Vol 2673 (11) ◽  
pp. 779-790
Author(s):  
Zeyu Zhang ◽  
Guohua Song ◽  
Zhiqiang Zhai ◽  
Chenxu Li ◽  
Yizheng Wu
Keyword(s):  
Sample Size ◽  
Motor Vehicle ◽  
Specific Power ◽  
Activity Data ◽  
Light Duty ◽  
Emission Estimation ◽  
Vehicle Activity ◽  
Light Duty Vehicles ◽  
Mean Square Errors

Vehicle-specific power (VSP) distributions, or operating mode (OpMode) distributions, are one of the most important parameters in VSP-based emission models, such as the motor vehicle emission simulator (MOVES) model. The collection of second-by-second vehicle activity data is required to develop facility- and speed-specific (FaSS) VSP distributions. This then raises the problem of how many trajectories are needed to develop FaSS VSP distributions for emission estimation. This study attempts to investigate the adaptive sample size for developing robust VSP distributions for emission estimations for light-duty vehicles. First, vehicle activity data are divided into trajectories and categorized into different trajectory pools. Then, the uncertainty of FaSS VSP distribution caused by sample size is analyzed. Further, the relationship between VSP distribution sample size and emission factor uncertainty is discussed. The case study indicates that error in developing FaSS VSP distributions decreases significantly with increased sample size. In different speed bins, the sample size required to develop robust FaSS VSP distributions and estimate emission factors is significantly different. In detail, in each speed bin, for a 90% confidence level, 30 trajectories (1,800 s) are enough to develop robust FaSS VSP distributions for light-duty vehicles with the root mean square errors (RMSEs) lower than 2%, which means errors in calculating fuel consumption and greenhouse gas (GHG) emissions are lower than 5%. However, 35 trajectories (2,100 s) are needed to estimate emissions of carbon monoxide (CO), nitrogen oxide (NOX), and hydrocarbons (HC) with an estimation error lower than 5%.

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