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.

Digital Signal Processing Approach to Identify the Boundary of Vehicle Idle Status during Operation

2018 ◽  
Vol 2672 (25) ◽  
pp. 35-45
Author(s):  
Qing Li ◽  
Fengxiang Qiao ◽  
Lei Yu ◽  
Shuyan Chen ◽  
Tiezhu Li
Keyword(s):  
Fuel Consumption ◽  
Digital Signal ◽  
Operating Mode ◽  
Frequency Component ◽  
High Frequency Component ◽  
Specific Power ◽  
Emission Measurement ◽  
Emission Rates ◽  
Wide Range ◽  
Light Duty Vehicle

The MOVES is a tool to estimate on- and off-road emissions, in which 23 operating mode identification bins were defined based on vehicles’ specific power, speed, and acceleration. Bin 1 indicates an idling mode with the speed within 1.0 mph. However, the speed boundary in an earlier model of MOBILE 6.2 was 2.5 mph. Neither the change in the idling definition of the two models nor the speed boundary were investigated and discussed. This study proposed a method to theoretically redefine the idle boundary by characterizing vehicle emission rates. Vehicle speeds close to 0 mph were carefully studied based on 10,000-mile on-board emission tests in the state of Texas. A portable emission measurement system was used to detect real-time emissions from a 12-year-old gasoline light-duty vehicle, while the vehicle’s activity information was collected from an On-Board Diagnostic (OBD) II port. Power spectral density analysis was conducted on the collected emission and fuel consumption rates to identify a cut-off point that separates the frequency period with higher and lower energy. A Chebeshev I filter was designed to remove the high-frequency component to visualize the variables of emissions and fuel consumption on the vehicle’s moving trend lines. Based on observation and analysis results, 2.26 mph was identified as a boundary for an idle mode at an acceptance level of 95% significant change. It is recommended that the proposed method be applied to the emissions of more different types of vehicles with a wide range of mileages to validate the newly defined idle boundary.

scholarly journals Variability in Measured Real-World Operational Energy Use and Emission Rates of a Plug-In Hybrid Electric Vehicle

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1140 ◽  
Author(s):  
H. Christopher Frey ◽  
Xiaohui Zheng ◽  
Jiangchuan Hu
Keyword(s):  
Real World ◽  
Hybrid Electric Vehicle ◽  
Energy Use ◽  
Average Energy ◽  
Specific Power ◽  
Emission Measurement ◽  
Emission Rates ◽  
Wide Range ◽  
Hybrid Electric ◽  
Cold Starts

Compared to comparably sized conventional light duty gasoline vehicles (CLDGVs), plug-in hybrid electric vehicles (PHEVs) may offer benefits of improved energy economy, reduced emissions, and the flexibility to use electricity as an energy source. PHEVs operate in either charge depleting (CD) or charge sustaining (CS) mode; the engine has the ability to turn on and off; and the engine can have multiple cold starts. A method is demonstrated for quantifying the real-world activity, energy use, and emissions of PHEVs, taking into account these operational characteristics and differences in electricity generation resource mix. A 2013 Toyota Prius plug-in was measured using a portable emission measurement system. Vehicle specific power (VSP) based modal average energy use and emission rates are inferred to assess trends in energy use and emissions with respect to engine load and for comparisons of engine on versus engine off, and cold start versus hot stabilized running. The results show that, compared to CLDGVs, the PHEV operating in CD mode has improved energy efficiency and lower CO2, CO, HC, NOx, and PM2.5 emission rates for a wide range of power generation fuel mixes. However, PHEV energy use and emission rates are highly variable, with periods of relatively high on-road emission rates related to cold starts.

Effect of Air-Conditioning on Light Duty Gasoline Vehicles Fuel Economy

2019 ◽  
Vol 2673 (5) ◽  
pp. 131-141 ◽  
Author(s):  
Tanzila Khan ◽  
H. Christopher Frey
Keyword(s):  
Fuel Economy ◽  
Real World ◽  
Air Conditioning ◽  
Energy Use ◽  
Motor Vehicle ◽  
The Real ◽  
Light Duty ◽  
Wide Range ◽  
Gasoline Vehicles ◽  
Few Data

With more stringent U.S. fuel economy (FE) standards, the effect of auxiliary devices such as air-conditioning (AC) have received increased attention. AC is the largest auxiliary engine load for light duty gasoline vehicles (LDGVs). However, there are few data regarding the effect of AC operation on FE for LDGVs based on real-world measurements, especially for recent model year vehicles. The Motor Vehicle Emission Simulator (MOVES) is a regulatory model for estimating on-road vehicle energy-use and emissions. MOVES adjusts vehicle energy-use rates for AC effects. However, MOVES-predicted FE with AC has not been evaluated based on empirical measurements. The research objectives are to quantify the LDGVs FE penalty from AC and assess the accuracy of MOVES2014a-predicted FE with AC. The AC effect on real-world fleet-average FE was quantified based on 78 AC-off vehicles versus 55 AC-on vehicles, measured with onboard instruments on defined study routes. MOVES2014a-based FE penalty from AC was evaluated based on real-world estimates and chassis dynamometer-based FE test results used for FE ratings. The real-world FE penalty ranges between 1.3% and 7.5% among a wide range of driving cycles. Fuel consumption at idle is 13% higher with AC on. MOVES underestimates the real-world FE with AC by 6%, on average. MOVES overestimates the AC effect on cycle-average FE ranging between 13.5% and 18.5% for real-world and MOVES default cycles, and between 11.1% and 14.5% for standard cycles.

scholarly journals Characterization of Exhaust CO, HC and NOx Emissions from Light-Duty Vehicles under Real Driving Conditions

Atmosphere ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1125
Author(s):  
Hui Mei ◽  
Lulu Wang ◽  
Menglei Wang ◽  
Rencheng Zhu ◽  
Yunjing Wang ◽  
...  
Keyword(s):  
Specific Power ◽  
Emission Measurement ◽  
Nox Emissions ◽  
Emission Rates ◽  
Gaseous Emissions ◽  
Passenger Cars ◽  
Light Duty ◽  
Driving Conditions ◽  
Hc Emissions ◽  
Light Duty Vehicles

On-road exhaust emissions from light-duty vehicles are greatly influenced by driving conditions. In this study, two light-duty passenger cars (LDPCs) and three light-duty diesel trucks (LDDTs) were tested to investigate the on-road emission factors (EFs) with a portable emission measurement system. Emission characteristics of carbon monoxide (CO), hydrocarbons (HC) and nitrogen oxides (NOx) emitted from vehicles at different speeds, accelerations and vehicle specific power (VSP) were analyzed. The results demonstrated that road conditions have significant impacts on regulated gaseous emissions. CO, NOx, and HC emissions from light-duty vehicles on urban roads increased by 1.1–1.5, 1.2–1.4, and 1.9–2.6 times compared with those on suburban and highway roads, respectively. There was a rough positive relationship between transient CO, NOx, and HC emission rates and vehicle speeds, while the EFs decreased significantly with the speed decrease when speed ≤ 20 km/h. The emissions rates of NOx and HC tended to increase and then decrease as the acceleration increased and the peak occurred at 0 m/s2 without considering idling conditions. For HC and CO, the emission rates were low and changed gently with VSP when VSP < 0, while emission rates increased gradually with the VSP increase when VSP > 0. For NOx NOx emission rates were lower and had no obvious change when VSP < 0. However, NOx emissions were positively correlated with VSP, when VSP > 0.

scholarly journals Evaluating the Effects of One-Way Traffic Management on Different Vehicle Exhaust Emissions Using an Integrated Approach

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Jieyu Fan ◽  
Kun Gao ◽  
Yingying Xing ◽  
Jian Lu
Keyword(s):  
Traffic Management ◽  
Integrated Approach ◽  
Exhaust Emissions ◽  
Traffic Emissions ◽  
Specific Power ◽  
Emission Measurement ◽  
Emission Rates ◽  
Vehicle Exhaust ◽  
Emission Data ◽  
The Road

One-way traffic management is a recognized traffic organization to improve traffic efficiency and safety, but its effects on different traffic emissions remains unclear. This paper aims to investigate the impacts of one-way traffic management on three typical vehicle exhaust emissions including Carbonic Oxide (CO), Hydrocarbon Compounds (HC), and Nitrogen Oxides (NOx) in a traffic system using an integrated approach. Field experiment was conducted to collect the vehicular emission data under different traffic conditions using the onboard portable emission measurement system. An instantaneous emission model (i.e., Vehicle Specific Power) is calibrated using the collected field emission data and is incorporated into the microscopic traffic simulation tool VISSIM for quantifying the emissions before and after one-way traffic management through simulation. Two scenarios based on real networks and traffic demands of peak hours in part areas of Shanghai are developed for simulation and evaluation. The results show that in the intersections, the emission rates of COHC, NOx after one-way traffic management is significantly reduced by 20.46%, 21.29% and 21.06%, respectively. In the road sections, the emission rates of CO, HC, NOx in the road sections decrease by 23.38% and 26.29%. The overall CO, HC, NOx emissions in the studied network reduce by 21.34%, 22.29% and 23.77% separately due to one-way traffic management. The results provide insights into the derivative effects of one-way traffic management on traffic emissions in the intersections, road sections and network levels, and thus support scientific traffic management for promoting the sustainability of transport system.

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

scholarly journals Particle Mass Emission Rates from Current-Technology, Light-Duty Gasoline Vehicles

2000 ◽  
Vol 50 (6) ◽  
pp. 930-935 ◽  
Author(s):  
Richard E. Chase ◽  
Gary J. Duszkiewicz ◽  
Trescott E. Jensen ◽  
Desmonia Lewis ◽  
E. John Schlaps ◽  
...  
Keyword(s):  
Particle Mass ◽  
Emission Rates ◽  
Current Technology ◽  
Light Duty ◽  
Gasoline Vehicles

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.

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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