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

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.

Download Full-text

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

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/2503-14 ◽

2015 ◽

Vol 2503 (1) ◽

pp. 128-136 ◽

Cited By ~ 8

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.

Download Full-text

Analysis of the influence of RDE test data processing methods on the emission results of China 6 light duty vehicles

E3S Web of Conferences ◽

10.1051/e3sconf/202126801022 ◽

2021 ◽

Vol 268 ◽

pp. 01022

Author(s):

Zhihong Wang ◽

Penghui Wu ◽

Nenghui Yu ◽

Yuanjun Zhang ◽

Zhijun Wang

Keyword(s):

Data Processing ◽

Test Data ◽

Emission Factor ◽

Vehicle Emission ◽

Emission Data ◽

Processing Methods ◽

Light Duty ◽

Light Duty Vehicle ◽

Light Duty Vehicles ◽

Data Processing Methods

The CO2 moving average window(MAW) method is used to process RDE (real drive emissions) emissions data in China 6 light duty vehicle emissions regulations, while the Euro 6 light duty vehicle emission regulations allow to use both of MAW and power binning(PB) method to deal with RDE emission data. In order to study the difference between the two data processing methods and analyze the differences in the emission results, 10 different types of light duty vehicles are conducted RDE test with PEMS (portable emissions measurement system), and the test data are processed by the two methods separately. The results show that there is a little difference between MAW and PB, while both of them can satisfy the vehicle emission assessment. The PB method calculates the emission factors higher than the MAW method. After removing the cold start and idle condition data, the results of PB is similar to MAW. Besides, reducing the average speed limit of urban working conditions in PB has a greater impact on the urban driving condition emission factor, but less on the whole cycle emission factor.

Download Full-text

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

Energies ◽

10.3390/en14237915 ◽

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.

Download Full-text

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

10.20944/preprints202111.0029.v1 ◽

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.

Download Full-text

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

Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering ◽

10.1177/0954407019898959 ◽

2020 ◽

Vol 234 (6) ◽

pp. 1563-1571 ◽

Cited By ~ 1

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.

Download Full-text

High Emitter Light Duty Vehicle Contributions to On-road Mobile Emissions in 2018 and 2030

Studies in Engineering and Technology ◽

10.11114/set.v2i1.838 ◽

2015 ◽

Vol 2 (1) ◽

pp. 47 ◽

Cited By ~ 3

Author(s):

Susan Collet ◽

Toru Kidokoro ◽

Yukio Kinugasa ◽

Prakash Karamchandani ◽

Allison DenBleyker

Keyword(s):

Air Quality ◽

Environmental Protection Agency ◽

Protection Agency ◽

Vehicle Miles Traveled ◽

Improvement Strategy ◽

Quality Improvement Strategy ◽

Light Duty ◽

Air Quality Improvement ◽

Light Duty Vehicle ◽

Tier 3

Quantifying the proportion of normal- and high-emitting vehicles and their emissions is vital for creating an air quality improvement strategy for emission reduction policies. This paper includes the California LEV III and United States Environmental Protection Agency Tier 3 vehicle regulations in this projection of high emitter quantification for 2018 and 2030. Results show high emitting vehicles account for up to 6% of vehicle population and vehicle miles traveled. Yet, they will contribute to over 75% of exhaust and 66% of evaporative emissions. As these high emitting vehicles are gradually retired from service and are removed from the roads, the overall effect on air quality from vehicle emissions will be reduced.

Download Full-text

Inter-Laboratory Correlation Exercise with Portable Emissions Measurement Systems (PEMS) on Chassis Dynamometers

Applied Sciences ◽

10.3390/app8112275 ◽

2018 ◽

Vol 8 (11) ◽

pp. 2275 ◽

Cited By ~ 9

Author(s):

Barouch Giechaskiel ◽

Simone Casadei ◽

Michele Mazzini ◽

Mario Sammarco ◽

Gisella Montabone ◽

...

Keyword(s):

Particle Number ◽

Laboratory Method ◽

Measurement Systems ◽

Type Approval ◽

Light Duty ◽

Repeatability And Reproducibility ◽

Light Duty Vehicle ◽

The Mean ◽

Mean Differences ◽

The Individual

The recently introduced Real Driving Emissions (RDE) light-duty vehicle emissions regulation requires testing with Portable Emissions Measurement Systems (PEMS) during type approval and in-service conformity. The studies on the accuracy of PEMS today are limited. An inter-laboratory correlation exercise with PEMS took place in Italy in 2017. Eight laboratories measured exhaust emissions from a Golden Euro 6 gasoline vehicle with a Golden PEMS installed in it, along with the individual lab’s own PEMS, following the regulated laboratory method (bags from the dilution tunnel). The data of the exercise were used to estimate the repeatability and reproducibility of the methodology with PEMS. The statistical analysis estimated reproducibility of 2.9% (bags) to 5.5% (lab PEMS) for CO2, 20–25% for CO (all methods), 23–31% for NOx (all methods), and 29% (tunnel, Golden PEMS) to 39% (lab PEMS) for particle number. The mean differences of the PEMS to the regulated method were ±1.5 g/km (or ±1%) for CO2, <16 mg/km (or <5%) for CO, <4 mg/km (or <11%) for NOx and 1 × 1011 particles/km (40%) for particle number. The results of this study confirm the satisfactory performance of PEMS and the permissible tolerances introduced in RDE regulation.

Download Full-text

Benefits of Electrified Powertrains in Medium- and Heavy-Duty Vehicles

World Electric Vehicle Journal ◽

10.3390/wevj11010012 ◽

2020 ◽

Vol 11 (1) ◽

pp. 12

Author(s):

Ram Vijayagopal ◽

Aymeric Rousseau

Keyword(s):

Environmental Protection ◽

Environmental Protection Agency ◽

Fuel Saving ◽

Heavy Duty ◽

Protection Agency ◽

Light Duty ◽

Design Choice ◽

The Us ◽

Light Duty Vehicles ◽

Heavy Duty Vehicles

The benefits of electrified powertrains for light-duty vehicles are well understood, however sufficient published information is not available on the benefits of advanced powertrains on the various types of medium and heavy duty vehicles. Quantifying the benefits of powertrain electrification will help fleet operators understand the advantages or limitations in adopting electrified powertrains in their truck fleets. Trucks vary in size and shape, as they are designed for specific applications. It is necessary to model each kind of truck separately to understand what kind of powertrain architecture will be feasible for their daily operations. This paper examines 11 types of vehicles and 5 powertrain technology choices to quantify the fuel saving potential of each design choice. This study uses the regulatory cycles proposed by the US Environmental Protection Agency (EPA) for measuring fuel consumption.

Download Full-text