Method for Translation of In-Use Fuel Consumption and NOX Emissions Between Different Heavy-Duty Vehicle Routes

Author(s):  
Oscar F. Delgado ◽  
Nigel N. Clark ◽  
Gregory J. Thompson

Portable emissions measurement systems (PEMS) are used to perform in-use measurements for emissions inventory and regulatory applications. PEMS data represent real world conditions more accurately than chassis dynamometer or engine dynamometer testing, arguably being the most realistic method of determining exhaust emissions over a certain driving route. However, measured emissions and fuel consumption depend strongly on both the route followed and the traffic situation that the vehicle encounters. A tool for translation of emissions and fuel consumption between diverse types of vehicle activity is required. The purpose of this paper is to assess the possibility of using route-averaged properties (kinematic parameters) for translation of fuel consumption and NOx emissions for a set of eighteen heavy-duty vehicles operating over up to eight different driving routes. A linear model developed for heavy-duty vehicle chassis dynamometer data modeling has been extended to in-use heavy-duty vehicle data. Two approaches were implemented; the first approach mimicked the prior chassis dynamometer work by incorporating average vehicle speed and average positive acceleration and the second approach incorporated road grade in a characteristic power parameter. The end result is a simple method which was shown to be accurate for estimation of fuel consumption (within 5% relative error) and NOx emissions (within 12% relative error) for over-the-road vehicles over “unseen” roads or traffic situations, without the need to perform additional over-the-road tests.

2013 ◽  
Vol 718-720 ◽  
pp. 1825-1830
Author(s):  
Kong Jian Qin ◽  
Chang Yuan Wang ◽  
Jia Yan ◽  
Xue Hao Liu

Refuse truck accounted for 70% of the sanitation vehicle, which was the major heavy duty vehicle type in city. Therefore its fuel economy and emission characteristics were under higher requirements. This research did the emission test on the chassis dynamometer by using compressed truck, testing C-WTCV and CCBC circle emission, and fuel consumption respectively. The research showed the Km fuel consumption of CCBC circle was about 1.3 times of the C-WTVC from the analysis of fuel consumption and the emission of CO2.From the analysis of emission factor, the emission of NOX and CO of the CCBC circle was both higher than the C-WTVC, respectively 1.9 times and 1.4 times. However, the emission of HC was only 36% of the C-WTVC. C-WTVC was very similar to the motor of the CCBC circle in city, however the motorway cycle and emission both had significant difference from CCBC circle.


2021 ◽  
Vol 268 ◽  
pp. 01055
Author(s):  
Dandan Xu ◽  
Zhongming Gao ◽  
Yong Guo ◽  
Yan Yan ◽  
Fengbin Wang ◽  
...  

This study selects a China VI heavy duty vehicle for PEMS test, and Based on the measurement results of vehicle specific power (VSP) parameters, the VSP calculation formula applicable to this study is proposed , And analyzes the distribution characteristics of VSP, and at the same time according to the fuel consumption and emission data of the actual road driving process collected by the vehicle, The effect of VSP on vehicle fuel consumption and emission characteristics and the correlation between the two are studied. Results show that VSP of the vehicle are mainly concentrated in the interval -10 ≤ VSP ≤ 10kw / t, in which the vehicle driving time accounts for about 99.3% of the total time; the correlation coefficient between VSP and average fuel consumption is about 0.93, there is a strong correlation; The changes of CO, CO2, NOX and PN with VSP all show as that under the same absolute value of VSP, the pollutants emission rate in the VSP> 0 interval is higher than the VSP <0 interval, in which the correlation between VSP and CO, CO2, PN emissions is more strong, but poorly correlated with NOX emissions.


Author(s):  
Peter Vasquez ◽  
Edwin Quiros ◽  
Gerald Jo Denoga ◽  
Robert Michael Corpus ◽  
Robert James Lomotan

Abstract Efforts to mitigate climate change include lowering of greenhouse gas emissions by reducing fuel consumption in the transport sector. Various vehicle technologies and interventions for better fuel economy eventually require chassis dynamometer testing using drive cycles for validation. As such, the methodology to generate these drive cycles from on-road data should produce drive cycles that closely represent actual on-road driving from the fuel economy standpoint. This study presents a comparison of the fuel economy measured from a drive cycle developed using road load energy as a major assessment criterion and the actual on-road fuel economy of a 2013 Isuzu Crosswind utility vehicle used in the UV Express transport fleet in Metro Manila, Philippines. In this approach to drive cycle construction from on-road data, the ratio of the total road load energy of the generated drive cycle to that of the on-road trip is made the same ratio as their respective durations. On-road velocity and fuel consumption were recorded as the test vehicle traversed the 42.5 km. Sucat to Lawton route and vice versa in Metro Manila. Gathered data were processed to generate drive cycles using the modified Markov Chain approach. Three drive cycles of decreasing duration, based on the practicality of testing on a chassis dynamometer, were generated using three arbitrary data compression ratios. These drive cycles were tested using the same vehicle on the chassis dynamometer and compared with the on-road data using road load energy, fuel economy, average speed, and maximum acceleration. For the 893-seconds drive cycle generated, the road load energy error was 3.93% and fuel economy difference of 1.14%. For the 774-seconds cycle generated, the road load energy error was 4.34% and fuel economy difference was 0.91%. For the 664-seconds drive cycle, the road load energy error was 3.68% and fuel economy difference was 0.91%. On-road fuel economy for the 42.5-km. route averaged over nine round trips was 8.785 km/L. Based on the results, the road load energy criterion approach of drive cycle construction methodology can generate drive cycles which can very closely estimate on-road fuel economy.


2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Qiang Liu ◽  
Jianguang Xie ◽  
Zhixiang Zhang

The fuel consumption model for a vehicle forms a basis and method for evaluating the social benefit of road reconstruction. Based on the theoretical fuel consumption model of vehicles, the influence mechanism of the apparent parameters of the road surface on the fuel consumption of vehicles and their sensitivity was analysed. The baseline state was defined on the basis of the roughness, a parameter with significant influence. In addition, a method for acquiring fuel consumption parameters was proposed to establish a one-parameter relational model for the roughness and fuel consumption of vehicles in the baseline state based on measured data. Moreover, by considering the effects of the friction coefficient, deflection of the road surface, and vehicle speed on the fuel consumption, a modified model for the fuel consumption of vehicles applicable to road reconstruction was established. Finally, a method for measuring the energy-saving benefit of vehicles was proposed based on the characteristics of reconstructed roads. The research provides a basis for evaluating the social benefit acquired from reconstructed roads.


1998 ◽  
Vol 1625 (1) ◽  
pp. 165-172 ◽  
Author(s):  
Catherine Ross ◽  
Randall Guensler ◽  
Paula Stevens

The next generation of air quality models demands a better understanding of medium- and heavy-duty vehicle activities and the relationship between these activities and emissions. Understanding fleet characteristics and their associated impact, therefore, is critically important. Data collected in a 1996 commercial vehicle trip survey for the Atlanta region are presented and analyzed. A survey data collection effort undertaken in 1996, which included the collection of data related to spatial, temporal, cargo, land use, and vehicle characteristics, is described. The results of a series of statistical analyses are reported and discussed. The results of geographic information systems analyses, which provide a spatial picture of commercial vehicle activity, are presented. The spatial analysis combines vehicle, cargo, and land use characteristics with spatial and temporal data within the study area. The results of this study provide a compelling snapshot of commercial vehicle activity in the Atlanta area.


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