Gurdas S. Sandhu

Road Grade Measurement Using In-Vehicle, Stand-Alone GPS with Barometric Altimeter

Real-world vehicle fuel use and emission rates are sensitive to road grade. There is a need for a practical method for measuring road grade in combination with on-board measurement of vehicle activity, energy use, and emissions using portable emissions measurement systems (PEMS). This paper focuses on quantification of the accuracy and precision of a low-cost method using a stand-alone global positioning system (GPS) receiver with an in-built barometric altimeter. Approximately 100 one-way runs were made on each of several study routes. The sensitivity of average grade estimates to the averaging distance over which grade is estimated is quantified. The repeatability of vehicle location and distance traveled is quantified. The run-to-run variability and confidence intervals for average estimates of grade are quantified. The accuracy of the grade estimates is evaluated in comparison to LIDAR-based estimates. The low-cost method is shown to be accurate, but imprecision in the measurements leads to a need for typically at least 10 or more repeated runs, depending on the desired precision of the average estimate of grade.

Effects of Errors on Vehicle Emission Rates from Portable Emissions Measurement Systems

Portable emissions measurement systems (PEMS) are useful for quantification of real-world vehicle activity, energy use, and emissions. However, there is no standard methodology for processing PEMS data; this can lead to errors in reported results. PEMS typically include tailpipe exhaust gas and particle analyzers, Global Positioning System (GPS) receivers, engine sensors, and electronic control unit (ECU) data loggers. The sensitivity of estimated emission rates to random errors in measurements is quantified. Methods are evaluated for identification and correction of improper synchronization of PEMS, ECU, and GPS data streams and for road grade estimation. Estimated fuel use and emission rates for light- and heavy-duty vehicles are sensitive to errors in intake manifold absolute pressure and engine revolutions per minute values and in indicators of air-to-fuel ratio including carbon dioxide and oxygen concentrations. Synchronization can be aided by maximizing the Pearson correlation coefficient between two indicator variables and confirming the result by matching concurrent increases in indicator variables. The effect of improper synchronization on estimated modal emission rates is quantified. Modal average emission rates based on vehicle-specific power (VSP) are more sensitive to improperly synchronized engine versus GPS data. Improperly synchronized data streams result in decreased variability between the lowest and highest modal average emission rates. Estimation of road grade from a linear least squares slope of elevation over a specified distance is demonstrated. VSP-based modal fuel use and pollutant emission rates are less sensitive to differences in road grade than to errors in synchronization.

Real-World Measurement and Evaluation of Duty Cycles, Fuels, and Emission Control Technologies of Heavy-Duty Trucks

The purpose of this study is to assess the robustness of relative comparisons of emission rates between fuels and technologies to differences in real-world duty cycles on the basis of in-use measurements of five heavy-duty diesel vehicles (HDDVs). Prior comparisons of biodiesel and ultra-low-sulfur diesel emissions, recent changes in emission standards applicable to HDDVs, and typical emission control technologies used in these vehicles are reviewed. The study methodology includes field measurements with a portable emission measurement system and related instruments and sensors for five HDDVs operated in normal service by professional drivers on multiple round-trip routes within North Carolina. Duty cycles and emission rates are quantified on the basis of the manifold absolute pressure, which is an indicator of engine load. Variability in engine load for each observed round trip is quantified on the basis of the cumulative distribution function of normalized manifold absolute pressure. The effect of variability in duty cycles on fuel-based emission rates for nitrogen oxides, carbon monoxide, hydrocarbons, and particulate matter is evaluated. Comparisons are made for emissions of three trucks operated on B20 biodiesel and ultra-low-sulfur diesel. Furthermore, comparisons of five trucks with model years ranging from 1999 to 2010 illustrate the impact of different emission standards and emission control technologies on real-world emission rates. A key finding is that relative comparisons pertaining to fuels and technologies are robust to variability in observed duty cycles.

In-use activity, fuel use, and emissions of heavy-duty diesel roll-off refuse trucks.

The objectives of this study were to quantify real-world activity, fuel use, and emissions for heavy duty diesel roll-off refuse trucks; evaluate the contribution of duty cycles and emissions controls to variability in cycle average fuel use and emission rates; quantify the effect of vehicle weight on fuel use and emission rates; and compare empirical cycle average emission rates with the U.S. Environmental Protection Agency’s MOVES emission factor model predictions. Measurements were made at 1 Hz on six trucks of model years 2005 to 2012, using onboard systems. The trucks traveled 870 miles, had an average speed of 16 mph, and collected 165 tons of trash. The average fuel economy was 4.4 mpg, which is approximately twice previously reported values for residential trash collection trucks. On average, 50% of time is spent idling and about 58% of emissions occur in urban areas. Newer trucks with selective catalytic reduction and diesel particulate filter had NOx and PM cycle average emission rates that were 80% lower and 95% lower, respectively, compared to older trucks without. On average, the combined can and trash weight was about 55% of chassis weight. The marginal effect of vehicle weight on fuel use and emissions is highest at low loads and decreases as load increases. Among 36 cycle average rates (6 trucks × 6 cycles), MOVES-predicted values and estimates based on real-world data have similar relative trends. MOVES-predicted CO2 emissions are similar to those of the real world, while NOx and PM emissions are, on average, 43% lower and 300% higher, respectively. The real-world data presented here can be used to estimate benefits of replacing old trucks with new trucks. Further, the data can be used to improve emission inventories and model predictions. Implications: In-use measurements of the real-world activity, fuel use, and emissions of heavy-duty diesel roll-off refuse trucks can be used to improve the accuracy of predictive models, such as MOVES, and emissions inventories. Further, the activity data from this study can be used to generate more representative duty cycles for more accurate chassis dynamometer testing. Comparisons of old and new model year diesel trucks are useful in analyzing the effect of fleet turnover. The analysis of effect of haul weight on fuel use can be used by fleet managers to optimize operations to reduce fuel cost.

Method for modeling driving cycles, fuel use, and emissions for over snow vehicles.

As input to a winter use plan, activity, fuel use, and tailpipe exhaust emissions of over snow vehicles (OSV), including five snow coaches and one snowmobile, were measured on a designated route in Yellowstone National Park (YNP). Engine load was quantified in terms of vehicle specific power (VSP), which is a function of speed, acceleration, and road grade. Compared to highway vehicles, VSP for OSVs is more sensitive to rolling resistance and less sensitive to aerodynamic drag. Fuel use rates increased linearly (R2>0.96) with VSP. For gasoline-fueled OSVs, fuel-based emission rates of carbon monoxide (CO) and nitrogen oxides (NOx) typically increased with increasing fuel use rate, with some cases of very high CO emissions. For the diesel OSVs, which had selective catalytic reduction and diesel particulate filters, fuel-based NOx and particulate matter (PM) emission rates were not sensitive to fuel flow rate, and the emission controls were effective. Inter vehicle variability in cycle average fuel use and emissions rates for CO and NOx was substantial. However, there was relatively little inter-cycle variation in cycle average fuel use and emission rates when comparing driving cycles. Recommendations are made regarding how real-world OSV activity, fuel use, and emissions data can be improved.