To accurately estimate real-world v

To accurately estimate real-world vehicle emission at 1 Hz the road grade for each second
of data must be quantified. Failure to incorporate road grade can result in over or underestimation
of a vehicle’s power output and hence cause inaccuracy in the instantaneous
emission estimate. This study proposes a simple LiDAR (Light Detection And Ranging) –
GIS (Geographic Information System) road grade estimation methodology, using GIS software
to interpolate the elevation for each second of data from a Digital Terrain Map (DTM).
On-road carbon dioxide (CO2) emissions from a passenger car were recorded by Portable
Emission Measurement System (PEMS) over 48 test laps through an urban-traffic network.
The test lap was divided into 8 sections for micro-scale analysis. The PHEM instantaneous
emission model (Hausberger, 2003) was employed to estimate the total CO2 emission
through each lap and section. The addition of the LiDAR-GIS road grade to the PHEM modelling
improved the accuracy of the CO2 emission predictions. The average PHEM estimate
(with road grade) of the PEMS measured section total CO2 emission (n = 288) was 93%, with
90% of the PHEM estimates between 80% and 110% of the PEMS recorded value. The
research suggests that instantaneous emission modelling with LiDAR-GIS calculated road
grade is a viable method for generating accurate real-world micro-scale CO2 emission estimates.
The sensitivity of the CO2 emission predictions to road grade was also tested by lessening
and exaggerating the gradient profiles, and demonstrates that assuming a flat profile
could cause considerable error in real-world CO2 emission estimation.

ผลลัพธ์ (อังกฤษ) 2:

Real-World Vehicle Emission Estimate accurately to 1 Hz at the Road grade for each Second
of Data must be quantified. Failure to incorporate Road grade Can Result in over or underestimation
of a Vehicle's Power output and hence Cause inaccuracy in the instantaneous
Emission Estimate. This Study Proposes a Simple LiDAR (Light Detection And Ranging) -
GIS (Geographic Information System) Road grade estimation methodology, using GIS Software
to Interpolate the Elevation for each Second of Data from a Digital Terrain Map (DTM).
On-Road carbon dioxide. (CO2) emissions from a passenger were Recorded by Car Portable
Emission Measurement System (PEMS) over 48 laps Through an Urban-Traffic Network Test.
The Test lap was divided into 8 Sections for Micro-scale Analysis. PHEM the instantaneous
Emission Model (Hausberger, 2003rd) was employed to Estimate the total CO2 Emission
Through lap and each section. The addition of the LiDAR-grade GIS Road to the PHEM modeling
improved the accuracy of the CO2 Emission Predictions. Estimate the average PHEM
(with Road grade) of the total CO2 Emission PEMS measured section (n = 288) was 93%, with
90% of the PHEM estimates between 80% and 110% of the PEMS Recorded value. The
Research suggests that instantaneous Emission modeling with LiDAR-GIS calculated Road
grade is a viable method for Generating Accurate Real-World Micro-scale CO2 Emission estimates.
The sensitivity of the CO2 Emission Predictions to Road grade was also tested by lessening
and exaggerating the gradient. profiles, and demonstrates that Assuming a Flat Profile
considerable Error Cause could in Real-World CO2 Emission estimation.