Road Grade Estimation Based on Power Demand Difference of Heavy-Duty Diesel Trucks for Emission Estimation

Abstract

Road grades have significant impacts on the emissions of heavy-duty diesel trucks (HDDTs), even in the same operating mode. Existing gradient identification methods are time-consuming and difficult to conduct for entire road networks; moreover, few previous studies have considered uncertainty of HDDT emissions caused by various road grades. In this study, an estimation method for road grade was developed based on second-by-second field operating data, with noise reduction performed using the Kalman filter. The consistency and symmetry of the road grade calculated by the proposed method were then analyzed. Finally, differences in emission rate and emission factor for carbon dioxide (CO2), carbon monoxide (CO), total hydrocarbon (THC), and nitrogen oxides (NOx) under various grades were compared. The results indicated that the grade recognition results of each truck were consistent, with an average grade difference of 0.153%. Based on symmetry analysis of the estimation results in opposite directions, the two opposite road grades were found to have a strong negative correlation, and the average error of the grade was 0.125%. Pollutant results showed the emission rate of CO was most affected by grade, followed by NOx, and THC was the least affected. The emission factors of CO2, CO, THC, and NOx were found to increase by 32.4% to 82.8%, 75.6% to 198.4%, 19.9% to 39.9%, and 73.1% to 186.3%, respectively at 1.0%, 2.0%, and 3.0% gradients compared with 0.0% gradient. This study can improve the estimation accuracy for HDDT emissions, especially in areas with undulating terrain such as mountains and hills.