Development of driving cycles for characterizing vehicular emission factors

Abstract

Driving cycles are one of the most useful tools in measuring and quantifying vehicular emissions by a dynamometer test in a standard and fast manner. Various driving cycles have been developed for the purposes of legislation, inspection and research. This research intends to develop a practical methodology, for developing a representative driving cycle which would reflect the real-world driving conditions. This methodology is convenient for constructing and updating the driving cycle under a systematic routine. The methodology involves collecting speed profiles, analyzing the data statistically, and developing a cycle construction mechanism. Both on-board and car chasing techniques were employed in collecting the driving speed data. The car chasing technique is considered as the most feasible methodology in collecting the real-world driving profiles. Ninety percent of the speed data were collected using the car chasing technique. The selected routes are the most popular commuting routes having the highest average annual daily traffic (AADT), and connect the major residential and commercial/industrial areas. A microwave speed sensor, a global positioning system receiver and an infra-red tachometer were installed to measure the vehicular driving activities. In the validation test, there was no significant difference in the measured speed data obtained by these three instruments. Statistical analyses were employed to develop the driving cycles. Thirteen critical driving characterizing parameters were employed as the target statistics characterizing the driving pattern when developing the driving cycle. Micro-trips (i.e., kinematic sequences between two successful idles) are the core components in establishing the driving cycle. They were randomly selected from the entire data pool and adhered to form the representative driving cycle. The thirteen parameters of the formed driving cycle had to meet the target statistics at a defined significance level. The Performance Value (PV) and Speed-acceleration probability distribution (SAPD) were applied to select the synthesized driving cycle that would best represent of the local driving behaviour. Compared to the popular driving cycles developed elsewhere, it appears that the refined Hong Kong Driving Cycle development methodology is robust in developing representative driving cycles.