A robust method for collecting and processing the on-road instantaneous data of fuel consumption and speed for motorcycles.

Using the laboratory-based fuel consumption models for predicting real-world fuel consumption requires the measurement of data under certain conditions to obtain high accuracy of predicted result. Therefore, it is necessary to develop a logging device for measuring the real-time fuel consumption and speed of vehicle on the road. This article presents a study on developing the on-board data logging device to collect real-world data of fuel consumption and speed for motorcycles with the update rate of 1 Hz. The instantaneous speed of the motorcycle was determined based on the rotational speed of the wheel and the wheel radius. Another module was used to determine the instantaneous fuel consumption rate (FR) though measuring the duration injection pulse. The relationship between the duration injection pulse and the injected amount of fuel was established with high correlation coefficient of 0.997. In addition, a filter was designed to remove noise in the dataset collected using the data logging device. The random errors in the speed and the FR profiles were detected and replaced, the percentage of these errors is 1.8% and 2.4%, respectively. The developed method is a precise one for transient fuel consumption and speed measurement. In chassis dynamometer test, the average deviation between steady speed measured by the chassis and the data logging device is only approximately 0.35%. At transient state, the biggest deviation between these two datasets is less than 3.5%. The average FR at steady speed measured by the developed method is slightly different from the one measured by the carbon balance method. The difference is 0.9%, 2.5%, and 0.25% at the speeds of 30 km/h, 50 km/h, and 70 km/h, respectively. Following the transient test cycle, the fuel consumption measured by the developed method is 4.35% lower than that determined by the carbon balance method. Implications: A robust method for collecting and processing the on-road instantaneous data of fuel consumption and speed was developed for motorcycles. The proposed method can record well the real-world driving data for motorcycles, including the fuel consumption and speed, with the update rate of 1 Hz. The filter was designed to minimize noise while maintaining data integrity of the collected dataset, the percentage of errors in the the speed and the FR profiles is 1.8% and 2.4%, respectively. The proposed method, therefore, can be used as effective tools for future studies relating to the fuel consumption and emission of motorcycles on the road.

Development of the specific emission factors for buses in Hanoi, Vietnam.

This paper develops the specific emission factors for buses in the real-world traffic conditions in the inner city of Hanoi, Vietnam. An engine stationary cycle consisting of 14 modes was developed based on the typical driving cycle of Hanoi buses which had been constructed with the application of Markov chain theory. This is the first engine stationary emissions test cycle constructed for heavy-duty engine in Vietnam. Based on this cycle, the country-specific emission factors (CSEFs) of air pollutants including CO, HC, NOx, CO2, and PM for buses in Hanoi have been developed using the emission measurements on the engine test bed. It is found that almost all developed emission factors are higher than those derived from the emission measurements to the ECE R49 on the same engine. These emission factors, therefore, can be used to improve the quality of the emission inventory of buses in Hanoi.

Development of the typical driving cycle for buses in Hanoi, Vietnam.

This paper develops a typical driving cycle for buses in Hanoi that does not require the deconstruction of the natural driving patterns. Real velocity-time data were collected along 15 routes in the inner city. The raw velocity-time series were preprocessed to remove errors, and smooth and denoise the data. These data, then, were tested for stationary behavior before being used in the construction of the driving cycle based on Markov chain theory. The 14 representative parameters of the driving cycle, including vehicle-specific power, which were extracted from 33 driving cycle parameters using the hierarchical agglomerative clustering method, were used to integrate the features of realistic driving patterns into the typical driving cycle. The conformity of the developed driving cycle with the real-world driving data was evaluated by the speed-acceleration frequency distribution (SAFD). A typical driving cycle for buses in Hanoi with a SAFD of 13.2% was developed. This is the first driving cycle developed for buses in Vietnam. Implications: A typical driving cycle was developed for the first time for buses in Hanoi. With the deviation in speed-acceleration frequency distribution (SAFD) reaching to 13.2%, the developed driving cycle reflects well the overall real-world driving data in the city. This driving cycle, therefore, can be applied for the development of the country-specific emission factors and emission inventories for buses which are a very good tool as well as useful information for integrated air quality management in Hanoi.