Artificial neural network as a predictive tool for emissions from heavy-duty diesel vehicles in Southern California

An artificial neural network (ANN) was trained on chassis dynamometer data and used to predict the oxides of nitrogen, carbon dioxide, hydrocarbons and carbon monoxide emitted from heavy-duty diesel vehicles. Axle speed, torque, their derivatives in different time steps, and two novel variables that defined speed variability over 150s were defined as the inputs for ANN. The novel variables that defined speed variability over 150s were defined as the inputs of ANN. The novel variables were used to assist in predicting off-cycle emissions. Each species was considered individually as an output of the ANN. The ANN was trained on the highway cycle and applied to the city / suburban heavy vehicle route (CSHVR) and urban dynamometer driving schedule (UDDS) with four different sets of inputs to predict the emissions for these vehicles. The research showed acceptable predication results for the ANN, even for the one trained with only eight inputs of speed, torque, their first and second derivatives at one second, and two variables related to the speed pattern over the last 150s. However, off-cycle operation (leading to high oxides of nitrogen emissions) was still difficult to model. The results showed an average accuracy of 0.97 for carbon dioxide, 0.89 for oxides of nitrogen, 0.70 for carbon monoxide and 0.48 for hydrocarbons over the course of CSHVR, the highway cycle and UDDS.

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/14680874
• Authors:
  • HASHEMI, N
  • CLARK, N N
• Publication Date: 2007-8

Language

• English

Media Info

• Pagination: 321-36
• Serial:
  • International Journal of Engine Research
  • Volume: 8
  • Issue Number: 4
  • Publisher: Sage Publications, Incorporated
  • ISSN: 1468-0874
  • EISSN: 20413149

Subject/Index Terms

• TRT Terms: Carbon dioxide; Carbon monoxide; Diesel engines; Force; Forecasting; Fuzzy logic; Hydrocarbons; Measuring instruments; Nitrogen oxides; Pollutants; Trucks
• ITRD Terms: 6155: Apparatus (measuring); 7393: Carbon dioxide; 7391: Carbon monoxide; 1314: Diesel engine; 2442: Emission; 5421: Force; 132: Forecast; 6485: Fuzzy logic; 7367: Hydrocarbon; 1236: Lorry; 7380: Nitrogen oxide
• Subject Areas: Energy; Environment; Motor Carriers; Vehicles and Equipment; I15: Environment; I90: Vehicles;

Filing Info

• Accession Number: 01076277
• Record Type: Publication
• Source Agency: Transport Research Laboratory
• Files: ITRD
• Created Date: Sep 18 2007 10:37AM