Vehicle-specific emissions modeling based upon on-road measurements.

Area of Science:

• Environmental Science
• Automotive Engineering
• Chemical Engineering

Background:

• Accurate vehicle emissions modeling is crucial for environmental monitoring and traffic management.
• Existing models often lack microscale precision or rely on data not readily available in real-world applications.
• Portable emissions measurement systems (PEMS) enable detailed, real-world vehicle data collection.

Purpose of the Study:

• To develop and compare vehicle-specific microscale fuel use and emissions rate models.
• To evaluate two modeling schemes: one using internally observable variables (IOVs) and another using externally observable variables (EOVs).
• To assess the practical applicability of these models for different assessment needs.

Main Methods:

• Utilized hot-stabilized tailpipe emissions data from real-world driving using PEMS.
• Developed semiempirical, physically based models using consecutive averaging periods.
• Compared model performance based on R-squared values for various pollutants (NO, HC, CO, CO2).

Main Results:

• IOV-based models demonstrated higher accuracy (R-squared up to 0.99 for CO2) compared to EOV-based models (R-squared up to 0.79 for CO2).
• EOV models showed moderate accuracy for NO, HC, and CO (R-squared 0.17-0.30), while IOV models performed better (R-squared 0.41-0.66).
• Both model types were sensitive to driving cycle events like high acceleration; EOV models are more practical due to data availability.

Conclusions:

• Vehicle-specific models based on IOVs provide superior accuracy for emissions prediction.
• EOV-based models, despite lower accuracy, offer practical value for traffic management and simulation where IOVs are unavailable.
• The choice of modeling approach depends on the required accuracy and data accessibility for specific applications.