As emissions regulations for transportation become stricter, it is increasingly important to
develop accurate nitrogen oxide (NO x) emissions models for heavy-duty vehicles. However …

In order to address the challenge of accurately predicting nitrogen oxide (NOx) emission
from diesel engines in transient operation using traditional neural network models, this study …

On-board diagnostics (OBD) data contain valuable information including real-world
measurements of vehicle powertrain parameters. These data can be used to gain a richer …

Deep learning has been used to predict engine phenomena that are otherwise difficult to
predict using conventional modeling approaches. Previous studies using deep learning for …

In this paper, a methodology based on data-driven models is developed to predict the NOx
emissions of an internal combustion engine using, as inputs, a set of ECU channels …

Owing to increasing interest in the environment, particularly on air quality, regulations in the
automobile industry have become stricter. Test cycles have been substituted to simulate real …

Deep-learning models were developed and evaluated for predicting the engine-out
emission of NOx—one of the main pollutants emitted from diesel engines—under transient …

Accurate and stable prediction of NOx emissions from diesel vehicles plays a crucial role in
the establishment of virtual NOx sensors and the development and design of diesel engines …

Euro 6 standards impose stringent nitrogen oxide (NOx) emission limits on diesel cars. NOx
emissions are significantly different between Euro 6 diesel cars and the previous standards …

The understanding and prediction of NOx emissions formation mechanisms during engine
transients are critical to the monitoring of real driving emissions. While many studies focus …