Deep neural network model with Bayesian hyperparameter optimization for prediction of NOx at transient conditions in a diesel engine

S Shin, Y Lee, M Kim, J Park, S Lee, K Min - Engineering Applications of …, 2020 - Elsevier
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 …

Future cities carbon emission models: hybrid vehicle emission modelling for low-emission zones

M Mądziel - Energies, 2023 - mdpi.com
Current emission models primarily focus on traditional combustion vehicles and may not
accurately represent emissions from the increasingly diverse vehicle fleet. The growing …

[PDF][PDF] Microscopic emission and fuel consumption modeling for light-duty vehicles using portable emission measurement system data

W Lei, H Chen, L Lu - World Academy of Science, Engineering and …, 2010 - Citeseer
Microscopic emission and fuel consumption models have been widely recognized as an
effective method to quantify real traffic emission and energy consumption when they are …

Predicting CO2 Emissions from Traffic Vehicles for Sustainable and Smart Environment Using a Deep Learning Model

AH Al-Nefaie, THH Aldhyani - Sustainability, 2023 - mdpi.com
Burning fossil fuels results in emissions of carbon dioxide (CO2), which significantly
contributes to atmospheric changes and climate disturbances. Consequently, people are …

NOx Emission prediction of heavy-duty diesel vehicles based on Bayesian optimization-Gated Recurrent Unit algorithm

Z Wang, K Luo, H Yu, K Feng, H Ding - Energy, 2024 - Elsevier
In accordance with the emission regulations specified in GB17691-2018 ″Emission Limits
and Measurement Methods for Heavy-Duty Vehicles (China VI)," this paper conducted …

Machine learning-based estimation of gaseous and particulate emissions using internally observable vehicle operating parameters

J Seo, Y Lim, J Han, S Park - Urban Climate, 2023 - Elsevier
Measuring vehicular emissions is crucial for emission management and air quality control.
However, conventional measurement equipment is costly and requires continuous …

Predicting transient diesel engine NOx emissions using time-series data preprocessing with deep-learning models

S Shin, Y Lee, J Park, M Kim… - Proceedings of the …, 2021 - journals.sagepub.com
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 …

An Optimal Approach to Vehicular CO2 Emissions Prediction using Deep Learning

S Sahay, P Pawar - 2023 International Conference on …, 2023 - ieeexplore.ieee.org
One of the biggest challenges faced by humanity today is climate change. Governmental
Organisations and Au-thorities all across the world, are now taking important steps to tackle …

Predicting tailpipe NOx emission using supervised learning algorithms

KB Altuğ, SE Küçük - 2019 3rd International Symposium on …, 2019 - ieeexplore.ieee.org
The dynamics underlying the tailpipe NOx emissions in vehicles is in a complex relationship
with multiple engine components in a temporal manner. Physical models constructed to …

Prediction of engine-out emissions using deep convolutional neural networks

A Warey, J Gao, R Grover - SAE International Journal of Advances and …, 2021 - sae.org
Abstract Analysis-driven pre-calibration of a modern automotive engine is extremely
valuable in significantly reducing hardware investments and accelerating engine designs …