Estimation of real-world fuel consumption rate of light-duty vehicles based on the records reported by vehicle owners

IY Zeng, S Tan, J Xiong, X Ding, Y Li, T Wu - Energies, 2021 - mdpi.com
Private vehicle travel is the most basic mode of transportation, so that an effective way to
control the real-world fuel consumption rate of light-duty vehicles plays a vital role in …

A comparative performance of machine learning algorithm to predict electric vehicles energy consumption: A path towards sustainability

I Ullah, K Liu, T Yamamoto… - Energy & …, 2022 - journals.sagepub.com
The rapid growth of transportation sector and related emissions are attracting the attention of
policymakers to ensure environmental sustainability. Therefore, the deriving factors of …

Comparative analysis of artificial neural networks and dynamic models as virtual sensors

WK Yap, V Karri - Applied Soft Computing, 2013 - Elsevier
This paper presents a comparison of predictive models for the estimation of engine power
and tailpipe emissions for a 4kW gasoline scooter. This study forms a benchmark toward …

[HTML][HTML] Development of a cold-start emission model for diesel vehicles using an artificial neural network trained with real-world driving data

J Seo, B Yun, J Kim, M Shin, S Park - Science of The Total Environment, 2022 - Elsevier
During the cold start and warm-up phase, modern vehicles emit considerable amounts of
pollutants due to the incomplete combustion and deteriorated performance of aftertreatment …

Assessment of On-Road High NOx Emitters by Using Machine Learning Algorithms for Heavy-Duty Vehicles

F Kazan, A Thiruvengadam, MC Besch - Emission Control Science and …, 2023 - Springer
The aim of this study was to develop a model structure and to train a model based on
chassis dynamometer datasets and subsequently use the trained model in conjunction with …

Development of fuel and emission models for high speed heavy duty trucks, light duty trucks, and light duty vehicles

S Park, H Rakha, M Farzaneh… - … IEEE Conference on …, 2010 - ieeexplore.ieee.org
The current state-of-practice emission modeling tools, namely: MOBILE, EMFAC, the
Comprehensive Modal Emission Model (CMEM), and VT-Micro model do not provide …

Application of neural network model to vehicle emissions

D Kim, J Lee - International Journal of Urban Sciences, 2010 - Taylor & Francis
The issue of air quality is now a major concern around the world and the vehicle emissions
model is very important. Most of the current vehicle emission models are multiple regression …

Deep learning model based CO2 emissions prediction using vehicle telematics sensors data

M Singh, RK Dubey - IEEE Transactions on Intelligent Vehicles, 2021 - ieeexplore.ieee.org
Climate change is one of the greatest environmental hazards to mankind. The emission of
greenhouse gases has resulted in a continuous increase in the temperature of the …

A deep transfer NOx emission inversion model of diesel vehicles with multisource external influence

Z Xu, R Wang, Y Kang, Y Zhang, X Xia… - Journal of Advanced …, 2021 - Wiley Online Library
By installing on‐board diagnostics (OBD) on tested vehicles, the after‐treatment exhaust
emissions can be monitored in real time to construct driving cycle‐based emission models …

Predicting the transient NOx emissions of the diesel vehicle based on LSTM neural networks

Y Wang, Y Yu, J Li - 2020 IEEE conference on …, 2020 - ieeexplore.ieee.org
Nitrogen oxide (NOx) emissions play an important role in the study of diesel engine pollutant
emissions. This study introduces the long short-term memory (LSTM) neural network to …