A review of the data-driven prediction method of vehicle fuel consumption

D Zhao, H Li, J Hou, P Gong, Y Zhong, W He, Z Fu - Energies, 2023 - mdpi.com
Accurately and efficiently predicting the fuel consumption of vehicles is the key to improving
their fuel economy. This paper provides a comprehensive review of data-driven fuel …

A review of applications of artificial intelligence in heavy duty trucks

S Katreddi, S Kasani, A Thiruvengadam - Energies, 2022 - mdpi.com
Due to the increasing use of automobiles, the transportation industry is facing challenges of
increased emissions, driver safety concerns, travel demand, etc. Hence, automotive …

Real-time vehicular fuel consumption estimation using machine learning and on-board diagnostics data

H Abediasl, A Ansari, V Hosseini… - Proceedings of the …, 2023 - journals.sagepub.com
Instantaneous fuel consumption estimation of fleet vehicles provides essential tools for fleet
operation optimization and intelligent fleet management. This study aims to develop …

Machine-learning-based digital twins for transient vehicle cycles and their potential for predicting fuel consumption

E Tomanik, AJ Jimenez-Reyes, V Tomanik, B Tormos - Vehicles, 2023 - mdpi.com
Transient car emission tests generate huge amount of test data, but their results are usually
evaluated only using their “accumulated” cycle values according to the homologation limits …

[HTML][HTML] Calculating Fuel Usage and Emissions for Refrigerated Road Transport Using Real-World Data

MJ du Plessis, J van Eeden, L Goedhals-Gerber… - … Research Part D …, 2023 - Elsevier
Road freight transportation is and will become increasingly important in all distribution
chains. However, little research has analysed actual logistics service provider (LSP) data on …

[HTML][HTML] Neural network surrogate models for aerodynamic analysis in truck platoons: Implications on autonomous freight delivery

T Liu, H Meidani - International Journal of Transportation Science and …, 2024 - Elsevier
Recent advances in connected vehicles have the potential to revolutionize the efficiency and
sustainability of transportation. In particular, truck platooning has emerged as a promising …

Assessment of Energy Consumption Characteristics of Ultra-Heavy-Duty Vehicles under Real Driving Conditions

S Jo, HJ Kim, SI Kwon, JT Lee, S Park - Energies, 2023 - mdpi.com
Passenger cars account for the largest share of GHG emissions in the road sector. However,
given that the number of heavy-duty vehicles registered is lower but accounts for about a …

Development of Machine Learning based approach to predict fuel consumption and maintenance cost of Heavy-Duty Vehicles using diesel and alternative fuels

S Katreddi - 2023 - search.proquest.com
One of the major contributors of human-made greenhouse gases (GHG) namely carbon
dioxide (CO 2), methane (CH 4), and nitrous oxide (NO X) in the transportation sector and …

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 …

Energy consumption analysis of metropolitan logistics vehicles based on an ensemble -means long short-term memory model

S Gan, Q Zhang, Y Wang - Energy & Environment, 2024 - journals.sagepub.com
In recent years, creating a green and low-carbon sustainable development has received
extensive attention, prompting considerable research into reducing pollution emissions in …