Cargando…

Internet-of-Things (IoT) Platform for Road Energy Efficiency Monitoring

The road transportation sector is a dominant and growing energy consumer. Although investigations to quantify the road infrastructure’s impact on energy consumption have been carried out, there are currently no standard methods to measure or label the energy efficiency of road networks. Consequently...

Descripción completa

Detalles Bibliográficos
Autores principales: Skar, Asmus, Vestergaard, Anders, Pour, Shahrzad M., Pettinari, Matteo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10007403/
https://www.ncbi.nlm.nih.gov/pubmed/36904960
http://dx.doi.org/10.3390/s23052756
_version_ 1784905512649752576
author Skar, Asmus
Vestergaard, Anders
Pour, Shahrzad M.
Pettinari, Matteo
author_facet Skar, Asmus
Vestergaard, Anders
Pour, Shahrzad M.
Pettinari, Matteo
author_sort Skar, Asmus
collection PubMed
description The road transportation sector is a dominant and growing energy consumer. Although investigations to quantify the road infrastructure’s impact on energy consumption have been carried out, there are currently no standard methods to measure or label the energy efficiency of road networks. Consequently, road agencies and operators are limited to restricted types of data when managing the road network. Moreover, initiatives meant to reduce energy consumption cannot be measured and quantified. This work is, therefore, motivated by the desire to provide road agencies with a road energy efficiency monitoring concept that can provide frequent measurements over large areas across all weather conditions. The proposed system is based on measurements from in-vehicle sensors. The measurements are collected onboard with an Internet-of-Things (IoT) device, then transmitted periodically before being processed, normalized, and saved in a database. The normalization procedure involves modeling the vehicle’s primary driving resistances in the driving direction. It is hypothesized that the energy remaining after normalization holds information about wind conditions, vehicle-related inefficiencies, and the physical condition of the road. The new method was first validated utilizing a limited dataset of vehicles driving at a constant speed on a short highway section. Next, the method was applied to data obtained from ten nominally identical electric cars driven over highways and urban roads. The normalized energy was compared with road roughness measurements collected by a standard road profilometer. The average measured energy consumption was 1.55 Wh per 10 m. The average normalized energy consumption was 0.13 and 0.37 Wh per 10 m for highways and urban roads, respectively. A correlation analysis showed that normalized energy consumption was positively correlated to road roughness. The average Pearson correlation coefficient was 0.88 for aggregated data and 0.32 and 0.39 for 1000-m road sections on highways and urban roads, respectively. An increase in IRI of 1 m/km resulted in a 3.4% increase in normalized energy consumption. The results show that the normalized energy holds information about the road roughness. Thus, considering the emergence of connected vehicle technologies, the method seems promising and can potentially be used as a platform for future large-scale road energy efficiency monitoring.
format Online
Article
Text
id pubmed-10007403
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-100074032023-03-12 Internet-of-Things (IoT) Platform for Road Energy Efficiency Monitoring Skar, Asmus Vestergaard, Anders Pour, Shahrzad M. Pettinari, Matteo Sensors (Basel) Article The road transportation sector is a dominant and growing energy consumer. Although investigations to quantify the road infrastructure’s impact on energy consumption have been carried out, there are currently no standard methods to measure or label the energy efficiency of road networks. Consequently, road agencies and operators are limited to restricted types of data when managing the road network. Moreover, initiatives meant to reduce energy consumption cannot be measured and quantified. This work is, therefore, motivated by the desire to provide road agencies with a road energy efficiency monitoring concept that can provide frequent measurements over large areas across all weather conditions. The proposed system is based on measurements from in-vehicle sensors. The measurements are collected onboard with an Internet-of-Things (IoT) device, then transmitted periodically before being processed, normalized, and saved in a database. The normalization procedure involves modeling the vehicle’s primary driving resistances in the driving direction. It is hypothesized that the energy remaining after normalization holds information about wind conditions, vehicle-related inefficiencies, and the physical condition of the road. The new method was first validated utilizing a limited dataset of vehicles driving at a constant speed on a short highway section. Next, the method was applied to data obtained from ten nominally identical electric cars driven over highways and urban roads. The normalized energy was compared with road roughness measurements collected by a standard road profilometer. The average measured energy consumption was 1.55 Wh per 10 m. The average normalized energy consumption was 0.13 and 0.37 Wh per 10 m for highways and urban roads, respectively. A correlation analysis showed that normalized energy consumption was positively correlated to road roughness. The average Pearson correlation coefficient was 0.88 for aggregated data and 0.32 and 0.39 for 1000-m road sections on highways and urban roads, respectively. An increase in IRI of 1 m/km resulted in a 3.4% increase in normalized energy consumption. The results show that the normalized energy holds information about the road roughness. Thus, considering the emergence of connected vehicle technologies, the method seems promising and can potentially be used as a platform for future large-scale road energy efficiency monitoring. MDPI 2023-03-02 /pmc/articles/PMC10007403/ /pubmed/36904960 http://dx.doi.org/10.3390/s23052756 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Skar, Asmus
Vestergaard, Anders
Pour, Shahrzad M.
Pettinari, Matteo
Internet-of-Things (IoT) Platform for Road Energy Efficiency Monitoring
title Internet-of-Things (IoT) Platform for Road Energy Efficiency Monitoring
title_full Internet-of-Things (IoT) Platform for Road Energy Efficiency Monitoring
title_fullStr Internet-of-Things (IoT) Platform for Road Energy Efficiency Monitoring
title_full_unstemmed Internet-of-Things (IoT) Platform for Road Energy Efficiency Monitoring
title_short Internet-of-Things (IoT) Platform for Road Energy Efficiency Monitoring
title_sort internet-of-things (iot) platform for road energy efficiency monitoring
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10007403/
https://www.ncbi.nlm.nih.gov/pubmed/36904960
http://dx.doi.org/10.3390/s23052756
work_keys_str_mv AT skarasmus internetofthingsiotplatformforroadenergyefficiencymonitoring
AT vestergaardanders internetofthingsiotplatformforroadenergyefficiencymonitoring
AT pourshahrzadm internetofthingsiotplatformforroadenergyefficiencymonitoring
AT pettinarimatteo internetofthingsiotplatformforroadenergyefficiencymonitoring