Cargando…
An Overview of Eco-Driving Theory, Capability Evaluation, and Training Applications
Constrained by traditional fuel-saving technologies that have almost reached the limit of fuel-saving potential, the difficulty in changing urban congestion, and the low market penetration rate of new energy vehicles, in the short term, eco-driving seems to be an effective way to achieve energy-savi...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8512309/ https://www.ncbi.nlm.nih.gov/pubmed/34640859 http://dx.doi.org/10.3390/s21196547 |
_version_ | 1784582959928442880 |
---|---|
author | Xu, Nan Li, Xiaohan Liu, Qiao Zhao, Di |
author_facet | Xu, Nan Li, Xiaohan Liu, Qiao Zhao, Di |
author_sort | Xu, Nan |
collection | PubMed |
description | Constrained by traditional fuel-saving technologies that have almost reached the limit of fuel-saving potential, the difficulty in changing urban congestion, and the low market penetration rate of new energy vehicles, in the short term, eco-driving seems to be an effective way to achieve energy-saving and emissions reduction in the transportation industry. This paper reviews the energy-saving theory and technology of eco-driving, eco-driving capability evaluation, and the practical application of eco-driving, and points out some limitations of previous studies. Specifically, the research on eco-driving theory mostly focuses on a single vehicle in a single scene, and there is a lack of eco-driving research for fleets or regions. In addition, the parameters used to evaluate eco-driving capabilities mainly focus on speed, acceleration, and fuel consumption, but external factors that are not related to the driver will affect these parameters, making the evaluation results unreasonable. Fortunately, vehicle big data and the Internet of Vehicles (V2I) provides an information basis for solving regional eco-driving, and it also provides a data basis for the study of data-driven methods for the fair evaluation of eco-driving. In general, the development of new technologies provides new ideas for solving some problems in the field of eco-driving. |
format | Online Article Text |
id | pubmed-8512309 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-85123092021-10-14 An Overview of Eco-Driving Theory, Capability Evaluation, and Training Applications Xu, Nan Li, Xiaohan Liu, Qiao Zhao, Di Sensors (Basel) Review Constrained by traditional fuel-saving technologies that have almost reached the limit of fuel-saving potential, the difficulty in changing urban congestion, and the low market penetration rate of new energy vehicles, in the short term, eco-driving seems to be an effective way to achieve energy-saving and emissions reduction in the transportation industry. This paper reviews the energy-saving theory and technology of eco-driving, eco-driving capability evaluation, and the practical application of eco-driving, and points out some limitations of previous studies. Specifically, the research on eco-driving theory mostly focuses on a single vehicle in a single scene, and there is a lack of eco-driving research for fleets or regions. In addition, the parameters used to evaluate eco-driving capabilities mainly focus on speed, acceleration, and fuel consumption, but external factors that are not related to the driver will affect these parameters, making the evaluation results unreasonable. Fortunately, vehicle big data and the Internet of Vehicles (V2I) provides an information basis for solving regional eco-driving, and it also provides a data basis for the study of data-driven methods for the fair evaluation of eco-driving. In general, the development of new technologies provides new ideas for solving some problems in the field of eco-driving. MDPI 2021-09-30 /pmc/articles/PMC8512309/ /pubmed/34640859 http://dx.doi.org/10.3390/s21196547 Text en © 2021 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 | Review Xu, Nan Li, Xiaohan Liu, Qiao Zhao, Di An Overview of Eco-Driving Theory, Capability Evaluation, and Training Applications |
title | An Overview of Eco-Driving Theory, Capability Evaluation, and Training Applications |
title_full | An Overview of Eco-Driving Theory, Capability Evaluation, and Training Applications |
title_fullStr | An Overview of Eco-Driving Theory, Capability Evaluation, and Training Applications |
title_full_unstemmed | An Overview of Eco-Driving Theory, Capability Evaluation, and Training Applications |
title_short | An Overview of Eco-Driving Theory, Capability Evaluation, and Training Applications |
title_sort | overview of eco-driving theory, capability evaluation, and training applications |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8512309/ https://www.ncbi.nlm.nih.gov/pubmed/34640859 http://dx.doi.org/10.3390/s21196547 |
work_keys_str_mv | AT xunan anoverviewofecodrivingtheorycapabilityevaluationandtrainingapplications AT lixiaohan anoverviewofecodrivingtheorycapabilityevaluationandtrainingapplications AT liuqiao anoverviewofecodrivingtheorycapabilityevaluationandtrainingapplications AT zhaodi anoverviewofecodrivingtheorycapabilityevaluationandtrainingapplications AT xunan overviewofecodrivingtheorycapabilityevaluationandtrainingapplications AT lixiaohan overviewofecodrivingtheorycapabilityevaluationandtrainingapplications AT liuqiao overviewofecodrivingtheorycapabilityevaluationandtrainingapplications AT zhaodi overviewofecodrivingtheorycapabilityevaluationandtrainingapplications |