A new algorithm for eco-friendly path guidance focused on electric vehicles

The automobile industry is showing increasing interest in eco-friendly electric vehicles (EVs) with the aim of replacing vehicles that rely on traditional fossil fuels for energy. This study investigates the routing of an EV with maximum efficiency relative to the terrain. As EVs have poor climbing...

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Published inEnergy (Oxford) Vol. 233; p. 121198
Main Authors Ku, Donggyun, Choi, Minje, Yoo, Nakyoung, Shin, Seungheon, Lee, Seungjae
Format Journal Article
LanguageEnglish
Published Oxford Elsevier Ltd 15.10.2021
Elsevier BV
Subjects
Online AccessGet full text
ISSN0360-5442
1873-6785
DOI10.1016/j.energy.2021.121198

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Abstract The automobile industry is showing increasing interest in eco-friendly electric vehicles (EVs) with the aim of replacing vehicles that rely on traditional fossil fuels for energy. This study investigates the routing of an EV with maximum efficiency relative to the terrain. As EVs have poor climbing ability due to limitations associated with battery efficiency, this study determines the optimal route using 3D spatial information data and the slope of each link in the route. In the transportation field, the Bureau of Public Roads function classifies the shortest paths and optimizes paths. By adding slope-related variables, a new functional expression that includes weighting as a result of slope-related speed reduction is constructed, and a new functional expression system and network are built. As a result of assigning a route to optimize battery efficiency, the energy efficiency was improved by 7.84 km/kWh at an average speed of 70 km/h. The effectiveness was verified by comparing the total travel time and energy efficiency differences between the two methods. The proposed approach enables efficient transport and ultimately achieves the goal of green transportation with maximum energy efficiency. •Routing electric vehicles with maximum efficiency depending on the terrain.•Electric vehicles have poor climbing ability due to limitations associated with battery efficiency.•Optimal route using 3D spatial information data and the slope that was calculated by digital elevation model of each link in the route.•More efficient operation is possible if the route selected based on battery efficiency is used.•The effect of activating eco-friendly vehicles is reducing carbon emissions.
AbstractList The automobile industry is showing increasing interest in eco-friendly electric vehicles (EVs) with the aim of replacing vehicles that rely on traditional fossil fuels for energy. This study investigates the routing of an EV with maximum efficiency relative to the terrain. As EVs have poor climbing ability due to limitations associated with battery efficiency, this study determines the optimal route using 3D spatial information data and the slope of each link in the route. In the transportation field, the Bureau of Public Roads function classifies the shortest paths and optimizes paths. By adding slope-related variables, a new functional expression that includes weighting as a result of slope-related speed reduction is constructed, and a new functional expression system and network are built. As a result of assigning a route to optimize battery efficiency, the energy efficiency was improved by 7.84 km/kWh at an average speed of 70 km/h. The effectiveness was verified by comparing the total travel time and energy efficiency differences between the two methods. The proposed approach enables efficient transport and ultimately achieves the goal of green transportation with maximum energy efficiency. •Routing electric vehicles with maximum efficiency depending on the terrain.•Electric vehicles have poor climbing ability due to limitations associated with battery efficiency.•Optimal route using 3D spatial information data and the slope that was calculated by digital elevation model of each link in the route.•More efficient operation is possible if the route selected based on battery efficiency is used.•The effect of activating eco-friendly vehicles is reducing carbon emissions.
The automobile industry is showing increasing interest in eco-friendly electric vehicles (EVs) with the aim of replacing vehicles that rely on traditional fossil fuels for energy. This study investigates the routing of an EV with maximum efficiency relative to the terrain. As EVs have poor climbing ability due to limitations associated with battery efficiency, this study determines the optimal route using 3D spatial information data and the slope of each link in the route. In the transportation field, the Bureau of Public Roads function classifies the shortest paths and optimizes paths. By adding slope-related variables, a new functional expression that includes weighting as a result of slope-related speed reduction is constructed, and a new functional expression system and network are built. As a result of assigning a route to optimize battery efficiency, the energy efficiency was improved by 7.84 km/kWh at an average speed of 70 km/h. The effectiveness was verified by comparing the total travel time and energy efficiency differences between the two methods. The proposed approach enables efficient transport and ultimately achieves the goal of green transportation with maximum energy efficiency.
ArticleNumber 121198
Author Choi, Minje
Lee, Seungjae
Yoo, Nakyoung
Shin, Seungheon
Ku, Donggyun
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Keywords Volume delay function
EV
Gradient
Traffic assignment
BPR
Transportation and energy
Electric vehicles
Digital elevation model
VDF
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Snippet The automobile industry is showing increasing interest in eco-friendly electric vehicles (EVs) with the aim of replacing vehicles that rely on traditional...
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StartPage 121198
SubjectTerms Algorithms
Automobile industry
Automobiles
batteries
Clean energy
Digital elevation model
Electric vehicles
Energy efficiency
Fossil fuels
Gradient
industry
landscapes
Mathematical analysis
Optimization
Route selection
Spatial data
Sustainable transportation
Traffic assignment
Transportation
Transportation and energy
Travel time
Volume delay function
Title A new algorithm for eco-friendly path guidance focused on electric vehicles
URI https://dx.doi.org/10.1016/j.energy.2021.121198
https://www.proquest.com/docview/2573515634
https://www.proquest.com/docview/2636383352
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