Quantifying the Impact of Traffic on Electric Vehicle Efficiency
While the influence of several factors on battery electric vehicle (BEV) efficiency has been investigated in the past, their impact on traffic is not yet fully understood, especially when driving in a natural environment. This paper investigates the influence of driving in intense traffic conditions...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-01-01
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| Series: | World Electric Vehicle Journal |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2032-6653/13/1/15 |
| _version_ | 1797489572713594880 |
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| author | Tim Jonas Christopher D. Hunter Gretchen A. Macht |
| author_facet | Tim Jonas Christopher D. Hunter Gretchen A. Macht |
| author_sort | Tim Jonas |
| collection | DOAJ |
| description | While the influence of several factors on battery electric vehicle (BEV) efficiency has been investigated in the past, their impact on traffic is not yet fully understood, especially when driving in a natural environment. This paper investigates the influence of driving in intense traffic conditions while considering the ambient temperature and driving behavior on BEV energy efficiency in a field study. A total of 30 BEV inexperienced drivers test drove a 2017 Volkswagen eGolf on a route with various road types in two different traffic intensity scenarios: During morning commute hours with higher traffic congestion and lower congestion hours throughout the middle of the day. Results support the hypothesis that traffic conditions significantly impact the vehicle’s efficiency, with additional consumption of approximately 4–5% in the high traffic scenario. By creating and comparing driving in traffic to an underlying base case scenario, the additional range potential by avoiding traffic for this particular vehicle can be quantified as up to seven miles. New patterns of BEV efficiencies emerged, which can help stakeholders understand how eco-driving can be strategically improved by selecting trip times and routes that avoid high traffic intensity. |
| first_indexed | 2024-03-10T00:18:32Z |
| format | Article |
| id | doaj.art-06be8ed57e05460598fc8b09af3d6504 |
| institution | Directory Open Access Journal |
| issn | 2032-6653 |
| language | English |
| last_indexed | 2024-03-10T00:18:32Z |
| publishDate | 2022-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | World Electric Vehicle Journal |
| spelling | doaj.art-06be8ed57e05460598fc8b09af3d65042023-11-23T15:45:56ZengMDPI AGWorld Electric Vehicle Journal2032-66532022-01-011311510.3390/wevj13010015Quantifying the Impact of Traffic on Electric Vehicle EfficiencyTim Jonas0Christopher D. Hunter1Gretchen A. Macht2Mechanical, Industrial and Systems Engineering, University of Rhode Island, Kingston, RI 02881, USACivil and Environmental Engineering, University of Rhode Island, Kingston, RI 02881, USAMechanical, Industrial and Systems Engineering, University of Rhode Island, Kingston, RI 02881, USAWhile the influence of several factors on battery electric vehicle (BEV) efficiency has been investigated in the past, their impact on traffic is not yet fully understood, especially when driving in a natural environment. This paper investigates the influence of driving in intense traffic conditions while considering the ambient temperature and driving behavior on BEV energy efficiency in a field study. A total of 30 BEV inexperienced drivers test drove a 2017 Volkswagen eGolf on a route with various road types in two different traffic intensity scenarios: During morning commute hours with higher traffic congestion and lower congestion hours throughout the middle of the day. Results support the hypothesis that traffic conditions significantly impact the vehicle’s efficiency, with additional consumption of approximately 4–5% in the high traffic scenario. By creating and comparing driving in traffic to an underlying base case scenario, the additional range potential by avoiding traffic for this particular vehicle can be quantified as up to seven miles. New patterns of BEV efficiencies emerged, which can help stakeholders understand how eco-driving can be strategically improved by selecting trip times and routes that avoid high traffic intensity.https://www.mdpi.com/2032-6653/13/1/15battery electric vehicletrafficdriving behavioreco-drivingefficiency |
| spellingShingle | Tim Jonas Christopher D. Hunter Gretchen A. Macht Quantifying the Impact of Traffic on Electric Vehicle Efficiency World Electric Vehicle Journal battery electric vehicle traffic driving behavior eco-driving efficiency |
| title | Quantifying the Impact of Traffic on Electric Vehicle Efficiency |
| title_full | Quantifying the Impact of Traffic on Electric Vehicle Efficiency |
| title_fullStr | Quantifying the Impact of Traffic on Electric Vehicle Efficiency |
| title_full_unstemmed | Quantifying the Impact of Traffic on Electric Vehicle Efficiency |
| title_short | Quantifying the Impact of Traffic on Electric Vehicle Efficiency |
| title_sort | quantifying the impact of traffic on electric vehicle efficiency |
| topic | battery electric vehicle traffic driving behavior eco-driving efficiency |
| url | https://www.mdpi.com/2032-6653/13/1/15 |
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