A computationally efficient simulation model for estimating energy consumption of electric vehicles in the context of route planning applications
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In all analyzed cases, the results obtained with the assumptions proposed in [1,37] (cases c and d) are very close to the assumption of case (b) (ηrb = 1).
“It can be observed that in all the analyzed cases, the results obtained with the assumptions proposed in the work of [1,37] (case (c) and case (d), respectively) are very close to the assumption of case (b) (η rb = 1).”
From Effect of Ambient Temperature on Electric Vehicles’ Energy Consumption and Range: Model Definition and Sensitivity Analysis Based on Nissan Leaf Data (2019) · cites this paper as [37]
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References 37 · Cited by 156
- Authors
- Genikomsakis, K. N., & Mitrentsis, G.
- Affiliations
- Universidad de Deusto (ES)
- Aristotle University of Thessaloniki (GR)
- Corresponding author
- Genikomsakis, Konstantinos N.
- Venue
- Transportation Research Part D: Transport and Environment
- Publisher
- Elsevier BV
- Published
- 2017-01
- Volume
- 50
- Pages
- 98-118
- ISSN
- 1361-9209 (ISSN-L)
- OpenAlex
- W2551377934
- Cited by
- 156
- References
- 37
- Citations by year
- 2026: 11 · 2025: 20 · 2024: 15 · 2023: 25 · 2022: 16 · 2021: 23 · 2020: 21 · 2019: 10 · 2018: 8 · 2017: 6 · 2016: 1
- FWCI
- 3.84
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Transportation Research Part D Transport and Environment (publishedVersion)
- Funders
- European Commission (609026)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Vehicles and Infrastructure
- Physical Sciences › Engineering › Automotive Engineering › Electric and Hybrid Vehicle Technologies
- Physical Sciences › Engineering › Automotive Engineering › Vehicle emissions and performance
- Keywords
- electric vehicles, load forecasting, route planning, energy-efficient routing, regenerative braking, motor overload, driving cycles, computational efficiency, road slope, vehicle performance modeling
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