Abstract
A major drawback of battery electric vehicles is their small range. For long-distance coverage, stops for charging are inevitable. Because of emerging technologies, charging durations can be reduced to 30 min; this reduction means that short stops for charging are possible, even during a long trip. In this study, the problem of finding optimal charging strategies was formulated as a time-dependent, bicriteria, shortest-path problem. The intention was to provide a new feature for navigation by computing for a predefined route when and how long a battery must be charged to reach a destination quickly and reliably (i.e., without the risk of an empty battery). Two algorithms for solving this problem are explained. A case study analyzed the performance of these two algorithms and the impact of several modifications of the underlying graph-based representation of charging possibilities. For practical relevance to be obtained, historical traffic data were used to estimate travel times and energy consumption within the case study, along with real-time traffic information from an online stream hosted by a professional traffic data provider.
| Original language | English |
|---|---|
| Pages (from-to) | 45-53 |
| Number of pages | 9 |
| Journal | Transportation Research Record |
| Volume | 2497 |
| DOIs | |
| State | Published - 2015 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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