Comparing technologies and algorithms behind mapping and routing APIs for Electric Vehicles
Abstract: The fast-developing industry of electric vehicles is growing, and so is the driver community, which puts pressure on the electric charging grid. The purpose of this thesis is to simplify for the drivers of electric cars to charge their cars during trips. The research questions investigated are” How do the technologies and algorithms behind navigation APIs differ from each other?” and “What information is provided by the charging station APIs and how do they collect data about new stations?”. Information for the thesis was collected by reading and analyzing both documentation and previous work, as well as by conducting experiments. The study was limited to purely electric vehicles. We created an application to conduct experiments on the API combination Mapbox and Open Charge Map, we call it ChargeX. We compare, TomTom, Tesla, Plugshare, Google Maps and ChargeX. The most common shortest-path algorithms are Dijkstra’s, A' and Bidirectional A'. They provide reasonable solutions to the shortest path problem. The algorithms can be improved by considering traffic flow, travel time and distance between origin and destination and apply it as weights on the edges. What has the largest impact on the final route is the choice of charging stations. The algorithm for picking charging stations can be optimized in several ways for example by considering real time availability information of the charging stations, prioritize highways, calculate the temperature and altitude impact on the battery or prioritize faster chargers such as superchargers for Tesla.
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