Literature Database Entry


Sven Schoenberg, "Trip Planning for Electric Vehicles," PhD Thesis, Department of Computer Science, Paderborn University (UPB), January 2023. (Advisor: Falko Dressler; Referees: Falko Dressler and Claudio Ettore Casetti)


Electric vehicles are ever increasing in popularity and will likely supersede vehicles with internal combustion engines in the future. But short driving ranges and long charging times still make them less convenient for long-distance travel. Also, drivers that cannot charge at home have to rely on the public charging infrastructure for everyday charging, which often requires extra time compared to filling up an internal combustion engine vehicle or charging at home. Another potential issue is that long wait times could occur when too many vehicles want to charge at the same time at the same charging station. In this thesis, we present several approaches to address these issues. First, by planning long-distance trips including charge stops, we can minimize the total travel time on long journeys. We select the best compromise between fast and energy-efficient routes by using a multicriteria shortest path search. We also take into account nonlinear charge curves and consider only partially charging the vehicle’s battery at the charge stops. To achieve practical computation times, we exploit the fact that most route queries are between the known locations of the charging stations and precompute parts of the shortest path search for these locations. Simulation experiments confirmed that our routing and charging strategy results in reduced total travel times compared to alternative strategies. Second, to minimize the extra time required for everyday charging, we plan urban trips including charge stops while taking the driver’s schedule for the day into account. The vehicle is charged either en route while stopping at a fast charging station, similar to using a gas station, or at a charging station close to the destination. The latter has the advantage that the driver can visit the destination and does not have to wait with the vehicle, but it is only feasible if a charging station is available within walking distance of the destination. Simulation results indicate that having both options can significantly improve the extra time spent with charging compared to being limited to one option. Third, we propose a central service that coordinates charging between vehicles to reduce the time people have to wait at charging stations. Vehicles can query wait time estimates for any charging station at any point in the future, if they agree to announce their own planned charge stops to the service in exchange. The wait time estimates can be used by the vehicles when planning their trips to avoid long wait times. In simulations, we were able to achieve a reduction in wait times of up to 98 %. Fourth, we introduce an approach to extend the public charging infrastructure. By analyzing typical driver schedules, we identify locations for new slow and fast charging stations and, using simulations, we determine a suitable number of charge points. With a combination of a few fast charging stations and many slow charging stations, we were able to significantly reduce the average extra time spent with charging.

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Sven Schoenberg

BibTeX reference

    author = {Schoenberg, Sven},
    title = {{Trip Planning for Electric Vehicles}},
    advisor = {Dressler, Falko},
    institution = {Department of Computer Science},
    location = {Paderborn, Germany},
    month = {1},
    referee = {Dressler, Falko and Casetti, Claudio Ettore},
    school = {Paderborn University (UPB)},
    type = {PhD Thesis},
    year = {2023},

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