Route Planning for Electric Vehicles with Dynamic Charging Strategy
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Solution Overview
Problem
The increasing demand for charging infrastructure for plug-in hybrid and electric vehicles leads to inhomogeneous occupancy of charging stations, resulting in long waiting times and increased travel duration, which negatively impacts the acceptance of electric vehicle technology.
Innovation Solution
A method for route planning that utilizes traffic data, historical traffic data, weather data, and current vehicle status to determine the expected occupancy of charging stations along a route, allowing for a dynamic charging strategy to be provided to the driver, which includes recommendations for location, charging duration, and number of charging processes, thereby optimizing the route to reduce travel time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If charging stations are distributed along the route, then charging availability is improved, but occupancy becomes inhomogeneous causing long waiting times
Solution Approach 1:
The system performs preliminary determination of expected occupancy at charging stations along the route before the vehicle arrives. By predicting occupancy based on traffic data and route information in advance, the system enables drivers to plan charging stops optimally, avoiding stations with high expected occupancy and reducing waiting time while maintaining charging availability.
Solution Approach 2:
The system provides feedback to the driver about expected occupancy at different charging stations along the route. This information allows the driver to make informed decisions about which station to visit, selecting stations with lower expected occupancy to minimize waiting time while ensuring charging services are available.
2Loss of time
If charging strategy is optimized based on traffic data, then travel duration is reduced, but system complexity increases
Solution Approach 1:
The system uses traffic data parameters (current traffic density, historical traffic patterns) to dynamically adjust the charging strategy. By changing the approach based on these parameters - such as selecting different charging stations or timing - the system reduces travel duration without requiring overly complex computational methods.
3Ease of operation
If charging stations are located at high-traffic areas, then accessibility is improved, but occupancy increases leading to longer queues
Solution Approach 1:
The system applies local quality by evaluating individual charging stations along the route and providing specific information about their expected occupancy. This allows the driver to select specific stations with lower expected occupancy rather than assuming all stations in high-traffic areas are equally busy, maintaining accessibility while avoiding high-occupancy locations.
Data Source
AI summary
A method determines an anticipated occupation of charging points and a charging strategy for a specified route. The method provides traffic data which is representative for the current traffic density on the route specified. An anticipated occupation of charging points along the specified route can be determined on the basis of the traffic data. A charging strategy can be determined on the basis of the traffic data and the determined anticipated occupation of charging points. The provision of information regarding a charging strategy to a driver allows the time required for the specified route to be reduced.