EV Charging Route Recommendation Using Station Pre-Selection
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Solution Overview
Problem
The insufficient electric vehicle charging infrastructure, particularly due to regional characteristics and built environment factors, leads to difficulties in finding suitable charging stations along navigation routes, resulting in challenges for electric vehicle users.
Innovation Solution
A charging station information providing server and application that receive route recommendation requests, search for direct routes, select charging station candidates based on customized conditions, and configure recommended charging routes using a route recommendation model, ensuring optimal charging station utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a direct route is provided without considering charging stations, then the route is simple and fast to calculate, but the electric vehicle may not have sufficient charge to reach the destination or next charging station
Solution Approach 1:
The system performs preliminary identification of charging stations along the direct route before finalizing the navigation path. By pre-selecting charging stations based on vehicle type, battery capacity, and route characteristics, the system ensures charge sufficiency is addressed in advance, allowing the route to maintain simplicity while guaranteeing charging needs are met.
Solution Approach 2:
The route calculation is segmented into two independent stages: first calculating the direct route from origin to destination, then separately identifying charging stations along that route. This segmentation allows the core route calculation to remain simple and fast, while charging station identification is handled as a separate overlay process that adds reliability without significantly increasing overall complexity.
2Reliability
If charging station information is integrated into navigation, then charging reliability is improved, but the navigation system becomes more complex
Solution Approach 1:
The system introduces a dedicated charging station identification module as an intermediary component that bridges the simple direct route calculation and the charging requirements. This intermediary selectively identifies and filters charging stations along the route based on specific criteria (vehicle type, battery capacity, charging speed preferences), adding charging reliability while maintaining a clear separation of concerns and limiting overall system complexity.
Solution Approach 2:
The navigation system maintains different levels of complexity for different functional components: the core route calculation remains simple and direct, while the charging station identification and selection applies localized, targeted analysis only where needed along the route. This local quality approach ensures charging reliability is improved through detailed analysis at specific points without making the entire navigation system unnecessarily complex.
3Reliability
If multiple charging station candidates are evaluated, then the recommended route becomes more reliable, but the calculation time increases
Solution Approach 1:
The system evaluates charging stations selectively rather than exhaustively. It identifies a sufficient number of charging station candidates along the direct route based on vehicle-specific requirements and route characteristics, without performing complete evaluations of all possible charging stations. This partial action approach provides reliable route recommendations with adequate charging options while avoiding the excessive calculation time that would result from evaluating every possible charging station.
Solution Approach 2:
The system uses parameter-based filtering to efficiently evaluate charging station candidates. By establishing key parameters such as vehicle type, battery capacity, minimum charge requirements, and optional preferences (charging speed, station type), the system可以快速 filter and rank charging stations along the route. This parameter-driven approach ensures reliable route recommendations are generated quickly without exhaustive evaluation of all charging stations.
4Ease of operation
If charging station selection is customized based on vehicle information and user preferences, then the service quality is improved, but the data processing complexity increases
Solution Approach 1:
The system performs preliminary collection and storage of vehicle information (type, battery capacity, charging port type) and user preferences (charging speed preferences, station type preferences) before route calculation. By having this data pre-available and organized, the charging station selection process can efficiently match vehicles with suitable charging stations without requiring complex real-time data processing during route calculation, thus improving service quality while limiting data processing complexity.
Solution Approach 2:
The system uses parameter-based matching to simplify customized charging station selection. By establishing clear parameters for vehicle characteristics and user preferences, the system can efficiently filter and rank charging station candidates that match these parameters. This parameter-driven matching approach enables high-quality customized service without requiring overly complex data processing algorithms.
Data Source
AI summary
A charging station information provision server receives a route recommendation request including route configuration information from an external device, in response to the received route recommendation request, searches for a direct route based on the route configuration information, selects a charging station candidate group based on the direct route using a charging station selection model with an input of condition information for customized recommendations, vehicle information, road condition information, and information about charging stations, uses a route recommendation model to configure at least one recommended charging route, based on the selected charging station candidate group, and transmits the at least one recommended charging route to the external device.