RFID EV Charge Linking for Telematics-Based Scheduling
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Solution Overview
Problem
Managing electric vehicle fleets and their charging infrastructure is challenging due to varying vehicle capabilities and charging station capabilities, leading to difficulties in scheduling and optimizing charging, tracking charging sessions, and accurately attributing costs.
Innovation Solution
Utilizing RFID identifiers associated with electric vehicles to initiate and track charging sessions independently of a smartphone app, allowing for retrieval of telematics data such as battery state of charge to optimize charging requests and accurately track costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If smartphone apps are used to link electric vehicles to charging sessions, then user interaction and charging initiation are simplified, but dependency on mobile devices increases and access is limited for users without smartphones
Solution Approach 1:
The patent introduces RFID tags and readers as intermediary devices that enable charging session initiation without requiring smartphone apps. The RFID tag attached to the vehicle communicates with the charging station's reader, serving as a mediator that bypasses the need for mobile device dependency while maintaining ease of operation.
Solution Approach 2:
The patent replaces the mechanical/software-based smartphone app interface with a radio frequency identification (RFID) system. This substitution eliminates the need for complex mobile device interactions, app installations, and software updates, while providing universal access through simple RFID tagging.
2Device complexity
If manual tracking of charging sessions is used, then system complexity is reduced, but tracking becomes increasingly impractical and error-prone as fleets expand
Solution Approach 1:
The system enables automatic charging session tracking where the RFID-based charging station and telematics system self-record charging events, vehicle identifiers, and cost information without requiring manual intervention. This automated self-service approach scales efficiently with fleet size while maintaining low complexity.
Solution Approach 2:
The patent implements automated feedback loops where charging data is automatically captured, transmitted to the cloud environment, processed, and used to update fleet management records. This continuous feedback mechanism ensures accurate tracking and cost attribution without increasing operational complexity.
3Device complexity
If generic charging requests are used, then charging process is simplified, but charging optimization based on individual vehicle needs is reduced
Solution Approach 1:
The patent applies local quality by tailoring charging requests to individual vehicle characteristics. The system retrieves vehicle-specific data such as battery state of charge, charging rate capabilities, and vehicle ID from telematics, then customizes charging parameters for each vehicle rather than applying generic charging protocols to all vehicles.
Solution Approach 2:
The system dynamically adjusts charging parameters based on real-time vehicle data. By changing parameters such as charging power level, session duration, and priority based on individual vehicle needs and battery state, the system optimizes charging efficiency while maintaining a streamlined request process through automated parameter adjustment.
4Adaptability or versatility
If charging data from various stations is aggregated manually, then data integration flexibility is increased, but the process becomes time-consuming and error-prone
Solution Approach 1:
The patent creates a universal data aggregation system in the cloud environment that handles multiple data sources and formats through standardized interfaces. The system can ingest charging data from different RFID readers and telematics systems using common protocols, eliminating the need for manual data collection and conversion while maintaining flexibility across diverse charging stations.
Data Source
AI summary
Certain aspects of the present disclosure provide systems and methods for linking an electric vehicle to a charging session to facilitate charge scheduling and charge optimization. In examples, a method includes receiving a charging request initiated by a proximity-based communication from a wireless identification tag, the charging request including a wireless identifier associated with the electric vehicle and derived from the wireless identification tag. The method also includes authorizing the charging request based on the wireless identifier, retrieving a unique telematics identifier corresponding to the wireless identifier, and querying a telematics system with the unique telematics identifier to obtain vehicle-specific data, where the vehicle-specific data includes a state of charge attribute for a battery associated with the electric vehicle. The method further includes determining a charge amount based on the state of charge attribute and authorizing the determined charge amount for the charging session.