EV Charging Station Availability Using Anonymized Vehicle Preferences
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing EV charging optimization algorithms require sensitive information about vehicle routes and battery levels, compromising privacy and increasing compute and bandwidth demands, making it challenging to provide real-time charging station availability without exposing private data.
Innovation Solution
A system where each vehicle computes probabilities of reaching nearby charging stations based on its battery level and preferences, sharing only anonymized data with the service provider to determine availability, reducing the need for sensitive information exchange.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If vehicles share detailed route and battery level information with service providers, then charging station availability can be determined accurately, but driver privacy is compromised and bandwidth consumption increases
Solution Approach 1:
The patent extracts only the essential information needed for availability determination (charging station preferences and arrival times) while leaving out sensitive personal data (detailed routes, battery levels, driver identity). This selective extraction maintains measurement precision for availability while protecting driver privacy.
Solution Approach 2:
The patent introduces an intermediary mechanism where vehicles submit charging station preferences and arrival times through a standardized interface, which the service provider then processes to determine availability. This intermediary layer filters out unnecessary personal information while preserving the functional data needed for accurate availability determination.
2Measurement precision
If vehicles share detailed route and battery level information with service providers, then charging station availability can be determined accurately, but bandwidth consumption increases
Solution Approach 1:
The patent extracts only the minimal necessary data elements (charging station identifiers and arrival times) required for availability determination, eliminating redundant information transmission. This reduces bandwidth consumption while maintaining the precision needed for accurate availability assessment.
3Loss of information
If service providers process detailed vehicle information centrally, then availability information can be provided comprehensively, but compute resource usage increases
Solution Approach 1:
The patent extracts and processes only the essential elements (charging station preferences and arrival times) at the service provider端, reducing the computational burden while maintaining comprehensive availability information. This selective processing approach balances information completeness with resource efficiency.
Data Source
AI summary
An approach is provided for electric vehicle charging station availability. The approach involves, for example, receiving transmissions from one or more vehicles. Each transmission comprises a list of charging stations, estimated times of arrival for the one or more vehicles to reach each charging station, and values computed to indicate a preference of the one or more vehicles to reach each charging station. The approach also involves processing the list of the one or more charging stations, estimated times of arrival, and preference values to determine respective probabilities that each charging station will be available at the estimated times of arrival. The approach further involves determining at least one recommended charging station from among the charging stations based on the respective probabilities.