EV Charging Station Selection Using Privacy-Preserving Location Approximation
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Solution Overview
Problem
Existing methods for locating charging stations for electric vehicles raise concerns regarding personal data processing, particularly due to GDPR regulations, necessitating a solution that respects data privacy while providing real-time charging station information.
Innovation Solution
A method that determines approximate vehicle positions by adding a random error to GPS data, allowing for the selection of nearby charging stations without storing precise location data, using statistical learning to identify parking habits and prioritize stations based on frequency and duration of use.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If precise GPS location data is collected and stored for real-time charging station selection, then the accuracy of charging station recommendation is improved, but personal data privacy protection deteriorates
Solution Approach 1:
The patent creates approximate position data as a copy of the precise GPS location, adding random error within a defined range. This copy retains sufficient accuracy for charging station selection while eliminating personally identifiable information, thus resolving the contradiction between location accuracy and privacy protection
Solution Approach 2:
The patent transforms the precise location parameter by introducing random error values within a specific range. This parameter change maintains the location data's utility for finding charging stations while degrading it enough to protect privacy, achieving both goals simultaneously
2Object-affected harmful factors
If approximate position data with random error is used instead of precise GPS data, then data privacy protection is improved, but the precision of vehicle location determination deteriorates
Solution Approach 1:
The patent applies partial degradation to the location data by adding random error within a controlled range rather than completely anonymizing the data. This partial action preserves sufficient accuracy for the specific application (charging station selection) while achieving privacy protection, resolving the contradiction between privacy and precision
3Adaptability or versatility
If real-time tracking of vehicle journeys is implemented to identify parking habits, then the personalization of charging station recommendation is improved, but the quantity of personal data processed increases
Solution Approach 1:
The patent extracts only the essential pattern information (parking habit frequencies and durations) from the journey data, discarding the detailed personal location information. This extraction achieves personalization through aggregated statistics while minimizing personal data retention, resolving the contradiction between personalization and data quantity
Data Source
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AI summary
The present invention relates to a method and a device for selecting a charging station for an electrically powered vehicle (10). To do this, first data indicative of the stop and/or start status of a motor of the vehicle (10) at the current moment are received by a remote device (101). The first data include a first position of the vehicle (10) at the current moment. A first approximate position of the vehicle at the current moment is determined by applying to the first position a first distance selected at random from a determined range of distances. This first approximate position is compared against a plurality of positions associated with a plurality of charging stations. The charging station closest to the first approximate position of the vehicle is then selected from among the stations that make up the plurality of charging stations.