Charging Station Feature Detection Using Vehicle Sensor Feedback
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Solution Overview
Problem
Existing charging station information systems are outdated and lack comprehensive, real-time data on charging station features, leading to inefficient and suboptimal user experiences for electric vehicle drivers.
Innovation Solution
A multi-modal model that integrates vehicle sensor data with cloud computing to collect and process images, videos, and customer feedback to create a continuously updated feature list for charging stations, using a charger monitoring server to manage and update a charger feature table.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional charging station information systems are used, then system simplicity is maintained, but information accuracy and real-time data availability deteriorate
Solution Approach 1:
The system uses existing vehicle sensors for multiple purposes: primary function for vehicle operation, secondary function for charging station feature detection. This multi-functionality improves information accuracy without proportionally increasing system complexity, as the sensors serve dual roles.
Solution Approach 2:
Vehicles automatically capture and transmit charging station feature data without manual intervention. The system self-updates the charger feature table by processing sensor data from multiple vehicles, eliminating the need for manual data collection and maintenance while improving real-time accuracy.
2Reliability
If manual data collection methods are used, then system complexity is reduced, but data currency and completeness worsen
Solution Approach 1:
The system implements continuous feedback loops where vehicles repeatedly detect charging station features and update the charger feature table. This ongoing feedback mechanism ensures data remains current and reliable, automatically correcting stale information without manual intervention.
Solution Approach 2:
The system proactively detects and updates charging station feature information before users need it. By continuously monitoring and updating the charger feature table in advance, the system ensures data is current when users query for charging stations, eliminating the need for reactive manual updates.
3Ease of operation
If comprehensive feature detection is implemented, then user experience quality improves, but system complexity and processing requirements worsen
Solution Approach 1:
The system segments charging station features into distinct categories (physical features, operational status, amenities) and processes them separately through specialized detection methods. This segmentation allows comprehensive feature detection without overwhelming processing complexity, as each feature type can be handled by appropriate sensors and algorithms.
Solution Approach 2:
The system combines sensor data from multiple vehicles to detect and verify charging station features. By merging data from multiple sources, the system achieves comprehensive and accurate feature detection while distributing processing load, reducing the complexity burden on any single vehicle or server.
Data Source
AI summary
A charger feature table is descriptive of which charging stations have which of a plurality of features. Vehicle data to capture according to each feature for each charging station, the vehicle data being specified in terms of types of sensors of vehicles of known configurations. A data request is broadcast to the vehicles indicating the vehicle data to be captured. New vehicle data is received from the vehicles responsive to the data request. A multi-modal model, trained to recognize the plurality of features using the types of sensors of the vehicles of known configurations, is used to determine an updated value for the feature based at least in part on the new vehicle data. The charger feature table is updated to include the updated value for the feature. The charger feature table is used to identify charging stations for a requesting vehicle.