Charging Station Usage Analytics for Unavailability Detection
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Solution Overview
Problem
Traditional self-test or diagnostic processes for vehicle charging stations are limited in identifying unavailability due to external factors such as environmental conditions, vandalism, or location issues, failing to accurately characterize operational stations that are not available for use.
Innovation Solution
A network service that processes correlated usage data as time series data to identify statistically significant deviations in usage patterns, generating notifications and instructions for mitigation actions, and utilizing additional diagnostic systems or scheduling service calls to verify and address unavailability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional self-test or diagnostic processes are used for charging stations, then the diagnostic system remains simple and easy to operate, but the system fails to accurately identify unavailability due to external factors such as environmental conditions, vandalism, or location issues
Solution Approach 1:
The patent combines multiple diagnostic approaches: traditional self-test functionality of charging stations is merged with external monitoring systems that track usage patterns and environmental factors. This integration allows the system to accurately identify unavailability caused by external factors like vandalism or environmental conditions while maintaining operational simplicity through centralized analysis.
Solution Approach 2:
The patent introduces an intermediary monitoring system that acts as a mediator between the charging station and the diagnostic analysis. This intermediary collects usage data, environmental information, and operational status, then processes this information to determine unavailability causes, preventing direct complexity at the charging station while improving identification accuracy.
2Reliability
If traditional self-test processes are used, then the system requires minimal resources and infrastructure, but it cannot detect unavailability caused by external factors such as environmental conditions or vandalism
Solution Approach 1:
An intermediary monitoring system is introduced that collects data from multiple sources including charging station self-tests, usage patterns, and environmental sensors. This intermediary processes the combined information to reliably characterize operational status, accurately detecting external factors like vandalism or environmental conditions without requiring direct modification of the charging station hardware.
Solution Approach 2:
The patent implements a feedback mechanism where usage data and operational status are continuously monitored and fed back to the diagnostic system. This feedback loop enables the system to learn from patterns and accurately identify unavailability causes over time, improving reliability through data-driven analysis rather than simple threshold-based self-tests.
3Measurement precision
If usage data is collected and analyzed to identify unavailability patterns, then the system can accurately characterize charging station availability, but additional infrastructure and data processing capabilities are required
Solution Approach 1:
The patent introduces a data processing intermediary that collects usage information from charging stations and analyzes patterns to identify unavailability. This intermediary handles the complexity of data aggregation, cleaning, and analysis, allowing accurate measurement precision while keeping the charging stations themselves simple and focused on their primary charging function.
Data Source
AI summary
The present disclosure related to a management of a plurality of charging stations utilizing collected usage data. A network service receives and maintains correlated charging station use data as time series data. The time series data corresponds to a defined time window in which individual time intervals may be characterized as use or non-use of the charging station. The non-use can be identified and compared to thresholds of non-use associated with charging stations that are characterized as operational. If an individual time interval of non-use exceeds a threshold, the individual unit may be considered operational but not available for service. More specifically, the network service determines whether any particular instance of sequential non-use corresponds to a statistically significant deviation of established periods of non-use. If such a deviation occurs, the consecutive period of non-use can be considered to be indicative of an unavailability of the charging station.