EV Charging Station Selection Using Occupancy And Speed Estimates
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Solution Overview
Problem
Users of electric vehicles face challenges in finding available charging stations and estimating charging speeds due to limited access to occupancy status information, which affects user experience and decision-making.
Innovation Solution
A computer-implemented method and system that determine the current geo-location and state of charge of an electric vehicle, identify nearby charging entities, calculate occupancy statuses, estimate charging speeds, and present a charging station map user interface to help users select the best charging option based on real-time data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If users search for charging stations without occupancy status information, then users can find charging entities, but users cannot make informed decisions about charging speed and availability
Solution Approach 1:
The system calculates and provides occupancy status information before the user arrives at the charging entity, allowing users to make informed decisions in advance about which charging stations to visit, rather than finding out occupancy status only upon arrival
Solution Approach 2:
The system implements a feedback mechanism where charging entity data is collected from multiple sources (charging stations, third-party systems, user inputs) and continuously updated to reflect real-time occupancy status, which is then fed back to users through the interface
2Measurement precision
If the system collects real-time occupancy data from multiple sources, then charging speed estimation accuracy improves, but system complexity increases
Solution Approach 1:
The system uses intermediary components including a third-party system for data exchange, a queue management system to handle multiple data sources, and standardized data formats to integrate information from diverse sources without directly connecting to each charging station's internal systems
Solution Approach 2:
The data collection system is segmented into multiple independent components: charging station data receivers, third-party system interfaces, user input processors, and a central occupancy status calculator, allowing each component to operate independently and be maintained separately
3Ease of operation
If the system provides detailed occupancy status and charging speed information, then user decision-making improves, but information processing requirements increase
Solution Approach 1:
The system calculates occupancy status locally at each charging entity rather than performing global computations, and provides information tailored to the user's specific location and needs, reducing overall computational requirements while maintaining decision-making quality
Data Source
AI summary
Systems and methods for selecting a charging entity based on occupancy status are provided. In one embodiment, a method includes determining a current geo-location and state of charge of a requesting vehicle and a plurality of charging entities that are within a remaining distance of the requesting vehicle. Occupancy statuses for one or more charging entities of the plurality of charging entities are determined based on a number charging vehicles and a charging parameter. The method includes estimating charging speeds for the one or more charging entities based on the occupancy statuses. A charging station map user interface that pin points the current geo-location of the requesting vehicle and the one or more charging entities is presented. The one or more charging entities are presented with labels. The method further includes reserving a charging station of a selected charging entity of the plurality of charging entities by selecting a label.