EV Charger Assignment via Clustering and Priority
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Solution Overview
Problem
The growth of electric vehicle charger infrastructure lags behind the increasing number of electric vehicles, leading to issues such as fully discharged vehicles during long-distance travel and lengthy waiting times at charging stations, especially when users lack advance planning.
Innovation Solution
A method and apparatus for assigning chargers to electric vehicles by clustering them based on location and destination, determining charging priorities, and optimizing charger allocation through data analysis and machine learning algorithms to enhance efficiency and user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If chargers are assigned on a first-come-first-served basis without clustering, then the system is simple to operate, but waiting time increases and charger utilization efficiency decreases
Solution Approach 1:
The system performs preliminary clustering of chargers into clusters before assignment occurs. This pre-organization of chargers into groups allows for more efficient allocation when vehicles arrive, reducing the time needed to assign chargers while maintaining operational simplicity through automated cluster-based assignment rules.
Solution Approach 2:
The system segments the charger infrastructure into multiple clusters based on geographic or operational criteria. This segmentation allows parallel processing of assignment decisions across different clusters, improving overall system efficiency and reducing waiting time without complicating the user experience.
2Ease of operation
If chargers are distributed uniformly across service areas, then charger accessibility is improved, but the degree of use of each charger becomes unbalanced leading to frequent breakdowns
Solution Approach 1:
The system applies different assignment strategies to different charger clusters based on their local characteristics such as demand patterns, geographic location, and usage history. This localized approach ensures that high-demand areas receive appropriate charger allocation while preventing overuse of specific chargers, thereby maintaining reliability without compromising accessibility.
Solution Approach 2:
The system monitors charger usage patterns and feeds this information back into the clustering and assignment process. By analyzing actual demand situations and adjusting cluster configurations accordingly, the system balances charger utilization across the network, preventing any single charger from being overused and breaking down.
3Device complexity
If charging reservation requests are processed individually without clustering, then processing is simpler, but charging priority determination becomes less accurate
Solution Approach 1:
The system performs preliminary clustering of charging requests based on vehicle characteristics, destination, and charging needs before priority determination. This pre-grouping allows for more accurate and efficient priority assignment by considering multiple factors simultaneously within each cluster, improving measurement precision without significantly increasing processing complexity.
Solution Approach 2:
The system segments charging requests into different clusters based on priority criteria such as vehicle type, charging urgency, and destination requirements. This segmentation enables parallel processing of priority determination across clusters while maintaining accurate prioritization within each segment, balancing complexity and precision.
Data Source
AI summary
The present invention relates to a method and an apparatus for assigning chargers to electric vehicles. The method comprises clustering chargers into at least one charger cluster, receiving charging reservation requests from the electric vehicles during a predetermined period of time, clustering the electric vehicles into at least one electric vehicle cluster, determining a charging priority between the electric vehicles based on the at least one electric vehicle cluster and assigning the chargers to the electric vehicles based on the determined charging priority. As a result of this, an efficient charging reservation is proposed to a user, so that it is possible to help the user utilize time efficiently.