EV Charge Point Selection Using Load Balancing and Occupancy
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Solution Overview
Problem
The existing EV charging infrastructure is inadequate to support the growing number of electric vehicles, leading to insufficient access to efficient charging stations, broken chargers, high rates, and confusion about charging times, which poses a significant barrier to the widespread adoption of EVs.
Innovation Solution
A system that analyzes metrics such as location, power availability, occupancy, and dynamic load balancing of charging stations to estimate charging times, providing color-coded icons on a map for user selection of optimal charging points.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If EV charging infrastructure is expanded to increase availability, then access to charging stations is improved, but investment cost and infrastructure complexity increase
Solution Approach 1:
The patent introduces a centralized server as an intermediary that coordinates between multiple charging stations and users. This server manages load balancing, user authentication, and charging session control, allowing individual charging stations to remain relatively simple while the system as a whole provides complex functionality through the mediating server.
Solution Approach 2:
The charging station system is designed with multi-functional capabilities including user authentication, real-time status monitoring, dynamic load balancing, and billing integration. This universal approach allows a single charging station design to serve multiple purposes and adapt to varying demand conditions without requiring separate specialized infrastructure for each function.
2Quantity of substance
If more charging points are deployed to meet demand, then charging availability is improved, but power distribution efficiency deteriorates due to load imbalance
Solution Approach 1:
The patent implements dynamic load balancing that continuously adjusts power distribution based on real-time conditions. The system monitors the state of charge, arrival times, and charging rates of multiple vehicles, then dynamically reallocates power from slower-charging vehicles to faster-charging vehicles. This dynamic adjustment optimizes overall power distribution efficiency across the charging station without requiring additional infrastructure.
Solution Approach 2:
The system changes operational parameters such as charging current and power allocation in real-time based on vehicle battery states and demand conditions. By adjusting these parameters dynamically rather than maintaining fixed charging rates, the system achieves more efficient power utilization across multiple charging points serving different vehicles simultaneously.
3Productivity
If charging stations operate at high occupancy, then infrastructure utilization is improved, but charging time increases due to queueing
Solution Approach 1:
The system performs preliminary actions by predicting vehicle arrivals and pre-allocation of charging resources. Users can reserve charging slots in advance, and the system prepares power allocation strategies before vehicles arrive. This preliminary planning reduces actual charging time when vehicles arrive, as the infrastructure is already optimized and ready to serve them immediately upon arrival.
Solution Approach 2:
The patent implements continuous feedback loops that monitor charging progress, vehicle departure times, and queue status. This feedback information is used to adjust power distribution in real-time and provide users with accurate estimated wait times. The feedback mechanism allows the system to optimize charging schedules dynamically, balancing high utilization with minimized charging time through informed decision-making.
Data Source
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AI summary
An apparatus and method relate to analyzing metrics relating to EV charging points and facilitating selection of an EV charge point based on metrics associated with the EV charge points. Methods may include: determining locations of one or more electric vehicle charging stations; determining a total power available at the one or more electric vehicle charging stations; determining, for the one or more electric vehicle charging stations, if dynamic load balancing is used; determining occupancy of charge points at each of the one or more electric vehicle charging stations; calculating an available power at a charge point of the one or more electric vehicle charging stations based on the total power available and the occupancy of charge points for the one or more electric vehicle charging stations; and calculating an estimated time to charge a vehicle at the one or more electric vehicle charging stations based on the available power.