EV Charging Network Controller Prioritizing Low Battery Vehicles
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Solution Overview
Problem
Range anxiety in battery electric vehicles (BEVs) and hybrid electric vehicles (HEVs is exacerbated by limited range per charge and inadequate charging infrastructure, further complicated by increased extreme weather leading to electrical blackouts.
Innovation Solution
A network of electric vehicle chargers with a controller that broadcasts commands for vehicles to charge when there's a threshold risk of utility grid power loss, prioritizing those with the lowest state of charge first, utilizing Internet-of-Things (IOT) devices connected to the utility grid to monitor power loss and communicate with vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If vehicles charge normally without prioritization, then charging infrastructure operates efficiently, but vehicles with low battery levels may not be charged in time during grid power loss events
Solution Approach 1:
The system performs preliminary actions by establishing charging priorities based on state of charge levels before grid power loss occurs. Vehicles are pre-identified and queued for charging based on their battery levels, ensuring that when power loss events happen, the prioritization is already in place and charging can immediately begin with the most critical vehicles first.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring vehicle state of charge levels and grid power conditions. This feedback loop allows the charging network to dynamically adjust charging priorities and respond to changing conditions, ensuring reliable charging for vehicles that need it most while adapting to real-time grid status.
2Reliability
If the charging network monitors and responds to grid power loss events, then vehicle charging reliability improves, but system complexity and communication requirements increase
Solution Approach 1:
The system uses an intermediary approach by implementing a centralized charging network controller that mediates between the utility grid and individual vehicles. This intermediary component consolidates the monitoring and decision-making functions, simplifying the overall system architecture while maintaining reliable charging during blackouts through coordinated control.
Solution Approach 2:
The charging network controller performs multiple functions including grid monitoring, vehicle communication, priority assignment, and charging coordination. By making the controller universal and multi-functional, the system reduces the need for separate dedicated components for each function, thereby managing complexity while achieving reliable blackout response.
3Reliability
If all vehicles are charged equally during grid power loss, then fairness is maintained, but vehicles with lowest state of charge may not receive adequate charging
Solution Approach 1:
The system applies local quality by differentiating charging treatment based on individual vehicle needs. Instead of uniform charging for all vehicles, the system assigns different charging priorities to different vehicles based on their state of charge levels, ensuring that vehicles with critically low batteries receive preferential treatment while maintaining overall system efficiency.
Solution Approach 2:
Charging priorities are established in advance based on vehicle state of charge levels before power loss events occur. This preliminary prioritization ensures that when blackouts happen, the system immediately knows which vehicles need charging most urgently, eliminating the need for complex real-time decisions during the event.
Data Source
AI summary
A network of electric vehicle chargers is provided. The network may include a controller that, responsive to data indicating a threshold risk of utility grid power loss in a defined geographic area, broadcasts commands summoning vehicles in the defined geographic area to travel to and charge via the network, and prioritize charging of the vehicles at the network according to charge state data such that the vehicles having lowest state of charge are charged first.