EV Charging Queue Management for Fleet Availability
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Solution Overview
Problem
The long charging time of electric vehicles, particularly autonomous electric vehicles, is a significant drawback compared to combustion vehicles, and existing wireless charging systems lack efficient management of vehicle queuing and charging station allocation, leading to potential delays and inefficiencies.
Innovation Solution
A method for managing the queuing and assignment of electric vehicles to charging stations based on departure time and charging time, utilizing a computing system to sort vehicles into tiers and assign them to charging stations, ensuring that vehicles with sooner departure times and faster charging needs are prioritized, thereby optimizing the use of charging infrastructure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If electric vehicles are charged using wireless charging systems, then charging convenience is improved, but charging time becomes excessively long compared to combustion vehicles
Solution Approach 1:
The system performs preliminary actions by sorting vehicles into tiers and creating optimized charge queues before charging begins. Vehicles are pre-assigned to charging stations based on their state of charge, battery capacity, and departure time, ensuring that charging sequences are determined in advance to minimize overall charging time and maximize fleet availability.
2Device complexity
If vehicles are charged on a first-come-first-served basis, then system simplicity is maintained, but fleet availability decreases due to inefficient charging station allocation
Solution Approach 1:
The system segments the charging queue into multiple tiers based on vehicle characteristics such as state of charge, battery capacity, and departure time. This segmentation allows for differentiated charging priorities, where vehicles with lower state of charge or smaller battery capacities are assigned higher priority, thereby optimizing fleet availability without requiring complete system redesign.
Solution Approach 2:
The system changes the parameter of queue assignment from simple first-come-first-served ordering to a multi-parameter sorting system that considers state of charge, battery capacity, and departure time. This parameter transformation enables more efficient charging station allocation while maintaining manageable system complexity through automated computational sorting.
3Productivity
If vehicles with large battery capacity and low state of charge are prioritized for charging, then overall charging efficiency is improved, but vehicles with urgent departure times may experience delays
Solution Approach 1:
The system transforms the queue ordering parameter from simple arrival time to a composite parameter that includes state of charge, battery capacity, and departure time. This allows the system to balance charging efficiency with urgent departure requirements by computationally determining optimal charge sequences that consider multiple factors simultaneously.
Solution Approach 2:
The charging queue system is made dynamic by continuously evaluating vehicle parameters and adjusting queue assignments. The system can adaptively reassign vehicles to different charging stations or queue positions based on changing conditions such as updated departure times or battery state changes, ensuring optimal balance between charging efficiency and service urgency.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces wait times and increases the availability of autonomous vehicles by prioritizing vehicles with urgent departure times and faster charging requirements, ensuring timely arrivals and reducing the likelihood of delays caused by vehicles with low state of charge and high capacity.
Implementation Method 1
wireless charging wherein an inductive coil at a charging station induces current in a corresponding coil on the vehicle
Data Source
AI summary
Electric vehicles arriving at a charging station transmit their state of charge, capacity, and departure time to a computer system. Vehicles are sorted into tiers according to departure time and sorted within tiers according to charging time based on state of charge and capacity. The vehicles are then assigned to queues according to the tiers and ordering within tiers such that vehicles with sooner departure times and shorter charge times are given priority. Where there are multiple queues, vehicles with a shorter charge time may be assigned to a first queue while remaining vehicles are assigned to one or more other queues. Charging stations may have different capacity and vehicles with higher priority according to sooner departure time and shorter charging time may be assigned to faster chargers.