Shared EV Charging Activation Using Reservation Wait-Time Priority
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Solution Overview
Problem
The simultaneous recharging of a large fleet of electric vehicles at shared charging stations can cause significant peaks in electricity consumption and imbalance in the electricity grid, making it difficult to manage energy conditions effectively.
Innovation Solution
A method that calculates average waiting times between vehicle reservations using artificial intelligence and adjusts the activation of charging stations based on these times to stagger recharging, reducing peak consumption and balancing energy conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If charging stations are automatically activated when electric vehicles are connected, then vehicles can be recharged immediately, but this causes significant peaks in electricity consumption and imbalance in the electricity grid
Solution Approach 1:
The system performs preliminary calculation of average waiting times between reservations using AI/ML models before making activation decisions. This allows the system to anticipate future vehicle usage patterns and schedule charging activation in advance, avoiding simultaneous activation of all charging stations and thereby preventing electricity consumption peaks while ensuring vehicles are charged before their next reservation.
2Use of energy by stationary object
If charging stations are activated in a staggered manner to reduce electricity consumption peaks, then energy grid balance is improved, but the complexity of the control system increases
Solution Approach 1:
The system uses AI/ML models to automatically analyze historical reservation data, calculate average waiting times, and generate optimized activation schedules without requiring manual intervention or complex centralized control. The system self-adjusts charging station activation based on predicted vehicle availability, simplifying the control architecture while achieving load balancing across the electricity grid.
3Use of energy by stationary object
If AI/ML models are used to calculate average waiting times and optimize charging activation, then electricity consumption peaks are reduced, but the computational requirements and processing time increase
Solution Approach 1:
The AI/ML models are trained in advance on historical reservation data to learn patterns of vehicle usage. Once trained, the models can quickly predict average waiting times for new vehicles without requiring complex real-time calculations. This preliminary training phase separates the heavy computational work from the real-time decision-making process, reducing processing delays while maintaining optimization effectiveness.
Data Source
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AI summary
The invention relates to a method for controlling the activation of charging stations for electric vehicles, which vehicles belong to a fleet of shared vehicles, said vehicles and said stations being located in a defined geographical zone. Said method comprises the following steps: a) implementing a logic computing process in a computer, which process is suitable for calculating, for each electric vehicle of the fleet which is available for reservation and is connected to a charging station, a mean wait time between two reservations during which said vehicle will not be reserved; b) providing the mean wait time values calculated in step a) to a computing application for managing charging stations which is implemented in a computing server, which values are used as input data for said application, the output data of said application being requests for activation of the charging stations; c) transmitting the activation requests to the charging stations to which the electric vehicles of the fleet which are available for reservation are connected, which transmission is carried out with said requests being prioritised on the basis of the values of the mean wait times calculated in step a).