EV Charging Control Module Using Fuzzy Logic for Grid Load Management
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Solution Overview
Problem
Current methods for recharging electric and plug-in hybrid vehicles face challenges in controlling electrical power demand, requiring extensive data collection and forecasting renewable energy production, which is difficult and often unreliable, leading to inefficiencies in energy usage and network strain.
Innovation Solution
A method and device that use a control module in each vehicle to determine a setpoint for electrical power based on the state of charge and recharging duration, adjusting power supply from the electrical distribution network using fuzzy logic and coefficients to optimize energy use, particularly promoting the use of renewable energy sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If methods for controlling electrical power for charging vehicles are implemented, then the impact on the national consumption curve is reduced, but a large amount of data collection and transmission is required
Solution Approach 1:
The patent extracts only the essential data elements needed for power control (vehicle identification, charging power request, state of charge) from the comprehensive data set previously required. This selective extraction reduces data transmission requirements while maintaining effective power control capability.
Solution Approach 2:
The control system is segmented into distributed components: a communication unit for minimal data exchange, a processing unit for local decision-making, and a control unit for execution. This segmentation allows each component to handle specific tasks with reduced data requirements compared to a centralized system.
2Use of energy by moving object
If renewable energy forecasting is used for recharging, then the use of renewable energy is promoted, but the forecast may not be available or may differ from actual production
Solution Approach 1:
The system implements feedback mechanisms where actual renewable energy production data is continuously compared with forecast data. This feedback loop allows the system to adapt to discrepancies between predicted and actual production, maintaining reliable renewable energy utilization even when forecasts are unavailable or inaccurate.
Solution Approach 2:
The charging control system dynamically adjusts its operation based on real-time renewable energy availability rather than relying solely on static forecasts. The system can flexibly respond to changing production conditions, promoting renewable energy use while adapting to actual rather than predicted production levels.
3Power
If the number of vehicles to be recharged is controlled, then the electrical power demand is managed, but the number of vehicles is variable in practice
Solution Approach 1:
The system dynamically determines the number of vehicles to charge based on real-time power availability and vehicle queue conditions. Rather than using a fixed control parameter, the system continuously adapts the charging fleet size to match actual renewable energy production and grid conditions, effectively managing power demand while accommodating vehicle number variability.
4Ease of operation
If extensive data transmission to a management module is required, then the charging control is comprehensive, but the implementation becomes complex and time-consuming
Solution Approach 1:
The patent extracts and transmits only the minimum necessary data elements (vehicle ID, charging power request, state of charge) to the management module, eliminating the need for comprehensive data transmission. This selective approach maintains charging control effectiveness while dramatically reducing system complexity and data transmission requirements.
Data Source
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AI summary
The invention relates to a method for recharging electric or hybrid vehicles (VE1) by charging stations (B1) connected to an electric power grid (14). The method comprises supplying, for each vehicle to be recharged, a control module (M1) built into said vehicle or to the charging station of said vehicle, with data representing a total electric power required (PS*) for recharging the vehicles, measuring the total electric power (PS) supplied by the electric power grid (14) for recharging the vehicles, and supplying data representing the total electric power measured to said control module for each vehicle to be recharged, and determining, by said control module for each vehicle to be recharged, a setting of the electric power for recharging said vehicle according to the difference between the total electric power required and the total electric power measured.