EV Charge Controller Switching for Grid Capacity Constraints
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Solution Overview
Problem
Charging electric vehicles (EVs) is challenging due to varying energy requirements and power sources, leading to inefficiencies and increased costs, particularly during peak demand conditions which can overload the power grid and result in higher demand charges.
Innovation Solution
A computer-implemented method and system that uses a processor to calculate the capacity of a power grid system, determine the power demand level of EVs, and compare it with the grid capacity. Based on this comparison, the system selects an appropriate charging mode, either an override mode or an internal combustion engine mode, to efficiently manage the power charging process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If electric vehicles are charged during peak demand conditions, then the charging speed and power availability improve, but the power grid becomes overloaded and demand charges increase
Solution Approach 1:
The system performs preliminary assessment of grid capacity and vehicle mission requirements before initiating charging. By calculating the power grid system capacity and comparing it with the power demand level needed to satisfy mission requirements, the system proactively determines the appropriate charging mode (override mode or internal combustion engine mode) to avoid grid overload while ensuring charging needs are met
Solution Approach 2:
The system dynamically adjusts the charging mode based on real-time conditions. The charge controller continuously monitors grid capacity and vehicle requirements, selecting between override mode (for faster charging when grid capacity allows) and internal combustion engine mode (when grid capacity is insufficient), thereby adapting the charging process to current grid conditions to prevent overload
2Loss of time
If higher power charging is used to reduce charging time, then the charging efficiency improves, but the demand charges and operating costs increase
Solution Approach 1:
The system dynamically selects charging modes based on grid capacity and mission requirements. When grid capacity is sufficient, the system uses override mode for faster charging. When grid capacity is limited, it switches to internal combustion engine mode, thereby optimizing the balance between charging time and demand charge costs
Solution Approach 2:
The system changes the charging parameters by selecting different charging modes (override mode vs. internal combustion engine mode) based on the comparison between grid capacity and power demand level. This parameter change allows the system to adapt charging speed to current conditions, reducing unnecessary demand charges while meeting mission requirements
Data Source
AI summary
A system is provided for performing an automated power charging process for one or more electric vehicles using a processor. Included in the processor is a charge controller that calculates a capacity of a power grid system by communicating with the power grid system via a network, and a power demand level of the one or more electric vehicles to satisfy one or more mission requirements of each electric vehicle. The power demand level of the one or more electric vehicles is compared with the capacity of the power grid system. In response to the comparison, at least one charging mode is selected from an override mode and an internal combustion engine mode for performing the automated power charging process. The charge controller automatically charges the one or more electric vehicles based on the selected at least one charging mode.