EV Charging Profile Control for Off-Peak Rate Optimization
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Solution Overview
Problem
Chargers for electric vehicles do not differentiate between on-peak and off-peak electricity rates, leading to increased costs for users.
Innovation Solution
An automated charging system that includes an electronic processor to store a power grid rate profile, determine a time to full charge, and generate a charging profile to optimize charging based on these rates, minimizing user cost.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If automated charging system optimizes charging based on rate profiles, then charging cost is reduced, but device complexity increases
Solution Approach 1:
The patent introduces a server as an intermediary component that receives rate profiles from utility providers and processes charging optimization centrally. The server communicates with chargers through standardized protocols, allowing complex rate profile processing without adding complexity to the charger hardware itself. This mediator approach resolves the contradiction by centralizing the computational complexity while maintaining simple end-user devices.
Solution Approach 2:
The system segments the charging optimization function into separate modular components: rate profile reception module, optimization algorithm module, and charger control module. This segmentation allows each component to be independently optimized and managed, reducing overall system complexity while enabling sophisticated charging cost optimization through coordinated operation of the segmented modules.
2Stability of the object's composition
If charging profile is generated to minimize utility load, then power grid stability is improved, but charging flexibility is reduced
Solution Approach 1:
The charging profile generation system dynamically adjusts charging parameters based on real-time rate profiles and grid conditions. The optimization algorithm continuously adapts the charging schedule to balance grid stability requirements with user charging needs, allowing the system to shift charging loads dynamically rather than using fixed schedules. This dynamic approach resolves the contradiction by making the system adaptable to both grid stability constraints and varying user requirements.
Solution Approach 2:
The system changes multiple charging parameters simultaneously (charging rate, start time, duration, power level) to achieve grid stability while maintaining charging flexibility. By adjusting these parameters within acceptable ranges rather than fixing a single charging schedule, the system can optimize for grid stability without completely eliminating user choice, thus resolving the contradiction between stability and flexibility.
Data Source
AI summary
A method including receiving, from a user, a rate profile. The method further including generating, using an electronic processor and based on the rate profile, a charging profile. The method further including charging, using a charging controller of a charger coupled to the electronic processor, based on the charging profile.