Adaptive EV Charging Control for Schedule-Driven Power Timing
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Solution Overview
Problem
Existing charging systems fail to adapt to changes in user schedules, leading to incomplete charging or unnecessary charging of moving objects.
Innovation Solution
A server that acquires user and other person schedule information, estimates power requirements, and controls charging devices to switch between usual and rapid charging modes based on schedule information, weather, and traffic conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If charging is controlled based on fixed schedules without considering schedule changes, then charging operations are simple to manage, but charging completion timing cannot be guaranteed when schedules change
Solution Approach 1:
The charging control system continuously monitors schedule changes and adjusts charging parameters in real-time. When a schedule change is detected, the system receives feedback about the new timeline and modifies charging power levels accordingly, ensuring charging completion aligns with updated deadlines while managing complexity through automated adaptive control
Solution Approach 2:
The charging control system transitions from static fixed-schedule control to dynamic adaptive control. It continuously adjusts charging power levels based on real-time schedule changes, vehicle state, and power availability, allowing the system to guarantee charging completion timing despite schedule variability without requiring overly complex manual intervention
2Speed
If rapid charging is always used to ensure timely charging completion, then charging speed is improved, but energy loss and cost increase
Solution Approach 1:
The system dynamically adjusts charging power levels based on real-time conditions. When time is critical, it switches to rapid charging mode to ensure timely completion. When time is not constrained, it transitions to standard charging mode to minimize energy loss and cost, optimizing the balance between charging speed and energy efficiency
Solution Approach 2:
The charging control system changes operating parameters (power level, charging mode) based on schedule urgency and vehicle state. It adjusts the charging power parameter dynamically, using high power only when necessary to meet tight deadlines, thereby reducing overall energy loss and charging cost while maintaining the ability to achieve timely completion when required
3Measurement precision
If charging is performed without considering weather and traffic conditions, then charging control is simple, but actual power consumption estimates are inaccurate
Solution Approach 1:
The system incorporates weather and traffic condition data into power consumption estimates through feedback mechanisms. It continuously updates estimation models with actual environmental conditions and compares predicted versus actual consumption, refining accuracy over time while managing complexity through automated data integration and adaptive modeling
Solution Approach 2:
The charging control system performs preliminary analysis of weather forecasts and traffic conditions before initiating charging. It pre-calculates expected power consumption based on anticipated conditions (temperature, humidity, traffic patterns) and adjusts charging parameters in advance, improving estimation accuracy without requiring complex real-time adjustments during charging
Data Source
AI summary
A server includes a processor configured to: acquire user schedule information indicating an action schedule of a user and other person schedule information indicating an action schedule of another person associated with the user; estimate, based on the user schedule information, a power amount for a moving object that the user is allowed to use, the moving object including a rechargeable secondary battery; and control a charging device to charge the moving object based on the power amount and the other person schedule information.