EV Charging Window Control for Off-Peak Battery Readiness
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Solution Overview
Problem
Manual vehicle charging processes are inefficient due to variations in external environmental conditions and variable power source metrics, often resulting in incomplete charging, reduced battery life, and increased costs, as they rely on user-initiated start times and lack optimal utilization of available charging windows.
Innovation Solution
A charging management application that determines optimal charging windows based on user preferences, environmental conditions, and available power sources, selecting the most cost-effective option by considering off-peak charging rates and ambient temperature to ensure efficient battery charging before vehicle use.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual charging processes are used with user-initiated start times, then user control over charging is maintained, but charging efficiency decreases and costs increase due to inability to utilize off-peak rates
Solution Approach 1:
The charging management application automatically determines charging windows and initiates charging processes without requiring continuous user intervention. The system self-manages the charging operation by monitoring power source metrics, environmental conditions, and battery state, while still allowing users to set preferences and review decisions.
Solution Approach 2:
The system performs preliminary analysis of power source metrics, environmental conditions, and charging requirements before initiating charging. It proactively identifies optimal charging windows in advance, allowing the battery to be charged during off-peak periods before vehicle use is needed.
2Device complexity
If charging is performed without considering environmental conditions, then charging process is simplified, but battery life is reduced due to suboptimal charging conditions
Solution Approach 1:
The charging management application continuously monitors environmental conditions (temperature, humidity) and power source metrics during charging, and uses this feedback to adjust charging parameters in real-time. This ensures charging occurs under optimal conditions while maintaining battery health.
Solution Approach 2:
The system dynamically adjusts charging parameters based on real-time environmental conditions and battery state. Rather than using fixed charging profiles, the charging rate and timing are adaptively modified to match current conditions, optimizing both battery life and charging efficiency.
3Device complexity
If charging windows are not optimized based on power source metrics, then charging process is simpler, but charging costs increase and completion reliability decreases
Solution Approach 1:
The system performs preliminary analysis of power source metrics and environmental conditions to identify optimal charging windows before charging begins. This advance planning ensures charging is scheduled during periods when power is available and conditions are favorable, increasing completion reliability.
Solution Approach 2:
The charging management application continuously monitors power source metrics during charging and uses feedback to adjust charging parameters. If conditions change or power becomes unavailable, the system adapts the charging window to ensure completion while minimizing costs.
4Speed
If charging is performed during peak power rates, then vehicle is ready for use faster, but charging costs increase significantly
Solution Approach 1:
The system schedules charging to occur during off-peak periods in advance, before vehicle use is needed. By performing charging preliminarily during lower-cost periods, the system avoids peak rates while ensuring the vehicle is ready when needed.
Solution Approach 2:
The charging management application utilizes periodic off-peak charging windows that occur at predictable intervals. Rather than charging continuously or during peak periods, the system exploits these periodic low-cost opportunities to accumulate charge over time.
Data Source
AI summary
The charging management system based on variable charging windows is disclosed. The system can receive and/or determine an anticipated/desired time for the beginning operation of the vehicle. The system obtains or identifies preferences for charging metrics, including desired charge, battery pack preconditioning, and other vehicle attributes. The system then determines a required start time for the desired charging metrics. Illustratively, the determined start time can be based on ambient environmental conditions that can influence charging times, such as differences in charging times based on temperature. The determined start time can also be based on rate schedules for one or more power sources, such as one or more off-peak charging rates, peak charging rates, etc.