Vehicle Charging Parameter Updates for Battery Degradation Control
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Solution Overview
Problem
Existing vehicle charging systems lack the ability to dynamically adjust charging parameters based on various factors such as time, cost, queue status, and emissions, leading to potential battery degradation.
Innovation Solution
A large language model is employed to update vehicle charging parameters, allowing the vehicle computer to actuate components to draw power at reduced rates when necessary, based on factors like time, emissions, and queue status, and provide explanations or recommendations for adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If the vehicle charges at the maximum transfer rate specified for the charging station, then the charging speed is improved, but the battery degradation increases
Solution Approach 1:
The charging system dynamically adjusts the power transfer rate based on real-time conditions including time of day, emissions constraints, queue status, and battery state of charge. The computer selectively modifies charging parameters during the charging operation rather than maintaining a fixed maximum rate, allowing optimization between charging speed and battery degradation based on varying operational contexts.
Solution Approach 2:
The system changes physical parameters of the charging process by adjusting the power transfer rate from the maximum specified rate to a reduced rate when conditions warrant it. The computer monitors multiple parameters (time, emissions, queue position, battery state) and modifies the charging current/voltage parameters accordingly to balance charging efficiency with battery health preservation.
2Object-affected harmful factors
If the vehicle charges at a reduced transfer rate to reduce battery degradation, then the battery health is improved, but the charging time increases
Solution Approach 1:
The charging rate is dynamically adjusted rather than fixed at a conservative reduced level. The computer increases the charge rate when time is critical (e.g., near the end of charging when less battery capacity remains to be filled, or when queue position indicates imminent completion) and reduces it when battery health is the priority, creating an adaptive balance between charging time and battery degradation.
Solution Approach 2:
The system periodically reassesses charging conditions and adjusts the power transfer rate in stages or intervals rather than maintaining a single fixed rate throughout. This allows the vehicle to charge at higher rates during periods when time loss is more acceptable and at lower rates during periods when battery protection is prioritized.
3Ease of operation
If the vehicle charges during peak pricing hours, then the charging convenience is improved, but the charging cost increases
Solution Approach 1:
The computer receives feedback regarding pricing conditions, time of day, and queue status, then uses this information to determine optimal charging parameters. The system continuously monitors pricing signals and adjusts the charging strategy accordingly, allowing the vehicle to take advantage of off-peak pricing when possible while maintaining operational convenience when needed.
Data Source
AI summary
A charging update request for charging a vehicle by a charging station is input to a large language model. Updated vehicle charging parameters are output from the large language model based on the charging update request. Upon determining that the charging update request is permitted for the charging station, power is drawn from the charging station based on the updated vehicle charging parameters.