Battery Swap Power Supply Prediction and Adjustment
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Solution Overview
Problem
The battery swap system faces challenges in providing a power supply amount that accurately matches user demand, as the full-charge capacity of batteries deteriorates with use and power demand fluctuates with season and battery age, leading to difficulties in maintaining optimal power supply levels.
Innovation Solution
An excess/deficiency determination device is implemented, comprising a demand prediction component, a supply amount prediction component, and an excess/deficiency determination prediction component, which uses usage history and battery deterioration data to forecast power demand and supply, determining if there is an excess or deficiency in power supply, and providing suggestions for adjusting the power supply amount accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the power supply amount is increased to meet fluctuating demand, then the reliability of power supply is improved, but the loss of energy increases due to excessive power supply
Solution Approach 1:
The system performs preliminary prediction of power demand and supply amount using usage history data before the actual power supply occurs. By predicting future power demand and supply capacity in advance, the system can proactively adjust battery configurations to match anticipated demand, avoiding both energy shortages and excessive power supply waste
Solution Approach 2:
The system continuously monitors actual power usage and compares it with predicted values, using this feedback to refine future predictions and adjustments. The usage history is continuously updated with actual consumption data, enabling the system to learn from past performance and improve the accuracy of power supply matching over time
2Quantity of substance
If the battery capacity is increased to ensure sufficient power supply, then the power supply amount is improved, but the device complexity increases due to managing larger battery systems
Solution Approach 1:
The system divides the battery fleet into multiple manageable units with distinct usage histories and deterioration patterns. Each battery's performance is tracked and predicted individually, allowing the system to optimize configurations by selecting specific batteries for specific time periods rather than managing all batteries as a single homogeneous group
Solution Approach 2:
The system dynamically changes operational parameters such as the number of batteries in service, charging schedules, and discharge rates based on predicted demand and supply conditions. By adjusting these parameters rather than physically reconfiguring the entire battery system, the system maintains flexibility while reducing management complexity
Data Source
AI summary
A supply amount change prediction component takes into account a decrease in full-charge capacity due to battery deterioration to predict a future amount of power supplied by a plurality of batteries, and a surplus calculator calculates the surplus of the power supply amount with respect to the power demand.