Battery Capacity Measurement Using Condition-Corrected Machine Learning
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for measuring battery capacity are inaccurate due to variations in measurement conditions such as temperature, humidity, charging rate, and discharging rate, leading to deviations in capacity values and inadequate quality control during battery production and operation.
Innovation Solution
A device and method using machine learning algorithms to derive capacity distributions and perform different machine learnings for each battery capacity range, correcting for usage conditions by analyzing capacity factor learning and measurement data to predict battery capacity accurately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional capacity measurement methods are used under varying measurement conditions, then measurement process is simple, but measurement precision deteriorates due to deviations caused by temperature, humidity, charging rate, and discharging rate variations
Solution Approach 1:
The patent applies parameter changes by using machine learning models that adapt to different measurement conditions (temperature, humidity, charging rate, discharging rate). The system learns the relationship between these parameters and capacity measurement deviations, then corrects the measurements by adjusting for these parameter variations, thereby improving measurement precision without requiring controlled environmental conditions.
Solution Approach 2:
The patent introduces machine learning models as intermediaries between the raw capacity measurement data and the final corrected capacity values. These models act as mediators that process the measurement data along with environmental parameters to produce corrected capacity values, eliminating the need for direct control of measurement conditions.
2Measurement precision
If multiple machine learning programs are performed for different battery capacity ranges, then measurement precision improves through corrected capacity values, but device complexity increases due to multiple processing steps
Solution Approach 1:
The patent segments the battery capacity measurement process into multiple stages, with different machine learning programs applied to different capacity ranges. This segmentation allows each model to be optimized for specific capacity intervals, improving overall measurement precision while organizing the complexity into manageable modular components.
Solution Approach 2:
The patent implements a dynamic measurement system where the choice and configuration of machine learning programs adapt based on the battery's capacity range. The system dynamically selects appropriate models and adjusts processing parameters according to the specific measurement context, optimizing precision for each scenario while managing complexity through adaptive rather than static processing.
3Adaptability or versatility
If capacity measurement is performed under different operating conditions, then adaptability improves for various usage scenarios, but measurement precision deteriorates due to condition-induced deviations
Solution Approach 1:
The patent uses parameter changes to maintain measurement precision across different operating conditions. The machine learning models are trained on data from various conditions and use these environmental parameters as inputs to correct measurements, allowing the system to adapt to different scenarios while maintaining accuracy through parameter-based compensation.
Solution Approach 2:
The patent creates a universal measurement system that functions accurately across multiple operating conditions. The machine learning models serve multiple functions by handling different environmental parameters (temperature, humidity, charging rate, discharging rate) simultaneously, making the system versatile while maintaining precision through integrated multi-parameter correction.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
The present application relates to a device and method for measuring the capacity of a battery.