Dynamic Anchor Battery Capacity Estimation
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Solution Overview
Problem
Existing battery capacity estimation methods produce noisy and inaccurate results due to reliance on single consistent anchor points, which are difficult to maintain and can propagate errors, especially as battery capacity degrades over time.
Innovation Solution
A method using blended data sets to estimate battery capacity by tracking variance in amp hours, voltage, and battery capacity values, allowing for dynamic adjustment of anchor points and correction of integrated current errors without requiring a single consistent anchor point, thereby improving accuracy and reducing error propagation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a single consistent anchor point is used for battery capacity estimation, then the estimation method is simple to implement, but the accuracy degrades over time due to error propagation and battery capacity degradation
Solution Approach 1:
The patent divides the battery's operational life into multiple time periods, each with its own data set and anchor point. Instead of relying on a single anchor point throughout the battery's life, the system creates segmented data sets (first data set, second data set, etc.) that can be independently analyzed and combined. This segmentation allows the system to maintain accuracy over time by resetting errors periodically while capturing the battery's degradation characteristics.
Solution Approach 2:
The patent implements dynamic anchor points that can be reset at different time periods based on integrated current error thresholds. The system transitions from static, fixed anchor points to dynamic, adjustable anchor points that adapt to the battery's changing conditions. The second data set can be reset based on one of the integrated current values from the first time period, allowing the system to maintain accuracy as the battery degrades.
2Measurement precision
If dynamic anchor points and data set resetting are implemented, then estimation accuracy is maintained over time, but the system complexity increases
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously monitors integrated current error and compares it against threshold values. When the error exceeds the threshold, the system automatically triggers a reset of the second data set based on values from the first time period. This feedback loop maintains accuracy without requiring complex manual intervention or overly sophisticated algorithms.
Solution Approach 2:
The system performs self-correction by automatically detecting when integrated current error exceeds thresholds and autonomously resetting the appropriate data sets. The battery management system monitors its own performance and corrects errors without external intervention, combining multiple data sets and resetting anchor points based on predetermined criteria, thereby maintaining accuracy while minimizing the need for complex external control mechanisms.
Data Source
AI summary
A method for battery capacity estimation is provided. The method includes monitoring a sensor, collecting a plurality of data points including a voltage-based state of charge value and an integrated current value, defining within the data points a first data set collected during a first time period and a second data set collected during a second time period, determining an integrated current error related to the second data set, comparing the integrated current error related to the second data set to a threshold integrated current error. When the error related to the second data set exceeds the threshold, the method further includes resetting the second data set based upon an integrated current value from the first time period. The method further includes combining the data sets to create a combined data set and determining a voltage slope capacity estimate as a change in integrated current versus voltage-based state of charge.