Battery Cell Control Using Nonlinear Voltage Failure Thresholds
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Solution Overview
Problem
Existing battery management systems struggle to accurately detect operational state abnormalities in rechargeable battery cells due to the use of static voltage rate-of-change thresholds, which can lead to delayed identification of failing cells and potential thermal runaway events.
Innovation Solution
Implementing a non-linear rate-of-change failure threshold that dynamically changes based on the discharge curve of the battery cell, allowing for more precise identification of operational state abnormalities and timely discontinuation of the cell's operational state to prevent damage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a static voltage rate-of-change threshold is used for battery cell monitoring, then the system complexity is reduced and ease of operation is improved, but the measurement precision deteriorates and reliability worsens due to delayed identification of failing cells
Solution Approach 1:
The patent applies the dynamics principle by transitioning from a static voltage rate-of-change threshold to a dynamic threshold that adapts to the battery cell's discharge characteristics. The system now uses a discharge curve model that changes with the state of charge and discharge rate, allowing the threshold to automatically adjust during operation. This resolves the contradiction by maintaining ease of operation through automated adaptation while significantly improving measurement precision in detecting abnormal voltage changes.
Solution Approach 2:
The patent implements parameter changes by modifying the threshold parameter from a fixed value to a variable that changes based on discharge conditions. The system calculates expected voltage rate-of-change based on the current state of charge and discharge rate, then compares actual measurements against this dynamic threshold. This approach improves measurement precision without complicating operation, as the parameter adaptation is performed automatically by the control system.
2Device complexity
If a static voltage rate-of-change threshold is used, then device complexity is reduced, but reliability deteriorates due to potential thermal runaway events from delayed abnormality detection
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing discharge curves for various state of charge and discharge rate conditions. During operation, the system quickly retrieves the appropriate curve and threshold values without performing complex real-time calculations. This maintains low device complexity while significantly improving reliability, as the system is prepared in advance with the knowledge needed to detect abnormalities accurately under any discharge condition.
Solution Approach 2:
The system implements feedback by continuously monitoring the actual voltage rate-of-change and comparing it against the dynamic threshold derived from the discharge curve. When an abnormality is detected (actual rate exceeds threshold), the system immediately discontinues operation of the affected cell. This feedback mechanism ensures high reliability by preventing thermal runaway while keeping device complexity manageable through efficient comparison logic.
3Measurement precision
If a non-linear rate-of-change failure threshold is implemented, then measurement precision is improved for detecting operational state abnormalities, but device complexity increases
Solution Approach 1:
The patent reduces device complexity by performing the complex non-linear calculations in advance. Discharge curves and corresponding thresholds are pre-computed for various operating conditions and stored in memory. During operation, the system simply retrieves the appropriate pre-computed values based on current state of charge and discharge rate, avoiding the need for real-time complex calculations. This maintains high measurement precision while keeping device complexity low.
Solution Approach 2:
The system uses copying by creating simplified representations of the complex discharge behavior through pre-computed lookup tables. Instead of implementing the full non-linear physics models in real-time, the system copies the essential characteristics into discrete threshold values that can be quickly compared against actual measurements. This approach preserves measurement precision while dramatically reducing computational complexity.
Data Source
AI summary
Rechargeable battery monitoring and control is provided using a non-linear rate-of-change failure threshold. A non-linear rate-of-change failure threshold is obtained indicative of an operational state abnormality in a rechargeable battery cell, and during the operational state of the rechargeable battery cell, a control compares an actual voltage rate-of-change of the rechargeable battery cell to the non-linear rate-of-change failure threshold. Based on the actual voltage rate-of-change of the rechargeable battery cell exceeding the non-linear rate-of-change failure threshold, the control identifies the operational state abnormality in the rechargeable battery cell. Based on identifying the operational state abnormality in the rechargeable battery cell, the control discontinues the operational state of the rechargeable battery cell.