Battery Health Characterization Using Normalized Pulse Measurements
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Solution Overview
Problem
Conventional systems for characterizing the health of rechargeable batteries are less accurate due to reliance on theoretical models that do not account for operational conditions or variances between batteries, leading to inadequate determination of state-of-charge and state-of-health.
Innovation Solution
A system and method that utilize empirical data by passing current pulses across the battery, measuring operational parameters, and applying standardized relationship data sets and baseline normalization coefficients to calculate the state-of-charge and state-of-health, accounting for variances and operational conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional theoretical models are used to characterize battery health, then the system complexity is reduced, but the measurement precision and reliability of state-of-charge and state-of-health determination deteriorate
Solution Approach 1:
The patent implements feedback mechanisms by continuously monitoring battery operational parameters (voltage, current, temperature) and using these measurements to update and refine the state-of-charge and state-of-health calculations. The system compares actual measurements with expected values from the standardized relationship data set, allowing dynamic adjustment and improvement of accuracy over time, thereby resolving the contradiction between measurement precision and system complexity.
Solution Approach 2:
The patent changes the approach from using fixed theoretical models to using empirically derived standardized relationship data sets that capture actual battery behavior under various conditions. By storing pre-characterized relationships between operational parameters and battery state in lookup tables, the system achieves high measurement precision without requiring complex real-time calculations, thus resolving the contradiction between accuracy and computational complexity.
2Reliability
If theoretical models are used for battery health characterization, then the ease of operation is improved, but the reliability of battery health assessment deteriorates due to inability to account for operational conditions and battery variances
Solution Approach 1:
The patent performs preliminary characterization of battery behavior under various operational conditions before actual use, storing the results in standardized relationship data sets. These pre-computed relationships account for different temperatures, charge rates, and battery aging states, allowing the system to reliably assess battery health during operation without requiring complex real-time modeling, thus resolving the contradiction between reliability and ease of operation.
Solution Approach 2:
The system accounts for operational conditions and battery-to-battery variances by using empirically derived parameters from actual battery testing rather than theoretical assumptions. The standardized relationship data sets incorporate real-world variations in battery behavior, enabling reliable health assessment across different operating conditions while maintaining operational simplicity through lookup-based calculations.
3Measurement precision
If empirical data and normalization procedures are implemented, then the measurement precision and reliability of battery characterization are improved, but the device complexity and time required for baseline characterization increase
Solution Approach 1:
The patent performs comprehensive baseline characterization and normalization coefficient calculation during the manufacturing or initial setup phase, storing these results for reuse. By completing the time-consuming empirical measurements and data normalization in advance, the system achieves high measurement precision during actual battery operation without incurring time delays during critical charging or monitoring operations, thus resolving the contradiction between measurement precision and time loss.
Solution Approach 2:
The system dynamically adapts by using pre-computed normalization coefficients specific to each battery's baseline characteristics. Once the initial characterization is complete, the system efficiently applies these coefficients to subsequent measurements, maintaining high precision while minimizing processing time. The system can also update normalization coefficients periodically without requiring full re-characterization, balancing accuracy with time efficiency.
Data Source
AI summary
A method for characterizing the health of a rechargeable battery includes measuring initial condition parameters of a rechargeable battery prior to the battery being placed into service. A baseline normalization of the initial condition parameters is performed using a standardized relationship data set for a norm battery to generate baseline normalization coefficients to normalize the initial condition parameters to the norm battery. Run-time condition parameters of the battery are measured after the battery is in service as part of a continuous built in test system. The run-time condition parameters are normalized using the standardized relationship data set for the norm battery and the baseline normalization coefficients to generate normalized run-time condition parameters for the battery. The normalized run-time condition parameters are then compared to the standardized relationship data set for the norm battery to calculate a state-of-charge and state-of-health for the battery as the run-time condition.