Battery Impedance Modeling for Accurate State Estimation
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Solution Overview
Problem
Conventional battery management systems struggle to accurately diagnose battery states due to limitations in reflecting complex electrochemical characteristics, particularly in lithium-ion batteries, leading to potential safety issues and performance degradation.
Innovation Solution
A battery management device that measures impedance data for each frequency band, generates graphs representing impedance characteristics, selects appropriate equivalent circuit models based on these graphs, and estimates battery states using curve fitting methods and trained models to improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional BMS uses DC data (cell voltage, current, surface temperature) for battery state diagnosis, then the system is simple to operate, but it cannot accurately reflect complex electrochemical characteristics leading to reduced measurement precision
Solution Approach 1:
The patent transforms the measurement approach by introducing frequency-domain impedance parameters (real part, imaginary part, phase angle) across multiple frequency bands (125Hz, 250Hz, 500Hz, 1kHz, 2kHz, 4kHz, 8kHz, 16kHz, 32kHz, 64kHz, 128kHz, 256kHz, 512kHz, 1MHz) instead of relying solely on time-domain DC parameters. This parameter transformation enables accurate capture of electrochemical characteristics while maintaining systematic analysis through equivalent circuit modeling.
Solution Approach 2:
The patent introduces equivalent circuit models (ECM) as intermediary representations that bridge the gap between raw impedance measurements and battery state estimation. The ECM parameters (resistors, capacitors, inductors arranged in specific configurations) serve as mediators that translate complex impedance spectra into meaningful state indicators, resolving the contradiction between measurement accuracy and system complexity.
2Measurement precision
If BMS uses single equivalent circuit model for all battery conditions, then the device complexity is reduced, but the measurement precision deteriorates due to inability to adapt to varying electrochemical characteristics
Solution Approach 1:
The patent implements dynamic model selection by establishing multiple equivalent circuit models with different configurations (e.g., Randles circuit, transmission line model, distributed RC network) and selecting the most appropriate model based on the measured impedance characteristics. This dynamic adaptation allows the system to maintain high measurement precision across varying battery states, temperatures, and frequency ranges.
Solution Approach 2:
The patent applies different equivalent circuit model configurations to different frequency bands and battery operating conditions. For example, simpler models may be used for high-frequency measurements while more complex distributed models are applied to low-frequency electrochemical processes. This localized model application optimizes both accuracy and computational efficiency for each specific measurement context.
3Measurement precision
If BMS measures impedance across all frequency bands continuously, then the measurement precision is maximized, but the energy consumption increases due to continuous AC signal application
Solution Approach 1:
The patent implements periodic or on-demand impedance measurements across frequency bands rather than continuous measurement. The system can trigger measurements based on specific conditions (e.g., state changes, error detection, scheduled intervals) and use the measured data to update equivalent circuit model parameters. This periodic approach maintains measurement precision when needed while significantly reducing overall energy consumption during normal operation.
Solution Approach 2:
The patent applies partial measurement strategies by selecting specific frequency bands relevant to the current diagnostic needs rather than measuring all frequency bands continuously. For example, during normal operation, only critical frequency ranges may be monitored, while full-spectrum measurements are performed only when detailed diagnostics are required or anomalies are detected.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances the accuracy of battery state estimation by selecting the most suitable equivalent circuit model, thereby improving safety and performance by accurately diagnosing battery conditions.
Implementation Method 1
an impedance measurement unit configured to measure impedance data of a battery for each frequency band
Data Source
AI summary
The present disclosure relates to a battery management device and method, particularly to a technique of estimating and optimizing battery state using frequency-band-specific impedance data, wherein the battery management device includes: an impedance measurement unit configured to measure frequency-band-specific impedance data of a battery; and a controller configured to acquire the frequency-band-specific impedance data measured by the impedance measurement unit, generate a graph representing the battery's impedance characteristics based on the impedance data, select a first equivalent circuit model among a plurality of predefined equivalent circuit models based on the graph, and estimate the battery state based on the selected first equivalent circuit model.