Battery Information Processing System for AC Impedance Analysis
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Solution Overview
Problem
The accuracy of evaluating battery module characteristics using AC impedance measurement is compromised due to State of Charge (SOC) dependency, leading to reduced signal-to-noise ratio and increased noise influence, especially when the amplitude of the AC signal is lowered to minimize SOC variation.
Innovation Solution
A battery information processing system that analyzes AC impedance measurements by plotting results on Bode diagrams, obtaining polynomial curves, and converting them to Nyquist diagrams to extract circuit constants, thereby reducing noise influence and improving accuracy in evaluating characteristics like full charge capacity and internal resistance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If the amplitude of the AC signal is lowered to minimize SOC variation, then the variation in SOC of the battery module is suppressed, but the signal-to-noise ratio between the application signal and noise is lowered
Solution Approach 1:
The patent introduces an intermediary processing step between signal application and measurement analysis: Fast Fourier Transform (FFT) processing. The raw impedance measurement data is converted through FFT to frequency domain representation, which serves as an intermediary that separates the signal components from noise components. This allows the system to maintain low signal amplitude (minimizing SOC variation) while still achieving accurate measurements through spectral analysis that enhances the signal-to-noise ratio in the frequency domain.
Solution Approach 2:
The patent replaces direct time-domain impedance measurement with frequency-domain analysis using FFT. Instead of directly analyzing the impedance response in the time domain where noise interferes with the signal, the system transforms the measurement to the frequency domain where signal components can be clearly distinguished from noise. This substitution of measurement domain (from time to frequency) enables accurate characterization of battery impedance while using minimal signal amplitude.
2Stability of the object's composition
If the amplitude of the AC signal is lowered, then variation in SOC can be suppressed, but accuracy in measurement of AC impedance may lower due to reduced signal-to-noise ratio
Solution Approach 1:
FFT processing serves as a mathematical intermediary that transforms the measurement data from time domain to frequency domain. This transformation allows the system to maintain low signal amplitude for SOC stability while achieving high measurement accuracy through frequency spectral analysis that enhances signal-to-noise ratio.
Solution Approach 2:
The patent changes the domain parameter of the measurement from time domain to frequency domain through FFT transformation. By analyzing impedance characteristics in the frequency domain rather than time domain, the system can extract accurate impedance values even when the time-domain signal has low amplitude, thus maintaining both SOC stability and measurement accuracy.
Data Source
AI summary
A battery information processing system includes an analyzer configured to analyze a result of measurement of an AC impedance of a module M. The analyzer plots the result of measurement of the AC impedance on a first frequency characteristic diagram which is a Bode diagram (a first diagram) relating to a real number component of the AC impedance and on a second frequency characteristic diagram which is a Bode diagram (a second diagram) relating to an imaginary number component of the AC impedance, obtains a polynomial curve L1 by fitting processing onto a result of plotting on the first diagram and obtains a polynomial curve L2 by fitting processing onto a result of plotting on the second diagram, and converts the polynomial curves L1 and L2 into an impedance curve Z on a Nyquist diagram.