Random Noise Generator for Battery Impedance Monitoring
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Solution Overview
Problem
Existing methods for determining battery impedance are not suitable for real-time, in-situ monitoring, as they are either too slow or inaccurate, especially under changing load conditions, which hinders the prediction of State Of Health (SOH) and State Of Charge (SOC) of batteries.
Innovation Solution
A method and apparatus using a random noise generator to create a broad-spectrum noise signal applied to the battery, coupled with current and voltage measurement, and signal processing to determine impedance across a frequency spectrum in near real-time, employing correlation and Fourier transforms to analyze the responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional EIS methods are used to measure battery impedance, then measurement precision is improved, but measurement time increases significantly making it unsuitable for real-time monitoring
Solution Approach 1:
The patent applies periodic sinusoidal excitation signals at multiple frequencies to the battery, measuring the voltage and current responses at each frequency to calculate impedance. This periodic action enables systematic extraction of impedance characteristics across the frequency spectrum while maintaining measurement speed through efficient signal processing
Solution Approach 2:
The patent implements continuous impedance monitoring by continuously applying excitation signals and processing responses in real-time. The system maintains continuous measurement of battery impedance across frequencies, enabling real-time SOH and SOC prediction without interrupting battery operation
2Measurement precision
If current integration method is used to monitor battery charge, then SOC estimation is obtained, but errors occur due to internal self-discharge currents
Solution Approach 1:
The patent uses battery impedance as an intermediary parameter to indirectly determine SOC and SOH. Instead of directly integrating current which is affected by self-discharge, the system measures impedance characteristics that correlate with state of charge and health, providing a more reliable indirect measurement method
Solution Approach 2:
The patent replaces the mechanical/current integration method with an electrical measurement approach using impedance spectroscopy. By substituting current integration with impedance-based estimation, the system eliminates errors associated with self-discharge currents while maintaining SOC monitoring capability
3Measurement precision
If voltage monitoring is used to estimate battery capacity, then SOC is determined, but errors occur when load is applied due to voltage drop from internal impedance
Solution Approach 1:
The patent uses impedance measurements as an intermediary to decouple the voltage measurement from load effects. By measuring the impedance separately through AC excitation signals and using this information to correct or interpret DC voltage readings, the system achieves accurate capacity estimation regardless of load conditions
4Measurement precision
If battery impedance is monitored to predict SOH, then battery life prediction is improved, but temperature and SOC variations affect impedance measurements
Solution Approach 1:
The patent uses periodic excitation signals to separate impedance measurements from DC operating conditions. By superimposing AC signals on the battery terminals and measuring the AC response, the system extracts impedance characteristics that are independent of DC voltage and current levels, reducing sensitivity to SOC and temperature variations
Solution Approach 2:
The patent measures impedance across multiple frequencies to create a frequency spectrum signature that is characteristic of the battery's health state. By using the full frequency spectrum rather than a single frequency, the system captures multiple electrochemical processes that provide robust SOH indicators less sensitive to variations in operating conditions
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
Enables fast and accurate in-situ monitoring of battery impedance, enhancing the prediction of battery SOH and SOC by reducing the impact of slow changes like temperature and SOC variations, thus improving the reliability of battery life predictions.
Implementation Method 1
A random noise generator produces a random noise signal
Implementation Method 2
a current generator converts the random noise signal to a random noise stimulus suitable for application to an energy-output device terminal
Implementation Method 3
the analyzer correlates the measured noise stimulus and the bias-reduced response to determine an impedance of the energy-output device
Data Source
AI summary
Disclosed are methods and apparatuses for determining an impedance of an energy-output device using a random noise stimulus applied to the energy-output device. A random noise signal is generated and converted to a random noise stimulus as a current source correlated to the random noise signal. A bias-reduced response of the energy-output device to the random noise stimulus is generated by comparing a voltage at the energy-output device terminal to an average voltage signal. The random noise stimulus and bias-reduced response may be periodically sampled to generate a time-varying current stimulus and a time-varying voltage response, which may be correlated to generate an autocorrelated stimulus, an autocorrelated response, and a cross-correlated response. Finally, the autocorrelated stimulus, the autocorrelated response, and the cross-correlated response may be combined to determine at least one of impedance amplitude, impedance phase, and complex impedance.