Multi-Frequency Impedance Estimation of Internal Battery Temperature
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Solution Overview
Problem
Existing methods for monitoring internal battery temperature, such as using surface-mounted thermocouples for larger batteries and single-frequency electrochemical impedance spectrometry for smaller batteries, are non-ideal due to delays, high computational costs, and inability to compensate for state-of-charge (SOC) and state-of-health (SOH) variations.
Innovation Solution
Estimating internal battery temperature using terminal impedance measurements at multiple frequencies combined with multivariable polynomial regression to reduce the effects of SOC and SOH variations, utilizing a weighted sum of polynomial functions and optionally incorporating terminal voltage and cell capacity measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If surface-mounted thermocouples are used for larger batteries, then temperature monitoring is achieved, but there is delay in heat conductivity from battery internal core to surface
Solution Approach 1:
The patent replaces the mechanical/physical thermocouple measurement system with an electrical impedance-based measurement system. By measuring terminal impedance at multiple frequencies and using multivariable polynomial regression, the system directly estimates internal battery temperature without relying on thermal conduction to the surface, thereby eliminating the time delay inherent in thermocouple-based methods.
2Measurement precision
If single-frequency electrochemical impedance spectrometry is used for smaller batteries, then temperature estimation is achieved, but it has high computational cost and cannot compensate for SOC and SOH variations
Solution Approach 1:
The patent transitions from single-frequency impedance measurement to multi-frequency impedance measurement, adding the frequency dimension to the measurement space. By measuring impedance at multiple frequencies and incorporating these measurements into a multivariable polynomial regression model, the system achieves better temperature estimation accuracy while compensating for SOC and SOH variations through the additional measurement dimensions.
3Measurement precision
If single-frequency impedance measurement is used, then temperature estimation is obtained, but SOC and SOH variations affect the measurement accuracy
Solution Approach 1:
The patent segments the impedance measurement into multiple frequency components, measuring terminal impedance at several distinct frequencies rather than a single frequency. This segmentation allows the multivariable polynomial regression model to differentiate between temperature effects and SOC/SOH effects, as different frequencies respond differently to these various parameters, enabling accurate temperature estimation despite SOC and SOH variations.
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
Provides a lower-cost, less-intrusive battery temperature monitoring solution with reduced computational cost and improved accuracy by canceling out SOC and SOH variations, enabling safer battery operation through precise temperature control.
Implementation Method 1
single-frequency electrochemical impedance spectrometry for smaller batteries
Data Source
Figure 1A~1B
Figure 2
Figure 3
AI summary
One embodiment is a method for estimating an internal temperature of a battery, the method comprising obtaining multiple terminal impedance measurements for the battery, wherein each of the terminal impedance measurements is obtained at a different one of a plurality of frequencies; automatically selecting one of a plurality of battery models using on a value of a parameter of the battery, wherein each of the battery models has been trained and corresponds to a different range of values for the battery parameter and wherein the value of the parameter of the battery falls within the range of values for the battery parameter corresponding to the selected one of the plurality of battery models; and applying the selected one of the plurality of battery models to the multiple terminal impedance measurements to estimate the internal temperature of the battery.