Battery SOH Estimation Using Adaptive G-Parameter Tracking
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Solution Overview
Problem
Conventional methods for estimating battery state of health (SOH) are inaccurate and require discontinuing battery use, are environment-dependent, and suffer from sensor error accumulation, limiting real-time accuracy and adaptability.
Innovation Solution
A method that estimates SOH in real time using voltage and current values by tracking the G and H parameters, employing an adaptive filter with recursive least squares (RLS) to update gain and covariance matrices, allowing for accurate SOH estimation without error accumulation across varying conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods measure released electric charge using electric sensors to estimate SOH, then battery capacity can be calculated, but the method requires discontinuing battery use and has unreliable accuracy due to accumulated sensor errors
Solution Approach 1:
The patent replaces physical electric sensors and charge measurement systems with a mathematical modeling approach using voltage-current relationships. The G-parameter model substitutes direct electrical measurement with computational estimation based on terminal voltage and current measurements, eliminating sensor error accumulation while maintaining continuous battery operation.
Solution Approach 2:
The patent introduces the G-parameter as an intermediary variable that mediates between measurable quantities (voltage and current) and the target parameter (SOH). This intermediary enables indirect estimation of battery health through the relationship V(t) = E(t) - G(t)×I(t), avoiding direct charge measurement and its associated errors.
2Adaptability or versatility
If conventional methods use OCV-SOC relationships to estimate SOH, then battery state can be diagnosed, but the method requires matching certain conditions and environments
Solution Approach 1:
The patent employs dynamic adaptation by updating the G-parameter model online during battery operation. The model adapts to changing environmental conditions and battery states through continuous parameter estimation, making the system versatile across different environments while maintaining reliable SOH estimation without requiring specific matching conditions.
3Productivity
If conventional methods track resistance component or impedance parameter values, then battery aging can be monitored, but the methods require discontinuing battery use and have complex procedures
Solution Approach 1:
The patent extracts only the essential voltage and current measurements needed for SOH estimation, eliminating the need for complex impedance spectroscopy or resistance tracking procedures. By focusing on the fundamental V-I relationship and the G-parameter, the method achieves real-time estimation with minimal measurement requirements and simplified procedures.
Data Source
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AI summary
Provided is a method of estimating the state of health of the battery according to various embodiments. The method of estimating the state of health of the battery comprises: measuring a voltage and current of a battery in use to periodically generate a voltage value and a current value; using an adaptive filter to periodically update a G parameter value and an H parameter value in real time from the voltage value and the current value, said parameters indicating the present state of the battery; and using an initial value and a final value of the G parameter that is preset and a present value of the G parameter to estimate the state of health of the battery in real time. The G parameter is a parameter that represents the sensitivity of the voltage to changes in the current of the battery, and the H parameter is a parameter that represents an effective potential determined by the local equilibrium potential distribution and resistance distribution inside the battery.