Battery Cell Impedance Estimation Using Offline Model Fitting
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Solution Overview
Problem
Existing methods for estimating the impedance of secondary battery cells in vehicles are computationally intensive and time-consuming, making them impractical for real-time applications, and fail to accurately account for aging effects on model parameters.
Innovation Solution
A method for model-based impedance estimation that involves initial parameterization using electrochemical impedance spectroscopy, generating a reference database off-board, and using polynomial fitting to adapt model parameters over the cell's lifetime, allowing for efficient impedance calculation during vehicle operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If electrochemical impedance spectroscopy measurements are performed to accurately determine impedance, then measurement precision is improved, but measurement time and cost increase significantly
Solution Approach 1:
The patent performs comprehensive impedance measurements and parameter identification in advance (before vehicle operation) to build a pre-characterized model of the battery cell. This preliminary characterization captures the cell's impedance behavior across different states of charge, temperatures, and aging conditions. During actual vehicle operation, the system uses this pre-built model with simple lookup tables and interpolation algorithms to rapidly estimate impedance without performing time-consuming measurements, thus resolving the contradiction between measurement precision and measurement time.
2Measurement precision
If computationally intensive optimization algorithms are used to estimate model parameters during vehicle operation, then parameter accuracy is improved, but computational time and resource consumption increase
Solution Approach 1:
The patent performs computationally intensive parameter identification and model optimization in advance (before vehicle operation) when computational resources are abundant. During vehicle operation, the system uses the pre-identified parameters and pre-computed lookup tables with simple interpolation algorithms to rapidly estimate impedance and state of health, avoiding real-time computational intensity while maintaining accuracy.
Solution Approach 2:
The patent creates simplified copies of the complex battery model in the form of lookup tables containing pre-computed impedance values and parameter relationships. These lookup tables are generated offline based on comprehensive measurements and simulations. During vehicle operation, the system copies relevant data from these tables through interpolation rather than performing complex real-time calculations, thus maintaining accuracy while dramatically improving computational efficiency.
3Productivity
If simplified computational models are used for real-time impedance estimation, then computational efficiency is improved, but prediction quality and accuracy deteriorate
Solution Approach 1:
The patent creates lookup tables that contain copies of comprehensive impedance data obtained from detailed measurements and simulations. These lookup tables preserve the complex electrochemical behavior characteristics while enabling fast retrieval through simple interpolation algorithms. The lookup tables are structured to cover the full operating range of the battery (different states of charge, temperatures, and aging conditions), allowing the simplified real-time model to accurately represent the complex battery physics without requiring complex calculations.
Solution Approach 2:
The patent transforms the complex time-domain electrochemical impedance data into frequency-domain representations and stores them as pre-computed lookup tables. The system dynamically selects and interpolates appropriate parameters from these tables based on current operating conditions (state of charge, temperature, aging state). This parameter transformation and selective interpolation approach maintains high prediction accuracy while enabling real-time computational efficiency.
Data Source
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AI summary
The invention relates to a method for the model-based estimation of the impedance of a galvanic cell (1) of a secondary battery (2) by means of an estimation model (4) executed on a computer unit (3). The invention is characterised by the following steps, carried out before the use of the cell (1) itself: initially parameterising the cell model (6); generating a reference database (7); fitting a respective model parameter reference value from the reference database (7) by means of polynomial fitting and storing the fitting coefficients determined in this way in a data memory; as well as the following method steps carried out during the use of the cell (1) itself: determining the difference between a measured cell voltage (Umes) and a cell voltage (Urec) calculated using the cell model (6); establishing an amplification factor and multiplying the voltage difference determined in the previous method step by the amplification factor; and incrementally determining the impedance of the cell (1), wherein the next increment of the impedance is calculated by adding the current increment of the impedance to the product of the amplification factor and the voltage difference calculated in the previous method step, wherein the variable model parameters are then set to track the thus calculated next increment of the impedance, while taking the fitting coefficients into consideration.