Lithium-Ion Electrode OCP Estimation Without Cell Teardown
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Solution Overview
Problem
Conventional methods for estimating open-circuit potential (OCP) in lithium-ion batteries require disassembling cells, which is expensive and potentially dangerous, and often rely on incomplete or inaccurate literature data, leading to errors in OCP curve reconstruction.
Innovation Solution
A non-invasive method using sensors and a computing device to measure operating parameters, apply physics-based models, and perform optimization to reconstruct OCP curves for lithium-ion battery electrodes, leveraging known information and experimental data to avoid teardown and enhance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional teardown and measurement process is used to obtain OCP data, then OCP measurement can be achieved, but the process becomes very expensive and potentially dangerous
Solution Approach 1:
The patent creates a virtual half-cell model that replicates the electrochemical behavior of actual electrode materials without requiring physical disassembly. By using computational models (MSMR, P2D) to simulate and reconstruct OCP curves from full-cell data, the system obtains accurate electrode potential information while avoiding the expensive and dangerous teardown process entirely.
2Ease of manufacture
If literature data is used for OCP curve reconstruction, then the process is simpler, but the data may be incomplete or inaccurate leading to errors
Solution Approach 1:
The system uses an iterative optimization process where the reconstructed OCP curves are continuously validated against experimental full-cell data. The model parameters are adjusted based on feedback from voltage measurements and differential capacity analysis, ensuring that the final OCP curves accurately represent the actual electrode behavior rather than relying on potentially inaccurate literature values.
Solution Approach 2:
The patent replaces the manual process of obtaining literature data and manually constructing OCP curves with an automated computational system. The computing device automatically performs data processing, model fitting, curve reconstruction, and validation, eliminating human error and ensuring consistent, accurate results while maintaining process simplicity.
3Measurement precision
If physics-based models are applied to reconstruct OCP curves, then accuracy is improved, but the complexity of the process increases
Solution Approach 1:
The patent introduces a computing device as an intermediary that handles the complexity of physics-based modeling. This device automatically performs the sophisticated calculations involving MSMR and P2D models, parameter optimization, and curve reconstruction, shielding the user from the mathematical and computational complexity while delivering accurate results.
Solution Approach 2:
The system performs preliminary data processing and model setup automatically before the actual OCP reconstruction. By pre-processing the full-cell data, pre-defining model parameters, and pre-establishing the computational framework, the system reduces the apparent complexity for the user while maintaining the rigor of physics-based modeling throughout the reconstruction process.
Data Source
AI summary
An open-circuit potential (OCP) estimation method includes measuring a set of operating parameters of a battery cell of a battery system, the battery cell being a lithium-ion type battery cell and comprising two electrodes, and performing an OCP estimation process based on the measured set of operating parameters, the OCP estimation process further including obtaining known information relating to the two electrodes, identifying one of the two electrodes as a known electrode based on the known information, applying a physics-based model to reconstruct an OCP curve for the known electrode, determining lithiation ranges of the other of the two electrodes based on experimental test results for the battery cell, reconstructing an OCP curve for the other of the two electrodes based on its lithiation ranges, and generating a final estimate of the OCP of the two electrodes of the battery cell based on the reconstructed OCP curves.