Battery Cell Lifespan Prediction With Storage Degeneration Correction
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Solution Overview
Problem
Conventional battery cell lifespan prediction methods fail to accurately account for storage degeneration, leading to distorted results, particularly in batteries with high nickel content positive electrode materials.
Innovation Solution
A method that virtually divides the battery cell capacity into multiple parts, measures charge and discharge cycle data for each part, corrects for storage degeneration, and predicts lifespan based on corrected data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the conventional N-division accelerated lifespan evaluation method is used to quickly predict battery lifespan, then the evaluation time is significantly reduced, but the prediction results become distorted due to unaccounted storage degeneration
Solution Approach 1:
The patent divides the battery capacity into multiple sections (e.g., 5 sections) and performs separate charge/discharge cycle tests for each section. This segmentation allows the storage degeneration to be measured and corrected for each capacity range individually, preventing the distortion that would occur in a conventional single-cycle evaluation method.
Solution Approach 2:
The patent performs preliminary storage tests at various SOC levels to determine the storage degeneration characteristics before conducting the accelerated lifespan evaluation. This preliminary action allows the system to pre-calculate correction factors that are then applied during the main evaluation, ensuring accurate compensation for storage effects without extending the main test duration.
2Measurement precision
If charge/discharge experiments are conducted under actual operating conditions to obtain accurate lifespan data, then the prediction accuracy is improved, but the time required to collect sufficient data increases to about 30 months
Solution Approach 1:
The patent changes the evaluation parameters by conducting accelerated charge/discharge cycle tests rather than slow actual operating condition tests. By using higher current rates and dividing the capacity into multiple sections, the system obtains equivalent or superior data quality in a fraction of the time, while still accounting for storage degeneration through the sectioned approach.
Solution Approach 2:
The patent introduces correction factors as an intermediary element that bridges the gap between accelerated test conditions and actual operating conditions. These correction factors, derived from storage tests at various SOC levels, allow the system to translate accelerated test results into accurate lifespan predictions that reflect real-world performance.
3Productivity
If the battery capacity is divided into multiple capacity parts for accelerated evaluation, then the evaluation time is reduced, but storage degeneration at specific capacity sections causes distorted results
Solution Approach 1:
The patent applies local quality by determining storage degeneration characteristics separately for each capacity section (e.g., 0-20%, 20-40%, etc.) rather than using a single average value. This allows the correction to be tailored to the specific degradation behavior of each section, particularly addressing the high nickel content material issues at specific SOC ranges.
Solution Approach 2:
The patent implements a feedback mechanism where storage degeneration is measured at each section, correction factors are calculated based on these measurements, and then these corrections are applied to the accelerated test results. This closed-loop approach ensures that the distortion caused by storage effects in specific sections is systematically identified and compensated.
Data Source
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AI summary
A method for predicting a lifespan of a battery cell of the present invention includes: virtually dividing a capacity of a battery cell, which is a measurement object for lifespan prediction, into two or more capacity parts, and measuring charge and discharge cycle data for each of the capacity parts; correcting the charge and discharge cycle data by reflecting storage degeneration of a positive electrode active material; and predicting a lifespan of the battery cell, based on the corrected charge and discharge cycle data.