Battery Cell Life Prediction from Manufacturing Cycle Slippage
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Solution Overview
Problem
Existing methods for estimating the life of a battery are time-consuming and cumbersome, making it difficult to predict battery life and detect failures at an early stage.
Innovation Solution
A system and method that collect life estimation data from a manufacturing process, calculate cumulative slippage data, and use linear regression to predict battery life based on correlations between slippage and performance, allowing for early detection of battery defects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If battery life is estimated by repetitive charging and discharging under actual usage conditions, then the accuracy of life prediction is improved, but the time and complexity of the estimation process increases significantly
Solution Approach 1:
The patent applies preliminary action by performing repetitive charging and discharging tests during the manufacturing process before the battery is deployed. This allows life estimation data to be collected in advance, enabling early detection of batteries with poor life characteristics and removing them from circulation before they can cause problems in actual usage.
Solution Approach 2:
The patent uses partial action by performing a limited number of charging and discharging cycles (e.g., 3-5 cycles) during manufacturing rather than requiring full lifecycle testing. This partial testing is sufficient to identify batteries with poor life characteristics, achieving adequate prediction accuracy without the time cost of complete lifecycle tests.
2Reliability
If battery life is estimated by repetitive charging and discharging tests, then long-term life can be predicted, but the process becomes cumbersome and complex
Solution Approach 1:
The patent performs life estimation tests during the manufacturing process rather than after deployment. By conducting charging and discharging tests in advance, the system can identify and remove batteries with poor life characteristics before they enter service, ensuring reliability without requiring complex ongoing monitoring systems.
Solution Approach 2:
The patent extracts batteries with poor life characteristics from the production batch during manufacturing testing. By identifying and removing defective units early in the manufacturing process, the system ensures that only batteries meeting life requirements are deployed, simplifying the overall quality assurance process.
3Reliability
If early detection of battery failures is implemented through extensive testing, then reliability is improved, but manufacturing efficiency decreases
Solution Approach 1:
The patent applies partial action by performing a limited number of charging and discharging cycles (e.g., 3-5 cycles) during manufacturing rather than requiring full lifecycle tests. This partial testing is sufficient to identify batteries with poor life characteristics, achieving adequate detection capability while maintaining manufacturing efficiency.
Solution Approach 2:
The patent performs essential life estimation tests during the manufacturing process to identify and remove batteries with poor life characteristics before deployment. This preliminary screening ensures reliability while keeping the testing process brief and efficient, avoiding excessive impact on manufacturing productivity.
Data Source
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AI summary
The present disclosure relates to a method of estimating a life of a battery including collecting life estimation data of a target battery cell from a manufacturing process device of the target battery cell, calculating slippage-related data based on the life estimation data, predicting a life of the target battery cell based on the calculated slippage-related data, and estimating a life quality of the target battery cell based on the predicted life.