Battery Diagnosis Using OCV Deviation to Simplify Data Requirements
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Solution Overview
Problem
Existing battery diagnosis methods, particularly in battery management systems, face challenges in accurately diagnosing battery abnormalities due to the complexity of data requirements, such as state of charge (SOC), current, and open circuit voltage (OCV), which can lead to increased memory usage and difficulty in diagnosing failures when specific information is missing.
Innovation Solution
A battery diagnosis apparatus and method that utilizes open circuit voltage (OCV) data to calculate OCV change values and deviation values within designated time windows, allowing for the diagnosis of battery abnormalities by comparing these values against thresholds and counts, thereby simplifying the diagnosis process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple factors (SOC, current, capacity, OCV) are used for battery diagnosis, then diagnosis accuracy is improved, but memory usage increases and diagnosis becomes difficult when specific information is missing
Solution Approach 1:
The patent extracts and focuses on a single critical factor (OCV - Open Circuit Voltage) from the multiple factors traditionally used for battery diagnosis. By taking out only the essential OCV parameter and its change over time, the system achieves effective diagnosis while eliminating the complexity of managing multiple data types (SOC, current, capacity) and reducing memory usage requirements.
2Reliability
If multiple factors are used for battery diagnosis, then diagnosis accuracy is improved, but the system becomes more complex and requires more memory
Solution Approach 1:
The patent extracts only the essential OCV data and its temporal changes, eliminating the need to store and process large quantities of additional data (SOC, current, capacity). This extraction approach maintains reliable battery failure detection while significantly reducing memory usage and data storage requirements.
Solution Approach 2:
The patent uses simple, easily obtainable OCV measurements that can be taken repeatedly over time without consuming valuable resources. By focusing on this single, readily available parameter measured at different time points, the system achieves effective diagnosis with minimal data storage requirements.
3Measurement precision
If comprehensive battery data is collected for diagnosis, then diagnosis accuracy is improved, but the system complexity and data processing burden increase
Solution Approach 1:
The patent extracts the essential diagnostic information from comprehensive battery data by focusing solely on OCV measurements at different time points. This extraction simplifies the diagnosis process to comparing OCV change values against thresholds, making the system easier to operate while maintaining accurate abnormality detection.
Solution Approach 2:
The patent transforms the diagnosis approach by changing the parameter from multiple static factors (SOC, current, capacity) to a dynamic parameter (OCV change over time). This parameter change simplifies the diagnosis process while maintaining the ability to detect battery abnormalities accurately through temporal comparison.
Data Source
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AI summary
A battery diagnosis apparatus according to an embodiment disclosed herein includes an obtaining unit configured to obtain open circuit voltage (OCV) data of a battery cell, a calculating unit configured to calculate an OCV change value of each of a plurality of battery cells included in a specific battery module, in a designated time window, based on the OCV data, and calculate an average-to-OCV deviation value indicating a difference value between an average OCV change value of the plurality of battery cells and an OCV change value of a specific battery cell among the plurality of battery cells, and a diagnosing unit configured to diagnose abnormality of the specific battery cell, based on the average-to-OCV deviation value of the specific battery cell.