Battery Diagnosis via SOC Deviation Analysis
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Solution Overview
Problem
Existing battery diagnosis methods struggle to accurately detect abnormalities in parallel cell blocks due to fluctuations in voltage during breaks or disconnections, especially in high-capacity batteries where voltage changes may be minimal.
Innovation Solution
A battery diagnosis apparatus that calculates State of Charge (SOC) and ΔSOC for each parallel cell block, identifies the largest block based on ΔSOC, and compares it to a reference value to determine abnormalities, while considering conditions such as SOC thresholds and polarization to enhance diagnostic accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If voltage measurement method is used to detect parallel connector break, then abnormality can be sensed, but measurement accuracy deteriorates when voltage fluctuation is small
Solution Approach 1:
The patent changes the detection parameter from voltage variation to SOC (State of Charge) variation. Instead of measuring voltage changes which may be minimal and hard to detect, the system calculates SOC before and after charging/discharging cycles and compares the differences. This parameter transformation enables reliable abnormality detection even when traditional voltage measurement would fail due to small signal variations.
2Device complexity
If simple voltage threshold comparison is used, then detection process is simple, but diagnostic accuracy deteriorates for high-capacity batteries
Solution Approach 1:
The patent performs preliminary SOC calculation before charging/discharging cycles and stores these baseline values. By pre-calculating and storing the initial SOC states, the system prepares reference data that enables accurate abnormality detection later without requiring complex real-time analysis during the actual charging/discharging process.
Solution Approach 2:
The system implements feedback by comparing the actual SOC change during charging/discharging against expected values and identifying the block with maximum SOC deviation. This feedback mechanism continuously monitors and compares SOC differences, enabling accurate identification of abnormal blocks even in high-capacity batteries where individual cell variations are minimal.
Data Source
AI summary
A battery diagnosis apparatus includes an SOC calculator, a ΔSOC obtaining unit, a largest block identification unit, and a diagnosis unit. The SOC calculator calculates an SOC for each parallel cell block included in a battery assembly based on an output from a battery sensor that detects a state of the battery assembly. When charging or discharging of the battery assembly is carried out, the ΔSOC obtaining unit obtains ΔSOC for each parallel cell block. The largest block identification unit identifies a largest block in a diagnosis target. When a degree of deviation between ΔSOC of the largest block and a ΔSOC reference value exceeds a prescribed level, the diagnosis unit determines that abnormality has occurred in the largest block in the diagnosis target.