Battery Abnormality Detection Using Voltage and Temperature Differentials
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Solution Overview
Problem
Existing battery abnormality detection methods struggle to accurately distinguish between temperature rises caused by external factors and internal battery abnormalities, such as internal short-circuits, especially when external heat influences are significant.
Innovation Solution
A battery abnormality detection system that acquires voltage and temperature data from multiple cells and temperature sensors within a battery pack. The system determines abnormalities by analyzing the transition of voltages and the difference in temperature changes between observation points, effectively canceling out external heat influences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If temperature difference or temperature rise rate is used for abnormality detection, then detection simplicity is improved, but detection accuracy deteriorates when external heat factors are present
Solution Approach 1:
The battery pack is divided into multiple temperature observation points (first observation point near the specific cell, second observation point as reference). By segmenting the temperature measurement into localized and reference points, the system can isolate the temperature change specific to the monitored cell from general external heat influences, thereby improving detection accuracy while maintaining operational simplicity.
Solution Approach 2:
The temperature difference between the first observation point (near the specific cell) and the second observation point (reference point) serves as an intermediary indicator. This temperature difference metric acts as a mediator that cancels out common external heat factors, allowing accurate detection of internal abnormalities without being misled by external thermal conditions.
2Device complexity
If single temperature observation point is used, then device complexity is reduced, but detection accuracy deteriorates due to inability to distinguish external heat influence
Solution Approach 1:
The temperature monitoring system is segmented into multiple observation points within the battery pack - a first observation point positioned near the specific cell under monitoring and a second observation point serving as a reference. This segmentation enables the system to distinguish between temperature changes caused by the specific cell's internal state versus those caused by external environmental factors, thereby improving detection accuracy without requiring excessive sensors.
Solution Approach 2:
The temperature difference between the first and second observation points serves as an intermediary metric that isolates the thermal signature of the specific cell from general battery pack or environmental temperature changes. This intermediary measurement approach enables accurate abnormality detection while keeping the sensor count manageable.
3Measurement precision
If voltage transition and temperature difference are both used for determination, then detection accuracy is improved, but device complexity increases
Solution Approach 1:
The determination process is segmented into two independent but complementary evaluation streams: voltage transition analysis of the specific cell and temperature difference analysis between observation points. By segmenting the detection methodology, the system can process voltage and temperature data through relatively simple respective algorithms, avoiding the need for complex integrated models while maintaining high detection accuracy through the combination of both indicators.
Solution Approach 2:
The temperature difference metric serves as an intermediary that simplifies the overall determination process. Instead of directly analyzing complex thermal fields or requiring sophisticated thermal models, the system uses the temperature difference between two points as a simplified intermediary indicator that, when combined with voltage transition data, enables accurate abnormality detection through relatively straightforward evaluation logic.
Data Source
AI summary
A battery abnormality detection system includes the following constituents. A battery data acquisition unit acquires voltages of one of a plurality of cells and a plurality of parallel cell blocks in a battery pack and temperatures at a plurality of observation points respectively measured by a plurality of temperature sensors provided in the battery pack. A determination unit determines presence or absence of an abnormality in one of a specific cell and a specific parallel cell block, based on a transition of a voltage of the one of the specific cell and the specific parallel cell block in a predetermined period in the battery pack and on a difference between a temperature change at a first observation point and a temperature change at a second observation point in the predetermined period in the battery pack.