Battery Rack Overvoltage Detection via Trend Intersection Analysis
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Solution Overview
Problem
Existing battery monitoring mechanisms rely on single state characteristics like voltage, current, or temperature, leading to misjudgments due to the lack of consideration for other state characteristics, resulting in erroneous detection of battery malfunctions.
Innovation Solution
A failure detection system for battery racks that utilizes a micro-controller to compute voltage and temperature data, including standard deviation, trend analysis, and slope calculations to generate alarm messages when abnormal conditions are detected, indicating potential overvoltage or temperature anomalies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single state characteristic (voltage, current, or temperature) is used for abnormality judgment, then the monitoring mechanism is simple, but misjudgments occur due to inability to consider other state characteristics
Solution Approach 1:
The patent combines multiple state characteristics (voltage, current, temperature) into a unified monitoring system that evaluates battery health comprehensively. The microcontroller integrates data from multiple sensors and applies weighted evaluation to determine abnormal conditions, resolving the contradiction by merging multiple monitoring functions into one coordinated system.
Solution Approach 2:
The monitoring system is designed to perform multiple functions simultaneously: voltage monitoring, current monitoring, temperature monitoring, and comprehensive health evaluation. This multi-functional approach allows the system to detect various types of abnormalities using a single integrated platform, improving detection precision without proportionally increasing complexity.
2Measurement precision
If temperature characteristics are used to evaluate battery condition, then temperature-based monitoring is implemented, but erroneous detection results occur due to lack of consideration for device operation state
Solution Approach 1:
The system incorporates feedback from device operation state (charging/discharging status) into the temperature evaluation process. The microcontroller adjusts temperature thresholds and evaluation criteria based on whether the device is currently operating or idle, preventing erroneous detections that would occur if temperature alone was considered without operational context.
Solution Approach 2:
The monitoring system dynamically adjusts evaluation parameters based on device operation state. When the device is charging or discharging, different temperature thresholds and evaluation weights are applied compared to idle states. This parameter adaptation allows accurate temperature-based anomaly detection while accounting for normal temperature variations during operation.
Data Source
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AI summary
A failure detection method for battery racks (100, 400) is disclosed and includes: continuously computing a voltage difference data in a computation frequency; computing a standard deviation by using the voltage difference data retrieved from each battery rack (100, 400) up to present; obtaining a first voltage trend and a second voltage trend according to the voltage difference data in a first period and the voltage difference data in a second period when the standard deviation is greater than a preliminary-filtered threshold; computing an intersection of the first voltage trend and the second voltage trend to obtain a voltage trend status; computing a voltage slope according to the voltage difference data of the second period; and generating an alarm message when the voltage trend status is abnormal and the voltage slope is greater than a slope threshold, where the alarm message indicates the position of a battery cell (120, 420) occurring overvoltage status.