Li-Ion Battery Peak Detection for Micro-Short Failure Sensing
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Solution Overview
Problem
Existing lithium ion battery failure detection techniques are inadequate for advanced applications like electric vehicles and aircrafts, as they struggle to detect micro-short circuits and dendrite generation in real-time, leading to insufficient safety margins and potential thermal runaway.
Innovation Solution
A power supply device with a measurement unit, peak detection units for current and voltage, and a determination unit using a neural network to detect maximum and minimum values at regular intervals, along with temperature measurement, to accurately determine battery failure and prevent thermal runaway.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional voltage or current measurement techniques are used to detect lithium ion battery failures, then the detection system is simple, but the detection precision is insufficient to reliably identify micro-short circuits and dendrite generation
Solution Approach 1:
The detection system is segmented into multiple specialized units: voltage detection unit, current detection unit, peak detection unit, and determination unit. Each unit focuses on detecting specific parameters (voltage, current, peak values) and processing them independently, which improves overall detection precision while maintaining manageable system complexity through modular design
Solution Approach 2:
The system transitions from conventional single-parameter detection to multi-dimensional detection by simultaneously monitoring both voltage and current parameters, and further by detecting peak values at regular time intervals. This multi-dimensional approach enables more reliable identification of micro-short circuits and dendrite generation that single-parameter systems miss
2Reliability
If peak detection at regular time intervals is implemented, then the detection of micro-short circuits improves, but the data processing complexity increases
Solution Approach 1:
The peak detection unit performs preliminary action by detecting and holding peak voltage and current values at regular time intervals before the actual failure occurs. This preliminary detection of extreme values enables the determination unit to identify micro-short circuits based on abnormal peak patterns, improving reliability while simplifying the final determination process
Solution Approach 2:
The determination unit receives feedback from the peak detection unit in the form of detected peak values and occurrence frequencies. By analyzing the feedback regarding whether peak detection values exceed predetermined thresholds or if occurrence frequencies meet abnormality criteria, the system reliably detects micro-short circuits while managing data processing through structured feedback loops
3Reliability
If multiple detection parameters (voltage, current, temperature) are monitored, then the comprehensiveness of failure detection improves, but the system complexity and cost increase
Solution Approach 1:
The detection system is designed with multi-functionality to monitor multiple parameters (voltage, current, temperature) using integrated detection units. The peak detection unit and determination unit process all these parameters uniformly, enabling comprehensive failure detection including micro-short circuits, dendrite generation, and thermal issues within a single unified system rather than separate specialized systems
Solution Approach 2:
The system merges voltage detection, current detection, temperature measurement, peak detection, and determination functions into an integrated battery failure detection system. By combining these functions and sharing common processing resources (peak detection unit, determination unit), the system achieves comprehensive monitoring while controlling overall complexity through functional integration
Data Source
AI summary
A power supply device includes a measurement unit that measures at least one of a voltage and a current of a lithium ion battery, a peak detection unit that detects at least one of a maximum value of the current and a minimum value of the voltage at regular time intervals using at least one of the voltage and the current measured by the measurement unit, and a determination unit that determines a failure of the lithium ion battery based on at least one of the maximum value of the current and the minimum value of the voltage detected at regular time intervals by the peak detection unit.