Fuel Cell Stack Diagnosis via Stepwise Current and Fourier Analysis
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Solution Overview
Problem
Current fuel cell stack diagnosis methods using sinusoidal AC current variations have limited decomposition performance and accuracy, especially when detecting abnormal states in larger units.
Innovation Solution
An apparatus and method that measures stack voltage and current to form a reference signal waveform, extracting reference current and voltage points, calculating an abnormality degree based on harmonic amplitudes, and determining the fuel cell stack's abnormal state without additional AC signals, enhancing detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a small AC current variation is applied to the stack for diagnosis, then the diagnosis method is simple, but the decomposition performance and detection accuracy are limited
Solution Approach 1:
The patent changes the parameter of diagnosis current from small AC variation to large stepwise current changes. The diagnosis current is increased in steps (e.g., 0A→50A→100A→150A) rather than using small sinusoidal variations, which enables better decomposition performance and detection accuracy while maintaining operational simplicity
Solution Approach 2:
The patent employs periodic stepwise current changes as a diagnostic approach. The current is increased in discrete steps and then returned to zero, creating a periodic diagnostic cycle that allows for effective signal decomposition and abnormality detection without requiring continuous small AC variations
2Area of stationary object
If the unit of detecting unit of the fuel cell stack is increased, then the diagnosis covers larger scale, but the detection accuracy decreases with traditional methods
Solution Approach 1:
The patent segments the voltage signal into multiple frequency components through Fourier transform analysis. By decomposing the voltage response into fundamental frequency and harmonic components, the system can detect abnormalities in large-scale stacks with high precision, as each frequency component provides specific diagnostic information about different aspects of stack performance
Solution Approach 2:
The patent changes the analysis parameter from raw voltage measurement to frequency-domain analysis using Fourier transform. This parameter transformation enables the system to maintain high detection accuracy even when diagnosing large-scale stacks, as the frequency decomposition reveals subtle abnormalities that would be obscured in time-domain measurements
3Loss of information
If additional AC signal is applied to the fuel cell stack for diagnosis, then more diagnostic information can be obtained, but the system complexity and energy consumption increase
Solution Approach 1:
The patent makes the fuel cell stack diagnose itself by utilizing its own operational voltage and current data. The control unit analyzes the voltage response to natural or stepwise current changes without requiring external AC signal injection equipment, thereby obtaining comprehensive diagnostic information while minimizing system complexity
Solution Approach 2:
The patent extracts diagnostic information from the existing operational parameters (voltage and current) of the fuel cell stack. By analyzing the voltage response to current changes and decomposing it into frequency components, the system extracts abundant diagnostic information without needing additional signal injection hardware, thus reducing system complexity
Data Source
AI summary
An apparatus for diagnosing a fuel cell and a vehicle system includes a measuring device that measures a stack voltage and a stack current from a fuel cell stack, and at least one processor that extracts a plurality of reference current points and a plurality of reference voltage points corresponding to the reference current points by analyzing the measured stack voltage and the measured stack current, calculates an abnormality degree of the fuel cell stack based on a reference signal waveform formed by using voltage differences between the reference voltage points, and determines an abnormal state of the fuel cell stack based on the calculated abnormality degree of the fuel cell stack.