Complex Impedance Analysis for Electrolysis State Diagnosis
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Solution Overview
Problem
Existing electrolysis devices face challenges in efficiently converting renewable energy into chemical substances like carbon monoxide and hydrogen, with limited diagnostic tools for monitoring their operational state and potential deterioration.
Innovation Solution
A state diagnosis system is introduced, comprising an impedance measuring device, processing units, and memory units to analyze complex impedance data, diagnose the state of electrolysis devices, and provide diagnostic data based on prior information, enabling effective monitoring and optimization of the electrolysis process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If electrolysis devices are used to convert renewable energy into chemical substances, then energy storage and chemical production are achieved, but limited diagnostic tools exist for monitoring operational state and deterioration
Solution Approach 1:
The patent replaces physical inspection and complex diagnostic procedures with electrical impedance measurement. By measuring impedance characteristics of the electrolysis device components (membrane, electrodes, seals), the system electronically detects operational state and deterioration without mechanical disassembly or complex diagnostic tools.
Solution Approach 2:
The patent introduces impedance measurement as an intermediary diagnostic method. Instead of directly monitoring chemical reactions or physical degradation, the system uses impedance characteristics as an intermediate parameter that reflects the operational state and deterioration of internal components, enabling indirect but effective monitoring.
2Productivity
If cell stacks are formed by stacking electrolysis cells to save space and improve efficiency, then productivity increases, but diagnostic capability for individual cells becomes more difficult
Solution Approach 1:
The patent applies segmentation by measuring impedance characteristics of individual cells within the cell stack separately. Instead of measuring the entire stack as one unit, the system can isolate and diagnose each cell's membrane, electrodes, and seals independently, enabling targeted identification of problematic cells while maintaining the productivity benefits of stacked configuration.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system enhances the efficiency and reliability of electrolysis processes by providing real-time diagnostics and optimizing operations, ensuring high yields of desired products like carbon monoxide and hydrogen.
Implementation Method 1
an impedance measuring device configured to measure a complex impedance of the electrolysis device
Implementation Method 2
an electrolysis device (electrochemical reaction device) such as a carbon dioxide electrolysis device
Implementation Method 3
The cathode reduces carbon dioxide to produce a carbon compound such as carbon monoxide (CO)
Implementation Method 4
an anode that oxidizes water (H2O)
Data Source
Figure 1
Figure 2~3
Figure 4
AI summary
A diagnosis system of an electrolysis device, includes: a device to output an impedance data indicating a measurement result of a complex impedance; a first memory unit to store prior data including a relation data indicating a relation between state of the device and a diagnosis result of a state of the device; a first processing unit to analyze the impedance data, judge validity of an analysis result, and output an analysis data indicating the analysis result in which data indicating at least a part of a frequency region of the measurement result is determined valid; a second processing unit to output a state data indicating the state based on first data including the analysis data; a second memory unit to store second data including the state data; and a third processing unit to output a diagnosis data based on data including the prior data and the second data.