Method for diagnosing starvation fault of proton exchange membrane fuel cell stack
A fuel cell stack and proton exchange membrane technology, applied in fuel cells, fuel cell additives, fuel cell control, etc., can solve the problems of time-consuming data sets, low fault identification accuracy, and difficulty in online fault detection by fault diagnosis methods. , to achieve the effect of long test cycle time, real-time fault diagnosis, and shortening of parameter extraction time
Active Publication Date: 2021-10-22
CHINA JILIANG UNIV
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But both have disadvantages. The model-based fault diagnosis method is difficult to carry out real-time online fault detection. The data-driven fault diagnosis method is limited by the number of data sets. The generation process of these data sets is very time-consuming, corresponding to various faults. The recognition accuracy is relatively low
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[0025] A specific implementation of a method for diagnosing a starvation fault of a proton exchange membrane fuel cell stack will be described below with reference to the accompanying drawings. The implementation process of the method for diagnosing the starvation fault of a proton exchange membrane fuel cell stack according to the present invention comprises the following steps:
[0026] Step 1: Measure the impedance information in the fuel cell stack by EIS method, such as figure 1 The value of the real and imaginary part of the impedance at the extracted frequency of 20KHz is shown to obtain the ohmic internal resistance R m ,Such as figure 2 As shown, the output voltage U under the corresponding current density i is obtained on the U-I curve; the total internal resistance R of the stack can be obtained by substituting U and i into the fuel cell output voltage model stack , to extract the working temperature T of the stack corresponding to the current density i stack , ...
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The invention discloses a starvation fault diagnosis method for a proton exchange membrane fuel cell stack. The method comprises the step of calculating index parameters of starvation fault diagnosis through real and imaginary part values corresponding to EIS specific frequency and a fuel cell internal resistance model; by using the starvation data obtained through simulation and normal electric pile data as initial analysis data, performing a principal component analysis method and a K-means clustering method for classification to acquire two centroid points mu1 and mu2 of a normal cluster set and a starvation cluster set; acquiring the experimental data points under different operation conditions by using a principal component analysis method and a K-means clustering method, comparing the data points with a mass center point mu1 of a normal data cluster and a mass center point mu2 of a starvation data cluster, so that whether the galvanic pile has a starvation fault and the degree of the starvation fault at the moment can be judged. The method has a good engineering application prospect.
Description
Technical field: [0001] The invention relates to a method for diagnosing starvation faults of a proton exchange membrane fuel cell stack. Background technique: [0002] With the depletion of traditional fossil energy, people in the 21st century will pay more attention to the development and utilization of new sustainable energy. A fuel cell is a low-pollution, high-efficiency power generation device that can use hydrogen, a new energy source, as a fuel without combustion. Among them, the proton exchange membrane fuel cell (PEMFC) uses Nafion membrane as the electrolyte, oxygen and hydrogen as the anode and cathode reactants, and heavy metal platinum / carbon as the catalyst. Features, it is very suitable for the energy supply of mobile equipment such as aerospace and military power energy, vehicle power energy, small power supply for portable electronic products, etc., and has a bright application prospect. With the continuous advancement of fuel cell technology and the stro...
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IPC IPC(8): H01M8/04664H01M8/04298H01M8/04992
CPCH01M8/04305H01M8/04992H01M8/04679Y02E60/50
Inventor 卫东高志严梦男郭倩
Owner CHINA JILIANG UNIV