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WaveNet-based fuel cell life prediction method

A fuel cell and life prediction technology, applied in neural learning methods, pattern recognition in signals, instruments, etc., can solve problems such as short-term life prediction and short prediction length, and achieve simple and clear algorithms, extended prediction time length, and training time little effect

Pending Publication Date: 2022-06-24
深圳市氢瑞燃料电池科技有限公司 +1
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Problems solved by technology

[0004] Based on this, it is necessary to address the above technical problems and provide a fuel cell life prediction method based on WaveNet to solve the problems that the existing prediction methods can only predict short-term life and short prediction length.

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  • WaveNet-based fuel cell life prediction method

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[0077] In order to facilitate understanding of the present invention, the present invention will be described more fully hereinafter with reference to the related drawings. Preferred embodiments of the invention are shown in the accompanying drawings. However, the present invention may be embodied in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.

[0078] It should be noted that when an element is referred to as being "connected" to another element, it can be directly connected to and integrated with the other element, or intervening elements may also be present. The terms "installed," "one end," "the other end," and similar expressions used herein are for illustrative purposes only.

[0079] It should be noted that if there are directional indications (such as up, down, left, right, front, back, etc.) involved in the embodiments of this application, th...

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Abstract

The invention discloses a WaveNet-based fuel cell life prediction method, which comprises the following steps of: decomposing preprocessed data by using an empirical mode decomposition algorithm to obtain a series of intrinsic mode components; then filtering the intrinsic mode component imf1 (t) with the noise and real signal aliasing phenomenon to obtain a first-order mode component; performing signal reconstruction on the first-order mode component and the unprocessed intrinsic mode component to obtain a WaveNet signal to be input; then, constructing a WaveNet-based fuel cell life prediction model by utilizing the initial parameters; and finally, inputting a to-be-input WaveNet signal into the WaveNet-based fuel cell life prediction model for training to obtain prediction data of the original life of the fuel cell. Through the prediction method provided by the invention, the prediction time step length can reach 500, and the long-term life prediction of the fuel cell is realized; the method needs less training time, and is very suitable for online real-time prediction.

Description

technical field [0001] The present application belongs to the technical field of fuel cells, and in particular relates to a method for predicting the lifetime of fuel cells based on WaveNet. Background technique [0002] Proton exchange membrane fuel cell (PEMFC), due to its non-polluting, high efficiency and low noise characteristics, has become one of the power generation tools for realizing low-carbon energy transformation, and has been widely used in many fields. At present, the operating life, long-term performance and maintenance cost of PEMFCs have become the main factors restricting their further commercialization. Therefore, accurate prediction of the performance degradation curve of fuel cells is an important part of its commercial development. The purpose of PEMFC life prediction is to make the system learn the aging trend (FDT) of the fuel cell by studying the historical experience data of the fuel cell, and then predict its remaining life, which plays the role ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06N3/08
CPCG06N3/08G06F2218/06G06F2218/10
Inventor 袁鹏杨骄高鹏然
Owner 深圳市氢瑞燃料电池科技有限公司
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