CN114204077B - SOFC system oscillation control and optimization method caused by water vapor flow oscillation - Google Patents

SOFC system oscillation control and optimization method caused by water vapor flow oscillation Download PDF

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CN114204077B
CN114204077B CN202210148483.4A CN202210148483A CN114204077B CN 114204077 B CN114204077 B CN 114204077B CN 202210148483 A CN202210148483 A CN 202210148483A CN 114204077 B CN114204077 B CN 114204077B
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杨霖
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Zhejiang Guohydrogen Energy Technology Development Co ltd
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    • HELECTRICITY
    • H01ELECTRIC ELEMENTS
    • H01MPROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M8/00Fuel cells; Manufacture thereof
    • H01M8/04Auxiliary arrangements, e.g. for control of pressure or for circulation of fluids
    • H01M8/04298Processes for controlling fuel cells or fuel cell systems
    • H01M8/04305Modeling, demonstration models of fuel cells, e.g. for training purposes
    • HELECTRICITY
    • H01ELECTRIC ELEMENTS
    • H01MPROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M8/00Fuel cells; Manufacture thereof
    • H01M8/04Auxiliary arrangements, e.g. for control of pressure or for circulation of fluids
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    • H01M8/04694Processes for controlling fuel cells or fuel cell systems characterised by variables to be controlled
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    • H01M8/04776Pressure; Flow at auxiliary devices, e.g. reformer, compressor, burner
    • HELECTRICITY
    • H01ELECTRIC ELEMENTS
    • H01MPROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M8/00Fuel cells; Manufacture thereof
    • H01M8/04Auxiliary arrangements, e.g. for control of pressure or for circulation of fluids
    • H01M8/04298Processes for controlling fuel cells or fuel cell systems
    • H01M8/04992Processes for controlling fuel cells or fuel cell systems characterised by the implementation of mathematical or computational algorithms, e.g. feedback control loops, fuzzy logic, neural networks or artificial intelligence
    • HELECTRICITY
    • H01ELECTRIC ELEMENTS
    • H01MPROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M8/00Fuel cells; Manufacture thereof
    • H01M8/06Combination of fuel cells with means for production of reactants or for treatment of residues
    • H01M8/0606Combination of fuel cells with means for production of reactants or for treatment of residues with means for production of gaseous reactants
    • H01M8/0612Combination of fuel cells with means for production of reactants or for treatment of residues with means for production of gaseous reactants from carbon-containing material
    • H01M8/0618Reforming processes, e.g. autothermal, partial oxidation or steam reforming
    • HELECTRICITY
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    • H01MPROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
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    • H01M8/10Fuel cells with solid electrolytes
    • H01M8/12Fuel cells with solid electrolytes operating at high temperature, e.g. with stabilised ZrO2 electrolyte
    • H01M2008/1293Fuel cells with solid oxide electrolytes
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02E60/30Hydrogen technology
    • Y02E60/50Fuel cells

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Abstract

The invention relates to the technical field of steam external reforming solid oxide fuel cells, in particular to a method for controlling and optimizing SOFC system oscillation caused by steam flow oscillation. The method comprises the following steps: modeling the SOFC system by steam external reforming; simulating and analyzing the oscillation condition of the water vapor flow; an oscillation control algorithm based on fuzzy control is introduced, and a control and optimization strategy is provided; and analyzing and optimizing the effect according to the simulation experiment result and applying the effect. According to the design, a water vapor oscillation model is constructed, so that frequent discharge experiments on an SOFC system are not needed, and system faults are avoided; single/double input fuzzy controllers are respectively designed, and the temperature and the voltage in the SOFC system can be controlled within a reasonable range through simulation, so that the system oscillation is controlled; and designing a fuzzy control rule and a control strategy to realize real-time tracking of a set value and prevent the propagation of oscillation in the SOFC system, thereby optimizing the performance of the system.

Description

SOFC system oscillation control and optimization method caused by water vapor flow oscillation
Technical Field
The invention relates to the technical field of steam external reforming solid oxide fuel cells, in particular to a method for controlling and optimizing SOFC system oscillation caused by steam flow oscillation.
Background
When research is conducted on a Solid Oxide Fuel Cell (SOFC) that is externally reformed by steam, it is common that oscillations occur and propagate in SOFC systems during SOFC power generation. Severe oscillations can cause the system to malfunction and fail to function properly. Measures must be taken to eliminate or reduce the effects of oscillations on the SOFC system so that the system can stabilize normal power generation and maintain a healthy operating condition. The simplest and most suitable approach is to control and optimize the root of the system oscillation after it has been successfully located, thereby preventing the oscillation from propagating in the system.
In previous research, a method combining data and a topological model is used to find that important roots of SOFC system oscillation are methane flow oscillation and water vapor oscillation, wherein the oscillation of methane flow can be directly measured by an instrument at an inlet, and the water vapor is generated by an evaporator reaction, the oscillation cannot be physically measured, and the water vapor oscillation has a critical influence on the oscillation of methane in an internal reaction. In practice, the methane flow oscillations are caused by the deionized water vapor oscillations in the reforming reaction which are subject to external disturbances, i.e., which cannot be directly measured by sensors. In order to optimize the system, the oscillation condition of the SOFC system is controlled, so that the influence of the oscillation on the system is eliminated.
Based on the existing SOFC independent power generation system in research, frequent discharge experiments on the SOFC system may not only cause the SOFC system to malfunction, making the SOFC power generation system unable to work normally, but also because the experiment period is too long, it is not appropriate to directly perform oscillation control on the system. However, no method strategy for controlling and optimizing SOFC system oscillation caused by water vapor flow oscillation is available on the premise of not damaging the SOFC power generation system. In view of this, we propose a method for controlling and optimizing SOFC system oscillation caused by water vapor flow oscillation.
Disclosure of Invention
The invention aims to provide a method for controlling and optimizing SOFC system oscillation caused by water vapor flow oscillation, so as to solve the problems in the background technology.
In order to solve the above technical problem, an object of the present invention is to provide a method for controlling and optimizing SOFC system oscillation caused by water vapor flow oscillation, including the following steps:
s1, modeling the SOFC system through steam external reforming to serve as a basic support of a subsequent control and optimization method;
s2, assuming that the irregular oscillation change of the methane flow except the specified input is only subjected to the change of the steam flow, simulating and analyzing the oscillation condition of the steam flow;
s3, introducing an oscillation control algorithm based on fuzzy control, and providing a corresponding control and optimization strategy aiming at the SOFC system oscillation root caused by water vapor oscillation;
and S4, analyzing the optimization effects of the two strategies respectively according to the simulation experiment results of the two fuzzy controllers, and applying the simulation optimization strategy to the real SOFC power generation system according to specific requirements.
As a further improvement of the present technical solution, in S1, the specific method for modeling the SOFC system by steam external reforming includes the following steps:
s1.1, constructing a 3kW SOFC independent power generation system consisting of an SOFC electric pile, a reformer subsystem, a heat exchanger subsystem, a fuel supply subsystem, an air supply subsystem, a tail gas combustion chamber subsystem and an electric control unit;
s1.2, aiming at the oscillation phenomenon in the SOFC system, establishing an SOFC system model capable of reflecting the inherent characteristics of the SOFC independent power generation system, and integrating and verifying the system model after modeling is completed.
As a further improvement of the technical solution, in S1.2, the specific method for establishing and integrating the SOFC system model includes the following steps:
s1.2.1, constructing a galvanic pile model: the model of the galvanic pile is subjected to node conversion, namely, the cell can be divided into 5 nodes, and then the ith node is modeled;
s1.2.2, construction of reformer model: the product composition of the reaction in the reformer can be estimated using a dynamic chemical equilibrium approach;
s1.2.3, constructing a tail gas combustion chamber model: mainly considering the wall of the combustion chamber and the high-temperature flue gas inside;
s1.2.4, constructing a heat exchanger model: the heat exchanger is used for heating cold air by adopting high-temperature gas, still adopts a sleeve type structure for simplifying a model, and changes the heat exchanger into 5 nodes according to the design concept of a galvanic pile model;
s1.2.5, constructing a fuel and air supply subsystem model: the air supply system takes an air compressor as an air supply source, adopts a blower model, and the fuel supply system takes a methane gas cylinder as the air supply source;
s1.2.6, system model integration: and integrating the system model according to a physical connection mode in the SOFC system, and initializing the density and specific heat capacity parameters of the object in the MATALB.
As a further improvement of the present technical solution, in S2, the specific method for simulating and analyzing the oscillation condition of the steam flow includes the following steps:
s2.1, designing a water vapor oscillation model in Matlab/Simulink to simulate oscillation of water vapor flow, and adding sine wave oscillation to the water vapor flow in the model;
s2.2, applying the model to carry out simulation experiment of SOFC system power generation;
s2.3, under the condition that the discharge current of the SOFC system is set to be constant (such as 20A), increasing the amplitude of water vapor flow oscillation in the model to determine the influence degree of the water vapor flow on the thermoelectric property of the system and the uncertainty of the simulated water vapor flow in the actual SOFC system;
and S2.4, increasing the discharge current when the oscillation degree of the steam flow is not changed, and observing temperature curves of an outlet of the reformer, an outlet of the heat exchanger, an inlet of the galvanic pile, an outlet of the galvanic pile and an outlet of the tail gas combustion chamber to analyze factors influencing the change of the discharge current in the power generation process of the SOFC system.
As a further improvement of the technical solution, in S2.1, the amplitude of the sine wave is set to 0.1Hz according to the number of moles of the actual steam flow, and random disturbance is added on the basis of the sine wave, specifically:
because the oscillation of the water vapor actually occurs at any time, the simulation time of 15000s or longer is set, and in the time range of 15000s, the flow of the water vapor is not processed in the first 7000s and is always a constant value, namely the water vapor does not oscillate in the time; sinusoidal disturbance is added on the basis of normal steam flow in the period of 7000-15000 s, and the steam oscillation in the period is represented.
As a further improvement of the technical solution, in S3, a specific method for providing a corresponding control and optimization strategy for SOFC system oscillation root caused by water vapor oscillation includes the following steps:
s3.1, collecting data of a power generation simulation experiment of the SOFC system, establishing a database, analyzing and diagnosing the oscillation root of the system by adopting a method of combining data driving and a topological model, and positioning the oscillation root of the system;
s3.2, aiming at different system oscillation root causes, designing a corresponding controller to control and optimize oscillation;
s3.3, designing a fuzzy controller: the single-input fuzzy controller with the input of the voltage of the galvanic pile and the output of the steam flow and the double-input fuzzy controller with the input of the voltage of the galvanic pile and the temperature of the outlet of the tail gas combustion chamber and the output of the steam flow are respectively designed.
As a further improvement of the present technical solution, in S3.2, for different system oscillation root causes, a specific method for designing a corresponding controller to control and optimize oscillation includes the following steps:
s3.1.1, for the oscillation caused by the poor regulation of the flow controller in the SOFC system, designing a single-loop PID controller, and eliminating the oscillation by adjusting control parameters or using a controller based on a multivariable model;
s3.1.2, for the oscillation caused by the valve static friction, eliminating the oscillation caused by the valve by identifying the viscous valve and maintaining;
s3.1.3, controlling the flow of the vapor by using a fuzzy control algorithm aiming at the oscillation caused by the flow of the vapor, taking the signal acquired by the sensor as the input of a fuzzy control rule after fuzzy quantization processing, and adding the output obtained by fuzzy logic reasoning to an actuator to act on the controlled object, thereby realizing the control of the system.
As a further improvement of the present technical solution, in S3.3, a specific method for designing a fuzzy controller includes the following steps:
s3.2.1, setting input and output domains of the controller, and dividing the input and output domains into 7 levels;
s3.2.2, dividing discourse domain fuzzy subsets and determining membership functions of discourse domains;
s3.2.3, designing fuzzy control rules according to the control strategy, and continuously adjusting the control rules.
As a further improvement of the present technical solution, in S3.2.3, the fuzzy control rule designed according to the control strategy includes but is not limited to:
aiming at the following relationship between the voltage of the galvanic pile and the flow of the water vapor, the fuzzy control rule is as follows: in order to make the oscillation of the stack voltage less obvious, a large amount of water needs to be introduced when the stack voltage is seriously lower than an ideal value, and a small amount of water needs to be introduced when the stack voltage is slightly lower than the ideal value; when the voltage of the electric pile is higher than an ideal value in different degrees, the steam flow of the corresponding degree needs to be reduced; when the voltage of the galvanic pile is at an ideal value, the flow of the water vapor is not changed;
for the tail gas combustion chamber, the fuzzy control rule is as follows: when the steam flow is just fully reacted with methane and the electrochemical reaction in the galvanic pile is sufficient, the outlet temperature of the tail gas combustion chamber is optimal; higher or lower water vapor flow rates, both above and below the desired level, result in higher temperatures in the tail gas combustor; when the flow of the water vapor is low, the temperature in the tail gas combustion chamber is higher than that when the flow of the water vapor is high, and the introduction amount of the water vapor/water is properly increased or reduced according to the required temperature of the tail gas combustion chamber.
As a further improvement of the present technical solution, in S4, specific contents of analyzing the optimization effects of the two strategies respectively according to the results of the simulation experiments of the two fuzzy controllers include, but are not limited to:
after the voltage of the galvanic pile is increased to serve as an input fuzzy controller, the oscillation conditions of the temperatures of the outlet of the reformer, the outlet of the heat exchanger, the inlet of the galvanic pile and the outlet of the galvanic pile are obviously reduced, and the system begins to tend to be stable; because the voltage of the electric pile is used as the only input of the controller, the voltage of the electric pile is well controlled, and the electrical characteristics of the system are well improved; however, the disadvantage of selecting only voltage as the input to the controller is that there is still a large oscillation in the temperature in the exhaust gas combustor, and therefore the controller needs to be improved, and the outlet temperature of the exhaust gas combustor is also considered to be added to the input of the fuzzy controller;
compared with a single-input fuzzy controller, after the temperature of the outlet of the combustion chamber is increased to serve as an input double-input fuzzy controller, the oscillation amplitudes of the temperatures of the outlet of the reformer, the outlet of the heat exchanger and the inlet and outlet of the galvanic pile become smaller; for the electrical characteristics of the system, the control effect of the double-input controller is not greatly different from that of the single-input controller; in order to control the root cause of oscillations in the system, a dual-input controller has a greater effect on improving the thermoelectric characteristics of the system than a single-input controller.
The second objective of the present invention is to provide a steam oscillation model simulation system and an operating device thereof, including a processor, a memory and a computer program stored in the memory and operated on the processor, wherein the processor is used for implementing the steps of the SOFC system oscillation control and optimization method caused by the steam flow oscillation when executing the computer program.
It is a further object of the present invention to provide a computer readable storage medium, which stores a computer program, which when executed by a processor, implements the steps of the above-mentioned SOFC system oscillation control and optimization method caused by water vapor flow oscillation.
Compared with the prior art, the invention has the beneficial effects that:
1. in the SOFC system oscillation control and optimization method caused by water vapor flow oscillation, model analysis is carried out on water vapor flow oscillation of one important oscillation root in the SOFC system, a fuzzy control algorithm is adopted to carry out control and elimination research on oscillation, a water vapor oscillation model is constructed on the basis of an SOFC independent power generation system in the existing research to simulate oscillation of water vapor flow, frequent discharge experiments on the SOFC system are not needed, and system faults are avoided;
2. in the SOFC system oscillation control and optimization method caused by water vapor flow oscillation, on the basis of the prior experience and thermal platform experiments, a fuzzy controller with a galvanic pile voltage as input and a double-input fuzzy controller with the galvanic pile voltage and the outlet temperature of a tail gas combustion chamber as input are respectively designed, the improvement effect and the control effect of the single/double-input fuzzy controller on the thermoelectric property of the system are obtained through simulation results, the temperature and the voltage in the SOFC system can be controlled in a reasonable range, and the system oscillation is controlled;
3. in the SOFC system oscillation control and optimization method caused by water vapor flow oscillation, a fuzzy control rule and a control strategy are designed aiming at experimental phenomena and prior knowledge, real-time tracking of a set value is realized, and propagation of oscillation in the SOFC system is prevented, so that the performance of the system is optimized, and the method has universal applicability to control and system performance optimization of different power series and different SOFC system oscillation variables.
Drawings
FIG. 1 is a schematic structural diagram of an SOFC independent power generation system in the present invention;
FIG. 2 is a schematic diagram of a stack structure according to the present invention;
FIG. 3 is a schematic diagram of an exemplary electronic computing device according to the present invention;
FIG. 4 is a diagram of a water vapor oscillation model according to the present invention;
FIG. 5 is a sinusoidal perturbation graph in the water vapor oscillation model of the present invention;
FIG. 6 is a graph showing the variation of the water vapor flow rate in the water vapor oscillation model according to the present invention;
FIG. 7 is a graph of the change in the outlet temperature of a reformer of an SOFC system without oscillation in accordance with the present invention;
FIG. 8 is a graph showing the temperature change at the outlet of the SOFC system heat exchanger when oscillation does not occur in the present invention;
FIG. 9 is a graph of inlet temperature change of a SOFC system cell stack without oscillation in accordance with the present invention;
FIG. 10 is a graph of the temperature change at the outlet of the SOFC system stack when oscillation does not occur in the present invention;
FIG. 11 is a graph of the change in temperature at the outlet of the SOFC system tail gas combustor without oscillation according to the present invention;
FIG. 12 is a graph of the voltage change of the SOFC system stack without oscillation in the present invention;
FIG. 13 is a graph of the change in the outlet temperature of the SOFC system reformer when the oscillation amplitude of the steam flow rate is small in the present invention;
FIG. 14 is a graph showing the temperature change at the outlet of the SOFC system heat exchanger when the oscillation amplitude of the water vapor flow is small in the present invention;
FIG. 15 is a graph of the inlet temperature change of the SOFC system cell stack when the oscillation amplitude of the water vapor flow is small in the present invention;
FIG. 16 is a graph showing the change of the SOFC system cell stack outlet temperature when the oscillation amplitude of the water vapor flow is small in the present invention;
FIG. 17 is a graph showing the change in temperature at the outlet of the SOFC system tail gas combustor when the oscillation amplitude of the water vapor flow rate is small in the present invention;
FIG. 18 is a voltage change curve diagram of an SOFC system cell stack when the oscillation amplitude of the water vapor flow is small in the invention;
FIG. 19 is a graph showing the change in the flow rate of water vapor in the present invention;
FIG. 20 is a graph of the change in outlet temperature of a SOFC system reformer with increased oscillation amplitude of the steam flow rate in accordance with the present invention;
FIG. 21 is a graph showing the temperature change at the outlet of the SOFC system heat exchanger when the oscillation amplitude of the water vapor flow rate is increased in the present invention;
FIG. 22 is a graph of the inlet temperature change of the SOFC system cell stack as the oscillation amplitude of the water vapor flow increases in the present invention;
FIG. 23 is a graph of the change in the SOFC system stack outlet temperature as the oscillation amplitude of the water vapor flow increases in the present invention;
FIG. 24 is a graph showing the temperature change at the outlet of the SOFC system tail gas combustor when the oscillation amplitude of the water vapor flow rate is increased in the present invention;
FIG. 25 is a graph of voltage change of a SOFC system stack as the oscillation amplitude of water vapor flow increases in the present invention;
FIG. 26 is a flow chart of the SOFC system oscillation root control and optimization strategy of the present invention;
FIG. 27 is a block diagram of the fuzzy control system of the present invention;
FIG. 28 is a graph of the membership function of voltage in the present invention;
FIG. 29 is a graph of a membership function for the outlet temperature of the tail gas combustor in accordance with the present invention;
FIG. 30 is a graph of a membership function for steam flow according to the present invention;
fig. 31 is a graph comparing the thermoelectric properties of the SOFC system of the present invention without controller versus reformer outlet temperature under single input controller control;
fig. 32 is a graph of thermoelectric properties of an SOFC system of the present invention without a controller versus heat exchanger outlet temperature under single input controller control;
fig. 33 is a graph comparing the thermoelectric properties of the SOFC system of the present invention without controller versus stack inlet temperature under single input controller control;
fig. 34 is a graph comparing the thermoelectric properties of the SOFC system of the present invention without controller versus stack outlet temperature under single input controller control;
figure 35 is a graph of thermoelectric properties of SOFC systems in accordance with the invention without controller versus exhaust gas combustor exit temperature under single input controller control;
fig. 36 is a graph comparing the thermoelectric properties of the SOFC system of the present invention without controller versus stack voltage under single input controller control;
FIG. 37 is a graph comparing reformer outlet temperature under different fuzzy controller control for the thermoelectric properties of the SOFC system of the present invention;
FIG. 38 is a graph comparing the thermoelectric properties of an SOFC system of the present invention with the outlet temperature of the heat exchanger under the control of different fuzzy controllers;
FIG. 39 is a graph comparing the inlet temperature of the cell stack under control of different fuzzy controllers for the thermoelectric properties of the SOFC system of the present invention;
FIG. 40 is a graph comparing the stack outlet temperature under different fuzzy controller control for the thermoelectric properties of the SOFC system of the present invention;
FIG. 41 is a graph comparing the thermoelectric properties of an SOFC system of the present invention with the exit temperature of the tail gas combustor under the control of different fuzzy controllers;
fig. 42 is a graph comparing stack voltages for different fuzzy controller controls for thermoelectric properties of SOFC systems of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1
As shown in fig. 1 to fig. 42, the present embodiment provides a method for controlling and optimizing SOFC system oscillation caused by water vapor flow oscillation, including the following steps:
s1, modeling the SOFC system through steam external reforming to serve as a basic support of a subsequent control and optimization method;
s2, assuming that the irregular oscillation change of the methane flow except the specified input is only subjected to the change of the steam flow, simulating and analyzing the oscillation condition of the steam flow;
s3, introducing an oscillation control algorithm based on fuzzy control, and providing a corresponding control and optimization strategy aiming at the SOFC system oscillation root caused by water vapor oscillation;
and S4, analyzing the optimization effects of the two strategies respectively according to the simulation experiment results of the two fuzzy controllers, and applying the simulation optimization strategy to the real SOFC power generation system according to specific requirements.
In this embodiment, in S1, the specific method for modeling the SOFC system using steam external reforming includes the following steps:
s1.1, constructing a 3kW SOFC independent power generation system consisting of an SOFC electric pile, a reformer subsystem, a heat exchanger subsystem, a fuel supply subsystem, an air supply subsystem, a tail gas combustion chamber subsystem and an electric control unit;
s1.2, aiming at the oscillation phenomenon in the SOFC system, establishing an SOFC system model capable of reflecting the inherent characteristics of the SOFC independent power generation system, and integrating and verifying the system model after modeling is completed.
The construction of the SOFC independent power generation system is the prior art and is a use basis of the method, and the system is constructed according to the working principle of the SOFC, the design requirement of the system process compactness and the limitation of key parts of the system on conditions such as temperature, pressure and the like.
Specifically, as shown in fig. 1, the fuel and the deionized water vapor are mixed and enter the reformer to react, and hydrogen and carbon monoxide are generated. After heat exchange with air at the cathode side in the heat exchanger, the air and the air enter the electric pile together to participate in electrochemical reaction. Thereafter, the unreacted fuel and air and the exhaust gas produced by the electrochemical reaction are combusted in the exhaust gas combustor. The process not only reduces the emission of pollution gas, but also more importantly, the heat energy generated after combustion is further recycled. This heat energy is not only used to preheat the heat exchanger, but the excess heat energy is further used to heat the cold water, thereby increasing the efficiency and fuel efficiency of the system. The system mainly comprises the following components:
(1) the galvanic pile is used as a core component of SOFC system power generation, and needs to be focused, and the galvanic pile used in the method is an anode-supported SOFC cross-flow galvanic pile with an external manifold; in the galvanic pile, the number of the battery pieces is 70, the size is preferably 15cm multiplied by 15cm, and the effective reaction active area is 13cm multiplied by 13 cm; the composite anode of the cell consists of a nickel-yttrium stabilized zirconia (Ni-YSZ) anode support body with the thickness of 1mm and an anode functional layer with the thickness of 10 mu m, wherein the electrolyte material is YSZ, and the cathode material is strontium-doped lanthanum manganite;
(2) for the reformer, the method uses high-temperature waste gas of the tail gas combustion chamber to slowly supply heat, and adopts an independent electric ignition mode to directly provide a heat source; this way, reaction conditions can be rapidly provided for the reforming reaction of methane and water; therefore, the inside of the reformer has reforming reaction and combustion reaction of methane and air;
(3) the tail gas combustion chamber is used for fully combusting gas at the outlet of the electric pile, so that on one hand, environmental pollution is avoided, and on the other hand, heat generated by reaction is a good heat source and is used for supplying heat to the whole system; flame drift and backfire phenomena often occur in the tail gas combustion chamber, and in order to prevent the tail gas combustion chamber from breaking down due to the phenomena, a porous medium is filled in the tail gas combustion chamber;
(4) SOFC systems have two heat exchangers, including a tail gas-air heat exchanger and a reforming-air heat exchanger; the tail gas-air heat exchanger heats cold air by using high-temperature tail gas in the tail gas combustion chamber, and the reforming-air heat exchanger exchanges heat between the reformed gas and the air after the heat exchange of the tail gas-air heat exchanger again so as to reduce the temperature difference between the reformed gas and the air and ensure the requirement of the temperature difference in the galvanic pile;
the system comprises a subsystem, a hot box, a cold zone component, a hot box, a cold box, a hot box, a cold box, a hot box, a cold box and a cold box, wherein the cold box and the cold box are arranged in the hot box; in order to prevent the heat box from carrying out heat transfer with the external environment, the outside of the heat box is wrapped by heat insulation cotton;
(5) for the fuel supply subsystem, the fuel used in the experiment was methane, with a nominal concentration of 99.5%; after the flow of methane from a gas cylinder is regulated by a flowmeter, the methane and water sent by a water pump enter a reformer together for reaction; in long-term operation, the cost of methane is much lower than that of hydrogen, so compared to a hydrogen-fueled SOFC system, a methane-fueled SOFC power generation system has more cost advantages; a pipeline in the fuel supply subsystem is filled with nitrogen which is used as protective gas to blow away combustible gas in the system as soon as possible;
(6) for the air supply subsystem, the required air is sent by an air compressor; in the experimental process, the temperature in the parts such as the galvanic pile, the combustion chamber and the like often fluctuates or suddenly rises, and the traditional SOFC power generation system usually manages and controls the temperature by regulating the flow of fuel or air; however, it is difficult to precisely control both the operating temperature and the space temperature by changing only one of the conditions; therefore, the method adds an air bypass which is directly communicated with the tail gas combustion chamber in the air supply subsystem, controls the temperature in the combustion chamber by controlling the flow of the air bypass, protects system equipment and further improves the control level of the temperature in the electric pile;
(7) in an SOFC power generation system, a proton flow controller is adopted for controlling the gas flow, and can be used for setting the gas flow and acquiring the gas flow in real time; the on-off of the gas pipeline is controlled by installing an electromagnetic valve in front of the proton flow controller, and the pressure value at the inlet of the gas pipeline is monitored by a pressure transmitter.
Specifically, in fig. 1, TC0-TC27 represent temperature information collected by thermocouples at corresponding locations, and the descriptions of the remaining variables are listed in table 1.
TABLE 1 description of the relevant variables in the structural schematic of the SOFC System
Figure 777111DEST_PATH_IMAGE001
In practice, however, there are many variables in SOFC systems, and the table above lists only those that can be directly acquired by the sensors; when the SOFC system becomes unstable due to oscillations, the gas concentration at the exit of the reformer, the stack and the tail gas combustor may deviate from the ideal, but the oscillations do not cause system failure. In fact, unlisted variables (e.g., gas concentrations) have been reflected indirectly by the variables in table 1, such as: key variables in the reforming reaction are methane flow, water flow, and water-to-carbon ratio (S/C). The S/C in the experiment is usually a fixed value and is taken as 2.0, so that the amount of water participating in the reforming reaction can be known through the flow rate of methane; when the S/C and methane flow are determined, the amount of gas involved in the reforming reaction can be determined. Therefore, when the system is not malfunctioning, an unknown variable such as a gas concentration can be calculated from the variables that have been measured. In order to improve the accuracy of arithmetic analysis and reduce the computational burden, the method only lists variables which can be directly measured by the sensor.
Further, in S1.2, the specific method for establishing and integrating the SOFC system model includes the following steps:
s1.2.1, constructing a galvanic pile model: the model of the galvanic pile is subjected to node conversion, namely, the cell can be divided into 5 nodes, and then the ith node is modeled;
s1.2.2, construction of reformer model: the product composition of the reaction in the reformer can be estimated using a dynamic chemical equilibrium approach;
s1.2.3, constructing a tail gas combustion chamber model: mainly considering the wall of the combustion chamber and the high-temperature flue gas inside;
s1.2.4, constructing a heat exchanger model: the heat exchanger is used for heating cold air by adopting high-temperature gas, still adopts a sleeve type structure for simplifying the model, and is also 'nodulated' into 5 nodes by referring to the design idea of the galvanic pile model;
s1.2.5, constructing a fuel and air supply subsystem model: the air supply system takes an air compressor as an air supply source, preferably adopts a blower model, and the fuel supply system adopts a methane gas cylinder as the air supply source;
s1.2.6, system model integration: the system model is integrated according to the physical connection mode in the SOFC system, and parameters in the model such as density, specific heat capacity and the like of an object are initialized in the MATALB.
Specifically, the purpose of constructing the SOFC system model is to: the oscillation phenomenon in the SOFC system needs to be diagnosed and controlled, frequent discharge experiments on the SOFC system can cause the SOFC system to break down, so that the SOFC power generation system cannot work normally, and the oscillation control on the system is not suitable due to the overlong experiment period; therefore, a model capable of reflecting the inherent characteristics of the SOFC independent power generation system is very important, and the model not only can be used as a research foundation for analyzing and optimizing the system and designing an oscillation control algorithm, but also can further optimize the physical structure of the SOFC independent power generation system, so that the model has important significance for modeling the SOFC power generation system.
The SOFC independent power generation system model in the description of the method mainly comprises the following steps: the system comprises a galvanic pile, a reformer, a tail gas combustor, a heat exchanger, a fuel and air supply subsystem. The built model needs to be based on the following assumptions:
to satisfy the ideal gas equation, all the gases in the system need to be idealized; the work of each battery in the electric pile is the same; the system does not have any form of heat transfer with the external environment; the parameter characteristics within the cell are evenly distributed.
Furthermore, when building each subsystem model, some parameters need to be calculated, including:
(1) and (3) electric pile model: as shown in fig. 2, for each node, the interior thereof is composed of a solid layer including a metal connector and a PEN layer, and a gas layer including an air layer and a fuel layer; wherein the voltage equation in each node is as follows:
Figure 694252DEST_PATH_IMAGE002
(1-1)
wherein
Figure 411672DEST_PATH_IMAGE003
In order to be at a nernst voltage,
Figure 806881DEST_PATH_IMAGE004
Figure 621253DEST_PATH_IMAGE005
Figure 381399DEST_PATH_IMAGE006
ohmic losses, activation losses and concentration losses, respectively;
the nernst voltage acquisition formula is as follows:
Figure 648432DEST_PATH_IMAGE007
(1-2)
wherein
Figure 277691DEST_PATH_IMAGE008
Is the value of the standard electric potential,
Figure 946570DEST_PATH_IMAGE009
in order to be the faraday constant,
Figure 877617DEST_PATH_IMAGE010
the gas constant is an ideal gas constant,
Figure 631946DEST_PATH_IMAGE011
is the temperature of the PEN layer(s),
Figure 306641DEST_PATH_IMAGE012
Figure 830027DEST_PATH_IMAGE013
and
Figure 197554DEST_PATH_IMAGE014
partial pressures of oxygen, hydrogen and water, respectively;
the ohmic loss is the voltage drop caused by the internal resistance of the cell plate, and the calculation formula is as follows:
Figure 439179DEST_PATH_IMAGE015
(1-3)
wherein
Figure 150521DEST_PATH_IMAGE016
In order to be the current density,
Figure 793992DEST_PATH_IMAGE017
and
Figure 129159DEST_PATH_IMAGE018
is a constant;
the activation loss is the energy consumed by the ions passing through the electrolyte during the electrochemical reaction, and the calculation formula is as follows:
Figure 795763DEST_PATH_IMAGE019
(1-4)
wherein
Figure 874578DEST_PATH_IMAGE020
In order to take part in the number of electrons in the electrochemical reaction,
Figure 310238DEST_PATH_IMAGE021
is the current density;
the concentration loss is a pressure drop loss caused by the concentration change of the gas on the surface of the electrode, the loss occurs because the fuel cannot be supplied in time, and the calculation formula of the concentration loss is as follows:
Figure 81885DEST_PATH_IMAGE022
(1-5)
wherein
Figure 32524DEST_PATH_IMAGE023
Is the limiting current density;
for heat transfer within each node, which is primarily heat transfer between the metal interconnect of the solid layer, the PEN layer, and the gaseous layer, the metal interconnect temperature calculation is as follows:
Figure 852712DEST_PATH_IMAGE024
(1-6)
wherein
Figure 205196DEST_PATH_IMAGE025
Figure 583963DEST_PATH_IMAGE026
Figure 21897DEST_PATH_IMAGE027
Figure 442514DEST_PATH_IMAGE028
Respectively the density, volume, specific heat capacity and temperature of the metal connector node,
Figure 852767DEST_PATH_IMAGE029
is the value of heat transfer at the inlet of the metal connector;
the PEN layer temperature calculation formula is as follows:
Figure 966216DEST_PATH_IMAGE030
(1-7)
wherein
Figure 829130DEST_PATH_IMAGE031
Figure 53438DEST_PATH_IMAGE032
Figure 52618DEST_PATH_IMAGE033
Figure 336969DEST_PATH_IMAGE034
Respectively the density, volume, specific heat capacity and temperature of the PEN layer node,
Figure 749496DEST_PATH_IMAGE035
for heat generated by PEN layer nodes and other units,
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is the energy generated in the reaction and is,
Figure 395296DEST_PATH_IMAGE037
is the released electrical energy;
the calculation formula of the temperature and the mole fraction of the gas is as follows:
Figure 522652DEST_PATH_IMAGE038
(1-8)
wherein
Figure 422474DEST_PATH_IMAGE039
Figure 988585DEST_PATH_IMAGE040
Figure 227936DEST_PATH_IMAGE041
Figure 588511DEST_PATH_IMAGE042
Figure 913313DEST_PATH_IMAGE043
Respectively the number of moles of gas, the specific heat capacity, the temperature, the inflow and outflow molar rates,
Figure 283114DEST_PATH_IMAGE044
and
Figure 615787DEST_PATH_IMAGE045
the enthalpy of the incoming and outgoing gases respectively,
Figure 412842DEST_PATH_IMAGE046
heat transferred between the gas and the solid;
value of heat transfer between solids
Figure 959361DEST_PATH_IMAGE047
The calculation formula of (a) is as follows:
Figure 132854DEST_PATH_IMAGE048
(1-9)
wherein
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In order to have an effective area for transferring heat,
Figure 49174DEST_PATH_IMAGE050
in order to be the heat transfer coefficient between solids,
Figure 145306DEST_PATH_IMAGE051
and
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is the temperature of the adjacent different solids,
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is the distance between solids;
heat transferred between gas and solid
Figure 234856DEST_PATH_IMAGE054
The calculation formula is as follows:
Figure 818285DEST_PATH_IMAGE055
(1-10)
wherein
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In order to be the area of heat convection,
Figure 990957DEST_PATH_IMAGE057
in order to be a heat transfer coefficient,
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is the temperature of the gas,
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A temperature that is a solid;
for the material flow in the node, the flow rates of the outlet and the inlet of the gaseous layer satisfy the following relationship:
Figure 300213DEST_PATH_IMAGE060
(1-11)
wherein
Figure 405572DEST_PATH_IMAGE061
Figure 886232DEST_PATH_IMAGE062
The flow rates of the outlet and inlet gases respectively,
Figure 614891DEST_PATH_IMAGE063
the amount of species of gas consumed for the electrochemical reaction.
(2) Reformer model: the electrochemical reactions that take place in the reformer are as follows:
Figure 471989DEST_PATH_IMAGE064
(1-12)
Figure 103958DEST_PATH_IMAGE065
(1-13)
Figure 755520DEST_PATH_IMAGE066
(1-14)
wherein, the first two reactions that occur predominantly, the product composition of the reaction in the reformer can be estimated using a dynamic chemical equilibrium approach;
the expression for all possible constituents in the reformer is as follows: the extent of reaction is such that all possible constituents involved in the reforming reaction are available
Figure 800836DEST_PATH_IMAGE067
And
Figure 133728DEST_PATH_IMAGE068
to show that:
Figure 682521DEST_PATH_IMAGE069
(1-15)
wherein n represents the amount of the substance,
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and
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indicating the degree of reaction, and both are greater than 0; the free enthalpy G is therefore calculated as follows:
Figure 174180DEST_PATH_IMAGE070
(1-16)
wherein N is the type number of gases in the product, T is the temperature, gi is the Gibbs free energy of the gas i at the corresponding temperature, and pi is the partial pressure of the gas;
the formula for pi is as follows:
Figure 13697DEST_PATH_IMAGE071
(1-17)
when the chemical reaction reaches equilibrium, it can be calculated by minimizing equation (2-16)
Figure 272640DEST_PATH_IMAGE067
And
Figure 964653DEST_PATH_IMAGE068
(3) tail gas combustion chamber model: the combustion chamber wall temperature calculation formula is as follows:
Figure 701665DEST_PATH_IMAGE072
(1-18)
wherein
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Figure 592577DEST_PATH_IMAGE074
And
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respectively the density, specific heat capacity and temperature of the combustion chamber wall,
Figure 47009DEST_PATH_IMAGE076
heat transferred to the combustion chamber walls;
the molar reaction rate R is calculated for the high temperature gases in the exhaust gas combustion chamber as follows:
Figure 690480DEST_PATH_IMAGE077
(1-19)
(4) model of heat exchanger: the temperature calculation formula of the solid in each node is mainly a pipeline of various gases, the temperature calculation formula refers to the formula (1-6), the gases are mainly high-temperature gas and cold air, and the temperature can be calculated according to the formula (1-8).
(5) Fuel and air supply subsystem model: blower power
Figure 479443DEST_PATH_IMAGE078
The calculation formula of (a) is as follows:
Figure 208365DEST_PATH_IMAGE079
(1-20)
wherein
Figure 287179DEST_PATH_IMAGE080
Figure 722840DEST_PATH_IMAGE081
Respectively are the constant-pressure specific heat capacity and the adiabatic coefficient of air,
Figure 228907DEST_PATH_IMAGE082
Figure 382808DEST_PATH_IMAGE083
Figure 265314DEST_PATH_IMAGE084
Figure 617798DEST_PATH_IMAGE085
respectively the air temperature at the inlet of the blower, the working efficiency and the air pressure at the outlet and the inlet,
Figure 498029DEST_PATH_IMAGE086
is the air molar flow rate;
the fuel supply system adopts a methane gas cylinder as a gas supply source, and the gas supply has certain delay due to the long transport pipeline, and the characteristic is expressed by the following formula:
Figure 935963DEST_PATH_IMAGE087
(1-21)
wherein
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Is a constant of time, and is,
Figure 265368DEST_PATH_IMAGE089
the time of gas delivery delay.
In this embodiment, in S2, the specific method for simulating and analyzing the oscillation condition of the water vapor flow includes the following steps:
s2.1, designing a water vapor oscillation model in Matlab/Simulink to simulate oscillation of water vapor flow, and adding sine wave oscillation to the water vapor flow in the model (as shown in FIG. 4);
s2.2, applying the model to carry out simulation experiment of SOFC system power generation;
s2.3, under the condition that the discharge current of the SOFC system is set to be constant (such as 20A), increasing the amplitude of water vapor flow oscillation in the model to determine the influence degree of the water vapor flow on the thermoelectric property of the system and the uncertainty of the simulated water vapor flow in the actual SOFC system;
and S2.4, increasing the discharge current when the oscillation degree of the steam flow is not changed, and observing temperature curves of an outlet of the reformer, an outlet of the heat exchanger, an inlet of the galvanic pile, an outlet of the galvanic pile and an outlet of the tail gas combustion chamber to analyze factors influencing the change of the discharge current in the power generation process of the SOFC system.
Wherein,
specifically, in 2.1, the amplitude of the sine wave is a small value (frequency is 0.1 Hz) set according to the number of moles of the actual flow rate of the water vapor, and in order to better simulate the actual conditions, such as the interference of noise and other external factors on the water vapor, random disturbance can be added on the basis of the sine wave, specifically:
because the oscillation of the water vapor actually occurs at any time, the simulation time of 15000s or longer can be set, and in the time range of 15000s, the flow of the water vapor is not processed at 7000s before and is always a constant value, namely the oscillation of the water vapor does not occur in the period of time; sinusoidal disturbance is added on the basis of normal steam flow in the period of 7000-15000 s, which represents that the steam oscillates due to incomplete vaporization or sudden boiling and the like in the period of time, as shown in fig. 6.
As shown in fig. 5, the water vapor oscillation situation is only shown for 100s of simulation time, which does not meet the experimental requirements of the method.
In the specific experimental process, methane and steam are key raw materials required by the operation of the SOFC system, and participate in reforming reaction in a reformer, the reaction product and air enter a galvanic pile together to participate in electrochemical reaction, and the gas at the outlet of the galvanic pile finally participates in oxidation reaction in a tail gas combustion chamber to generate heat required by the system; the supply of methane and water vapor therefore plays a crucial role in the thermal, electrical, and gas stability of the system, and when the flow of water vapor oscillates, which in turn causes the methane flow to oscillate, it inevitably causes corresponding changes in the thermoelectric properties of the system.
7-12 and 13-18 are graphs of temperature and voltage at the reformer outlet, heat exchanger outlet, cell stack inlet, cell stack outlet, and tail gas combustor outlet, respectively, without oscillations in the SOFC system and with small amplitude of water vapor flow oscillations; as can be seen from fig. 7-12, the temperature and voltage changes of the subsystems of the SOFC system are very smooth, and no sudden rise or fall occurs in the time trend graph; when the reaction reaches an equilibrium state, the values of the temperature and the voltage in the system tend to be stable and almost unchanged; the variation curves of these variables are consistent with the signal variation actually collected by the sensor during the experiment, which again verifies the accuracy of the model.
Fig. 13-18 show the temperature and voltage variation of the system with a small amplitude of water vapor oscillation. It can be seen from the figure that when the water vapour starts to oscillate at 7000s, the temperature and voltage within the system also start to oscillate to different extents, but the general trend is the same as when no oscillation occurs. If the flow rate of the water vapor is only reduced in a unilateral way, the unreacted methane is increased, and the methane is combusted in the tail gas combustion chamber, so that the internal temperature of the tail gas combustion chamber is increased. The high temperature tail gas will be used to exchange heat with the cold air in the heat exchanger, whereby the temperature of the heat exchanger will also rise. The steam flow is reduced, the hydrogen generated by the reforming reaction is reduced, and the reduction of the hydrogen inevitably leads to the reduction of the voltage of the electric pile. In addition, the reforming reaction is a reversible endothermic reaction, the amount of water vapor is reduced, the reaction absorbs less heat, and the temperature of the electric pile is higher. When the water vapor is increased, the voltage of the electric pile and the temperature of the electric pile are just opposite to the situation that the water vapor is reduced, but the temperature of the tail gas combustion chamber and the temperature of the heat exchanger are consistent with the result obtained by reducing the water vapor. This is because although the methane burned in the combustor is reduced, more hydrogen and carbon monoxide are produced. Hydrogen and carbon monoxide which do not participate in electrochemical reaction in the galvanic pile can be combusted in the tail gas combustion chamber, so that more heat is generated to increase the temperature of the tail gas combustion chamber, and the temperature of the heat exchanger is also higher similarly. But the design of the oscillation model uses sine waves subject to random interference, and the period of the sine waves is short. The steam flow does not only rise or fall over a period of time, but rather exhibits an oscillating tendency, falling very quickly after rising and rising again very quickly after falling. Thus, under the influence of the oscillation of the water vapor flow, the temperature and voltage in the system do not just rise or fall, but float up and down the standard values obtained without oscillation.
The oscillations of the steam are very significant when designing the model, but as can be seen from fig. 13-18, the oscillations of the temperature and voltage at the outlet of the reformer, the outlet of the heat exchanger, the inlet of the cell stack, the outlet of the cell stack, and the outlet of the tail gas combustor are not as severe as the oscillations of the steam flow. Due to the operation principle of the SOFC system and the connectivity of the system, oscillations propagate in the system from the water vapor flow along the SOFC system operating path to the reformer outlet temperature, the heat exchanger outlet temperature, the temperature of the stack inlet and outlet, resulting in the oscillations being gradually damped. Although according to the working flow of the system, the tail gas combustion chamber works after the galvanic pile. However, as can be seen from fig. 17, the outlet temperature of the exhaust gas combustor oscillates significantly more strongly than the inlet and outlet temperatures of the other subsystems. This is because the combustion reaction in the tail gas combustor burns the combustible gas at the outlet of the stack with air, thereby providing the heat required by the system. The water vapor flow oscillations cause fuel flow oscillations, which in turn change the extent of the combustion reaction within the combustion chamber. The combustion reaction is very rapid and violent, and the slight change of the combustible gas required by the reaction has great influence on the combustion reaction. In addition, in the experimental process, the temperature in the tail gas combustion chamber can be increased suddenly due to the fact that fuel is added slightly frequently, so that the automatic protection function of the system is triggered, and the experiment bench is further stopped. The results of the model are contrary to the experimental phenomena, which explains why the oscillation of the exhaust gas combustion chamber outlet temperature is more pronounced. Fig. 18 is a graph of voltage variation, and it can be seen that although the voltage oscillations are not as severe as the tail gas combustor temperature oscillations, floating above and below 0.82V, in an acceptable range, they are also very significant. Therefore, the oscillation of the water vapor flow rate affects the electrical characteristics of the system. Without the measures to control or optimize the system, the system will not discharge well.
In addition, in order to determine the influence degree of the magnitude of the water vapor flow on the thermoelectric characteristics of the system and the uncertainty of the simulated water vapor flow in the actual SOFC system, the amplitude of the water vapor flow oscillation in the model is increased, as shown in fig. 19, and the set flow value is far larger than the actual value of the water vapor flow in the power generation experiment of the SOFC system. As the amplitude of the steam flow oscillations is increased, the oscillations in reformer outlet, heat exchanger outlet, stack inlet, stack outlet temperature become more severe as shown in fig. 20-25. The change of the stack inlet and outlet temperatures is not the change trend of fig. 7-12 and fig. 13-18, and the temperature starts to gradually rise at 13000 s. If the temperature continues to rise, the materials of the stack cannot withstand such high temperatures, resulting in failure of the stack. The temperature oscillations of the exhaust gas combustion chamber become more severe and the exhaust gas combustion chamber can be broken without any measures. The voltage of the electric pile also oscillates more seriously and exceeds the normal voltage range of 0.8-0.83 of the single-chip battery, the output electrical characteristics of the system are seriously influenced, and the load cannot be normally supplied with power.
The curves in fig. 7-12, 13-18 and 20-25 are obtained with the discharge current of the SOFC system set to 20A. When the discharge current is increased and the oscillation degree of the steam flow is unchanged, the temperature curves of the outlet of the reformer, the outlet of the heat exchanger, the inlet of the galvanic pile, the outlet of the galvanic pile and the outlet of the tail gas combustion chamber are all observed to be shifted upwards for some distance, namely the temperatures are all larger, and the voltage change curve is shifted downwards than before. In the power generation process of the SOFC system, the discharge current is continuously changed along with the requirement of a load. If the current is too large, the system will also malfunction due to too high a temperature, ultimately affecting the performance of the system.
Therefore, for the above analysis, in order to extend the lifetime of the SOFC system and obtain good thermoelectric properties, the oscillation of the water vapor flow rate must be controlled and optimized, so as to perfectly explain the advantages of low emission, high efficiency, and long lifetime of the SOFC.
In this embodiment, as shown in fig. 26, in S3, a specific method for providing a corresponding control and optimization strategy for SOFC system oscillation root caused by water vapor oscillation includes the following steps:
s3.1, collecting data of a power generation simulation experiment of the SOFC system, establishing a database, analyzing and diagnosing the oscillation root of the system by adopting a method of combining data driving and a topological model, and positioning the oscillation root of the system;
s3.2, aiming at different system oscillation root causes, designing a corresponding controller to control and optimize oscillation;
s3.3, designing a fuzzy controller: the single-input fuzzy controller with the input of the galvanic pile voltage and the output of the water vapor flow and the double-input fuzzy controller with the input of the galvanic pile voltage and the outlet temperature of the tail gas combustion chamber and the output of the water vapor flow are respectively designed.
Further, in S3.2, for different system oscillation root causes, a specific method for designing a corresponding controller to control and optimize oscillation includes the following steps:
s3.1.1, for the oscillation caused by the poor regulation of the flow controller in the SOFC system, designing a single-loop PID controller, and eliminating the oscillation by adjusting control parameters or using a controller based on a multivariable model;
s3.1.2, for the oscillation caused by the valve static friction, eliminating the oscillation caused by the valve by identifying the viscous valve and maintaining;
s3.1.3, aiming at the oscillation caused by the water vapor flow, a fuzzy control algorithm designed by expert knowledge or experience is used for controlling the flow of the water vapor, the signal acquired by the sensor is subjected to fuzzy quantization processing and then is used as the input of a fuzzy control rule, the output obtained by fuzzy logic reasoning is added to the actuator and acts on the controlled object, and therefore the control of the system is realized, as shown in fig. 27.
Among them, S3.1.3, in the SOFC system, supply of methane and water vapor plays an important role in thermal, electrical, and gas stability of the system. When the steam flow oscillates and consequently the methane flow oscillates, it inevitably results in a large change in the thermoelectric properties of the system. According to the simulation and analysis of the SOFC system oscillation root, when the water vapor flow oscillates, the oscillation degrees of the temperatures of the reformer outlet, the heat exchanger outlet, the galvanic pile inlet and the galvanic pile outlet are gradually decreased along with the working path of the SOFC system, and are far less than the significance of the oscillation of the water vapor flow. Because the system is bulky and the working pipe is long, there is a certain hysteresis of temperature change when the oscillation of the water vapor flow is propagated to the temperature of the tail gas combustion chamber. However, since the combustion reaction takes place in the exhaust gas combustion chamber, this leads to a significantly more severe oscillation of the outlet temperature of the exhaust gas combustion chamber than the inlet and outlet temperatures of the other subsystems. Therefore, the exhaust gas combustor exit temperature is a variable of interest. The oscillations of the voltage are more severe and significant than the oscillations of other temperatures than the outlet temperature of the exhaust gas combustion chamber. When the flow rate of the water vapor slightly fluctuates, the voltage immediately follows the change. This is because in a thermoelectric coupled SOFC system, the response speed of the electrical characteristic is significantly higher than that of the thermal characteristic. Therefore, in order to stably generate power, it is necessary to control the voltage to a state where the voltage does not oscillate sharply as much as possible.
Further, in S3.3, the specific method for designing the fuzzy controller includes the following steps:
s3.2.1, setting input and output domains of the controller, and dividing the input and output domains into 7 levels;
s3.2.2, dividing discourse domain fuzzy subsets and determining membership functions of discourse domains;
s3.2.3, designing fuzzy control rules according to the control strategy, such as adjusting the water quantity introduced according to the following relation between the cell stack voltage and the water vapor flow, and continuously adjusting the control rules according to experience.
Wherein, in S3.2.1, the discourse area of the voltage is set in the range of [0.5,0.9] V, the discourse area of the tail gas combustion chamber is set in the range of [1040,1180] K, and the corresponding flow rate range of the water vapor is [0.01,0.026] mol/s.
Further, fuzzy subsets of stack voltage, exhaust gas combustor exit temperature, water vapor flow are denoted as { l3, l2, l1, ok, h1, l2, l3 }; l1, l2, l3 respectively represent small, medium and large deviations below the ideal value, ok represents the ideal value, h1, h2, h3 respectively represent small, medium and large deviations above the ideal value;
in addition, a membership function is used to describe the membership of a certain element to a certain fuzzy subset on the set. According to practical experience, in the method, the triangular membership functions are selected as the membership functions of the galvanic pile voltage, the outlet temperature of the tail gas combustion chamber and the steam flow, as shown in FIGS. 28-30. Since the stack voltage is affected more when the water vapor flow rate is lower than the ideal value. Therefore, when designing the membership functions for the stack voltages, the values of the fuzzy subsets are not uniform.
Specifically, in S3.2.3, the fuzzy control rules designed according to the control strategy include, but are not limited to:
aiming at the following relationship between the voltage of the galvanic pile and the flow of the water vapor, the fuzzy control rule is as follows: in order to make the oscillation of the stack voltage less obvious, a large amount of water needs to be introduced when the stack voltage is seriously lower than an ideal value, and a small amount of water needs to be introduced when the stack voltage is slightly lower than the ideal value; when the voltage of the electric pile is higher than an ideal value in different degrees, the steam flow of the corresponding degree needs to be reduced; when the voltage of the galvanic pile is at an ideal value, the flow of the water vapor is not changed;
for the tail gas combustion chamber, the fuzzy control rule is as follows: when the steam flow is just fully reacted with methane and the electrochemical reaction in the galvanic pile is sufficient, the outlet temperature of the tail gas combustion chamber is optimal; higher or lower water vapor flow rates, both above and below the desired level, result in higher temperatures in the tail gas combustor; when the flow of the water vapor is low, the temperature in the tail gas combustion chamber is higher than that when the flow of the water vapor is high, and the introduction amount of the water vapor/water is properly increased or reduced according to the required temperature of the tail gas combustion chamber.
Further, table 2 shows the control rules of the designed single input fuzzy controller. Table 3 shows the control rules for the designed dual input fuzzy controller:
TABLE 2 control rules for Single input controllers
Figure 113239DEST_PATH_IMAGE090
TABLE 3 control rules for dual input controllers
Figure 976152DEST_PATH_IMAGE091
In this embodiment, as shown in fig. 31 to fig. 42, in S4, specific contents of analyzing the optimization effects of the two strategies respectively according to the simulation experiment results of the two fuzzy controllers include, but are not limited to:
after the voltage of the galvanic pile is increased to serve as an input fuzzy controller, the oscillation conditions of the temperatures of the outlet of the reformer, the outlet of the heat exchanger, the inlet of the galvanic pile and the outlet of the galvanic pile are obviously reduced, and the system begins to tend to be stable; because the voltage of the electric pile is used as the only input of the controller, the voltage of the electric pile is well controlled, and the electrical characteristics of the system are well improved; however, the disadvantage of selecting only voltage as the input to the controller is that there is still a large oscillation in the temperature in the exhaust gas combustor, and therefore the controller needs to be improved, and the outlet temperature of the exhaust gas combustor is also considered to be added to the input of the fuzzy controller;
compared with a single-input fuzzy controller, after the temperature of the outlet of the combustion chamber is increased to serve as an input double-input fuzzy controller, the oscillation amplitude of the temperature of the outlet of the reformer, the temperature of the outlet of the heat exchanger and the temperature of the inlet and the outlet of the galvanic pile becomes smaller; for the electrical characteristics of the system, the control effect of a double-input controller is not much different from that of a single-input controller; in order to control the root cause of oscillations in the system, a dual-input controller has a greater effect on improving the thermoelectric characteristics of the system than a single-input controller.
First, fig. 31-36 are graphs comparing the temperature of the outlet of the reformer, the outlet of the heat exchanger, the inlet of the cell stack, the outlet of the tail gas combustor and the voltage of the cell stack without the controller and the voltage of the cell stack under the control of the fuzzy controller under the condition that the oscillation amplitude of the steam flow is large. In the figure, the upper curve represents the change of temperature and voltage in the SOFC system without a controller, and the lower curve represents the change of temperature and voltage in the SOFC system after adding the fuzzy controller having the stack voltage as an input. It can be seen that after the fuzzy controller using the cell stack voltage as an input is added, the oscillation conditions of the temperatures of the outlet of the reformer, the outlet of the heat exchanger, the inlet of the cell stack and the outlet of the cell stack are obviously reduced, and the temperature change curve of the inlet and the outlet of the cell stack no longer has a rising trend, which is consistent with the temperature change curve of the inlet and the outlet of the cell stack when oscillation does not occur in fig. 7-12, indicating that the system starts to tend to be stable. The oscillation amplitude of the outlet temperature of the tail gas combustion chamber is also reduced greatly, but compared with the situation when oscillation does not occur, the outlet temperature of the tail gas combustion chamber still has large fluctuation and oscillates in the 1060-1160K temperature interval. Over time, the material ages rapidly, shortening the life of the SOFC system. The stack voltage is well controlled, not only the degree of oscillation is greatly reduced, but also almost in the range of a suitable voltage of 0.8-0.83V. Although temperature is not taken into account as an input to the controller because of the large hysteresis of the thermal characteristics of the system compared to the electrical characteristics, the thermal characteristics within the system are still greatly improved and the system begins to stabilize. This is because the SOFC system is a thermoelectric coupled system, and the thermal and electrical characteristics in the system are not isolated from each other.
Secondly, fig. 37 to 42 are graphs comparing the temperature of the outlet of the reformer, the outlet of the heat exchanger, the inlet of the cell stack, the outlet of the tail gas combustor and the change of the cell stack voltage under the control of different fuzzy controllers under the condition that the oscillation amplitude of the steam flow is large. In the figure, the upper curve represents the change of temperature and voltage in the SOFC system after the fuzzy controller with the stack voltage as input is added, and the lower curve represents the change of temperature and voltage in the SOFC system after the fuzzy controller with the stack voltage and the combustor outlet temperature as input is added. It can be seen from the figure that compared to the single input fuzzy controller, the dual input fuzzy controller with increased combustor exit temperature as input, the exhaust combustor exit temperature is reduced from the original oscillation range of 100K to about 50K, which is much improved. The reason why the oscillation is not controlled completely in the non-oscillation state or is controlled less is that the flow rate of the water vapor is changed after the control by the fuzzy controller. When the influence of the change is transmitted to the tail gas combustion chamber, the tail gas passes through subsystems such as a reformer, a heat exchanger, a galvanic pile, a pipeline and the like layer by layer, and great hysteresis exists. And the combustion reaction occurs in the tail gas combustion chamber, and the reaction is rapid and violent. Therefore, it is difficult to control the temperature in the exhaust gas combustion chamber to be smaller. For the electrical characteristics of the system, the double-input controller and the single-input controller control the voltage of the electric pile in a reasonable range. In conclusion, the dual-input controller has a greater effect of improving the thermoelectric property of the system to control the root cause of the oscillation in the system, and the propagation of the oscillation in the SOFC system is weakened from the root cause of the oscillation, so that the system obtains a better thermoelectric property, the service life of the system is prolonged, and the control and optimization of the system are realized.
As shown in fig. 3, the present embodiment further provides a water vapor oscillation model simulation system and an operating device thereof, where the operating device includes a processor, a memory, and a computer program stored in the memory and operated on the processor.
The processor comprises one or more than one processing core, the processor is connected with the memory through the bus, the memory is used for storing program instructions, and the steps of the SOFC system oscillation control and optimization method caused by the water vapor flow oscillation are realized when the processor executes the program instructions in the memory.
Alternatively, the memory may be implemented by any type or combination of volatile or non-volatile memory devices, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.
In addition, the present invention further provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the steps of the SOFC system oscillation control and optimization method caused by the water vapor flow oscillation.
Optionally, the present invention also provides a computer program product containing instructions which, when run on a computer, cause the computer to perform the steps of the above-described SOFC system oscillation control and optimization method caused by water vapor flow oscillations.
It will be understood by those skilled in the art that the processes for implementing all or part of the steps of the above embodiments may be implemented by hardware, or may be implemented by a program instructing relevant hardware, and the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
The foregoing shows and describes the general principles, broad features, and advantages of the present invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and the above embodiments and descriptions are only preferred embodiments of the present invention and are not intended to limit the present invention, and that various changes and modifications may be made without departing from the spirit and scope of the invention, which fall within the scope of the claimed invention. The scope of the invention is defined by the appended claims and equivalents thereof.

Claims (1)

1. The SOFC system oscillation control and optimization method caused by water vapor flow oscillation is characterized in that: the method comprises the following steps:
s1, modeling the SOFC system through steam external reforming to serve as a basic support of a subsequent control and optimization method;
s2, assuming that the irregular oscillation change of the methane flow except the specified input is only subjected to the change of the steam flow, simulating and analyzing the oscillation condition of the steam flow;
s3, introducing an oscillation control algorithm based on fuzzy control, and providing a corresponding control and optimization strategy aiming at the SOFC system oscillation root caused by water vapor oscillation;
s4, aiming at simulation experiment results of the two fuzzy controllers, respectively analyzing optimization effects of the two strategies, and applying the simulation optimization strategies to a real SOFC power generation system according to specific requirements;
in S1, the specific method for modeling the SOFC system using steam external reforming includes the steps of:
s1.1, constructing a 3kW SOFC independent power generation system consisting of an SOFC electric pile, a reformer subsystem, a heat exchanger subsystem, a fuel supply subsystem, an air supply subsystem, a tail gas combustion chamber subsystem and an electric control unit;
s1.2, aiming at the oscillation phenomenon in the SOFC system, establishing an SOFC system model capable of reflecting the inherent characteristics of the SOFC independent power generation system, and integrating and verifying the system model after modeling is completed;
in S1.2, the specific method for establishing and integrating the SOFC system model includes the following steps:
s1.2.1, constructing a galvanic pile model: the model of the galvanic pile is subjected to node conversion, namely, the cell can be divided into 5 nodes, and then the ith node is modeled;
s1.2.2, construction of reformer model: the product composition of the reaction in the reformer can be estimated using a dynamic chemical equilibrium approach;
s1.2.3, constructing a tail gas combustion chamber model: mainly considering the wall of the combustion chamber and the high-temperature flue gas inside;
s1.2.4, constructing a heat exchanger model: the heat exchanger is used for heating cold air by adopting high-temperature gas, still adopts a sleeve type structure for simplifying the model, and is also 'nodulated' into 5 nodes by referring to the design idea of the galvanic pile model;
s1.2.5, constructing a fuel and air supply subsystem model: the air supply system takes an air compressor as an air supply source, adopts a blower model, and adopts a methane gas cylinder as the air supply source;
s1.2.6, system model integration: integrating the system model according to a physical connection mode in the SOFC system, and initializing the density and specific heat capacity parameters of an object in the MATALB;
in S2, the specific method for simulating and analyzing the oscillation of the water vapor flow includes the following steps:
s2.1, designing a water vapor oscillation model in Matlab/Simulink to simulate oscillation of water vapor flow, and adding sine wave oscillation to the water vapor flow in the model;
s2.2, applying the model to carry out simulation experiment of SOFC system power generation;
s2.3, under the condition that the discharge current of the SOFC system is set to be constant, increasing the amplitude of water vapor flow oscillation in the model to determine the influence degree of the water vapor flow on the thermoelectric property of the system and simulate the uncertainty of the water vapor flow in the actual SOFC system;
s2.4, when the oscillation degree of the water vapor flow is not changed, increasing the discharge current, and observing temperature curves of an outlet of the reformer, an outlet of the heat exchanger, an inlet of the galvanic pile, an outlet of the galvanic pile and an outlet of the tail gas combustion chamber to analyze factors influencing the change of the discharge current in the power generation process of the SOFC system;
in the step S2.1, the amplitude of the sine wave is set to 0.1Hz according to the number of moles of the actual flow rate of the water vapor, and random disturbance is added on the basis of the sine wave, specifically:
because the oscillation of the water vapor actually occurs at any time, the simulation time of 15000s or longer is set, and in the time range of 15000s, the flow of the water vapor is not processed in the first 7000s and is always a constant value, namely the water vapor does not oscillate in the time; adding sinusoidal disturbance on the basis of normal steam flow in the time of 7000-15000 s to represent that the steam oscillates in the time;
in S3, the specific method for providing a corresponding control and optimization strategy for SOFC system oscillation root caused by water vapor oscillation includes the following steps:
s3.1, collecting data of a power generation simulation experiment of the SOFC system, establishing a database, analyzing and diagnosing the oscillation root of the system by adopting a method of combining data driving and a topological model, and positioning the oscillation root of the system;
s3.2, aiming at different system oscillation root causes, designing a corresponding controller to control and optimize oscillation;
s3.3, designing a fuzzy controller: respectively designing a single-input fuzzy controller with the input of the galvanic pile voltage and the output of the single-input fuzzy controller as the water vapor flow, and a double-input fuzzy controller with the input of the galvanic pile voltage and the outlet temperature of the tail gas combustion chamber and the output of the double-input fuzzy controller as the water vapor flow;
in S3.2, for different system oscillation root causes, a specific method for designing a corresponding controller to control and optimize oscillation includes the following steps:
s3.1.1, for the oscillation caused by the poor regulation of the flow controller in the SOFC system, designing a single-loop PID controller, and eliminating the oscillation by adjusting control parameters or using a controller based on a multivariable model;
s3.1.2, for the oscillation caused by the valve static friction, eliminating the oscillation caused by the valve by identifying the viscous valve and maintaining;
s3.1.3, aiming at the oscillation caused by the water vapor flow, controlling the flow of the water vapor by using a fuzzy control algorithm, carrying out fuzzy quantization processing on the signals acquired by the sensor to be used as the input of a fuzzy control rule, and adding the output obtained by fuzzy logic reasoning to an actuator to act on a controlled object, thereby realizing the control of the system;
in S3.3, the specific method for designing the fuzzy controller includes the following steps:
s3.2.1, setting input and output domains of the controller, and dividing the input and output domains into 7 levels;
s3.2.2, dividing discourse domain fuzzy subsets and determining membership functions of discourse domains;
s3.2.3, designing fuzzy control rules according to the control strategy, and continuously adjusting the control rules.
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