CN114725436A - Control method of fuel cell air system - Google Patents
Control method of fuel cell air system Download PDFInfo
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- CN114725436A CN114725436A CN202210560766.XA CN202210560766A CN114725436A CN 114725436 A CN114725436 A CN 114725436A CN 202210560766 A CN202210560766 A CN 202210560766A CN 114725436 A CN114725436 A CN 114725436A
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- fuel cell
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M8/00—Fuel cells; Manufacture thereof
- H01M8/04—Auxiliary arrangements, e.g. for control of pressure or for circulation of fluids
- H01M8/04082—Arrangements for control of reactant parameters, e.g. pressure or concentration
- H01M8/04089—Arrangements for control of reactant parameters, e.g. pressure or concentration of gaseous reactants
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/15—Correlation function computation including computation of convolution operations
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M8/00—Fuel cells; Manufacture thereof
- H01M8/04—Auxiliary arrangements, e.g. for control of pressure or for circulation of fluids
- H01M8/04298—Processes for controlling fuel cells or fuel cell systems
- H01M8/04992—Processes 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
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M8/00—Fuel cells; Manufacture thereof
- H01M8/06—Combination of fuel cells with means for production of reactants or for treatment of residues
- H01M8/0662—Treatment of gaseous reactants or gaseous residues, e.g. cleaning
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- Y—GENERAL 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
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/30—Hydrogen technology
- Y02E60/50—Fuel cells
Abstract
The invention provides a control method of a fuel cell air system, which is different from the traditional control method for constructing a variable load path based on a steady-state point, but takes the optimal economy as a control target in the dynamic variable load process, and solves the optimal economy dynamic variable load path by solving an objective function or a method based on rules, thereby realizing the optimal economy control of the fuel cell air system.
Description
Technical Field
The invention relates to the field of fuel cells, in particular to a control method of a fuel cell air system.
Background
The air exhaust of the fuel cell system is high-pressure gas, and in order to improve the efficiency of the fuel cell system, an air compressor-expander integrated gas compression and energy recovery scheme is usually adopted, but because the existing air compressor-expander is coaxially designed, when the current is low, the air pressure is low, and the recovery efficiency is poor. During the operation of the fuel cell system, the fuel cell system usually includes a steady-state operation point and a dynamic load variation process, and usually, the dynamic load variation process is generally realized by continuously jumping between discrete steady-state operation points, but the efficiency optimization problem of the dynamic load variation process is not fully considered in this control manner.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a control method of a fuel cell air system, which can realize the economic optimization control of a dynamic variable load process.
The fuel cell air system comprises a flow meter, an air compressor, a fuel cell stack, a pressure regulating valve and an expander; the flow meter and the air compressor are arranged on an air inlet pipe of the fuel cell stack, and the pressure regulating valve and the expander are arranged on an air tail pipe of the fuel cell stack; the expansion machine and the air compressor are coaxially arranged, and the recovered energy is utilized to assist the air compressor to work.
The control method provided by the invention comprises the following steps:
s1: receiving target power, and determining the operating parameters of the air system corresponding to the target power as target points;
s2: judging the number of steady-state points between the target power and the current power; if there are more than two steady-state points, executing step S31, if there is only one steady-state point, executing step S41, if there is no steady-state point, executing step S51;
s31: solving and determining an intermediate point with optimal economy through an objective function optimization algorithm or a rule-based method;
s32: the operation parameters of the air system are changed to the middle point and then changed to the target point;
s41: the operation parameters of the air system are changed to a steady-state point closest to the target power and then changed to a target point;
s51: and directly changing the operating parameters of the air system to target points.
Specifically, the steady-state point referred to in step S2 is a plurality of discrete points calibrated in advance by the fuel cell system, for example, a steady-state point is calibrated every 10kW from 10kW to 100kW, and when the steady-state point is reached, the operating parameters of the fuel cell system are kept constant, such as current density or power, air pressure and flow, hydrogen pressure, water temperatures at the outlet and inlet of the stack, water content in the membrane, and the like, and the voltage can be kept stable for a long time.
The objective function optimization algorithm is to construct an objective function by taking energy consumed by an air compressor and an expander as a target and taking controllability of hydrothermal management inside a fuel cell stack as a boundary condition, and solve an optimal solution of the objective function. Specifically, the objective function is:
wherein J is the energy consumed in the time of Δ t = t1-t0, P (t) is the power consumption P of the air compressorACMPPower consumption P of expansion machineTurboAt time t0, the air compressor is at the initial operating point, and at time t1, the air compressor is at the target point. PACMPAnd PTurboCan be determined according to conventional theoretical formulas or empirical formulas, and the invention is not particularly limited in this regard.
The rule-based method specifically means that an intermediate point with optimal economy is determined on an air compressor MAP by a preset geometric method. Preferably, the geometric method is: and drawing a tangent line of the target parameter equal efficiency line and a perpendicular line from the current parameter to the target parameter equal efficiency line, and taking an intersection point of the tangent line and the perpendicular line as a middle point.
Alternatively, the step S41 solves and determines the most economical intermediate point by an objective function optimization algorithm or a rule-based method; then, step S42 is executed: and (4) the operation parameters of the air system are changed to the middle point and then changed to the target point.
Also alternatively, the step S51 solves and determines the most economical intermediate point by an objective function optimization algorithm or a rule-based method; then, step S52 is executed: and (4) the operation parameters of the air system are changed to the middle point and then changed to the target point. It will be appreciated that the alternative enables further optimisation of the efficiency of the dynamic load change process whilst also adding to some extent the complexity of the system control method.
According to the control method provided by the invention, the fuel cell air system takes the optimal economy as a control target in the dynamic variable load process, and the dynamic variable load path with the optimal economy is obtained by solving an objective function or a rule-based method, so that the economic optimization control of the fuel cell air system is realized.
Drawings
The foregoing and other objects, features and advantages of the disclosure will be apparent from the following more particular descriptions of exemplary embodiments of the disclosure as illustrated in the accompanying drawings wherein like reference numbers generally represent like parts throughout the exemplary embodiments of the disclosure.
Fig. 1 shows the basic constitution of a fuel cell air system;
FIG. 2 is a flowchart showing a control method in the embodiment;
fig. 3 shows a dynamic load change path diagram corresponding to the control method in the embodiment.
Description of reference numerals: 1-a flow meter; 2, an air compressor; 3-a dispensing valve; 4-fuel cell stack, 5-pressure regulating valve; 6-expander.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The term "include" and variations thereof as used herein is meant to be inclusive in an open-ended manner, i.e., "including but not limited to". Unless specifically stated otherwise, the term "or" means "and/or". The term "based on" means "based at least in part on". The terms "one example embodiment" and "one embodiment" mean "at least one example embodiment". The term "another embodiment" means "at least one additional embodiment". The terms "first," "second," and the like may refer to different or the same object. Other explicit and implicit definitions are also possible below.
Fig. 1 shows the basic configuration of a fuel cell air system. As shown in fig. 1, the fuel cell air system includes a flow meter 1, an air compressor 2, a distribution valve 3, a fuel cell stack 4, a pressure regulating valve 5, and an expander 6.
The flow meter 1, the air compressor 2 and the distribution valve 3 are arranged on an air inlet pipeline of the fuel cell stack 4 and are used for providing air required by electrochemical reaction for the fuel cell stack 4; the pressure regulating valve 5 and the expander 6 are arranged on an air exhaust pipeline of the fuel cell stack 4, and the expander 6 recovers energy by utilizing high-pressure air exhaust exhausted by the fuel cell stack 4 and is coaxially arranged with the air compressor 2.
In addition to the above components, the fuel cell air system generally further includes components such as an intercooler, a humidifier, a gas-liquid separator, and a temperature sensor, a pressure sensor, and the like, and those skilled in the art can configure the components according to actual needs, which is not described in detail herein.
Fig. 2 shows a specific embodiment of the control method of the present invention. As shown in fig. 2, the control method in this embodiment includes the following steps:
s1: receiving target power, and determining the operating parameters of the air system corresponding to the target power as target points;
s2: judging the number of steady-state points between the target power and the current power; if there are more than two steady-state points, executing step S31, if there is only one steady-state point, executing step S41, if there is no steady-state point, executing step S51;
s31: the method for solving and determining the intermediate point with the optimal economy through a rule-based method specifically comprises the following steps: drawing a tangent line of the equal efficiency line where the target point is located and a perpendicular line from the current parameter to the equal efficiency line where the target point is located, and taking an intersection point of the tangent line and the perpendicular line as a middle point;
s32: the operation parameters of the air system are changed to the middle point and then changed to the target point;
s41: the operation parameters of the air system are changed to a steady-state point closest to the target power and then changed to a target point;
s51: and directly changing the operating parameters of the air system to target points.
Fig. 3 illustrates a specific application scenario as an example. Fig. 3 shows a MAP of the air compressor, where n1, n2, n3 represent equal rotational speed lines, and k1, k2, k3 represent equal efficiency lines. In a specific application scenario, there are 2 steady-state points B between the target power and the current power1、B2A-B is usually performed, as per the control method in the prior art1-B2-a load change path of C. According to the control method provided in the above embodiment, since there are two stable points, step S31 is performed, the intermediate point D is determined by the intersection of the tangent and the perpendicular, and then the load is changed from the current point a to the intermediate point D and then to the target point C in step S32.
Having described embodiments of the present disclosure, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terms used herein were chosen in order to best explain the principles of the embodiments, the practical application, or technical improvements to the techniques in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (7)
1. A control method of a fuel cell air system is characterized in that the fuel cell air system comprises a flow meter, an air compressor, a fuel cell stack, a pressure regulating valve and an expander; the flow meter and the air compressor are arranged on an air inlet pipe of the fuel cell stack, and the pressure regulating valve and the expander are arranged on an air tail pipe of the fuel cell stack; the expansion machine and the air compressor are coaxially arranged, and the recovered energy is utilized to assist the air compressor to work;
the control method comprises the following steps:
s1: receiving target power, and determining the operating parameters of the air system corresponding to the target power as target points;
s2: judging the number of steady-state points between the target power and the current power; if there are more than two steady-state points, executing step S31, if there is only one steady-state point, executing step S41, if there is no steady-state point, executing step S51;
s31: solving and determining an intermediate point with optimal economy through an objective function optimization algorithm or a rule-based method;
s32: the operation parameters of the air system are changed to the middle point and then changed to the target point;
s41: the operation parameters of the air system are changed to a steady-state point closest to the target power and then changed to a target point;
s51: and directly changing the operating parameters of the air system to target points.
2. The control method of the fuel cell air system according to claim 1, wherein the objective function optimization algorithm is to construct an objective function by taking energy consumed by the air compressor and the expander as an objective and taking controllability of hydrothermal management inside the fuel cell stack as a boundary condition, and solve an optimal solution of the objective function.
3. The fuel cell air system control method according to claim 2, wherein the objective function is:
wherein J is the energy consumed in the time of Δ t = t1-t0, P (t) is the power consumption P of the air compressorACMPPower consumption P of expansion machineTurboWherein the air compressor is located at the initial operation point at time t0, and the air compressor is located at the target point at time t 1.
4. The fuel cell air system control method according to claim 1, wherein the rule-based method is to determine an economically optimal intermediate point on an air compressor MAP by a predetermined geometric method.
5. The fuel cell air system control method according to claim 4, characterized in that the geometric method is: and drawing a tangent line of the equal efficiency line where the target point is located and a perpendicular line from the current parameter to the equal efficiency line where the target point is located, and taking the intersection point of the tangent line and the perpendicular line as a middle point.
6. The fuel cell air system control method according to claim 1, wherein the step S41 is to determine an economically optimal intermediate point by solving an objective function optimization algorithm or a rule-based method; then, step S42 is executed: and (4) the operation parameters of the air system are changed to the middle point and then changed to the target point.
7. The fuel cell air system control method according to claim 1, wherein the step S51 is to determine an economically optimal intermediate point by solving an objective function optimization algorithm or a rule-based method; then, step S52 is executed: and (4) the operation parameters of the air system are changed to the middle point and then changed to the target point.
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