WO2023117184A1 - Procédé de surveillance d'un système de pile à combustible - Google Patents

Procédé de surveillance d'un système de pile à combustible Download PDF

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Publication number
WO2023117184A1
WO2023117184A1 PCT/EP2022/079596 EP2022079596W WO2023117184A1 WO 2023117184 A1 WO2023117184 A1 WO 2023117184A1 EP 2022079596 W EP2022079596 W EP 2022079596W WO 2023117184 A1 WO2023117184 A1 WO 2023117184A1
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WO
WIPO (PCT)
Prior art keywords
fuel
fuel cell
cell system
parameter
oxidant
Prior art date
Application number
PCT/EP2022/079596
Other languages
German (de)
English (en)
Inventor
Tobias Alexander Beck
Felix Schaefer
Original Assignee
Robert Bosch Gmbh
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Robert Bosch Gmbh filed Critical Robert Bosch Gmbh
Publication of WO2023117184A1 publication Critical patent/WO2023117184A1/fr

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Classifications

    • 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
    • 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
    • H01M8/04097—Arrangements for control of reactant parameters, e.g. pressure or concentration of gaseous reactants with recycling of the reactants
    • 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
    • H01M8/04313—Processes for controlling fuel cells or fuel cell systems characterised by the detection or assessment of variables; characterised by the detection or assessment of failure or abnormal function
    • H01M8/0432—Temperature; Ambient temperature
    • 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
    • H01M8/04313—Processes for controlling fuel cells or fuel cell systems characterised by the detection or assessment of variables; characterised by the detection or assessment of failure or abnormal function
    • H01M8/0438—Pressure; Ambient pressure; Flow
    • H01M8/04388—Pressure; Ambient pressure; Flow of anode reactants at the inlet or inside the fuel cell
    • 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
    • H01M8/04313—Processes for controlling fuel cells or fuel cell systems characterised by the detection or assessment of variables; characterised by the detection or assessment of failure or abnormal function
    • H01M8/0444—Concentration; Density
    • H01M8/04447—Concentration; Density of anode reactants at the inlet or inside the fuel cell
    • 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
    • H01M8/04313—Processes for controlling fuel cells or fuel cell systems characterised by the detection or assessment of variables; characterised by the detection or assessment of failure or abnormal function
    • H01M8/04537—Electric variables
    • H01M8/04604—Power, energy, capacity or load
    • H01M8/04619—Power, energy, capacity or load of fuel cell stacks
    • 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
    • H01M8/0606—Combination of fuel cells with means for production of reactants or for treatment of residues with means for production of gaseous reactants
    • H01M8/0612—Combination 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
    • H01M8/0618—Reforming processes, e.g. autothermal, partial oxidation or steam reforming

Definitions

  • a method for monitoring a fuel cell system, in particular a solid oxide fuel cell system, has already been proposed, with at least one operating parameter of the fuel cell system being recorded and processed.
  • the invention is based on a method for monitoring a fuel cell system, in particular a solid oxide fuel cell system, with at least operating parameters of the fuel cell system being recorded and processed.
  • the fuel cell system preferably comprises at least one fuel cell unit as a functional unit, which in particular comprises at least one fuel cell, a stack of fuel cells and/or a combination of a plurality of stacks of fuel cells.
  • the fuel cell and/or the fuel cells of the fuel cell unit are/are preferably designed as high-temperature fuel cells.
  • the fuel cell unit is preferably provided to convert a fuel with supply of an oxidant in a conversion process to generate electrical energy.
  • the fuel is preferably in the form of natural gas.
  • the fuel can be used as the main source of energy Hydrocarbon compounds and/or hydrogen as a mixture or as a pure substance and/or ammonia and/or liquid organic hydrogen carriers and/or the like.
  • the oxidant is preferably in the form of ambient air. However, it is also conceivable that the oxidant is in the form of an industrial fluid, preferably with a documented oxygen content.
  • the fuel cell unit preferably comprises at least one fuel electrode, which is preferably provided for direct contact with the fuel during the conversion process.
  • the fuel cell unit preferably comprises at least one oxidant electrode, which is preferably provided for direct contact with the oxidant during the conversion process.
  • the fuel cell unit comprises, for example, at least one molten carbonate fuel cell (MCFC) and/or particularly preferably at least one solid oxide fuel cell (SOFC).
  • MCFC molten carbonate fuel cell
  • SOFC solid oxide fuel cell
  • the fuel cell system preferably comprises at least one further unit which enables and/or supports operation of the fuel cell unit, in particular is intended to handle the fuel and/or the oxidant.
  • “Provided” should preferably be understood to mean specially set up, specially designed and/or specially equipped.
  • the fact that an object is provided for a specific function should preferably be understood to mean that the object fulfills and/or executes this specific function in at least one application and/or operating state.
  • a handling of the fuel and / or the oxidant includes, without being limited to, for example, a supply to the fuel cell unit, a removal of emerging from the fuel cell unit reaction products, temperature control, heat recovery from the reaction products, treatment and / or pre-processing, a Utilization of residual amounts of fuel, which is added to the reaction products, or the like.
  • further functional units include at least one fuel line to the fuel cell unit, at least one oxidant line to the fuel cell unit, at least one discharge line away from the fuel cell unit, at least one fuel feed unit, at least one oxidant feed unit, at least one recirculation feed unit for returning a fuel exiting from the fuel cell unit Fluids, at least one heat exchanger and/or at least one afterburner or the like.
  • the fuel cell system preferably includes at least one computing unit.
  • a "processing unit” is to be understood as a unit with an information input, an information processing and an information output.
  • the arithmetic unit advantageously has at least one processor, a memory, input and output means, further electrical components, an operating program, control routines, control routines and/or calculation routines.
  • the computing unit can preferably be arranged locally together with the units or implemented on an external device, for example a server, which communicates with a local control unit of the fuel cell system.
  • the computing unit preferably determines at least one fuel parameter in at least one method step. In the method step, the computing unit determines and/or characterizes the composition of the fuel as a function of available operating parameters of the fuel cell system.
  • At least one temperature of one of the units of the fuel cell system, the fuel and/or the oxidant, a volume flow of the fuel and/or the oxidant, an electrical current generated by the fuel cell unit or the like is at least recorded by the computing unit of the fuel cell system and preferably regulated.
  • the computing unit preferably queries the available operating parameters from the computing unit of the fuel cell system and/or from sensor elements of the fuel cell system.
  • the computing unit preferably determines the current fuel parameters in real time. “Real time” should be understood to be faster than an average reaction speed of the fuel cell system to a change in one of the operating parameters.
  • the operating parameter of the fuel cell system can, for example, as a volume flow "V Ng ", a volume flow of methane “V NgAsI f CH4 ", a volume flow of the inflowing oxidant "V air in “, an exhaust gas oxidant temperature "t Air tgb In “, a fuel outlet temperature "t An Ou t “, an afterburner exhaust gas temperature “t tgb out”, a fuel conveyor temperature “t Ng Biwr Ou t”, an exhaust gas temperature "t Ofl Fcs Out “, an oxidant extraction temperature Biwr out”, a recirculate temperature "t Ago Achx Out “, an exhaust gas heat exchanger inlet temperature " t Og Airhx In “, an exhaust gas heat exchanger outlet temperature “t Og Atrhx out”, an oxidant heat exchanger inlet temperature “t Air Airhx In ”, an oxidant heat exchanger outlet temperature “t Air Airhx Out ”> a fuel reformer outlet temperature “t Agr Ref
  • the above list is an exemplary list of fuel cell system operating characteristics that may be used to estimate a fuel parameter. Depending on the configuration of the fuel cell system, it is conceivable that further operating parameters of the fuel cell system are recorded and used to estimate a fuel parameter. In particular, it is conceivable that temperatures, pressures, volume flows or electrical outputs of other units of the fuel cell system are used.
  • a “fuel” should be understood to mean a fuel that is supplied to the fuel cell unit to generate electricity.
  • the fuel is preferably in the form of natural gas. In principle, it is also conceivable for the fuel to be in the form of another gas, for example hydrogen, ammonia gas, or another gas that appears sensible to a person skilled in the art.
  • a “fuel parameter” should be understood to mean a parameter that specifies the fuel.
  • the fuel parameter is a characteristic gas mixture parameter of the fuel.
  • a fuel parameter is preferably in the form of a concentration of specific gas components in the fuel.
  • the fuel parameter is preferably in the form of a concentration of an inert gas component of the fuel.
  • the fuel parameter is preferably designed as a CO2 concentration or as an N2 concentration of the fuel.
  • the fuel parameter is in the form of an H2 concentration, CH4 concentration, a C2H6 concentration, a C3H8 concentration, an H2O concentration.
  • the fuel parameter is a concentration of another gas component of a gas present in the fuel.
  • a fuel parameter is designed as a parameter that reflects another property of the fuel.
  • the fuel parameter is designed as an H/C ratio, ie as a ratio of hydrogen to carbon in the fuel.
  • the fuel parameter is designed as a gas coefficient K e _ which indicates a number of electrons potentially available for a reaction in moles per mole of fuel.
  • the fuel parameter is in the form of a heat capacity of the fuel, preferably a specific heat capacity. In principle, it is also conceivable that the fuel parameter is in the form of a density of the natural gas. In principle, it is also conceivable that the fuel parameter is in the form of a calorific value of the fuel, in particular of the natural gas.
  • a fuel parameter is “estimated” should be understood to mean that it is determined as precisely as possible using the available input data, ie the operating parameters of the fuel cell system.
  • a composition of the fuel currently being used can be determined easily during operation of the fuel cell system, without using a corresponding gas sensor. Due to the configuration according to the invention, operation of the fuel cell system can advantageously be monitored with few components. In particular, time-consuming, space-consuming and/or expensive sensor elements, such as in particular gas analysis devices or the like, can be dispensed with.
  • the method can be used on an advantageously large number of, in particular already existing, fuel cell systems, in particular without conversion.
  • the fuel cell system can advantageously be operated efficiently.
  • the computing effort, energy expenditure and/or time expenditure for a simulation and/or calculation of the characteristic system parameter can advantageously be kept small.
  • a “machine learning method” should preferably be understood to mean a computer-implemented, arithmetic method that can be determined, in particular estimated, based on incomplete data that are to be determined, in particular for a current fuel parameter that is to be determined.
  • the machine learning method is preferably designed as a Gaussian process.
  • a machine learning The method should be understood in particular as a computer-implemented method that has a computer architecture that is set up to generate knowledge from experience, in particular to learn from examples and to generalize it.
  • the machine learning method preferably includes at least one self-adaptive algorithm.
  • the machine learning method is designed as a module for multi-layer deep learning (deep learning module), in particular with at least one neural network.
  • deep learning module is to be understood in particular as a multi-layer machine learning module that is set up to independently specify features relevant to learning.
  • the machine learning module is set up to process learning-relevant features specified by a user.
  • the machine learning method is formed by a neural network.
  • a “neural network” is to be understood in particular as a computer architecture that includes artificial neurons networked with one another.
  • the neural network can be designed in particular as a single-layer feedforward network, as a multi-layer feedforward network, as a recurrent network or as another neural network that appears sensible to a person skilled in the art.
  • the machine learning module, in particular the neural network is preferably set up for training in order to process the operating characteristics of the fuel cell system and the fuel parameters.
  • the machine learning module, in particular the neural network is preferably set up to learn a connection with the corresponding fuel parameters of the fuel using the operating parameters .
  • the machine learning module, in particular a neural network, trained using operating parameters of the fuel cell system and the fuel parameters is preferably able to estimate at least one fuel parameter using a plurality of measured operating parameters. As a result, a method for estimating at least one fuel parameter can be designed particularly advantageously.
  • the machine learning method be designed as a Gaussian process.
  • a “Gaussian process” should preferably be understood to mean a computer-implemented, stochastic process. This can the machine learning method for estimating the fuel parameter can be designed in a particularly simple manner.
  • a data record is generated in a learning process step, in which a measured fuel parameter is stored linked to corresponding operating parameters.
  • a “learning process step” should preferably be understood as a process step that takes place before regular operation of the fuel cell device and in which a connection between the operating parameters of the fuel cell system and the fuel parameters is determined by various measurements at different loads, settings and time / age of the fuel cell system and in a data set are saved.
  • the fuel cell system can exhibit a degradation behavior that can preferably be mapped in the modeling.
  • the machine learning method for estimating the fuel parameter can be designed in a particularly simple manner.
  • the fuel parameters are determined from the detected operating parameters of the fuel cell system using the data record generated in the learning method.
  • the machine learning method for estimating the fuel parameter can be designed particularly well.
  • a confidence parameter is determined in the method step, which reflects an accuracy of the estimation of the fuel parameter.
  • a "confidence parameter” should preferably be understood as a parameter that reflects an accuracy of an estimate of the fuel parameter.
  • the confidence parameter is preferably dependent on how accurately a data set of measured operating parameters during operation correlates with the operating parameters measured in the learning method step. If the operating parameters measured in the method step deviate far from the operating parameters stored in a measuring point in the learning method step, the accuracy of the estimated fuel parameter is lower. Deviate from the operating parameters measured in the process step does not deviate or deviates only slightly from the operating parameters stored in a measuring point in the learning method step, the accuracy of the estimated fuel parameter is high. As a result, the accuracy of the estimated fuel parameter can advantageously be determined, and regulation of the fuel cell system can thus advantageously be adapted to possible uncertainties.
  • the operating parameter of the fuel cell system used in the method step is formed in the fuel cell system.
  • An “operating parameter of the fuel cell system in the form of pressure” should preferably be understood to mean a pressure of an operating substance, such as the fuel, the oxidant, the recirculation gas or an exhaust gas, measured on a unit of the fuel cell system.
  • An “operating parameter of the fuel cell system in the form of temperature” should preferably be understood to mean a temperature of an operating substance, such as the fuel, the oxidant, the recirculation gas or an exhaust gas, measured on a unit of the fuel cell system.
  • an “operating parameter of the fuel cell system in the form of a volume flow” should preferably be understood to mean a volume flow of a fuel, such as the fuel, the oxidant, the recirculation gas or an exhaust gas, measured on a unit of the fuel cell system.
  • An “operating parameter of the fuel cell system in the form of electrical power” should preferably be understood to mean a power provided by the fuel cell unit.
  • An “operating parameter of the fuel cell system in the form of a speed” should preferably be understood to mean a speed of a rotating component, for example a turbine, a blower, an ejector or a conveyor in the fuel cell system. As a result, the fuel parameter can be estimated particularly easily using the operating parameters.
  • the fuel parameter determined in the method step is in the form of a concentration of a specific gas fraction in the fuel.
  • a “concentration of a specific gas fraction” should preferably be a CO2 ratio or an N2 ratio in the fuel are understood.
  • the fuel parameter is in the form of an H2 concentration (hydrogen concentration) or a CH4 concentration (methane concentration).
  • the at least one estimated fuel parameter is used to control the fuel cell system.
  • the fuel cell system can be regulated particularly precisely.
  • a fuel cell system with at least one computing unit for carrying out a corresponding method is also proposed.
  • a particularly advantageous fuel cell system in particular a particularly advantageous solid oxide fuel cell system, can be provided.
  • the method according to the invention for a fuel cell system should not be limited to the application and embodiment described above.
  • the method according to the invention and the fuel cell system according to the invention can have a number of individual elements, components and units as well as method steps that differs from a number specified here in order to fulfill a functionality described herein.
  • values lying within the specified limits should also be considered disclosed and can be used as desired.
  • FIG. 1 shows a fuel cell system according to the invention for a method according to the invention
  • FIG. 2 shows a schematic representation of a data set with different measuring points created in a learning method step and a data set with several measuring points created in a validation method step
  • FIG. 3 shows a schematic flow chart of the method according to the invention.
  • FIG. 1 shows a fuel cell system 12.
  • the fuel cell system 12 is designed as a solid oxide fuel cell system.
  • the fuel cell system 12 includes at least one fuel cell unit 14, which includes at least one solid oxide fuel cell, SOFC for short.
  • the fuel cell unit 14 is shown here functionally as a single fuel cell.
  • the fuel cell unit 14 comprises at least one fuel electrode 16.
  • the fuel electrode 16 is designed as an anode of the fuel cell unit 14.
  • the fuel cell unit 14 comprises at least one oxidant electrode 18.
  • the oxidant electrode 18 is designed as a cathode of the fuel cell unit 14.
  • the fuel cell unit 14 comprises an electrolyte 20 arranged between the oxidant electrode 18 and the fuel electrode 16.
  • the fuel cell system 12 preferably comprises at least one fuel line 22 from a fuel supply to the fuel cell unit 14.
  • the fuel line 22 is preferably used to transport a fuel to the at least one fuel electrode 16 intended.
  • the fuel cell system 12 preferably includes at least one fuel delivery unit 24, which is arranged in the fuel line 22, for delivering the fuel to the fuel cell unit 14.
  • the fuel delivery unit 24 is designed as a compressor, a fan, a pump or the like.
  • the fuel cell system 12 preferably includes a reformer 26.
  • the reformer 26 is preferably arranged in the fuel line 22 between the fuel cell unit 14 and the fuel delivery unit 24 .
  • the reformer 26 is provided for generating a reformed fuel upstream of the fuel cell unit 14 .
  • the fuel cell system 12 preferably includes at least one oxidant line 28 from an oxidant supply to the fuel cell unit 14.
  • the oxidant line 28 is preferably provided for transporting an oxidant to the at least one oxidant electrode 18 of the fuel cell unit 14.
  • the fuel cell system 12 includes an oxidant delivery unit 30 which is arranged in the oxidant line 28 which is provided for delivering the oxidant to the oxidant electrode 18 .
  • the oxidant delivery unit 30 is designed as a compressor, a fan, a pump or the like.
  • the fuel cell system 12 preferably includes at least one equalizing heat exchanger 32 which thermally couples the fuel line 22 and the oxidant line 28 .
  • the compensation heat exchanger 32 is preferably arranged in the fuel line 22 between the fuel cell unit 14 and the reformer 26 .
  • the compensation heat exchanger 32 is arranged in the oxidant line 28 between the fuel cell unit 14 and the oxidant delivery unit 30 .
  • the fuel cell system 12 includes at least one fuel discharge line 34 which is connected to the fuel cell unit 14 .
  • the fuel discharge line 34 is connected to the fuel electrode 16 and is intended to discharge the fluid emerging from the fuel electrode 16 .
  • the fuel cell system 12 includes at least one oxidant discharge line 36, which is connected to the fuel cell unit 14, in particular to the oxidant electrode 18, and is provided for discharging the fluid emerging from the oxidant electrode 18.
  • the fuel cell system 12 preferably includes an afterburner 38.
  • the fuel discharge line 34 and the oxidant discharge line 36 preferably lead from the fuel cell unit 14 into the afterburner 38.
  • the fuel cell system 12 preferably includes an exhaust gas line 40, which is provided for discharging an exhaust gas from the afterburner 38.
  • the fuel cell system 12 comprises at least one exhaust gas oxidant heat exchanger 42, which is used to thermally couple the exhaust gas line 40 and the oxidant line 28 is provided.
  • the exhaust gas oxidant heat exchanger 42 is preferably arranged downstream of the afterburner 38 .
  • the exhaust gas oxidant heat exchanger 42 is arranged in the oxidant line 28 between the compensation heat exchanger 32 and the oxidant delivery unit 30 .
  • the fuel cell system 12 comprises at least one exhaust gas fuel heat exchanger 44 which is provided for a thermal coupling of the exhaust gas line 40 and the fuel line 22 .
  • Exhaust gas fuel heat exchanger 44 is preferably arranged downstream of afterburner 38 and upstream of exhaust gas oxidant heat exchanger 42 .
  • Exhaust gas fuel heat exchanger 44 is arranged in fuel line 22 between reformer 26 and fuel delivery unit 24 .
  • the fuel cell system 12 includes a recirculation line 46.
  • the recirculation line 46 leads from the fuel discharge line 34 to the fuel line 22.
  • a feed point 48 of the recirculation line 46 is preferably arranged in the fuel line 22 between the fuel delivery unit 24 and the reformer 26.
  • An extraction point 50 of the recirculation line 46 is preferably arranged in the fuel discharge line 34 between the fuel cell unit 14 and the afterburner 38 .
  • the fuel cell system 12 includes a recirculation delivery unit 52 which is arranged in the recirculation line 46 which is provided for recirculating a portion of the fluid exiting from the fuel electrode 16 .
  • the recirculation delivery unit 52 is preferably designed as a compressor, a fan, a pump or the like.
  • the fuel cell system 12 includes a calorimetric flow meter 54 which is arranged in the fuel line 22 .
  • the calorimetric flow meter 54 is provided to determine a volume flow of fuel that is pumped into the fuel cell system 12 .
  • the fuel cell system 12 includes a further calorimetric flow meter 56, which is arranged in the recirculation line 46, in particular upstream or downstream of the recirculation delivery unit 52.
  • the fuel cell system 12 includes a further calorimetric flow meter 62, which is arranged in the oxidant line 28.
  • the calorimetric flow meter 62 is intended to determine a volume flow of the oxidant that is conveyed into the fuel cell system 12 via the oxidant line 28 becomes.
  • the fuel cell system 12 comprises at least one recirculation fuel heat exchanger 58 which thermally couples the fuel line 22 and the recirculation line 46 .
  • the recirculation fuel heat exchanger 58 is preferably arranged in the fuel line 22 between the fuel delivery unit 24 and the fuel cell unit 14, here upstream or alternatively downstream of the exhaust gas fuel heat exchanger 44.
  • the recirculation fuel heat exchanger 58 is arranged in the recirculation line 46 upstream of the recirculation delivery unit 52 of the fuel cell system 12.
  • the fuel cell system 12 preferably comprises at least one recirculation oxidant heat exchanger 60 which thermally couples the recirculation line 46 and the oxidant line 28 .
  • the recirculation oxidant heat exchanger 60 is preferably arranged in the recirculation line 46 upstream of the recirculation delivery unit 52 .
  • the recirculation oxidant heat exchanger 60 is arranged in the oxidant line 28 between the fuel cell unit 14 and the oxidant delivery unit 30, here upstream of the exhaust gas oxidant heat exchanger 42 or alternatively downstream of the exhaust gas oxidant heat exchanger 42.
  • the recirculation line 46 together with the fuel line 22 and the fuel discharge line 34, forms a line loop in which the fuel cell unit 14, the equalizing heat exchanger 32, the recirculation fuel heat exchanger 58, the recirculation oxidant heat exchanger 60, the exhaust gas fuel heat exchanger 44, the recirculation delivery unit 52 and/or the reformer 26 are arranged are.
  • the fuel delivery unit 24, the oxidant delivery unit 30, the afterburner 38 and/or the exhaust gas oxidant heat exchanger 42 are arranged outside of the line loop.
  • the fuel cell system 12 has additional units, such as additional heat exchangers, conveyor units, or other devices for treating the fuel, the oxidant, the exhaust gas fuel or the exhaust gas oxidant.
  • the other units of the fuel cell system 12 can be integrated in the fuel cell system in a manner known to those skilled in the art in addition to or in part instead of the units described above.
  • the fuel cell system 12 comprises at least one computing unit 64.
  • the computing unit 64 is provided for carrying out a method 10.
  • FIG. 3 shows a schematic representation of a flow chart for the method 10.
  • the method 10 is provided for monitoring the fuel cell system 12.
  • the arithmetic unit 64 is provided to record and process different operating parameters of the fuel cell system 12 .
  • a number of operating parameters of the fuel cell system 12 are recorded and processed.
  • Various operating parameters that are recorded and processed in the method 10 are described below by way of example. In principle, it is also conceivable that not all of the operating parameters described below, or also additional operating parameters, are determined and evaluated in the method 10 according to the invention. In configurations of a fuel cell system 12, which has a different structure than that described above and, for example, has a different number of units, other operating parameters can also be determined and evaluated in the method.
  • a first operating parameter is in the form of a volume flow of the inflowing fuel “V Ng ”.
  • the volume flow “V Ng ” of the fuel in the form of natural gas is determined by the calorimetric flow meter 54 which is arranged in the fuel line 22 .
  • a second operating parameter is designed as a volume flow of the fuel converted into methane "V NgAsI f CHA ".
  • the volume flow of methane " ⁇ NgAsifcHi” is calculated from the measured volume flow "V Ng " of the fuel designed as natural gas.
  • a third operating parameter is in the form of a volume flow of the inflowing oxidant “V air in ”.
  • the volume flow “V air in ” of the oxidant formed as a fish air is determined by the calorimetric flow meter 62 which is arranged in the oxidant line 28 .
  • a fourth operating parameter is an exhaust gas oxidant temperature “t Air tgb In ” of an exhaust gas oxidant at an inlet of the afterburner 38 .
  • the exhaust gas oxidant temperature “t Air tgb In ” is detected by a temperature sensor (not shown) installed at the inlet of the afterburner 38 in the oxidant discharge line 36 .
  • a sensor signal provided by the temperature sensor is recorded and processed by the arithmetic unit 64 .
  • a fifth operating parameter is in the form of a fuel outlet temperature at an outlet of the fuel electrode 16 of the fuel cell unit 14 .
  • the fuel outlet temperature “t An Out t ” is detected by a temperature sensor (not shown) installed at the outlet of the fuel electrode 16 in the fuel discharge line 34 .
  • a sensor signal provided by the temperature sensor is recorded and processed by the computing unit 64 .
  • a sixth operating parameter is in the form of an afterburner exhaust gas temperature “t tgb out ” of an exhaust gas flowing out of the afterburner 38 .
  • the afterburner exhaust gas temperature “t tgb Out ” is detected by a temperature sensor (not shown) installed in the exhaust pipe 40 at the outlet of the afterburner 38 .
  • a sensor signal provided by the temperature sensor is recorded and processed by the arithmetic unit 64 .
  • a seventh operating parameter is in the form of a fuel feeder temperature “tNg Biwr out ” of the fuel at an outlet of fuel feed unit 24 .
  • the fuel feeder temperature “t Ng Biwr Ou t ” is detected by a temperature sensor (not shown) installed in the fuel line 22 at the outlet of the fuel feed unit 24 .
  • a sensor signal provided by the temperature sensor is recorded and processed by the arithmetic unit 64 .
  • An eighth operating parameter is in the form of an exhaust gas temperature “t Og Fcs out ” of the fuel cell system 12 at an outlet of the exhaust gas 40 flowing out of the afterburner 38 .
  • the exhaust gas temperature “t Og Fcs out ” of the fuel cell system 12 is detected by a temperature sensor (not shown) installed at the outlet of the afterburner 38 downstream of the exhaust gas oxidant heat exchanger 42 in the exhaust gas line 40 .
  • a temperature sensor (not shown) installed at the outlet of the afterburner 38 downstream of the exhaust gas oxidant heat exchanger 42 in the exhaust gas line 40 .
  • the sensor signal provided by the temperature sensor is recorded and processed by the arithmetic unit 64 .
  • a ninth operational parameter is as an oxidant delivery temperature
  • t A tr Biwr out" of the oxidant is formed at an output of the oxidant delivery unit 30 .
  • the oxidant delivery temperature “t Air Biwr Ou t ” is detected by a temperature sensor (not shown) installed in the oxidant line 28 at the outlet of the oxidant delivery unit 30 .
  • a sensor signal provided by the temperature sensor is recorded and processed by the arithmetic unit 64 .
  • a tenth operating characteristic is designed as a recirculation temperature “t Ago Achx Out ” of a recirculated fuel at a recirculation outlet of the recirculation oxidant heat exchanger 60 in the recirculation line 46 .
  • the recirculate temperature “t Ago Achx out ” is detected by a temperature sensor (not shown) installed at the recirculate outlet of the recirculation fuel heat exchanger 58 in the recirculation line 46 .
  • a sensor signal provided by the temperature sensor is recorded and processed by the arithmetic unit 64 .
  • An eleventh operating parameter is in the form of an exhaust gas heat exchanger inlet temperature “tog Airhx in ” of an exhaust gas at an exhaust gas inlet of the exhaust gas oxidant heat exchanger 42 in the exhaust pipe 40 .
  • the exhaust gas heat exchanger inlet temperature “t Og A irhx in ” is detected by a temperature sensor (not shown) installed at the exhaust gas inlet of the exhaust gas oxidant heat exchanger 42 in the exhaust pipe 40 .
  • a sensor signal provided by the temperature sensor is recorded and processed by the arithmetic unit 64 .
  • a twelfth operating parameter is in the form of an exhaust gas heat exchanger outlet temperature “t Og Air x out ” of an exhaust gas at an exhaust gas outlet of the exhaust gas oxidant heat exchanger 42 in the exhaust pipe 40 .
  • the exhaust gas heat exchanger inlet temperature "t Og A irhx in” is introduced via an exhaust gas outlet of the exhaust gas oxidant heat exchanger 42 in the exhaust pipe 40, not shown temperature sensor detected.
  • a sensor signal provided by the temperature sensor is recorded and processed by the arithmetic unit 64 .
  • a thirteenth operating parameter is an oxidant heat exchanger inlet temperature “t Air Airhx In ” of an oxidant at an oxidant inlet of the exhaust gas oxidant heat exchanger 42 in the oxidant line 28 .
  • the oxidant heat exchanger inlet temperature “t Air Airhx In ” is detected by a temperature sensor (not shown) installed at the oxidant inlet of the exhaust gas oxidant heat exchanger 42 in the oxidant line 28 .
  • a sensor signal provided by the temperature sensor is recorded and processed by the arithmetic unit 64 .
  • a fourteenth operating parameter is in the form of an oxidant heat exchanger outlet temperature “t Air Airhx Out ” of an oxidant at an oxidant outlet of the exhaust gas oxidant heat exchanger 42 in the oxidant line 28 .
  • the oxidant heat exchanger outlet temperature “t Air Airhx Ou t” is detected by a temperature sensor (not shown) installed in the oxidant line 28 at the oxidant outlet of the exhaust gas oxidant heat exchanger 42 .
  • a sensor signal provided by the temperature sensor is recorded and processed by the arithmetic unit 64 .
  • a fifteenth operating parameter is in the form of a fuel reformer outlet temperature “t Agr Ref Out ” of the fuel at an outlet of the reformer 26 .
  • the fuel reformer outlet temperature “t Agr Ref Out ” is detected by a temperature sensor (not shown) installed in the fuel line 22 at the outlet of the reformer 26 .
  • a sensor signal provided by the temperature sensor is recorded and processed by the arithmetic unit 64 .
  • a sixteenth operating parameter is in the form of an output electrical output power “P stk ” of the fuel cell unit 14 .
  • the electrical output power "P stk " of the fuel cell unit 14 is determined by measuring the output currents and output voltages of the fuel cell unit 14 accordingly. In principle, it is also conceivable that further pressures, temperatures or volume flows are determined and processed in the method as further operating parameters.
  • the computing unit 64 is provided in the method 10 to regulate the fuel cell system 12 .
  • the fuel has a major influence on the operation of the fuel cell system 12 .
  • the fuel is in the form of a gas.
  • the fuel is preferably in the form of natural gas. In principle, it would also be conceivable for the fuel to be formed from another gas that appears sensible to a person skilled in the art.
  • the fuel in the form of natural gas can vary in quality and composition. A composition of the fuel formed as natural gas may fluctuate with time and place. For efficient operation of the fuel cell system 12 and its regulation, it is advantageous to know the composition of the fuel and to regulate the fuel cell system 12 accordingly.
  • the method 10 for monitoring the fuel cell system 12 includes a method step 66 in which at least one current fuel parameter of the fuel is determined.
  • the fuel parameter determined in method step 66 is in the form of a concentration of a specific gas fraction in the fuel.
  • the current fuel parameter is designed as a parameter of the fuel that is present in the combustion engine at the time of determination fabric cell system 12 is implemented.
  • a wide variety of fuel parameters can be determined in method step 66 by means of the method. In the following, the determination of two fuel parameters will be described as an example. A determination of a fuel parameter in the form of a CO2 concentration (carbon dioxide concentration) of the fuel is described as an example. In addition, a fuel parameter in the form of an N2 concentration (nitrogen concentration) is formed as an example.
  • the fuel parameters are configured here, for example, as inert gas components of the fuel designed as natural gas.
  • other fuel parameters such as a concentration of other components of the fuel, in an equivalent method step.
  • H2 concentration hydrogen concentration
  • CH4 concentration methane concentration
  • the current fuel parameters are estimated using several of the operating parameters described above.
  • the operating parameters of fuel cell system 12 are recorded and evaluated.
  • the operating parameters of the fuel cell system 12 used in method step 66 are embodied in the fuel cell system 12 as a pressure, as a volume flow, as a temperature, as an electrical power, as an electrical current, or as a rotational speed.
  • the current fuel parameters, the current N2 concentration in the fuel and the current CO2 concentration in the fuel are estimated from the recorded and evaluated operating parameters.
  • the current fuel parameters ie the current N2 concentration in the fuel and the current CO2 concentration in the fuel, are calculated using the detected operating parameters of the fuel cell system 12 .
  • the computing unit 64 calculates the current fuel parameters in the method step 66 based on the detected operating parameters of the fuel cell system 12 .
  • the calculated fuel parameters are estimates of the actual parameters.
  • all fuel parameters described above are evaluated and calculated to estimate the fuel parameters.
  • the fuel parameters are used to estimate the Volume flow "V Ng ", the volume flow of methane “V NgAs if C H4", the volume flow of the inflowing oxidant "V air in ", the exhaust gas oxidant temperature "t Air tgb In “, the fuel outlet temperature "t An O ut ", the afterburner exhaust gas temperature " t tgb Out is the fuel feeder temperature «t Ng Biwr Ou t ", the exhaust gas temperature "t Og Fcs out “, the oxidant feed temperature »t Air Biwr out “, the recirculation temperature ⁇ o ⁇ out, the exhaust gas heat exchanger inlet temperature "t Og Airhx In the exhaust gas heat exchanger outlet temperature "tog Airhx out
  • the current fuel parameters are estimated by means of a machine learning method using the operating parameters of fuel cell system 12.
  • the machine learning process is computer-implemented and is executed on the computing unit. In principle, it is also conceivable that only one fuel parameter is estimated in method step 66 using the machine learning method.
  • the current fuel parameters are estimated in method step 66 by means of the machine learning method using all of the operating parameters of the fuel cell system 12 described above.
  • the fuel parameters are estimated using the recorded operating parameters using a previously created data set.
  • the previously created dataset contains information about a relationship between the fuel parameters to be estimated and the recorded operating parameters of the fuel cell system.
  • the fuel parameters are estimated in method step 66 by comparison with the data set, in particular by a relationship stored in the data set between the operating parameters of the fuel cell system 12 and the fuel parameters.
  • the machine learning method is designed as a Gaussian process.
  • the machine learning method designed as a Gaussian process is computer-implemented and is executed in method step 66 on computing unit 64 .
  • the machine learning method, which is designed as a Gaussian process is intended to use a stored data set, in which relationships between the operating parameters of the fuel cell system 12 and the fuel parameters are stored, to determine the fuel parameters from recorded operating parameters, in particular to estimate them, and in doing so a probability of accuracy of the determined fuel parameters.
  • a learning method step 68 precedes the estimation of the fuel parameters by means of the operating parameters in the machine learning method designed as a Gaussian process.
  • a data record is generated in which the corresponding operating parameters are measured in different operating states of the fuel cell system 12, with known fuel parameters of the fuel used, and linked to the corresponding fuel parameters in the data record.
  • a composition of the fuel preferably natural gas
  • ie the fuel parameters of the fuel is measured by means of a gas measuring sensor, in particular by means of a gas chromatograph, and recorded and processed by the computing unit 64 .
  • several measuring points are stored for the data set, at which the fuel cell system 12 is operated differently.
  • the learning process step 68 several measuring points with different operating parameters of the fuel cell system 12 and/or different fuel parameters are stored for the data set. For this purpose, different output powers “P stk ” of the fuel cell unit 14, different pressures at different points of the fuel cell system 12, different temperatures and/or different compositions of the fuel, ie different fuel parameters, are used for the different measuring points. A number N of measuring points are recorded to create the data record. A number N of measurement points taken in the learning process step 68 to create the data set is preferably greater than 25.
  • the number N of measuring points that are made in the learning method step 68 to generate the data set is preferably greater than 50, particularly preferably greater than 100 and in a particularly advantageous embodiment of the learning method step 68 greater than 200
  • Learning method step 68 determined data set with a variety of measurement points is stored on the computing unit.
  • the learning process step 68 can be performed on the assembled fuel cell system 12 for which the process step 66 for estimating the fuel parameters is performed.
  • the learning method step 68 is carried out on a fuel cell system of identical construction and the data set is transmitted to the computing unit 64 of the fuel cell system 12 .
  • method step 66 the current fuel parameters are determined from the detected operating parameters of fuel cell system 12 using the data record generated in learning method step 68 .
  • Method step 66 is carried out during control operation of fuel cell system 12 .
  • Method step 66, in which the current fuel parameters are determined can be carried out continuously during the regular operation of the fuel cell system 12. In principle, it is also conceivable that method step 66 for estimating the fuel parameters is carried out repeatedly at defined time intervals.
  • all of the above-mentioned operating parameters of fuel cell system 12, which for reasons of clarity are not all to be listed again here, are recorded and processed with the data record generated in learning method step 68. The recorded operating parameters are compared with the operating parameters stored in the data record and the fuel parameters linked to the operating parameters in the data record are estimated for the fuel currently converted into electricity in the fuel cell system 12 .
  • a confidence parameter is determined.
  • the confidence parameter gives an accuracy of the estimate of the in the method step 66 estimated fuel parameters.
  • the confidence parameter is determined on the basis of a correlation of the operating parameters stored in the measuring points in learning method step 68 with the operating parameters measured during method step 66 . The more closely the operating parameters measured in the method correlate with the operating parameters stored in a measuring point in the data set, the greater the confidence parameter and the more accurate the estimation of the corresponding fuel parameters.
  • FIG. 2 shows schematically a plot 72 of a data set determined in the learning method step with various measuring points 74 for estimating a fuel parameter designed as a CO2 concentration.
  • the respective operating parameters of the fuel cell system 12 are stored for each of the measuring points 74 shown. All of the recorded operating parameters of the fuel cell system 12 are stored for each of the measurement points 74 .
  • the CO2 concentrations of the fuel are plotted on the Y-axis of the plot.
  • the number of measuring points is plotted on the X-axis of the plot 72 .
  • a plot 76 of a data set determined in a validation method step 70 is shown on the right-hand side of FIG.
  • Measuring points 78 determined by the machine learning method in validation method step 70 are plotted on plot 76 with the corresponding determined operating parameters of the fuel cell system. Furthermore, values for the fuel parameters measured by means of a corresponding gas sensor are entered in the plot 76 for the validation method step 70 . It can be seen here that the fuel parameters estimated using the method are close to the fuel parameters actually measured.
  • the validation method step 70 can preferably be used to adapt the data set determined in the learning method step. In this way, an accuracy of the estimates of the fuel parameters can be improved.
  • the estimated fuel parameters are used to control the fuel cell system 12 .
  • the fuel cell system can be controlled more precisely using the estimated current fuel parameters.
  • a Buffers for safety-relevant control variables such as a gas utilization factor FU, are kept as small as possible.
  • a machine learning method designed as a Gaussian process can be used to estimate the two fuel parameters, ie the CO2 concentration and the N2 concentration in the fuel gas.
  • a separate machine learning method designed as a Gaussian process is carried out for each estimate of one of the two operating parameters.
  • a Gaussian process instead of a Gaussian process, another machine learning method can also be used, such as an artificial neural network.
  • an artificial neural network As a result, particularly fast, accurate and low-computing power estimation of the fuel parameters can be achieved, preferably given a large number of input variables, that is to say operating parameters of the fuel cell system 12 used for the estimation.
  • other machine learning methods are also conceivable.
  • a machine learning method with a convolutional approach can also be used.
  • a convolutional Gaussian process as well as a convolutional neural network are conceivable. In such a convolutional machine learning method, the history of measured operating parameters of the fuel cell system and the fuel parameters are included in the estimation of the current fuel parameter. In this way, in particular, the accuracy of the estimation can be improved, and the computing effort of the computing process can be reduced, as a result of which efficiency can be improved.
  • the fuel cell systems 12 and also the method 10 for estimating the fuel parameters can be calibrated against one another.

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Abstract

L'invention concerne un procédé de surveillance d'un système de pile à combustible (12), en particulier d'un système de pile à combustible à oxyde solide, selon lequel au moins des paramètres de fonctionnement du système de pile à combustible (12) sont détectés et traités. Selon l'invention, au moins un paramètre de combustible instantané est estimé lors d'au moins une étape de procédé (66) sur la base de paramètres de fonctionnement du système de pile à combustible (12).
PCT/EP2022/079596 2021-12-21 2022-10-24 Procédé de surveillance d'un système de pile à combustible WO2023117184A1 (fr)

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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20060134478A1 (en) * 2003-05-21 2006-06-22 Nissan Motor Co., Ltd. Fuel cell system
DE112008000843T5 (de) * 2007-05-25 2010-02-25 Toyota Jidosha Kabushiki Kaisha, Toyota-shi Brennstoffzellensystem und Brennstoffzellensystemsteuerverfahren
DE102011108101A1 (de) * 2010-07-27 2012-04-05 Gm Global Technology Operations Llc (N.D.Ges.D. Staates Delaware) Diagnose und Beseitigung eines geringen Anodenwasserstoffpartialdruckes in einem PEM-Brennstoffzellensystem
DE102012105327A1 (de) * 2011-08-09 2013-02-14 General Motors Llc Verfahren zur Korrektur von Permeationsunsicherheiten unter Verwendung eines Konzentrationssensors
DE102016117234A1 (de) * 2015-09-23 2017-03-23 GM Global Technology Operations LLC Validierung und korrektur der schätzung der h2-konzentration an der gen 2 anode

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102020202881A1 (de) 2020-03-06 2021-09-09 Robert Bosch Gesellschaft mit beschränkter Haftung Verfahren zu einer Betriebsüberwachung zumindest einer Brennstoffzellenvorrichtung und Brennstoffzellenvorrichtung

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20060134478A1 (en) * 2003-05-21 2006-06-22 Nissan Motor Co., Ltd. Fuel cell system
DE112008000843T5 (de) * 2007-05-25 2010-02-25 Toyota Jidosha Kabushiki Kaisha, Toyota-shi Brennstoffzellensystem und Brennstoffzellensystemsteuerverfahren
DE102011108101A1 (de) * 2010-07-27 2012-04-05 Gm Global Technology Operations Llc (N.D.Ges.D. Staates Delaware) Diagnose und Beseitigung eines geringen Anodenwasserstoffpartialdruckes in einem PEM-Brennstoffzellensystem
DE102012105327A1 (de) * 2011-08-09 2013-02-14 General Motors Llc Verfahren zur Korrektur von Permeationsunsicherheiten unter Verwendung eines Konzentrationssensors
DE102016117234A1 (de) * 2015-09-23 2017-03-23 GM Global Technology Operations LLC Validierung und korrektur der schätzung der h2-konzentration an der gen 2 anode

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