Method and control device for operating a vehicle with a fuel cell device and vehicle

Abstract

The invention relates to a method (300) for operating a vehicle with a fuel cell device. The method (300) comprises a determination step (305) and a variation step (310). In the determination step (305), boundary conditions present during current vehicle operation are determined. In the variation step (310), control variables for operating the fuel cell device (100) are varied using optimization targets in order to establish an optimal operating point for the fuel cell device (100) given the determined boundary conditions.

Description

State of the art

[0001] The invention relates to a method and a control device for operating a vehicle with a fuel cell device, as well as to a vehicle according to the preamble of the independent claims. The present invention also relates to a computer program.

[0002] Hydrogen-based PEM fuel cells are considered a mobility concept of the future, as they only emit water as exhaust gas and allow for fast refueling times. Disclosure of the invention

[0003] Against this background, the approach presented here comprises a method for operating a vehicle with a fuel cell device, a control device that uses this method, a vehicle, and finally a corresponding computer program according to the main claims. Advantageous further developments and improvements of the device specified in the independent claim are possible through the measures listed in the dependent claims.

[0004] The advantages achievable with the approach presented here consist in particular of creating a method that enables reliable and safe operation of a vehicle with a fuel cell device.

[0005] A method for operating a vehicle with a fuel cell device is presented, comprising a determination step and a variation step. In the determination step, boundary conditions present during current vehicle operation are identified. In the variation step, control variables for operating the fuel cell device are varied using optimization objectives to establish an optimal operating point for the fuel cell device given the identified boundary conditions.

[0006] The vehicle can be a passenger car or a truck. It can be equipped with a fuel cell to generate the electrical energy required for propulsion. To operate the fuel cell optimally, it is advantageous to continuously adjust its operating point to reflect current boundary conditions that influence its operation. For optimal operation, enabling efficient and dynamic power delivery while achieving the desired fuel cell lifespan, a variety of control variables, such as operating pressure, can be set within the system. Typically, optimal operating points for the fuel cell are defined during development and stored in a control unit using control logic and characteristic maps.However, the optimal operating conditions can shift depending on boundary conditions, such as ambient pressure. The approach presented here can, with minimal development effort, consider a combination of numerous relevant environmental conditions and control variables, enabling the identification of an optimal combination of control objectives and thus an optimal operating point for each combination of boundary conditions. This approach can therefore effectively model the full complexity of the fuel cell device. The vehicle's fuel cell device, also referred to as a fuel cell system, includes, for example, a fuel cell stack. Existing fuel cell designs can be used for this purpose. Boundary conditions can include ambient pressure, ambient temperature, and / or ambient humidity.Additionally or alternatively, the boundary conditions can be a membrane state of the fuel cell stack, a coating state of the fuel cell stack, and / or the electrochemically active surface area (ECSA) of the fuel cell stack. This determination step can be repeated to continuously ascertain the current boundary conditions during vehicle operation.The controlled variables can be various parameters of the fuel cell device, such as electrical current, coolant temperature, coolant flow rate, pressure, and stoichiometry on the anode and cathode sides; an EGR rate if exhaust gas recirculation (EGR) is installed (i.e., partial reinjection of cathode exhaust gas into the cathode intake air path); humidification if, for example, a membrane humidifier with a bypass is installed; and a purge rate and purge duration on the anode side. The optimization objectives can include system efficiency, lifetime, and / or power dynamics. The approach presented here allows for the establishment of an optimal operating point for the fuel cell device, given the determined boundary conditions.

[0007] The process can include a step of providing information about the optimal operating point for the determined boundary conditions. This information can be provided to an interface with at least one other vehicle. Additionally or alternatively, the information can be provided to an external device, which both the vehicle and the other vehicle can access. The other vehicle can retrieve the information from the external device and, using the vehicle's optimal operating point, determine an optimal operating point applicable to itself. The vehicles can thus exchange their optimal operating points and optimally adjust their own vehicle operation.

[0008] The process can include a step of reading information about a further optimal operating point that applies to additional boundary conditions. This information can be read via an interface to another vehicle, where the additional boundary conditions were present during operation of that vehicle. These additional boundary conditions might have been present, for example, during current or previous operation of the other vehicle. With this reading step, the vehicle can then read the optimal operating point of the other vehicle.

[0009] In the variation step, the controlled variables can be varied using information about the other optimal operating point. Using the optimal operating point of the other vehicle, the optimal operation of the vehicle can be adjusted. In this way, for example, the vehicle itself can use data obtained from another vehicle using the procedure described here.

[0010] The procedure can include a step of weighting the optimization objectives. This allows, for example, consideration of changes in the optimization objectives over the lifetime of the fuel cell device.

[0011] In the variation step, the controlled variables can be varied within predefined operating limits. These predefined operating limits can be, for example, the operating limits of a fuel cell stack, a compressor, and / or a turbine within the fuel cell system. For the fuel cell stack, these limits might include minimum moisture content (membrane aging), minimum flow rate (droplet discharge), and / or minimum partial pressure of the reactants (gas supply). For the compressor, these limits might include the surge line (stable operation), maximum speed, and / or maximum temperature. For the turbine, these limits might include the suction line (maximum flow rate), maximum speed, and maximum temperature.

[0012] This process can be implemented, for example, in software or hardware, or in a hybrid form of software and hardware, for example in a control unit.

[0013] The approach presented here further creates a control device designed to execute, control, or implement the steps of a variant of the method presented here in corresponding facilities. This embodiment of the invention, in the form of a control device, also allows the problem underlying the invention to be solved quickly and efficiently.

[0014] For this purpose, the control device can have at least one processing unit for processing signals or data, at least one storage unit for storing signals or data, at least one interface to a sensor or actuator for reading sensor signals from the sensor or for outputting data or control signals to the actuator, and / or at least one communication interface for reading or outputting data embedded in a communication protocol. The processing unit can be, for example, a signal processor, a microcontroller, or the like, and the storage unit can be flash memory or a magnetic storage device.The communication interface can be configured to read or output data wirelessly and / or via wired connections, whereby a communication interface that can read or output wired data can, for example, read this data electrically or optically from or output it into a corresponding data transmission line.

[0015] In this context, a control device can be understood as an electrical device that processes sensor signals and outputs control and / or data signals accordingly. The control device can have an interface, which may be implemented in hardware and / or software. In the case of a hardware-based interface, the interfaces can, for example, be part of a so-called system ASIC, which incorporates various functions of the control device. However, it is also possible that the interfaces are separate integrated circuits or at least partially comprised of discrete components. In the case of a software-based interface, the interfaces can be software modules, which, for example, are located on a microcontroller alongside other software modules.

[0016] A vehicle comprises an embodiment of a control device mentioned herein and a fuel cell device.

[0017] Also advantageous is a computer program product or computer program with program code that can be stored on a machine-readable carrier or storage medium such as a semiconductor memory, a hard disk memory or an optical memory and is used to carry out, implement and / or control the steps of the method according to one of the embodiments described above, in particular if the program product or program is executed on a computer or device.

[0018] Examples of the approach presented here are shown in the drawings and explained in more detail in the following description. It shows: Fig. 1 a schematic representation of an embodiment of a fuel cell device; Fig. 2 a schematic representation of a fleet operation to illustrate an exemplary embodiment of a method for operating a vehicle; Fig. 3 a flowchart of an embodiment of a method for operating a vehicle with a fuel cell device; and Fig. 4 A block diagram of an exemplary embodiment of a control device for operating a vehicle.

[0019] In the following description of favorable embodiments of the present invention, the same or similar reference numerals are used for the elements shown in the various figures and acting similarly, without repeating these elements.

[0020] Fig. Figure 1 shows a schematic representation of an embodiment of a fuel cell device 100. The fuel cell device 100 is arranged in a vehicle 105 only as an example.

[0021] The vehicle 105 includes, in addition to the fuel cell device 100, a control device 108 for operating the vehicle with the fuel cell device 100. Optionally, the control device 108 is a component of the fuel cell device 100.

[0022] The fuel cell device 100 comprises at least one fuel cell 110. Fuel, in particular hydrogen, is supplied to an anode 112 of the fuel cell 110 via an anode line 114, while cathode air, in particular filtered ambient air, is supplied to a cathode 116 of the fuel cell 110 via a cathode line 118. An electrochemical reaction of hydrogen with atmospheric oxygen takes place in the fuel cell 110. Hydrogen ions are transported through a membrane 120. The illustration of only one fuel cell 110 is purely exemplary and is intended only to facilitate a simpler understanding of the approach presented here, whereby the fuel cell stack can comprise several fuel cells 110 connected in series.

[0023] The cathode line 118 has, for example, an air filter 122 at its inlet to filter the ambient air according to the requirements of the fuel cell 110. A compressor 124, for example in the form of a vacuum, ensures that sufficient air reaches the cathode 116 of the fuel cell 110. A heat exchanger 126 is provided to cool the compressed air, or cathode air, to a suitable temperature after it has passed through the compressor 124.

[0024] A suitable pressure in the cathode line 118 can be set using a valve 128, e.g. in the form of a throttle valve, and a valve 130, e.g. in the form of a throttle valve, at the outlet of the cathode line 118.

[0025] The anode line 114 includes a fuel or hydrogen tank 132, which has a shut-off valve 134 for switching off the fuel supply, e.g., in the event of a fault, and a pressure regulator 136 for setting a suitable pressure in the anode line 114. An additional heat exchanger 138 is arranged between the shut-off valve 134 and the pressure regulator, but this is only an example.

[0026] Unused fuel can be mixed with fresh fuel using a recirculation pump 140, e.g. in the form of a jet pump.

[0027] A purge valve 142, e.g. in the form of a switching or proportional valve, ensures the regulation of the hydrogen content in the anode line 114.

[0028] The electrical power is supplied via a control unit 144 to an electrical system, e.g., in the vehicle 105, with an inverter 146, an electric motor 148, and a drive transmission 150. The electrical system can also include one or more low-voltage (LV) batteries 152 and a traction battery 154. The traction battery 154 supplies energy to the electric motor 148. The LV battery 152 supplies the LV consumers in the vehicle 105's electrical system.

[0029] The heat generated during the operation of the fuel cell 110 is dissipated via a cooling line 156, which has a specific low electrical conductivity. The cooling line 156 includes a cooler 158 and a recirculation pump 160 to absorb and remove the excess heat generated during the operation of the fuel cell 110. During startup, the cooling line 156 can be used to heat the fuel cell 110 to a suitable operating temperature.

[0030] With the help of the cooling line 156, the fuel cell 110 can be connected to the electrical on-board network of the vehicle 105 via a first protection circuit 162 and a second protection circuit 164 with a pre-charge switch and, if necessary, a pre-charge resistor.

[0031] According to one embodiment, the fuel cell device 100 comprises an electrical system 170, a hydrogen system 172, an air system 174 and a thermal system 176, the piping systems of which are Fig. 1 are represented by different dashed lines.

[0032] During operation of the vehicle 105 and thus the fuel cell device 100, boundary conditions that influence the operation of the fuel cell device 100 typically change constantly. For example, the ambient pressure or ambient temperature can change. By appropriately adjusting the control variables used to regulate the operation of the fuel cell device 100, a suitable optimal operating point can be found for a changed combination of boundary conditions. According to the approach described here, a method is used in which, according to one embodiment, the currently prevailing boundary conditions are first recorded, and then the control variables are varied using optimization objectives until an operating point of the fuel cell device adapted to the determined boundary conditions is found.According to one embodiment, at least some of the steps of the method are carried out using devices of the control device 108.

[0033] According to one embodiment, the boundary conditions, i.e., values ​​representing the boundary conditions, are detected using suitable sensor devices of the vehicle 105 and / or read out from a control unit of the vehicle 105.

[0034] Fig. Figure 2 shows a schematic representation of a fleet operation 200 to illustrate an embodiment of a method for operating a vehicle 105. The fleet operation 200 comprises, by way of example, only three vehicles 105, 205, 210. The vehicles 105, 205, 210 each have a fuel cell device, as exemplified by the following: Fig. 1 is described.

[0035] Block 220 represents the definition of operating limits for the fuel cell devices of vehicles 105, 205, 210 in development 215. Operating limits defined in this way can apply to all vehicles 105, 205, 210.

[0036] Vehicle 105 is designed to determine an operating point optimized for the current boundary conditions for operating the vehicle's fuel cell device, using currently existing boundary conditions, optionally the defined operating limits and optimization goals, and optionally also to provide this to the other vehicles 205, 210.

[0037] The blocks provided for this purpose according to an exemplary embodiment are described below using vehicle 105 as an example.

[0038] A block 225 in the vehicle 105 represents a weighting of optimization goals, and a block 230 represents a variation of boundary conditions. The optimization goals specify, for example, in which respect the operation of the fuel cell device is to be optimized. Possible optimization goals include, for example, low fuel consumption, high output power, high power dynamics, or a long service life. The boundary conditions typically vary over time. For example, the ambient pressure changes when the vehicle 105 is traveling in mountainous terrain. The temperature, for example, changes throughout the day. The currently prevailing boundary conditions are determined, by way of example, via a sensor device 232. A current combination of boundary conditions is provided by block 230 according to an exemplary embodiment.

[0039] Using a suitable methodology 235, for example an AI methodology based on artificial intelligence, the information from blocks 220, 225, 230 is processed to find an optimal operating point for the current boundary conditions.

[0040] For example, methodology 235 includes a block 240 and a block 245. According to an exemplary embodiment, the information provided by blocks 220, 225, and 230 is used in block 240 to vary control variables of the fuel cell device. By considering the operating limits provided by block 220, it is possible to prevent the control variables from being varied into an impermissible range. Using the control variables varied by block 240, an optimal operating point for the current boundary conditions is found in block 245.

[0041] According to one embodiment, the optimal operating point found for the current boundary conditions and the current optimization goals is used within the vehicle 100 to operate the fuel cell device.

[0042] Optionally, the determined optimal operating point is subsequently output to a block 250. Block 250 represents, for example, an external device that vehicles 105, 205, and 210 can access to exchange their respective optimal operating points for different boundary conditions and optimization goals.

[0043] Vehicles 205 and 210 determine their respective optimal operating point in the same way as vehicle 105.

[0044] Vehicle 105 outputs the optimal operating point according to an exemplary embodiment to block 250 and receives from block 250 the optimal operating points found by vehicles 205, 210 for the boundary conditions prevailing at vehicles 205, 210, which may differ from the boundary conditions prevailing for vehicle 105.

[0045] According to one embodiment, the approach presented here varies the control objectives during operation instead of using fixed operating points. This variation makes it possible to find an optimal combination with regard to various optimization goals, such as efficiency, service life, and dynamics, depending on a multitude of changing boundary conditions, such as ambient pressure, ambient temperature, ambient humidity, stack condition, and operating history. By using large datasets from fleet operation in combination with AI methods, an improvement in terms of optimization goals is achieved compared to the classic approach of optimization through trials on individual systems during the development stage, while simultaneously saving on costly test series. Instead of one or more fixed characteristic maps, only the operating limits are stored in the control unit, where the AI ​​methodology searches for an optimum adapted to the system-specific boundary conditions.

[0046] One embodiment of the method described here is based, for example, on determining the operating limits of the various components in the system during development, such as vehicle development or fuel cell device development, as schematically represented by Block 220. For a fuel cell stack, these limits include, for example, a minimum moisture content (membrane aging), a minimum flow rate (droplet discharge), and / or a minimum partial pressure of the reactants (gas supply). For the compressor, for example, a surge limit (stable operation), a maximum speed, and / or a maximum temperature are defined. For the turbine, for example, a suction limit (maximum flow rate), a maximum speed, and / or a maximum temperature are defined.

[0047] Within the defined operating limits, operating the fuel cells is generally possible, but only advantageous at certain points with regard to the optimization goals. Several conflicting optimization goals exist for the fuel cell system, including the battery, which can be weighted differently, as schematically illustrated in Block 225. These include system efficiency, lifespan, and / or performance dynamics.

[0048] The boundary conditions, represented by block 230, for the operational optimization of the individual fuel cell system differ depending on the area of ​​application, use case, and aging. These boundary conditions are determined, for example, by physical or virtual sensors. Possible differing boundary conditions include, with regard to the environment, pressure, temperature, and / or humidity, such as those prevailing in the vicinity of vehicle 105; with regard to the ECSA stack, the membrane condition and / or coating condition; and with regard to vehicle 105, the required electrical power (average and variance) and / or the number of starts and stops.

[0049] The operation of the fuel cell device is significantly influenced by several control variables, which are specified by the control unit to achieve the required system performance within a small margin of error, taking into account the optimization goals mentioned above. These include electrical current, coolant temperature and flow rate, pressure and stoichiometry on the anode and cathode sides, EGR rate (if EGR is installed), humidification (if, for example, a membrane humidifier with bypass is installed), and / or purge rate and purge duration on the anode side. According to one embodiment, all or at least one of the control variables are varied to find the optimal operating point.

[0050] For example, during operation of the fuel cell device, one or more of the controlled variables are varied, and the resulting operating states of the fuel cell device are evaluated. According to one embodiment, the variation is continued until the optimal operating point is found.

[0051] According to one embodiment, the operating limits are known for each system in vehicles 105, 205, 210 of fleet 200.

[0052] Depending on the application, a different weighting of optimization goals is advantageous. For example, a long-haul truck may require high efficiency and service life, while dynamics are of secondary importance. Conversely, a delivery van in urban traffic may require higher performance dynamics, with only slight reductions in service life and efficiency.

[0053] During operation, vehicle 105 is exposed to the current individual boundary conditions. According to one embodiment, an AI methodology 235 is used to find the optimal operating point (sum of control objectives) for the given combination of boundary conditions and weighted optimization goals.

[0054] The process will now be explained using the controlled variable operating pressure and the optimization goal of system efficiency as an example. However, the procedure can be applied to all other combinations.

[0055] Vehicle 105 is operated at sea level, while vehicle 205 operates at an altitude of 1500 meters. Both vehicles, 105 and 205, are therefore exposed to different boundary conditions (ambient pressures). The choice of the controlled variable, operating pressure, directly influences the optimization goal of efficiency: increasing the pressure increases the stack performance but also requires additional compressor power. Overall, a system efficiency optimum is achieved at a specific pressure in vehicle 105. With reduced ambient pressure in vehicle 205, this optimum shifts towards a lower pressure because the compressor power increases proportionally. The classic approach with predefined operating points would lead to a deviation from the optimum with efficiency losses or a significantly increased data input effort, especially if further effects such as temperature dependencies and stack state dependencies are to be considered.In this example, methodology 255 finds an optimal choice of the controlled variable operating pressure for the prevailing boundary condition in the additional vehicle 205, in this case the reduced ambient pressure. This information is shared with other vehicles 105 and 210 in the fleet 200. If, in the future, the additional vehicle 210 in the fleet 200 registers a decrease in ambient pressure, the operating pressure is directly reduced to the value found by the additional vehicle 205. Based on this, variations are used to find a new, individual system optimum for the additional vehicle 210. Monitoring the individually found optima allows conclusions to be drawn about other potentially relevant boundary conditions. For example, the additional vehicle 210 might be identified with a slightly higher operating pressure as its optimum if the stack has aged more over its service life and exhibits a higher ECSA loss.In total, each vehicle (105, 205, 210) has its own optimal combination of control objectives (operating points), depending on the boundary conditions. The exchange of data between vehicles (105, 205, 210) further accelerates this individual optimization. Analyzing the entire fleet data allows for the identification of deviations from the desired behavior and the identification of potential further interrelationships. This, in turn, accelerates the development of the next product generation.

[0056] The following section briefly presents various operating strategies. One such strategy involves adjusting the target weighting over the vehicle's lifetime: Depending on the individual operating conditions of the vehicles in the field, different aging rates will occur. For example, if a component stack in a vehicle ages significantly faster than anticipated, the weighting of the optimization goals will shift, for instance, from system efficiency to lifetime. The driver can also adjust the weighting, for example, by selecting a driving mode. An Eco driving mode, for instance, results in optimal efficiency, while a Sport driving mode results in optimal dynamics.

[0057] Another operating strategy option involves detecting and exchanging shifted operating limits: Over the lifetime of the system, for example, the coating quality of the gas diffusion layer(s) (GDL) or the flow field in cells of the stack can deteriorate, necessitating a higher minimum flow rate for droplet discharge. If insufficient droplet discharge is detected via a voltage drop, the stored operating limit is adjusted. This information can also be shared within the fleet, enabling analysis of the aging mechanism using a wide range of field data. By individually adjusting the operating limits, they can be defined more precisely and progressively, thus enabling, for example, increased system efficiency.

[0058] Another operating strategy option considers dynamic effects: Fuel cell systems exhibit a multitude of dynamic effects. For example, the cell membrane dries out, a process that takes dozens of seconds. Therefore, selecting control variables with regard to optimization goals that would not be optimal in steady-state operation is advantageous in the short term. For instance, a short-term oversupply of reactants to the cathode is initiated, enabling higher power dynamics. Similarly, a short-term increase in gas flow for droplet discharge is advantageously utilized. To prevent drying, the oversupply state with high stoichiometry is only applied briefly, for less than 10 seconds. In the proposed approach, the historical temporal evolution of the control variables is therefore additionally considered in the AI ​​methodology.

[0059] The aim of the approach presented here, according to one example, is to operate the system as efficiently, dynamically and / or with as little aging as possible, while simultaneously reducing development effort.

[0060] The approach presented here utilizes the largest possible datasets, as illustrated in an exemplary implementation; only the operational boundaries are initially predefined. This advantageously reduces development effort. Furthermore, the system efficiency, dynamics, and lifespan of each individual system in the field are increased, depending on the specific boundary conditions, leading to reduced consumption, improved user experience, and / or extended durability. Additionally, interrelationships within real-world systems under diverse boundary conditions are investigated. This facilitates faster development and the identification of potential deviations of systems in the field from the desired behavior.

[0061] The approach presented here can be used for all mobile PEM fuel cell systems and can be demonstrated by analyzing the operating strategy of different systems in fleet operation.

[0062] The approach presented here can also be understood as AI-supported optimization of the operation of fuel cell systems in fleet networks.

[0063] Fig. Figure 3 shows a flowchart of an embodiment of method 300 for operating a vehicle with a fuel cell device. Method 300 is, for example, the one described in Fig. 2 described methods, the vehicle resembles or corresponds, for example, to the vehicle from one of the figures described above.

[0064] The procedure 300 includes a step 305 of determining boundary conditions, a step 310 of varying controlled variables and optionally a step 315 of providing information as well as a step 320 of reading in information and a step 325 of weighting optimization goals.

[0065] In step 305 of the determination process, boundary conditions present during current vehicle operation are determined. In step 310 of the variation process, control variables for operating the fuel cell device are varied using optimization objectives to establish an optimal operating point for the fuel cell device given the determined boundary conditions. For example, the control variables are varied within predefined operating limits.

[0066] According to one embodiment, in step 315 of the provisioning process, information about the optimal operating point for the determined boundary conditions is provided to an interface to at least one other vehicle or an external device. Step 315 of the provisioning process is executed using the varied control variables.

[0067] According to another embodiment, in step 320 of the input process, information about a further optimal operating point applicable to additional boundary conditions is read in via an interface to another vehicle. These additional boundary conditions were present, for example, during the operation of the other vehicle. In step 310 of the variation process, the controlled variables are varied, for example, using the information read in step 320.

[0068] For example, step 310 of the variation process is performed using the optimization goals weighted in step 325 of the weighting process.

[0069] Fig. Figure 4 shows a block diagram of an exemplary embodiment of a control device 108 for operating a vehicle. The control device 108 is designed to implement the method from Fig. 3 or a similar method to control and / or operate. The control device 108 is similar to or corresponds to the control device from Fig. 1.

[0070] For this purpose, the control device 108 has a unit 405 for determining boundary conditions, a unit 410 for varying controlled variables and optionally a unit 415 for providing information as well as a unit 420 for reading in information and a unit 425 for weighting optimization goals.

[0071] Unit 405, for determining, is designed to ascertain the boundary conditions present during current vehicle operation. Unit 410, for varying, is designed to vary control variables for operating the fuel cell device using optimization objectives in order to establish an optimal operating point for the fuel cell device given the determined boundary conditions. For example, the control variables are varied within predefined operating limits.

[0072] According to one embodiment, the unit 415 is designed to provide information about the optimal operating point for the determined boundary conditions to an interface to at least one other vehicle or an external device.

[0073] According to a further embodiment, unit 420 is configured for data input, enabling it to read information about a further optimal operating point applicable to additional boundary conditions via an interface to another vehicle. These additional boundary conditions were present, for example, during the operation of the other vehicle. The controlled variables are then varied, for example, using the input information.

Claims

[1] Method (300) for operating a vehicle (105) with a fuel cell device (100), wherein the method (300) comprises the following steps: Determine (305) boundary conditions that exist during a current operation of the vehicle (105), and Varying (310) control variables for operating the fuel cell device (100) using optimization targets to set an optimal operating point of the fuel cell device (100) for the determined boundary conditions. [2] Method (300) according to claim 1, comprising a step (315) of providing information about the optimal operating point for the determined boundary conditions to an interface to at least one further vehicle (205). [3] Method (300) according to one of the preceding claims, comprising a step (320) of reading in information about a further optimal operating point applicable to further boundary conditions via an interface to a further vehicle (205), wherein the further boundary conditions were present during operation of the further vehicle (205). [4] Method (300) according to claim 3, wherein in step (310) of varying the controlled variables are varied using the information about the further optimal operating point. [5] Method (300) according to one of the preceding claims, comprising a step (325) of weighting the optimization objectives. [6] Method (300) according to one of the preceding claims, wherein in step (310) of varying the controlled variables are varied within predetermined operating limits. [7] Control device (108) which is configured to perform and / or control the steps of the method (300) according to any one of the preceding claims 1 to 6 in corresponding units. [8] Vehicle (105) with a control device (108) according to claim 7 and a fuel cell device (100). [9] Computer program configured to perform and / or control the steps of the method (300) according to any of the preceding claims. [10] Machine-readable storage medium on which the computer program according to claim 9 is stored.

Images