Controller model determination method, hydrogen flow control method and device

Abstract

The invention relates to a controller model determination method and a hydrogen flow control method and device. The controller model determination method comprises the steps of determining a linear parameter change model corresponding to an engine, and performing model decomposition processing on the linear parameter change model to obtain a minimum phase component; the minimum phase component represents a stable component in the linear parameter change model; filtering the minimum phase component to obtain an initial controller model corresponding to a controller corresponding to the engine; and determining a target controller model corresponding to the controller according to the initial controller model and a nominal model corresponding to the engine. By adopting the method, the accuracy of hydrogen flow metering control of the aero-engine can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of engines, and particularly to a method for determining a controller model, a method and device for controlling hydrogen flow rate. Background Art

[0002] With the wide application of hydrogen energy in aero-engines, the hydrogen flow rate measurement part has become an important part of aero-engines. However, due to the compressibility of hydrogen, for example, the time constant of the hydrogen flow rate change varies with the change of the pipeline volume and direction between each metering valve nozzle, making it difficult to accurately measure the hydrogen flow rate, thus resulting in damage to the engine performance.

[0003] Therefore, it is difficult to accurately control the hydrogen flow rate measurement of aero-engines in the case of uncertainty in hydrogen flow rate measurement. Summary of the Invention

[0004] Based on this, in view of the above technical problems, it is necessary to provide a method for determining a controller model, a method and device for controlling hydrogen flow rate, which can improve the accuracy of controlling the hydrogen flow rate measurement of aero-engines.

[0005] In a first aspect, the present application provides a method for determining a controller model. The method includes:

[0006] Determine a linear parameter change model corresponding to the engine, and perform model decomposition processing on the linear parameter change model to obtain a minimum phase component; the minimum phase component represents the stable component in the linear parameter change model;

[0007] Perform filtering processing on the minimum phase component to obtain an initial controller model corresponding to the controller of the engine;

[0008] Determine a target controller model corresponding to the controller according to the initial controller model and the nominal model corresponding to the engine.

[0009] In one embodiment, the determining the target controller model corresponding to the controller according to the initial controller model and the nominal model corresponding to the engine includes:

[0010] Obtain model statistical data corresponding to the initial controller model and the nominal model;

[0011] Determine the target controller model according to the model statistical data.

[0012] In one embodiment, the obtaining the model statistical data corresponding to the initial controller model and the nominal model includes:

[0013] Calculate the product of the initial controller model and the nominal model, and calculate the difference between 1 and the product;

[0014] Calculate the ratio of the initial controller model to the difference, and use the ratio as the model statistical data.

[0015] In one embodiment, the filtering the minimum-phase component to obtain the initial controller model corresponding to the controller of the engine includes:

[0016] Perform an inverse transformation on the minimum-phase component to obtain the minimum-phase component after the inverse transformation;

[0017] Filter the minimum-phase component after the inverse transformation using a preset filter to obtain the initial controller model.

[0018] In one embodiment, the cut-off frequency of the filter is related to at least one of the nominal model included in the nominal model, the robust stability parameter of the engine, and the robust performance parameter of the engine.

[0019] In a second aspect, the present application further provides a hydrogen flow control method applied to a controller, where the target controller model corresponding to the controller is determined according to the controller model determination method described in any one of the first aspects above. The method includes:

[0020] Obtain the engine speed command signal and the speed feedback signal;

[0021] Determine the metering opening signal corresponding to the metering unit in the engine according to the speed command signal and the speed feedback signal;

[0022] Drive the driving mechanism of the engine to work according to the metering opening signal to obtain an opening feedback signal;

[0023] Determine the target hydrogen flow according to the metering opening signal and the opening feedback signal, and input hydrogen to the combustion chamber of the engine according to the target hydrogen flow.

[0024] In one embodiment, the determining the target hydrogen flow according to the metering opening signal and the opening feedback signal includes:

[0025] Calculate the signal difference between the metering opening signal and the opening feedback signal;

[0026] Control the opening controller to perform a conversion process on the signal difference to obtain a hydrogen flow signal;

[0027] Calculate the product of the hydrogen flow rate and the metering uncertainty coefficient, and determine the product as the target hydrogen flow rate.

[0028] Thirdly, the present application also provides a device for determining a controller model. The device includes:

[0029] A first determination module, configured to determine a linear parameter change model corresponding to an engine, and perform model decomposition processing on the linear parameter change model to obtain a minimum-phase component; the minimum-phase component represents a stable component in the linear parameter change model;

[0030] A first acquisition module, configured to perform filtering processing on the minimum-phase component to obtain an initial controller model corresponding to a controller of the engine;

[0031] A second determination module, configured to determine a target controller model corresponding to the controller according to the initial controller model and a nominal model corresponding to the engine.

[0032] Fourthly, the present application also provides a hydrogen flow rate control device, which is applied to a controller, and the target controller model corresponding to the controller is determined according to the controller model determination method described in any item of the first aspect above. The device includes:

[0033] A second acquisition module, configured to acquire a speed command signal and a speed feedback signal of the engine;

[0034] A third determination module, configured to determine a metering opening signal corresponding to a metering unit in the engine according to the speed command signal and the speed feedback signal;

[0035] A third acquisition module, configured to drive a driving mechanism of the engine to work according to the metering opening signal to obtain an opening feedback signal;

[0036] A fourth determination module, configured to determine a target hydrogen flow rate according to the metering opening signal and the opening feedback signal, and input hydrogen into a combustion chamber of the engine according to the target hydrogen flow rate.

[0037] Fifthly, the present application also provides a computer device. The computer device includes a memory and a processor, the memory stores a computer program, and when the processor executes the computer program, the steps of the methods described in the first aspect and the second aspect above are implemented.

[0038] Sixthly, the present application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the methods described in the first aspect and the second aspect above are implemented.

[0039] In a seventh aspect, the present application also provides a computer program product. The computer program product includes a computer program which, when executed by a processor, implements the steps of the methods described in the first and second aspects above.

[0040] In the above controller model determination method, hydrogen flow control method and device, the server first determines a linear parameter change model corresponding to the engine, and performs model decomposition processing on the linear parameter change model to obtain a minimum-phase component. Then, the minimum-phase component is filtered to obtain an initial controller model corresponding to the controller of the engine. Subsequently, based on the initial controller model and the nominal model corresponding to the engine, a target controller model corresponding to the controller is determined. Since the minimum-phase component represents the stable component of the linear parameter change model corresponding to the engine, and filtering the minimum-phase component can improve the stability of the determined initial controller model, using the initial controller model and the nominal model to determine the target controller model can enable the target controller model to satisfy the performance of the engine under specific working conditions while ensuring the stability of the controller. Furthermore, using the controller corresponding to the target controller model can accurately control the hydrogen flow measurement input to the engine combustion chamber. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] To more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following will briefly introduce the drawings required for use in the description of the embodiments of the present application or related technologies. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0042] Figure 1 It is an application environment diagram of the controller model determination method in an embodiment;

[0043] Figure 2 It is a flowchart of the controller model determination method in an embodiment;

[0044] Figure 3 It is a flowchart of step 203 in an embodiment;

[0045] Figure 4 It is a flowchart of step 301 in an embodiment;

[0046] Figure 5 It is a flowchart of step 202 in an embodiment;

[0047] Figure 6 It is a flowchart of the hydrogen flow control method in an embodiment;

[0048] Figure 7 It is a schematic flowchart of step 604 in an embodiment;

[0049] Figure 8 It is a structural block diagram of a controller model determination device in an embodiment;

[0050] Figure 9 It is a structural block diagram of a hydrogen flow control device in an embodiment;

[0051] Figure 10 It is an internal structure diagram of a computer device in an embodiment. Detailed implementation manners

[0052] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0053] With the wide application of hydrogen energy in aero-engines, the hydrogen flow measurement part has become an important part of aero-engines. However, due to the compressibility of hydrogen, at different times, the hydrogen flow will change with the changes in the pipeline volume, direction, temperature, pressure, etc. between the nozzles of each metering valve. Therefore, in the application of using hydrogen to drive the operation of aero-engines, the mechanical and hydraulic characteristics of the hydrogen metering device should be considered to accurately control the hydrogen flow.

[0054] In the traditional technology, during the process of controlling the speed of an aero-engine, a proportional integral (PI) controller is usually adopted. The PI controller is a linear controller that can, according to the control deviation between the given value and the actual output value, form a control quantity through the linear combination of the proportion and integral of the deviation, so as to control the hydrogen flow input into the combustion chamber of the aero-engine and achieve the control of the speed of the aero-engine. However, the control parameters of the PI controller are relatively complex, and in the actual control process, the control parameters cannot be directly and quickly adjusted; moreover, the robustness of the control process using the PI controller is relatively weak. Therefore, there is a problem in the traditional technology that it is difficult to accurately control the hydrogen flow measurement of aero-engines. In view of this, the present application proposes a method for determining a controller model to determine the controller corresponding to the aero-engine, so as to improve the accuracy of the hydrogen flow measurement control of the aero-engine.

[0055] The controller model determination method provided by the embodiments of the present application can be applied to, for example Figure 1In the described implementation environment, the implementation environment includes a server, which can be implemented by an independent server or a server cluster composed of multiple servers. The data storage system can store the data that the server needs to process. The data storage system can be integrated on the server, or placed in the cloud or on other network servers. Among them, the server can determine the linear parameter change model corresponding to the engine, and perform model decomposition processing on the linear parameter change model to obtain the minimum phase component; the minimum phase component represents the stable component in the linear parameter change model; then, perform filtering processing on the minimum phase component to obtain the initial controller model corresponding to the controller of the engine, and then, according to the initial controller model and the nominal model corresponding to the engine, determine the target controller model corresponding to the controller.

[0056] In other possible implementation manners, the controller model determination method provided by the embodiments of the present application can also be applied to a terminal, and the terminal can be, but is not limited to, various personal computers, laptop computers, smart phones, tablet computers, Internet of Things devices, and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, etc. The portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc.

[0057] In an exemplary embodiment, as Figure 2 shown, a controller model determination method is provided. Taking the method applied to the Figure 1 server in it as an example for illustration, the method includes the following steps:

[0058] Step 201, determine the linear parameter change model corresponding to the engine, and perform model decomposition processing on the linear parameter change model to obtain the minimum phase component; the minimum phase component represents the stable component in the linear parameter change model.

[0059] Among them, the linear parameter change model refers to a mathematical model obtained by modeling the control system of an aeroengine according to the change of the engine's parameters over time or operating conditions. According to the linear parameter change model, the control system of the engine can be accurately controlled. It can be understood that according to the linear parameter change model, the controller corresponding to the engine can be scheduled under different working conditions, so as to ensure the performance of the engine under different working conditions.

[0060] Among them, the minimum phase component refers to the component with the minimum delay in the unit impulse response of the control system in the control system, and can represent the stable component in the linear parameter change model.

[0061] It should be noted that when decomposing the linear parameter varying model, the model can be decomposed into components including pure time delay and unstable zeros, and a minimum-phase component. Among them, pure time delay refers to the time delay phenomenon that occurs in the measurement link, transmission link or other links of the measurement object, and is also called transportation lag. In a control system, the existence of pure time delay will make the control action untimely, resulting in an increase in the maximum deviation of the controlled variable, a decrease in control quality, and a reduction in system stability. Unstable zeros refer to the frequency points in a control system that make the response of the control system unstable. When the frequency of the input signal of the control system is equal to the unstable zero, the output of the system will become infinite, resulting in system instability.

[0062] In this embodiment, the server can pre-construct a linear parameter varying model according to the performance of the engine under different working conditions, and then perform model decomposition processing on the linear parameter varying model, taking the part that removes the components including pure time delay and unstable zeros in the linear parameter varying model as the minimum-phase component.

[0063] Step 202: Perform filtering processing on the minimum-phase component to obtain the initial controller model corresponding to the controller of the engine.

[0064] It should be noted that under ideal conditions, the controller parameters corresponding to the engine can be determined according to the minimum-phase component. However, since the minimum-phase component contains a time-delay component, where the time-delay component refers to the time interval between when the control system receives an instruction and starts to effectively respond to the instruction. In a control system, the time-delay component can directly affect the stability and response speed of the control system. Therefore, it is necessary to perform filtering processing on the minimum-phase component.

[0065] Optionally, the algorithm for performing filtering processing can be Kalman filtering, wavelet transform, adaptive filtering, etc., and this embodiment does not limit this.

[0066] In this embodiment, a filtering algorithm can be used to perform filtering processing on the minimum-phase component to filter out the time-delay component in the minimum-phase component, and take the filtered minimum-phase component as the initial controller model corresponding to the controller.

[0067] Step 203: Determine the target controller model corresponding to the controller according to the initial controller model and the nominal model corresponding to the engine.

[0068] Among them, the nominal model corresponding to the engine refers to the model determined according to the performance parameters of the engine under specific working conditions, where the performance parameters of the engine are specified in the technical specifications of the engine, for example, the effective power of the engine, the effective torque of the engine, the engine speed, etc.

[0069] In this embodiment, the server can calculate the ratio between the initial controller model and the nominal model, and determine the ratio as the target controller model.

[0070] In the above method for determining the controller model, the server first determines the linear parameter change model corresponding to the engine, and performs model decomposition processing on the linear parameter change model to obtain the minimum-phase component. Then, the minimum-phase component is filtered to obtain the initial controller model corresponding to the controller of the engine. Subsequently, based on the initial controller model and the nominal model corresponding to the engine, the target controller model corresponding to the controller is determined. Since the minimum-phase component represents the stable component of the linear parameter change model corresponding to the engine, and filtering the minimum-phase component can improve the stability of the determined initial controller model. Therefore, using the initial controller model and the nominal model to determine the target controller model can enable the target controller model to ensure the stability of the controller while meeting the performance of the engine under specific working conditions. Furthermore, using the controller corresponding to the target controller model can accurately control the hydrogen flow rate measurement input to the engine combustion chamber.

[0071] In an exemplary embodiment, as Figure 3 shown, this embodiment relates to the process of how the server determines the target controller model corresponding to the controller based on the initial controller model and the nominal model corresponding to the engine. The above step 203 includes:

[0072] Step 301, obtain the model statistical data corresponding to the initial controller model and the nominal model.

[0073] Among them, the model statistical data refers to the statistical data obtained by converting the initial controller model and the nominal model into mathematical expression forms and performing mathematical operations on the initial controller model and the nominal model in the mathematical expression forms.

[0074] In a possible implementation manner, as Figure 4 shown, the above step 301 includes:

[0075] Step 401, calculate the product of the initial controller model and the nominal model, and calculate the difference between 1 and the product.

[0076] In this embodiment, the initial controller model can be expressed as , and the nominal model can be expressed as , then 1 minus the product of the initial controller model and the nominal model can be expressed as: .

[0077] Step 402, calculate the ratio of the initial controller model to the difference, and use the ratio as the model statistical data.

[0078] In this embodiment, the model statistical data can be expressed as: .

[0079] Step 302: Determine the target controller model according to the model statistical data.

[0080] In this embodiment, the model statistical data can be determined as the target controller model, that is, the target controller model can be expressed as:

[0081]

[0082] In this embodiment, the server can obtain the model statistical data corresponding to the initial controller model and the nominal model, and can determine the target controller model according to the model statistical data. Since the process of determining the model statistical data is relatively simple, the model statistical data can be obtained quickly, and then the efficiency of determining the target controller model according to the model statistical data can be improved.

[0083] In an exemplary embodiment, as Figure 5 shown, this embodiment relates to the process of how the server filters the minimum-phase component to obtain the initial controller model corresponding to the controller of the engine. The above step 202 includes:

[0084] Step 501: Perform an inverse transformation on the minimum-phase component to obtain the minimum-phase component after the inverse transformation.

[0085] It should be noted that before filtering the minimum-phase component, an inverse transformation can be performed on the stable component, that is, the minimum-phase component, in the linear parameter change model representing the engine, so as to process the minimum-phase component into the corresponding time-domain component according to the frequency-domain characteristics of the filter. Optionally, the inverse transformation algorithm for performing the inverse transformation can be the inverse Laplace transform, the inverse Fourier transform, etc., and this embodiment does not limit this.

[0086] In this embodiment, the server can use the inverse transformation algorithm to perform an inverse transformation on the minimum-phase component, and use the processed result as the minimum-phase component after the inverse transformation.

[0087] In this embodiment, the minimum-phase component can be expressed as , and the minimum-phase component after the inverse transformation can be expressed as:

[0088]

[0089] Step 502: Use a preset filter to filter the minimum-phase component after the inverse transformation to obtain the initial controller model.

[0090] It can be understood that the minimum-phase component after the inverse transformation process contains a pure lead component. Here, the pure lead component refers to the part where the phase in the frequency response of the control system leads the input signal. In a control system, the pure lead component is usually used to improve the dynamic performance of the control system. For example, it can reduce the overshoot and settling time of the control system. However, in practical applications, it is difficult to achieve. Therefore, a filter can be used to filter the minimum-phase component after the inverse transformation process.

[0091] Optionally, the filter can be a Butterworth filter, a Chebyshev filter, etc., and this embodiment does not limit it.

[0092] In this embodiment, the server can input the minimum-phase component after the inverse transformation process into a preset filter, use the filter for filtering, and determine the result output by the filter as the initial controller model.

[0093] In this embodiment, the filter can be expressed as:

[0094]

[0095] where is the cut-off frequency of the filter.

[0096] Then the initial controller model q can be expressed as:

[0097]

[0098] It can be understood that since the initial controller model contains an adjustable parameter, the cut-off frequency of the filter, when adjusting the parameters of the initial controller model, the adjusted parameters can be obtained quickly, improving the parameter adjustment efficiency of the controller.

[0099] Optionally, the cut-off frequency of the filter is related to at least one of the nominal performance parameters included in the nominal model, the robust stability parameter of the engine, and the robust performance parameter of the engine.

[0100] The process in which the cut-off frequency of the filter satisfies the above relevant conditions is described below:

[0101] 1. The nominal performance parameters included in the nominal model include the sensitivity coefficient and the input disturbance. The cut-off frequency of the filter needs to satisfy:

[0102]

[0103] where is the sensitivity coefficient, is the input disturbance, is the nominal model, It is the minimum-phase component after the inverse transformation process.

[0104] 2. The robust stability parameters of the engine include the range of model multiplicative uncertainty, and the cut-off frequency of the filter needs to satisfy:

[0105]

[0106] where, is the range of model multiplicative uncertainty.

[0107] 3. The robust performance parameters of the engine include that the cut-off frequency of the filter needs to satisfy:

[0108]

[0109] where w is the weight of the stable component.

[0110] It can be understood that when it is necessary to adjust the parameters of the cut-off frequency, by directly adjusting the above parameters, the parameter adjustment can be carried out intuitively, thereby improving the parameter adjustment efficiency of the cut-off frequency, and further improving the parameter adjustment efficiency of the initial controller model.

[0111] In this embodiment, the server performs an inverse transformation process on the minimum-phase component to obtain the minimum-phase component after the inverse transformation process, and then uses a preset filter to perform a filtering process on the minimum-phase component after the inverse transformation process to obtain an initial controller model. Since the minimum-phase component after the inverse transformation process can represent the stable component in the linear change model of the engine, using the filter to perform a filtering process on the minimum-phase component after the inverse transformation process can filter out the pure leading term in the filtering process of the minimum-phase component after the inverse transformation process, thereby reducing the overshoot and adjustment time of the control system, and further improving the stability of the obtained initial controller model and the adjustment efficiency of parameter adjustment for the initial controller model.

[0112] On the basis of obtaining the target controller model by using the above controller model determination method, the controller corresponding to the target controller model can be used to control the hydrogen flow measurement for driving the engine to rotate. In an exemplary embodiment, as Figure 6 shown, the embodiment of the present application further provides a hydrogen flow control method, and the above method includes:

[0113] Step 601, obtain the speed command signal and speed feedback signal of the engine.

[0114] Among them, the rotational speed command signal refers to the speed used to control the rotation of the crankshaft of the engine. Optionally, the rotational speed command signal of the engine can be manually input, or the rotational speed command signal of the engine can also be determined according to the operating conditions of the engine. Among them, the rotational speed feedback signal refers to the actual rotational speed measured by the rotational speed sensor after the engine rotates according to the rotational speed command signal.

[0115] In this embodiment, the controller can receive the rotational speed command signal transmitted from an external device through the input interface, and receive the rotational speed feedback signal sent by the rotational speed sensor of the engine.

[0116] Step 602: Determine the metering opening signal corresponding to the metering unit in the engine according to the rotational speed command signal and the rotational speed feedback signal.

[0117] Among them, the metering unit is a component in the engine used to control the hydrogen flow rate of the hydrogen fuel entering the combustion chamber. The metering unit can adjust the supply amount of hydrogen according to the requirements of the engine to ensure that the engine can obtain the best combustion effect and performance under different operating conditions. The metering opening signal refers to the opening value of the valve of the metering unit.

[0118] In this embodiment, the controller can calculate the error value between the rotational speed command signal and the rotational speed feedback signal, then determine the hydrogen flow rate command signal according to the error value, and use the conversion function to convert the hydrogen flow rate command signal to obtain the metering opening signal.

[0119] Step 603: Drive the drive mechanism of the engine to work according to the metering opening signal to obtain the opening feedback signal.

[0120] Among them, the drive mechanism of the engine provides propulsion power or support force for the engine. The drive mechanism includes components such as hydraulic cylinders, metering valves, and servo valves. After the drive mechanism works, it can change the valve opening of the metering unit. In this embodiment, the valve opening corresponding to the operation of the drive mechanism can be determined as the opening feedback signal.

[0121] In this embodiment, the controller can input the metering opening signal into the servo valve in the drive mechanism to drive the servo valve to start moving, so that the piston of the hydraulic cylinder starts to move, thereby changing the valve opening of the metering unit. Then, the change value of the valve opening of the metering unit is determined as the opening feedback signal.

[0122] Step 604: Determine the target hydrogen flow rate according to the metering opening signal and the opening feedback signal, and input hydrogen into the combustion chamber of the engine according to the target hydrogen flow rate.

[0123] Among them, the target hydrogen flow rate refers to the quantity of hydrogen fuel required for the engine to reach the rotational speed value corresponding to the rotational speed command signal under the given rotational speed command signal.

[0124] In this embodiment, the controller can adjust the metering opening signal according to the opening feedback signal until the metering opening signal enables the engine to meet the rotational speed value corresponding to the rotational speed command signal. Then, the hydrogen flow rate corresponding to the increased opening signal is determined as the target hydrogen flow rate. Subsequently, hydrogen is input into the combustion chamber of the engine according to the target hydrogen flow rate to provide power for the engine after hydrogen combustion.

[0125] In this embodiment, by acquiring the rotational speed command signal and the rotational speed feedback signal of the engine, the controller can determine the metering opening signal corresponding to the metering unit in the engine according to the rotational speed command signal and the rotational speed feedback signal. Then, the driving mechanism of the engine is driven to work according to the metering opening signal to obtain the opening feedback signal. Subsequently, the target hydrogen flow rate can be determined according to the metering opening signal and the opening feedback signal, and hydrogen is input into the combustion chamber of the engine according to the target hydrogen flow rate. Since the controller is a controller corresponding to the target controller model determined according to the above-mentioned controller model determination method, the robustness and parameter adjustment efficiency in the control process are improved, thereby the accuracy of the determined target hydrogen flow rate can be improved, and further the robustness of the rotational speed control of the aeroengine under the condition of uncertain hydrogen flow rate metering can be improved.

[0126] In an exemplary embodiment, as Figure 7 shown, this embodiment relates to the process of how the controller determines the target hydrogen flow rate according to the metering opening signal and the opening feedback signal. The above step 604 includes:

[0127] Step 701, calculate the signal difference between the metering opening signal and the opening feedback signal.

[0128] In this embodiment, the controller can respectively convert the metering opening signal into a metering opening signal value and convert the opening feedback signal into an opening feedback signal value, and then calculate the signal difference between the metering opening signal value and the opening feedback signal value.

[0129] Step 702, control the opening controller to perform conversion processing on the signal difference to obtain a hydrogen flow rate signal.

[0130] Among them, the opening controller refers to a device that controls the opening value of the valve of the metering unit, and the hydrogen flow rate signal refers to the metering value of the hydrogen flow rate output by the controller according to the signal difference.

[0131] In this embodiment, the controller can input the signal difference into the opening controller, use the opening controller to adjust the metering opening signal according to the signal difference to obtain a new metering opening signal, and then the controller uses the conversion function to perform conversion processing on the new metering opening signal to obtain a hydrogen flow rate signal.

[0132] Step 703: Calculate the product of the hydrogen flow rate and the metering uncertainty coefficient, and determine the product as the target hydrogen flow rate.

[0133] It should be noted that since hydrogen is a compressible gas and there is metering uncertainty, the metering uncertainty coefficient related to hydrogen can be determined based on historical experience. Among them, the target hydrogen flow rate refers to the hydrogen flow rate actually input into the combustion chamber of the engine considering the metering uncertainty of hydrogen.

[0134] In this embodiment, the controller can calculate the product of the hydrogen flow rate and the metering uncertainty coefficient, and then determine the obtained product as the target hydrogen flow rate.

[0135] In this embodiment, by calculating the signal difference between the metering opening signal and the opening feedback signal, the controller can control the opening controller to perform conversion processing on the signal difference to obtain a hydrogen flow rate signal. Then, it can calculate the product of the hydrogen flow rate and the metering uncertainty coefficient, and determine the product as the target hydrogen flow rate. Since the metering uncertainty of hydrogen flow rate is considered in the process of determining the target hydrogen flow rate, and the product of the hydrogen flow rate and the metering uncertainty coefficient is determined as the target hydrogen flow rate, the accuracy of the determined target hydrogen flow rate can be improved.

[0136] For the convenience of understanding by those skilled in the art, taking a server as an example, the above method for determining the controller model will be introduced in detail below. This method may include:

[0137] S1: Determine the linear parameter change model corresponding to the engine.

[0138] S2: Perform model decomposition processing on the linear parameter change model to obtain the minimum phase component.

[0139] S3: Perform inverse transformation processing on the minimum phase component to obtain the minimum phase component after inverse transformation processing.

[0140] S4: Use a preset filter to perform filtering processing on the minimum phase component after inverse transformation processing to obtain the initial controller model corresponding to the controller.

[0141] S5: Calculate the product of the initial controller model corresponding to the controller and the nominal model included in the nominal model, and calculate the difference between 1 and the product.

[0142] S6: Calculate the ratio of the initial controller model corresponding to the controller to the difference, and use the ratio as the target controller model corresponding to the controller.

[0143] It should be noted that for the descriptions in S1 - S6 above, reference can be made to the relevant descriptions in the above embodiments, and their effects are similar. This embodiment will not be elaborated here.

[0144] For the convenience of those skilled in the art to understand, for the controller obtained by the controller model determination method provided in this application, the following details the process of controlling the hydrogen flow rate using this controller, and this process may include:

[0145] S1. Obtain the engine speed command signal and the speed feedback signal.

[0146] S2. Calculate the first signal difference between the speed command signal and the speed feedback signal.

[0147] S3. Determine the metering opening signal corresponding to the metering unit in the engine according to the first signal difference.

[0148] S4. Control the servo valve in the driving mechanism of the engine to work according to the metering opening signal, so that the hydraulic cylinder in the driving mechanism moves to generate a displacement signal.

[0149] S5. The displacement sensor obtains an opening feedback signal according to the measured displacement signal.

[0150] S6. Calculate the second signal difference between the metering opening signal and the opening feedback signal.

[0151] S7. Control the opening controller to perform conversion processing on the second signal difference to obtain a hydrogen flow rate signal.

[0152] S8. Calculate the product of the hydrogen flow rate and the metering uncertainty coefficient, and determine the product as the target hydrogen flow rate.

[0153] S9. Input hydrogen into the combustion chamber of the engine according to the target hydrogen flow rate.

[0154] It should be noted that for the descriptions in S1-S9 above, reference can be made to the relevant descriptions in the above embodiments, and their effects are similar, so they will not be elaborated in this embodiment.

[0155] It should be understood that although each step in the flowcharts involved in the above embodiments is shown in sequence according to the indication of the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same moment, but can be executed at different moments. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least a part of other steps or steps or stages in other steps.

[0156] Based on the same inventive concept, an embodiment of the present application further provides a controller model determination device for implementing the controller model determination method involved above. The implementation solution provided by this device for solving problems is similar to the implementation solution described in the above method. Therefore, the specific limitations in one or more embodiments of the controller model determination device provided below can refer to the limitations on the controller model determination method in the foregoing, and will not be repeated here.

[0157] In one embodiment, as Figure 8 shown, a controller model determination device is provided, including: a first determination module 801, a first acquisition module 802, and a second determination module 803, where:

[0158] The first determination module 801 is configured to determine a linear parameter change model corresponding to an engine, and perform model decomposition processing on the linear parameter change model to obtain a minimum phase component; the minimum phase component represents a stable component in the linear parameter change model;

[0159] The first acquisition module 802 is configured to perform filtering processing on the minimum phase component to obtain an initial controller model corresponding to the controller of the engine;

[0160] The second determination module 803 determines a target controller model corresponding to the controller according to the initial controller model and the nominal model corresponding to the engine.

[0161] The controller model determination device provided in this embodiment can execute the above method embodiment, and its implementation principle and technical effect are similar, and will not be repeated here.

[0162] In one embodiment, the above second determination module 803 includes:

[0163] An acquisition unit, configured to acquire model statistical data corresponding to the initial controller model and the nominal model;

[0164] A determination unit, configured to determine a target controller model according to the model statistical data.

[0165] The controller model determination device provided in this embodiment can execute the above method embodiment, and its implementation principle and technical effect are similar, and will not be repeated here.

[0166] In one embodiment, the above acquisition unit is specifically configured to:

[0167] Calculate the product of the initial controller model and the nominal model, and calculate the difference between 1 and the product;

[0168] Calculate the ratio of the initial controller model to the difference, and use the ratio as the model statistical data.

[0169] The controller model determination device provided in this embodiment can execute the above method embodiment, and its implementation principle and technical effects are similar, which will not be elaborated here.

[0170] In one embodiment, the above first acquisition module 802 includes:

[0171] A transformation unit, configured to perform an inverse transformation process on the minimum-phase component to obtain the minimum-phase component after the inverse transformation process;

[0172] A filtering unit, configured to filter the minimum-phase component after the inverse transformation process by using a preset filter to obtain an initial controller model.

[0173] Optionally, the cut-off frequency of the filter is related to at least one of the nominal model included in the nominal model, the robust stability parameter of the engine, and the robust performance parameter of the engine.

[0174] The controller model determination device provided in this embodiment can execute the above method embodiment, and its implementation principle and technical effects are similar, which will not be elaborated here.

[0175] Each module in the above controller model determination device can be implemented in whole or in part by software, hardware, and their combination. The above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0176] Based on the same inventive concept, the embodiment of the present application also provides a hydrogen flow control device for implementing the above-mentioned hydrogen flow control method. The solution provided by the device to solve the problem is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the hydrogen flow control device provided below can refer to the limitations on the hydrogen flow control method in the above text, which will not be elaborated here.

[0177] In one embodiment, as Figure 9 shown, a hydrogen flow control device is provided, which is applied to a controller. The target controller model corresponding to the controller is determined by the above controller model determination device, and includes: a second acquisition module 901, a third determination module 902, a third acquisition module 903, and a fourth determination module 904, where:

[0178] The second acquisition module 901 is configured to acquire a speed command signal and a speed feedback signal of the engine;

[0179] The third determination module 902 is configured to determine a metering opening signal corresponding to the metering unit in the engine according to the speed command signal and the speed feedback signal;

[0180] A third acquisition module 903, configured to drive a driving mechanism of an engine to operate according to a metering opening signal, and obtain an opening feedback signal;

[0181] A fourth determination module 904, configured to determine a target hydrogen flow rate according to the metering opening signal and the opening feedback signal, and input hydrogen into a combustion chamber of the engine according to the target hydrogen flow rate.

[0182] The hydrogen flow rate control device provided in this embodiment can execute the above method embodiment, and its implementation principle and technical effect are similar, which will not be elaborated here.

[0183] In one embodiment, the above fourth determination module 904 includes:

[0184] A first calculation unit, configured to calculate a signal difference between the metering opening signal and the opening feedback signal;

[0185] Conversion processing, configured to control an opening controller to perform conversion processing on the signal difference to obtain a hydrogen flow rate signal;

[0186] A second calculation unit, configured to calculate a product of the hydrogen flow rate and a metering uncertainty coefficient, and determine the product as the target hydrogen flow rate.

[0187] The hydrogen flow rate control device provided in this embodiment can execute the above method embodiment, and its implementation principle and technical effect are similar, which will not be elaborated here.

[0188] Each module in the above hydrogen flow rate control device can be implemented in whole or in part by software, hardware, and their combination. The above modules can be embedded in a processor in a computer device in a hardware form or independent of the processor, or stored in a memory in the computer device in a software form, so as to be called by the processor to execute the operations corresponding to the above respective modules.

[0189] In an exemplary embodiment, a computer device is provided. The computer device can be a server, and its internal structure diagram can be as Figure 10As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the control parameter data of the controller corresponding to the engine. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with an external terminal through a network connection. The computer program, when executed by the processor, implements a method for determining a controller model.

[0190] Those skilled in the art can understand that Figure 10 the structure shown in is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0191] In one embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, the following steps are implemented:

[0192] Determine the linear parameter change model corresponding to the engine, and perform model decomposition processing on the linear parameter change model to obtain the minimum phase component; the minimum phase component represents the stable component in the linear parameter change model;

[0193] Perform filtering processing on the minimum phase component to obtain the initial controller model corresponding to the controller of the engine;

[0194] According to the initial controller model and the nominal model corresponding to the engine, determine the target controller model corresponding to the controller.

[0195] In one embodiment, when the processor executes the computer program, the following steps are also implemented:

[0196] Obtain the model statistical data corresponding to the initial controller model and the nominal model;

[0197] Determine the target controller model according to the model statistical data.

[0198] In one embodiment, when the processor executes the computer program, the following steps are also implemented:

[0199] Calculate the product of the initial controller model and the nominal model, and calculate the difference between 1 and the product;

[0200] Calculate the ratio of the initial controller model to the difference, and use the ratio as the model statistical data.

[0201] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0202] Perform an inverse transformation on the minimum-phase component to obtain the minimum-phase component after the inverse transformation;

[0203] Filter the minimum-phase component after the inverse transformation using a preset filter to obtain the initial controller model.

[0204] Optionally, the cut-off frequency of the filter is related to at least one of the nominal performance parameters included in the nominal model, the robust stability parameter of the engine, and the robust performance parameter of the engine.

[0205] In one embodiment, a computer device is further provided, including a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, the following steps are implemented:

[0206] Obtain the engine speed command signal and the speed feedback signal;

[0207] Determine the metering opening signal corresponding to the metering unit in the engine according to the speed command signal and the speed feedback signal;

[0208] Drive the drive mechanism of the engine to work according to the metering opening signal to obtain the opening feedback signal;

[0209] Determine the target hydrogen flow rate according to the metering opening signal and the opening feedback signal, and input hydrogen into the combustion chamber of the engine according to the target hydrogen flow rate.

[0210] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0211] Calculate the signal difference between the metering opening signal and the opening feedback signal;

[0212] Control the opening controller to perform a conversion process on the signal difference to obtain the hydrogen flow rate signal;

[0213] Calculate the product of the hydrogen flow rate and the metering uncertainty coefficient, and determine the product as the target hydrogen flow rate.

[0214] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0215] Determine the linear parameter change model corresponding to the engine, and perform model decomposition processing on the linear parameter change model to obtain the minimum-phase component; the minimum-phase component represents the stable component in the linear parameter change model;

[0216] Perform filtering processing on the minimum-phase component to obtain the initial controller model corresponding to the controller of the engine;

[0217] According to the initial controller model and the nominal model corresponding to the engine, determine the target controller model corresponding to the controller.

[0218] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0219] Obtain the model statistical data corresponding to the initial controller model and the nominal model;

[0220] Determine the target controller model according to the model statistical data.

[0221] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0222] Calculate the product of the initial controller model and the nominal model, and calculate the difference between 1 and the product;

[0223] Calculate the ratio of the initial controller model to the difference, and use the ratio as the model statistical data.

[0224] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0225] Perform inverse transformation processing on the minimum-phase component to obtain the minimum-phase component after inverse transformation processing;

[0226] Use a preset filter to perform filtering processing on the minimum-phase component after inverse transformation processing to obtain the initial controller model.

[0227] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0228] Optionally, the cut-off frequency of the filter is related to at least one of the nominal performance parameters included in the nominal model, the robust stability parameter of the engine, and the robust performance parameter of the engine. In one embodiment, a computer-readable storage medium is further provided, on which a computer program is stored, and when the computer program is executed by the processor, the following steps are implemented:

[0229] Obtain the speed command signal and the speed feedback signal of the engine;

[0230] According to the speed command signal and the speed feedback signal, determine the metering opening signal corresponding to the metering unit in the engine;

[0231] Drive the driving mechanism of the engine according to the metering opening signal to obtain an opening feedback signal;

[0232] Determine the target hydrogen flow rate according to the metering opening signal and the opening feedback signal, and input hydrogen into the combustion chamber of the engine according to the target hydrogen flow rate.

[0233] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0234] Calculate the signal difference between the metering opening signal and the opening feedback signal;

[0235] Control the opening controller to perform conversion processing on the signal difference to obtain a hydrogen flow rate signal;

[0236] Calculate the product of the hydrogen flow rate and the metering uncertainty coefficient, and determine the product as the target hydrogen flow rate.

[0237] In one embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0238] Determine the linear parameter change model corresponding to the engine, and perform model decomposition processing on the linear parameter change model to obtain a minimum-phase component; the minimum-phase component characterizes the stable component in the linear parameter change model;

[0239] Perform filtering processing on the minimum-phase component to obtain an initial controller model corresponding to the controller of the engine;

[0240] Determine the target controller model corresponding to the controller according to the initial controller model and the nominal model corresponding to the engine.

[0241] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0242] Obtain the model statistical data corresponding to the initial controller model and the nominal model;

[0243] Determine the target controller model according to the model statistical data.

[0244] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0245] Calculate the product of the initial controller model and the nominal model, and calculate the difference between 1 and the product;

[0246] Calculate the ratio of the initial controller model to the difference, and use the ratio as the model statistical data.

[0247] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0248] Perform an inverse transformation on the minimum-phase component to obtain the minimum-phase component after the inverse transformation;

[0249] Filter the minimum-phase component after the inverse transformation using a preset filter to obtain an initial controller model.

[0250] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0251] Optionally, the cut-off frequency of the filter is related to at least one of the nominal performance parameters included in the nominal model, the robust stability parameter of the engine, and the robust performance parameter of the engine.

[0252] In one embodiment, a computer program product is further provided, including a computer program that implements the following steps when executed by a processor:

[0253] Obtain the engine speed command signal and the engine speed feedback signal;

[0254] Determine the metering opening signal corresponding to the metering unit in the engine according to the engine speed command signal and the engine speed feedback signal;

[0255] Drive the drive mechanism of the engine to work according to the metering opening signal to obtain an opening feedback signal;

[0256] Determine the target hydrogen flow rate according to the metering opening signal and the opening feedback signal, and input hydrogen into the combustion chamber of the engine according to the target hydrogen flow rate.

[0257] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0258] Calculate the signal difference between the metering opening signal and the opening feedback signal;

[0259] Control the opening controller to perform a conversion process on the signal difference to obtain a hydrogen flow rate signal;

[0260] Calculate the product of the hydrogen flow rate and the metering uncertainty coefficient, and determine the product as the target hydrogen flow rate.

[0261] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., without limitation.

[0262] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in this specification.

[0263] The above embodiments only represent several implementation manners of the present application, and the description is relatively specific and detailed, but it should not be construed as a limitation on the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A controller model determination method, characterized in that: The method comprises: Determine a linear parameter variation model corresponding to the engine, and perform model decomposition processing on the linear parameter variation model to obtain a minimum phase component; the minimum phase component represents a stable component in the linear parameter variation model; Performing filtering processing on the minimum phase component to obtain an initial controller model corresponding to the controller corresponding to the engine; A target controller model corresponding to the controller is determined according to the initial controller model and a nominal model corresponding to the engine.

2. The method according to claim 1, characterized in that: The step of determining a target controller model corresponding to the controller according to the initial controller model and a nominal model corresponding to the engine comprises: Obtaining model statistical data corresponding to the initial controller model and the nominal model; The target controller model is determined according to the model statistical data.

3. The method according to claim 2, characterized in that The obtaining of model statistical data corresponding to the initial controller model and the nominal model includes: Calculating the product of the initial controller model and the nominal model, and calculating the difference between 1 and the product; A ratio of the initial controller model to the difference is calculated, and the ratio is used as the model statistical data.

4. The method according to claim 1, characterized in that: The filtering process of the minimum phase component to obtain an initial controller model corresponding to the controller corresponding to the engine includes: Performing inverse transformation processing on the minimum phase component to obtain the minimum phase component after inverse transformation processing; The minimum phase component after the inverse transformation is filtered using a preset filter to obtain the initial controller model.

5. The method according to claim 4, characterized in that The cutoff frequency of the filter is related to at least one of a nominal performance parameter included in the nominal model, a robust stability parameter of the engine, and a robust performance parameter of the engine.

6. A hydrogen flow control method, characterized in that: Applied to a controller, the target controller model corresponding to the controller is determined according to the controller model determination method according to any one of claims 1 to 5, the method comprising: Obtaining a speed command signal and a speed feedback signal of the engine; Determining a metering opening signal corresponding to a metering unit in the engine according to the speed command signal and the speed feedback signal; driving the driving mechanism of the engine to work according to the metering opening signal to obtain an opening feedback signal; A target hydrogen flow rate is determined according to the metering opening signal and the opening feedback signal, and hydrogen is input into the combustion chamber of the engine according to the target hydrogen flow rate.

7. The method according to claim 6, characterized in that Determining the target hydrogen flow rate according to the metering opening signal and the opening feedback signal includes: Calculating a signal difference between the metering opening signal and the opening feedback signal; Controlling the opening controller to convert the signal difference to obtain a hydrogen flow signal; The product of the hydrogen flow rate and the measurement uncertainty coefficient is calculated, and the product is determined as the target hydrogen flow rate.

8. A controller model determination device, characterized in that: The device comprises: A first determination module is used to determine a linear parameter variation model corresponding to the engine, and perform model decomposition processing on the linear parameter variation model to obtain a minimum phase component; the minimum phase component represents a stable component in the linear parameter variation model; A first acquisition module is used to filter the minimum phase component to obtain an initial controller model corresponding to the controller corresponding to the engine; The second determination module determines a target controller model corresponding to the controller according to the initial controller model and a nominal model corresponding to the engine.

9. A hydrogen flow control device, characterized in that: Applied to a controller, the target controller model corresponding to the controller is determined according to the controller model determination method according to any one of claims 1 to 5, and the device comprises: A second acquisition module is used to acquire a speed command signal and a speed feedback signal of the engine; A third determination module, used to determine a metering opening signal corresponding to a metering unit in the engine according to the speed command signal and the speed feedback signal; A third acquisition module is used to drive the driving mechanism of the engine to work according to the metering opening signal to obtain an opening feedback signal; The fourth determination module is used to determine a target hydrogen flow rate according to the metering opening signal and the opening feedback signal, and input hydrogen into the combustion chamber of the engine according to the target hydrogen flow rate.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

12. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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