Boost pressure determination method and boost pressure determination device for engine

Abstract

The present disclosure provides a method and device for determining boost pressure of an engine. The method includes extracting operating condition data of an engine under all operating conditions to obtain target operating condition parameters of the engine, wherein the operating condition data characterizes the relationship between engine speed, torque and time; using a genetic algorithm and a target engine simulation model for joint solution to obtain target boost pressure parameters, wherein the target engine simulation model operates under the target operating condition parameters, and the target engine simulation model is generated according to the configuration parameters of the engine and a simple supercharger model; based on the target operating condition parameters, according to the target boost pressure parameters and the target engine simulation model, determining the supercharger boundary conditions; and determining the supercharger model corresponding to the engine according to the target boost pressure parameters and the supercharger boundary conditions.

Description

Technical Field

[0001] The present disclosure relates to the technical field of power systems, and more specifically, to a boost pressure determination method for an engine, a boost pressure determination device, an electronic device, a computer-readable storage medium, and a computer program product. Background Art

[0002] In order to reduce the fuel consumption rate of the automobile power system and improve the energy efficiency of the whole vehicle, the above goals can be achieved by narrowing the operating range of the engine. At this time, the engine needs to work as concentratedly as possible in the high-efficiency operating range, especially for series, series-parallel and power-split hybrid vehicles.

[0003] The development focus of hybrid-specific engines is to match the engine's efficient operating range with the hybrid system and to maximize the thermal efficiency of the engine's efficient operating range. Supercharging can effectively improve the engine's minimum fuel consumption rate and shift the efficient operating range to low speeds, which is very beneficial for improving the fuel economy of hybrid engines.

[0004] The current boost matching method only calculates the steady-state required flow and boost pressure of the engine, uses this as the basis for boost matching and then iterates and verifies. However, the engine and the boost system operate in coordination, and the operating state of the engine will change with the changes in the boost system. This is a complex process. Calculating the steady-state required flow and boost pressure of the engine requires multiple iterations, and it is difficult to ensure the accuracy of the matching results. Moreover, this matching method cannot obtain the only optimal solution for the key parameters of the boost system under a specific engine operating condition. Summary of the invention

[0005] In view of this, embodiments of the present disclosure provide a method for determining boost pressure of an engine, a device for determining boost pressure, an electronic device, a computer-readable storage medium, and a computer program product.

[0006] One aspect of an embodiment of the present disclosure provides a method for determining boost pressure of an engine, comprising:

[0007] Extracting the operating condition data of the engine under all operating conditions to obtain the target operating condition parameters of the engine, wherein the operating condition data represents the relationship between the engine speed, torque and time;

[0008] Using a genetic algorithm and a target engine simulation model to perform a joint solution to obtain target supercharging parameters, wherein the target engine simulation model operates under the target operating parameters, and the target engine simulation model is generated based on the configuration parameters of the engine and a simple supercharger model;

[0009] Based on the target operating condition parameters, according to the target boost parameters and the target engine simulation model, determining the supercharger boundary conditions;

[0010] According to the target supercharging parameters and the supercharger boundary conditions, a supercharger model corresponding to the engine is determined.

[0011] According to an embodiment of the present disclosure, the above target engine simulation model is generated in the following manner:

[0012] Obtain configuration parameters of the above engine;

[0013] Using preset simulation software to construct an initial engine simulation model based on the configuration parameters, wherein the initial engine simulation model at least includes a supercharging system model, an engine model, and an intake air cooler model;

[0014] The target engine simulation model is obtained by replacing the supercharging system model in the initial engine simulation model with a simple supercharger model, wherein the simple supercharger model is a supercharger model that can determine the supercharger operating state in a single working condition only by setting parameters without using a detailed supercharger map, and the setting parameters include compressor efficiency, turbine efficiency, turbine flow regulating bypass valve flow surface diameter and turbine equivalent nozzle area.

[0015] According to an embodiment of the present disclosure, before replacing the supercharging system model with the simplified supercharger model, the method further includes:

[0016] Running the initial engine simulation model and outputting operating parameters, wherein the operating parameters at least include fuel consumption rate, maximum combustion pressure in the cylinder, intake flow rate and pressure, and exhaust pressure;

[0017] When the difference between the above-mentioned operating parameters and the calibration parameters of the above-mentioned engine is greater than the preset error range, the model parameters of the above-mentioned initial engine simulation model are adjusted to obtain an adjusted initial engine simulation model, so as to replace the supercharging system model in the above-mentioned adjusted initial engine simulation model with the above-mentioned simple supercharger model.

[0018] According to an embodiment of the present disclosure, a target engine simulation model is iteratively solved using a genetic algorithm to obtain target boost parameters, including:

[0019] When the target engine simulation model is operated under the target operating parameters, the engine fuel consumption rate and the maximum combustion pressure in the cylinder of the simple supercharger model in the target engine simulation model are iteratively solved by using the engine simulation model under different turbine equivalent nozzle areas, wherein the turbine equivalent nozzle area satisfies a preset nozzle constraint condition;

[0020] Based on preset combustion pressure constraints and minimum fuel consumption rate, the genetic algorithm is used to process input data to obtain a target turbine equivalent nozzle area, wherein the target boost parameter includes the target turbine equivalent nozzle area, and the input data includes multiple turbine equivalent nozzle areas, the engine fuel consumption rate corresponding to each turbine equivalent nozzle area, and the maximum combustion pressure in the cylinder.

[0021] According to an embodiment of the present disclosure, the boost pressure determination method further includes:

[0022] Replacing the simplified supercharger model in the target engine simulation model with a common supercharger model to obtain a verification engine simulation model, wherein the common supercharger model uses a supercharger map of a target supercharger corresponding to the supercharger model;

[0023] Run the above verification engine simulation model under all working conditions and output the operation results;

[0024] When the above operation results indicate that the above common supercharger model and the engine model are operating normally, the target supercharger corresponding to the above supercharger model is confirmed as a successfully matched supercharger.

[0025] According to an embodiment of the present disclosure, the above-mentioned target boost parameters include a target high-pressure turbine equivalent nozzle area of ​​a high-pressure stage supercharger and a target low-pressure turbine equivalent nozzle area of ​​a low-pressure stage supercharger;

[0026] Wherein, based on the above target operating condition parameters, according to the above target boost parameters and the above target engine simulation model, the supercharger boundary conditions are determined, including:

[0027] The target high-pressure turbine equivalent nozzle area and the target low-pressure turbine equivalent nozzle area are input into the target engine simulation model to obtain a modified target engine simulation model.

[0028] The modified target engine simulation model is run under the target operating parameters to output the intake flow rate of the engine and the pressure ratio between the high-pressure stage supercharger and the low-pressure stage supercharger, wherein the supercharger boundary condition includes the intake flow rate and the pressure ratio.

[0029] According to an embodiment of the present disclosure, determining a supercharger model corresponding to the engine according to the target supercharging parameter and the supercharger boundary condition includes:

[0030] The supercharger models of the high-pressure stage supercharger and the low-pressure stage supercharger are determined respectively according to the above target high-pressure turbine equivalent nozzle area and the above target low-pressure turbine equivalent nozzle area and the above supercharger boundary conditions.

[0031] According to an embodiment of the present disclosure, the engine is a fuel engine in a hybrid transportation device.

[0032] Another aspect of the embodiment of the present disclosure provides a boost pressure determination device for an engine, comprising:

[0033] An extraction module is used to extract the operating condition data of the engine under all operating conditions to obtain the target operating condition parameters of the engine, wherein the operating condition data represents the relationship between the engine speed, torque and time;

[0034] An iteration module, used for performing joint iterative solution using a genetic algorithm and a target engine simulation model to obtain target supercharging parameters, wherein the target engine simulation model operates under the target operating parameters, and the target engine simulation model is generated according to the configuration parameters of the engine and a simple supercharger model;

[0035] A first determination module is used to determine the supercharger boundary conditions based on the target operating condition parameters, the target boost parameters and the target engine simulation model;

[0036] The second determination module is used to determine the supercharger model corresponding to the engine according to the target supercharging parameter and the supercharger boundary condition.

[0037] Another aspect of an embodiment of the present disclosure provides an electronic device, comprising: one or more processors; and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method described above.

[0038] Another aspect of an embodiment of the present disclosure provides a computer-readable storage medium storing computer-executable instructions, which are used to implement the method described above when executed.

[0039] Another aspect of an embodiment of the present disclosure provides a computer program product, wherein the computer program product includes computer executable instructions, and the instructions are used to implement the method described above when executed.

[0040] According to the embodiment of the present disclosure, the target operating parameters of the engine are obtained by extracting the operating data of the engine under all operating conditions, and the target boost parameters are obtained by joint iterative solution using the genetic algorithm and the target engine simulation model. Based on the target operating parameters, the supercharger boundary conditions are determined according to the target boost parameters and the target engine simulation model. Finally, the supercharger model corresponding to the engine is determined according to the target boost parameters and the supercharger boundary conditions. By combining the genetic algorithm with the target engine simulation model, the changing trend of the engine performance when the key parameters of the supercharging system change can be accurately predicted, and the matching process can be completed without multiple iterations, saving matching time. At the same time, the use of the simple supercharger model reduces the number of optimization variables and combined with the genetic algorithm can ensure that the supercharger can operate in the most efficient area under the target operating conditions, maximizing the operating efficiency of the engine. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The above and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0042] Figure 1 An exemplary system architecture to which the boost pressure determination method according to an embodiment of the present disclosure can be applied is schematically shown;

[0043] Figure 2 A flow chart of a method for determining boost pressure according to an embodiment of the present disclosure is schematically shown;

[0044] Figure 3 A schematic diagram of a code for parameter extraction according to an embodiment of the present disclosure is schematically shown;

[0045] Figure 4 A schematic diagram of the structure of a target engine simulation model according to an embodiment of the present disclosure is shown;

[0046] Figure 5 The structural diagram of a simple supercharger model according to an embodiment of the present disclosure is schematically shown;

[0047] Figure 6 Schematically shows a schematic diagram of input parameters of a simple supercharger model according to an embodiment of the present disclosure;

[0048] Figure 7 A schematic diagram of the operating characteristics of a low-pressure compressor according to an embodiment of the present disclosure is schematically shown;

[0049] Figure 8 The schematic diagram schematically shows the operating characteristics of the high pressure compressor according to an embodiment of the present disclosure;

[0050] Fig. 9 A schematic diagram showing the improvement result of the fuel consumption rate of the engine matching the target working condition according to an embodiment of the present disclosure is shown;

[0051] Fig.10 A block diagram schematically shows a boost pressure determination device according to an embodiment of the present disclosure;

[0052] Fig.11 A block diagram of an electronic device suitable for implementing the method described above according to an embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0053] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0054] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise", "include", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0055] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification, and should not be interpreted in an idealized or overly rigid manner.

[0056] When using expressions such as "at least one of A, B, and C, etc.", they should generally be interpreted according to the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0057] The embodiment of the present disclosure provides a method and device for determining the boost pressure of an engine. The method includes extracting the operating condition data of the engine under all operating conditions to obtain the target operating condition parameters of the engine, wherein the operating condition data characterizes the relationship between the engine speed, torque and time; using a genetic algorithm and a target engine simulation model for joint solution to obtain the target boost pressure parameters, wherein the target engine simulation model operates under the target operating condition parameters, and the target engine simulation model is generated according to the configuration parameters of the engine and a simple supercharger model; based on the target operating condition parameters, according to the target boost pressure parameters and the target engine simulation model, determining the supercharger boundary conditions; according to the target boost pressure parameters and the supercharger boundary conditions, determining the supercharger model corresponding to the engine.

[0058] Figure 1 An exemplary system architecture 100 to which the boost determination method according to an embodiment of the present disclosure can be applied is schematically shown. It should be noted that: Figure 1 What is shown is merely an example of a system architecture to which the embodiments of the present disclosure can be applied, in order to help those skilled in the art understand the technical content of the present disclosure, but it does not mean that the embodiments of the present disclosure cannot be used in other devices, systems, environments or scenarios.

[0059] like Figure 1 As shown, the system architecture 100 according to this embodiment may include terminal devices 101, 102, 103, a network 104 and a server 105. The network 104 is used to provide a medium for communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired and / or wireless communication links, etc.

[0060] Users can use terminal devices 101, 102, 103 to interact with server 105 through network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101, 102, 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients and / or social platform software, etc. (only as examples).

[0061] The terminal devices 101 , 102 , and 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, and desktop computers.

[0062] The server 105 may be a server that provides various services, such as a background management server (only an example) that provides support for websites browsed by users using the terminal devices 101, 102, and 103. The background management server may analyze and process the received data such as user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal device.

[0063] It should be noted that the boost determination method provided in the embodiment of the present disclosure can generally be performed by the server 105. Accordingly, the boost determination device provided in the embodiment of the present disclosure can generally be arranged in the server 105. The boost determination method provided in the embodiment of the present disclosure can also be performed by a server or server cluster that is different from the server 105 and can communicate with the terminal devices 101, 102, 103 and / or the server 105. Correspondingly, the boost determination device provided in the embodiment of the present disclosure can also be arranged in a server or server cluster that is different from the server 105 and can communicate with the terminal devices 101, 102, 103 and / or the server 105. Alternatively, the boost determination method provided in the embodiment of the present disclosure can also be performed by the terminal devices 101, 102, or 103, or can also be performed by other terminal devices different from the terminal devices 101, 102, or 103. Correspondingly, the boost determination device provided in the embodiment of the present disclosure may also be arranged in the terminal device 101 , 102 , or 103 , or in other terminal devices different from the terminal device 101 , 102 , or 103 .

[0064] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0065] Figure 2 The flowchart of the boost pressure determination method according to the embodiment of the present disclosure is schematically shown.

[0066] like Figure 2 As shown, the boost pressure determination method for an engine includes operations S201-S204.

[0067] In operation S201, operating condition data of the engine under all operating conditions is extracted to obtain target operating condition parameters of the engine, wherein the operating condition data represents the relationship between engine speed, torque and time;

[0068] In operation S202, a genetic algorithm and a target engine simulation model are used to perform a joint solution to obtain a target supercharging parameter with the lowest engine fuel consumption rate, wherein the target engine simulation model is operated under target operating parameters, and the target engine simulation model is generated according to the configuration parameters of the engine and a simple supercharger model;

[0069] In operation S203, based on the target operating condition parameters, according to the target boost parameters and the target engine simulation model, a supercharger boundary condition is determined;

[0070] In operation S204, a supercharger model corresponding to the engine is determined according to the target supercharging parameters and the supercharger boundary conditions.

[0071] According to an embodiment of the present disclosure, the operating condition data Engine_map is an array, the first column of Engine_map is time, the second column is the engine speed at each time step, and the third column is the engine torque at each time step. The operating condition data under full operating conditions may refer to the engine data recorded when a vehicle equipped with the engine is running on a specific road spectrum (e.g., part of an urban road and part of a suburban road), wherein the vehicle may be a pure fuel-driven vehicle or a hybrid vehicle, and the present disclosure uses a hybrid vehicle for exemplary description.

[0072] According to an embodiment of the present disclosure, the engine operating condition data is extracted and analyzed to obtain the target operating condition parameters of the engine under the target operating condition, wherein the target operating condition may refer to the commonly used operating condition of the engine, such as the speed and torque within the efficient operating range of the engine at the most fuel-efficient vehicle speed.

[0073] According to the embodiment of the present disclosure, a target engine simulation model operating under target operating parameters is constructed, and the supercharger model of the target engine simulation model is a simple supercharger model that does not use a specific supercharger map. The optimal target supercharging parameters of the simple supercharger model, such as the turbine equivalent nozzle area of ​​the supercharger, can be determined by using a genetic algorithm to jointly solve the model. The target operating parameters are then brought back to the target engine simulation model, so that the supercharger boundary conditions can be determined. Finally, the supercharger model corresponding to the engine can be determined using the target supercharging parameters and the supercharger boundary conditions, thereby determining the supercharger corresponding to the engine.

[0074] According to the embodiment of the present disclosure, the target operating parameters of the engine are obtained by extracting the operating data of the engine under all operating conditions, and the target supercharging parameters are obtained by joint solution using the genetic algorithm and the target engine simulation model. Based on the target supercharging parameters, the supercharger boundary conditions are determined according to the target supercharging parameters and the target engine simulation model. Finally, the supercharger model corresponding to the engine is determined according to the target supercharging parameters and the supercharger boundary conditions. By combining the genetic algorithm with the target engine simulation model, the changing trend of the engine performance when the key parameters of the supercharging system change can be accurately predicted, and the matching process can be completed without multiple iterations, saving matching time. At the same time, the use of the simple supercharger model reduces the number of optimization variables and combined with the genetic algorithm can ensure that the supercharger can operate in the most efficient area under the target operating conditions, maximizing the operating efficiency of the engine.

[0075] Figure 3 A code schematic diagram of parameter extraction according to an embodiment of the present disclosure is schematically shown.

[0076] According to an embodiment of the present disclosure, the extraction of target operating condition parameters can be performed using Figure 3 The Matlab program shown, other programs capable of performing the extraction may also be used.

[0077] Figure 4 The structural diagram of the target engine simulation model according to the embodiment of the present disclosure is schematically shown.

[0078] According to an embodiment of the present disclosure, the target engine simulation model is generated in the following manner:

[0079] Get the configuration parameters of the engine;

[0080] Using preset simulation software to build an initial engine simulation model based on configuration parameters, wherein the initial engine simulation model at least includes a supercharging system model, an engine model, and an intake air cooler model;

[0081] A simple supercharger model is used to replace the supercharging system model in the initial engine simulation model to obtain a target engine simulation model, wherein the simple supercharger model is a supercharger model that does not require a detailed supercharger map and can determine the supercharger operating state in a single working condition only by setting parameters, and the setting parameters include compressor efficiency, turbine efficiency, turbine flow regulating bypass valve flow surface diameter, turbine equivalent nozzle area, etc.

[0082] According to an embodiment of the present disclosure, the configuration parameters may refer to the factory configuration parameters of the engine, such as intake and exhaust lines, valve timing, etc., and the preset simulation software may be GT-Power simulation software.

[0083] According to an embodiment of the present disclosure, in the constructed initial engine simulation model, the engine cylinder combustion can use the DIWiebe non-predictive model to achieve fast solution, the cylinder heat transfer can use the Woschni model, and the engine controls the cyclic injection amount by setting BMEP.

[0084] According to an embodiment of the present disclosure, the supercharging system model is replaced with a simple supercharger model that does not require a specific MAP diagram (i.e., supercharger map) based on the initial engine simulation model. The single-stage simple supercharger model is as follows: Figure 4 As shown, the simple supercharger model uses the compressor (Compressor Simple) module to simulate the compressor operating state, and uses the turbine (Turbine Simple) module to simulate the turbine operating state.

[0085] According to an embodiment of the present disclosure, before replacing the supercharging system model with the simplified supercharger model, the method further includes:

[0086] Running the initial engine simulation model and outputting operating parameters, wherein the operating parameters at least include fuel consumption rate, maximum combustion pressure in the cylinder, intake flow and pressure, and exhaust pressure;

[0087] When the difference between the operating parameters and the calibration parameters of the engine is greater than a preset error range, the model parameters of the initial engine simulation model are adjusted to obtain an adjusted initial engine simulation model, so as to replace the supercharger system model in the adjusted initial engine simulation model with a simple supercharger model.

[0088] According to an embodiment of the present disclosure, the calibration parameters may refer to factory parameters of the engine, such as fuel consumption rate, maximum combustion pressure in cylinder, intake flow and pressure, exhaust pressure, etc. The preset error range may be specifically set according to actual needs, such as 3%.

[0089] According to an embodiment of the present disclosure, in order to avoid the problem of mismatch between the determined supercharger model and the engine due to inaccurate model, it is necessary to calibrate the constructed initial engine simulation model. Therefore, the initial engine simulation model is first run, and the difference between the output operating parameters and the calibration parameters of the factory configuration is calculated. If the calculated difference value is greater than the preset error range, it is necessary to adjust the model parameters of the initial engine simulation model until the calculated difference value is less than the preset error range. At this time, the simple supercharger model is used to replace the boost system model in the adjusted initial engine simulation model. The calibrated model can be more similar to the actual engine, so that the supercharger determined by the method of the present disclosure can be more suitable for the engine.

[0090] Figure 5 The structural diagram of a simple supercharger model according to an embodiment of the present disclosure is schematically shown. Figure 6 The figure schematically shows an input parameter diagram of a simple supercharger model according to an embodiment of the present disclosure.

[0091] According to an embodiment of the present disclosure, a target engine simulation model is iteratively solved using a genetic algorithm to obtain target boost parameters, including:

[0092] When the target engine simulation model is operated under the target operating parameters, the engine fuel consumption rate and the maximum combustion pressure in the cylinder of the simple supercharger model in the target engine simulation model are iteratively solved by using the engine simulation model under different turbine equivalent nozzle areas, wherein the turbine equivalent nozzle area satisfies a preset nozzle constraint condition;

[0093] Based on preset combustion pressure constraints and minimum fuel consumption rate, the genetic algorithm is used to process input data to obtain a target turbine equivalent nozzle area, wherein the target boost parameter includes the target turbine equivalent nozzle area, and the input data includes multiple turbine equivalent nozzle areas, the engine fuel consumption rate corresponding to each turbine equivalent nozzle area, and the maximum combustion pressure in the cylinder.

[0094] According to an embodiment of the present disclosure, the present disclosure is exemplified by two-stage supercharging:

[0095] According to an embodiment of the present disclosure, the compressor module calculates the intake mass flow rate and the supercharger outlet temperature based on the inlet temperature, pressure ratio, efficiency and input power. The turbine module uses a simple orifice flow model and external efficiency to predict the output power, mass flow rate and outlet temperature, calculates the mass flow rate by the inlet pressure and outlet pressure, calculates the output power by the pressure ratio, mass flow rate and efficiency, and calculates the outlet temperature by the pressure ratio and efficiency. In the absence of a specific supercharger MAP diagram (i.e., supercharger spectrum diagram), the use of this simple supercharger model can obtain the trend of engine performance changes when the relevant parameters of the turbocharged engine change.

[0096] According to the embodiments of the present disclosure, Figure 5 The input parameters for the simple supercharger model shown are Figure 6 As shown, the compressor module input parameter is the compressor efficiency η C and compressor shaft work W C ; The input parameter of the turbine module is the turbine efficiency η T , Turbine flow control bypass valve flow surface diameter d T and turbine equivalent nozzle area F T For the supercharger system model using a simple supercharger model, the compressor shaft work W C Provided by the turbine power output, the compressor efficiency η C and turbine efficiency η T It can be set according to the supercharger technology level that the supercharger manufacturer can provide (the common range is 0.6-0.8).

[0097] According to the embodiment of the present disclosure, the supercharging system matching work for the two-stage supercharging system matching target working condition only needs to determine the turbine equivalent nozzle area F of the supercharger. T The diameter d of the flow regulating bypass valve of the turbine under this condition TTo ensure that the high- and low-pressure stage turbines operate as efficiently as possible when the two-stage supercharging system matches the target operating conditions, the high- and low-pressure stage turbine flow control bypass valves are not opened when the two-stage supercharging system matches the target operating conditions, and the intercooler temperature of the interstage cooling zone module is set to the rated point of 50°C, and the two-stage supercharging system matches the target operating conditions of 38°C. Through the above analysis, the optimization variables are determined to be the high- and low-pressure stage turbine equivalent nozzle areas F HT and F LT .

[0098] According to the embodiment of the present disclosure, the target engine simulation model is adjusted so that the engine runs at the speed and torque under the target operating parameters, and the engine fuel consumption rate and the maximum combustion pressure in the cylinder corresponding to different turbine equivalent nozzle areas can be output. Of course, the turbine equivalent nozzle areas at this time all meet the preset nozzle constraint conditions, and the preset nozzle constraint conditions are the turbine equivalent nozzle area range determined based on prior knowledge. The target engine simulation model is coupled with the genetic algorithm solver using the genetic algorithm tool of GT-Power, that is, multiple turbine equivalent nozzle areas, the engine fuel consumption rate and the maximum combustion pressure in the cylinder corresponding to each of the turbine equivalent nozzle areas are jointly solved, so as to realize the high and low pressure stage turbine equivalent nozzle area F HT and F LT The optimization operation is solved by using the NSGA-III genetic algorithm, which can be used to calculate nonlinear problems with multiple independent variables (i.e., turbine equivalent nozzle area, engine fuel consumption rate, and maximum combustion pressure in the cylinder) and multiple constraints (i.e., preset combustion pressure constraints, minimum fuel consumption rate, and preset nozzle constraints). It can be used in the supercharger matching process to obtain the global optimal solution of the key parameters of the supercharger for a single working condition, thereby determining the optimization variables of the genetic algorithm as shown in formula (1):

[0099] X = {F HT , F LT} (1)

[0100] Among them, F HT is the high-pressure turbine equivalent nozzle area, that is, the high-pressure turbine equivalent nozzle area, in mm 2 ; F HT is the low-pressure turbine equivalent nozzle area, that is, the low-pressure turbine equivalent nozzle area, in mm 2 In order to reduce the amount of calculation and consider the actual working performance of the two-stage booster system, the value range of the preset nozzle constraint conditions is shown in Table 1.

[0101] Table 1

[0102] Optimization variables Value range <![CDATA[F HT / mm 2 ]]> 0～20000 <![CDATA[F LT / mm 2 ]]> 0～20000

[0103] It should be noted that if the optimization variable X = F is used for single-stage superchargingT , the corresponding preset nozzle constraint value range is 0 to 20000.

[0104] According to an embodiment of the present disclosure, under the condition of satisfying the preset nozzle constraint condition, the optimization variables are optimized and calculated by matching the target operating condition parameters in the two-stage supercharging system so that the engine fuel consumption rate f(X) reaches the minimum, that is, min f(X), wherein the preset combustion pressure constraint condition is as shown in formula (2):

[0105] P i (X)≤P max (2)

[0106] Among them, P i is the maximum combustion pressure of the engine, in MPa; P max is the maximum combustion pressure limit of the engine allowed by the engine mechanical strength. The genetic algorithm parameter settings are shown in Table 2.

[0107] Table 2

[0108] Setting parameters Value Group size 10 Maximum number of iterations 50 Crossover probability 0.7 Mutation probability 0.01

[0109] According to the embodiment of the present disclosure, the optimal high- and low-pressure stage turbine equivalent nozzle areas F of the two-stage supercharging system matching the target operating parameters can be obtained by finally completing the optimization process. HTO and F LTO , that is, the target high-pressure turbine equivalent nozzle area F HTO and the target low-pressure turbine equivalent nozzle area F LTO .

[0110] According to the embodiments of the present disclosure, the present disclosure determines the target boost parameters by jointly solving the genetic algorithm and the target engine simulation model. Compared with the related art of calculating the engine fuel consumption rate and the maximum combustion pressure in the cylinder for each turbine equivalent nozzle area, and then determining the turbine equivalent nozzle area corresponding to the minimum engine fuel consumption rate, the method of the present disclosure can obtain the optimal target turbine equivalent nozzle area under the condition of multiple independent variable inputs, and the target turbine equivalent nozzle area balances the engine fuel consumption rate and the maximum combustion pressure in the cylinder, thereby helping to improve the overall performance of the engine + boost system constructed using the target turbine equivalent nozzle area determined by the present disclosure.

[0111] According to an embodiment of the present disclosure, the target boost parameters include a target high-pressure turbine equivalent nozzle area of ​​the high-pressure stage supercharger and a target low-pressure turbine equivalent nozzle area of ​​the low-pressure stage supercharger;

[0112] Wherein, based on the target operating condition parameters, according to the target boost parameters and the target engine simulation model, the supercharger boundary conditions are determined, including:

[0113] The target high-pressure turbine equivalent nozzle area and the target low-pressure turbine equivalent nozzle area are input into the target engine simulation model to obtain the modified target engine simulation model.

[0114] The modified target engine simulation model is run under the target operating parameters to output the engine's intake air flow rate and the pressure ratio between the high-pressure stage supercharger and the low-pressure stage supercharger, wherein the supercharger boundary conditions include the intake air flow rate and the pressure ratio.

[0115] According to an embodiment of the present disclosure, the target high-pressure turbine equivalent nozzle area F HTO and the target low-pressure turbine equivalent nozzle area F LTO The simple supercharger model in the target engine simulation model is brought back for simulation calculation. The engine is operated at the speed and torque of the target operating parameters. The intake flow rate and the high- and low-pressure stage supercharger pressure ratio when the engine is running in this state are recorded. This is the supercharger boundary condition under the optimal matching scheme of the two-stage supercharger.

[0116] According to an embodiment of the present disclosure, determining a supercharger model corresponding to an engine according to target supercharging parameters and supercharger boundary conditions includes:

[0117] The supercharger models of the high-pressure stage supercharger and the low-pressure stage supercharger are determined respectively according to the target high-pressure turbine equivalent nozzle area and the target low-pressure turbine equivalent nozzle area and the supercharger boundary conditions.

[0118] According to an embodiment of the present disclosure, the target high-pressure turbine equivalent nozzle area F HTO and the target low-pressure turbine equivalent nozzle area F LTO The supercharger boundary conditions under the optimal matching scheme of the two-stage supercharger are used as the basis for selecting the models of the high-pressure stage supercharger and the low-pressure stage supercharger in the two-stage supercharger, thereby confirming the models of the high-pressure stage supercharger and the low-pressure stage supercharger and the corresponding supercharger MAP diagram.

[0119] According to an embodiment of the present disclosure, the boost pressure determination method further includes:

[0120] Replacing the simplified supercharger model in the target engine simulation model with a common supercharger model to obtain a verification engine simulation model, wherein the common supercharger model uses a supercharger map of the target supercharger corresponding to the supercharger model;

[0121] Run and verify the engine simulation model under all operating conditions and output the operation results;

[0122] When the operation results show that both the common supercharger model and the engine model are operating normally, the target supercharger corresponding to the supercharger model is confirmed as a successfully matched supercharger.

[0123] According to the embodiment of the present disclosure, the simple supercharger model of the target engine simulation model that does not need to use a specific MAP diagram is replaced with a common supercharger model that uses a MAP diagram (i.e., a supercharger spectrum diagram) to confirm the working state of the supercharger. The verification engine simulation model is run within the full range of engine operating conditions, and the simulation verification of the two-stage supercharging matching result is performed to observe whether the supercharger has surge or other abnormal operating phenomena, and verify the supercharger operating characteristics and the working state of the engine within the full range of engine operating conditions. If normal, the two-stage supercharging scheme is successfully matched, so that the target supercharger corresponding to the confirmed supercharger model can be confirmed as a successfully matched supercharger.

[0124] Figure 7 The operating characteristics diagram of the low-pressure stage compressor according to an embodiment of the present disclosure is schematically shown. Figure 8 A schematic diagram of the operating characteristics of a high pressure stage compressor according to an embodiment of the present disclosure is schematically shown. Fig. 9 A schematic diagram of the improvement results of the fuel consumption rate of the engine matching the target operating condition according to an embodiment of the present disclosure is schematically shown.

[0125] According to an embodiment of the present disclosure, the boost determination method of the present disclosure is used to perform a hybrid engine two-stage boost matching operation on a single-stage variable geometry turbocharger (VGT) diesel engine, and the simulation results are as follows:

[0126] The operating characteristics of the low pressure compressor are as follows: Figure 7 As shown in Figure 2, it can be seen that when the engine is running at the matching point, the low-pressure compressor operates in the highest efficiency area of ​​the compressor with an efficiency higher than 0.8, and the operating characteristics of the high-pressure compressor are as follows: Figure 8 As shown in the figure, when the engine is running at the matching point, the high-pressure compressor operates in the compressor's highest efficiency zone with an efficiency higher than 0.81. The two-stage supercharger can operate in the highest efficiency zone at the target matching point and can also operate normally under the external characteristic conditions. It can be seen that the matched two-stage supercharger model is close to the optimal solution.

[0127] Fig. 9 The improvement of the fuel consumption rate of the engine matching the target operating condition shows that, by using the boost determination method of the present invention, the engine achieves a 4.9% improvement in fuel consumption rate under the common operating condition of the hybrid power system.

[0128] In summary, the boost determination method disclosed in the present invention can ensure that the two-stage supercharger can operate in the most efficient area under common hybrid operating conditions, effectively improving the fuel economy of the hybrid-specific engine.

[0129] Fig.10 The block diagram of the boost pressure determination device according to the embodiment of the present disclosure is schematically shown.

[0130] like Fig.10As shown, the boost pressure determination device 1000 for an engine includes an extraction module 1010 , an iteration module 1020 , a first determination module 1030 , and a second determination module 1040 .

[0131] An extraction module 1010 is used to extract the operating condition data of the engine under all operating conditions to obtain the target operating condition parameters of the engine, wherein the operating condition data represents the relationship between the engine speed, torque and time;

[0132] Iteration module 1020, used for performing joint solution using genetic algorithm and target engine simulation model to obtain target supercharging parameters, wherein the target engine simulation model operates under target operating parameters, and the target engine simulation model is generated according to the configuration parameters of the engine and the simplified supercharger model;

[0133] A first determination module 1030 is used to determine a supercharger boundary condition based on a target operating condition parameter, a target boost parameter and a target engine simulation model;

[0134] The second determination module 1040 is used to determine the supercharger model corresponding to the engine according to the target supercharging parameters and the supercharger boundary conditions.

[0135] According to the embodiments of the present disclosure, the target operating parameters of the engine are obtained by extracting the operating data of the engine under all operating conditions, and the target supercharging parameters are obtained by joint solution using a genetic algorithm and a target engine simulation model. Based on the target operating parameters, the supercharger boundary conditions are determined according to the target supercharging parameters and the target engine simulation model. Finally, the supercharger model corresponding to the engine is determined according to the target supercharging parameters and the supercharger boundary conditions. By combining the genetic algorithm with the target engine simulation model, the changing trend of the engine performance when the key parameters of the supercharging system change can be accurately predicted, and the matching process can be completed without multiple iterations, saving matching time. At the same time, the use of a simple supercharger model reduces the number of optimization variables and combined with the genetic algorithm can ensure that the supercharger can operate in the most efficient area under the target operating conditions, maximizing the operating efficiency of the engine.

[0136] According to an embodiment of the present disclosure, a target engine simulation model is generated by an acquisition unit, a construction unit, and a obtaining unit.

[0137] An acquisition unit, used for acquiring configuration parameters of the engine;

[0138] A construction unit, configured to construct an initial engine simulation model based on configuration parameters using preset simulation software, wherein the initial engine simulation model at least includes a supercharging system model, an engine model, and an intake air cooler model;

[0139] A unit is obtained, which is used to replace the supercharging system model in the initial engine simulation model with a simple supercharger model to obtain a target engine simulation model, wherein the simple supercharger model is a supercharger model that does not require a detailed supercharger map and can determine the supercharger operating state in a single working condition only by setting parameters, and the setting parameters include compressor efficiency, turbine efficiency, turbine flow regulating bypass valve flow surface diameter and turbine equivalent nozzle area.

[0140] According to an embodiment of the present disclosure, a first operating unit and an adjusting unit are further included between the constructing unit and the obtaining unit.

[0141] A first operation unit is used to operate the initial engine simulation model and output operation parameters, wherein the operation parameters at least include fuel consumption rate, maximum combustion pressure in the cylinder, intake flow and pressure, and exhaust pressure;

[0142] The adjustment unit is used to adjust the model parameters of the initial engine simulation model when the difference between the operating parameters and the calibration parameters of the engine is greater than a preset error range, so as to obtain an adjusted initial engine simulation model, so as to replace the supercharging system model in the adjusted initial engine simulation model with a simple supercharger model.

[0143] According to an embodiment of the present disclosure, the iteration module 1020 includes a solving unit and a first determining unit.

[0144] A solving unit is used for iteratively solving the engine fuel consumption rate and the maximum combustion pressure in the cylinder of the simple supercharger model in the target engine simulation model under different turbine equivalent nozzle areas by using the engine simulation model when the target engine simulation model is running under the target operating parameters, wherein the turbine equivalent nozzle area satisfies the preset nozzle constraint condition;

[0145] The first determination unit is used to process input data using a genetic algorithm based on preset combustion pressure constraints and a minimum fuel consumption rate to obtain a target turbine equivalent nozzle area, wherein the target boost parameter includes a target turbine equivalent nozzle area, and the input data includes multiple turbine equivalent nozzle areas, the engine fuel consumption rate corresponding to each turbine equivalent nozzle area, and a maximum combustion pressure in the cylinder.

[0146] According to an embodiment of the present disclosure, the boost determination device 1000 further includes a replacement module, an operation module, and a third determination module.

[0147] A replacement module, used to replace the simplified supercharger model in the target engine simulation model with a common supercharger model to obtain a verification engine simulation model, wherein the common supercharger model uses a supercharger map of the target supercharger corresponding to the supercharger model;

[0148] The operation module is used to run and verify the engine simulation model under all working conditions and output the operation results;

[0149] The third determination module is used to confirm the target supercharger corresponding to the supercharger model as a successfully matched supercharger when the operation result shows that the common supercharger model and the engine model are both operating normally.

[0150] According to an embodiment of the present disclosure, the target boost parameters include a target high-pressure turbine equivalent nozzle area of ​​the high-pressure stage supercharger and a target low-pressure turbine equivalent nozzle area of ​​the low-pressure stage supercharger.

[0151] According to an embodiment of the present disclosure, the first determining module 1030 includes an input unit and a second operating unit.

[0152] An input unit is used to input a target high-pressure turbine equivalent nozzle area and a target low-pressure turbine equivalent nozzle area into a target engine simulation model to obtain a modified target engine simulation model

[0153] The second operating unit is used to operate the modified target engine simulation model under the target operating parameters, and output the engine's intake flow rate, and the pressure ratio between the high-pressure stage supercharger and the low-pressure stage supercharger, wherein the supercharger boundary conditions include the intake flow rate and the pressure ratio.

[0154] According to an embodiment of the present disclosure, the second determining module 1040 includes a second determining unit.

[0155] The second determination unit is used to determine the supercharger models of the high-pressure stage supercharger and the low-pressure stage supercharger respectively according to the target high-pressure turbine equivalent nozzle area and the target low-pressure turbine equivalent nozzle area and the supercharger boundary conditions.

[0156] According to the modules and units of the embodiments of the present disclosure, any multiple or at least part of the functions of any multiple thereof can be implemented in one module. According to the modules and units of the embodiments of the present disclosure, any one or more can be split into multiple modules for implementation. According to the modules and units of the embodiments of the present disclosure, any one or more can be at least partially implemented as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a System on a Chip, a System on a Substrate, a System on a Package, an Application Specific Integrated Circuit (ASIC), or can be implemented by hardware or firmware of any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation modes of software, hardware and firmware or in any appropriate combination of any of them. Alternatively, according to the modules and units of the embodiments of the present disclosure, one or more can be at least partially implemented as a computer program module, and when the computer program module is run, the corresponding function can be executed.

[0157] For example, any multiple of the extraction module 1010, the iteration module 1020, the first determination module 1030, and the second determination module 1040 can be combined in one module / unit for implementation, or any one of the modules / units can be split into multiple modules / units. Alternatively, at least part of the functions of one or more of these modules / units can be combined with at least part of the functions of other modules / units and implemented in one module / unit. According to an embodiment of the present disclosure, at least one of the extraction module 1010, the iteration module 1020, the first determination module 1030, and the second determination module 1040 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation methods of software, hardware, and firmware or in an appropriate combination of any of them. Alternatively, at least one of the extraction module 1010, the iteration module 1020, the first determination module 1030, and the second determination module 1040 may be at least partially implemented as a computer program module, and when the computer program module is executed, a corresponding function may be performed.

[0158] It should be noted that the boost pressure determination device part in the embodiment of the present disclosure corresponds to the boost pressure determination method part in the embodiment of the present disclosure, and the description of the boost pressure determination device part specifically refers to the boost pressure determination method part, which will not be repeated here.

[0159] Fig.11 A block diagram of an electronic device suitable for implementing the method described above according to an embodiment of the present disclosure is schematically shown. Fig.11 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0160] like Fig.11 As shown, the electronic device 1100 according to an embodiment of the present disclosure includes a processor 1101, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1102 or a program loaded from a storage part 1108 to a random access memory (RAM) 1103. The processor 1101 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 1101 may also include an onboard memory for caching purposes. The processor 1101 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0161] In RAM 1103, various programs and data required for the operation of electronic device 1100 are stored. Processor 1101, ROM 1102 and RAM 1103 are connected to each other through bus 1104. Processor 1101 performs various operations of the method flow according to the embodiment of the present disclosure by executing the program in ROM 1102 and / or RAM 1103. It should be noted that the program can also be stored in one or more memories other than ROM 1102 and RAM 1103. Processor 1101 can also perform various operations of the method flow according to the embodiment of the present disclosure by executing the program stored in the one or more memories.

[0162] According to an embodiment of the present disclosure, the electronic device 1100 may further include an input / output (I / O) interface 1105, which is also connected to the bus 1104. The system 1100 may further include one or more of the following components connected to the I / O interface 1105: an input portion 1106 including a keyboard, a mouse, etc.; an output portion 1107 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 1108 including a hard disk, etc.; and a communication portion 1109 including a network interface card such as a LAN card, a modem, etc. The communication portion 1109 performs communication processing via a network such as the Internet. A drive 1110 is also connected to the I / O interface 1105 as needed. A removable medium 1111, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 1110 as needed, so that a computer program read therefrom is installed into the storage portion 1108 as needed.

[0163] According to an embodiment of the present disclosure, the method flow according to an embodiment of the present disclosure can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable storage medium, and the computer program contains a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 1109, and / or installed from the removable medium 1111. When the computer program is executed by the processor 1101, the above-mentioned functions defined in the system of the embodiment of the present disclosure are executed. According to an embodiment of the present disclosure, the system, equipment, device, module, unit, etc. described above can be implemented by a computer program module.

[0164] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

[0165] According to an embodiment of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium. For example, it may include, but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM (Erasable Programmable Read Only Memory, EPROM) or flash memory), a portable compact disk read-only memory (Computer Disc Read-Only Memory, CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, an apparatus or a device.

[0166] For example, according to an embodiment of the present disclosure, the computer-readable storage medium may include the ROM 1102 and / or the RAM 1103 described above and / or one or more memories other than the ROM 1102 and the RAM 1103 .

[0167] An embodiment of the present disclosure also includes a computer program product, which includes a computer program, and the computer program contains a program code for executing the method provided by the embodiment of the present disclosure. When the computer program product runs on an electronic device, the program code is used to enable the electronic device to implement the boost determination method provided by the embodiment of the present disclosure.

[0168] When the computer program is executed by the processor 1101, the above functions defined in the system / device of the embodiment of the present disclosure are executed. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0169] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices, magnetic storage devices, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of signals on a network medium, and downloaded and installed through the communication part 1109, and / or installed from a removable medium 1111. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0170] According to an embodiment of the present disclosure, the program code for executing the computer program provided by the embodiment of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect through the Internet).

[0171] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions. It can be understood by those skilled in the art that the features recorded in the various embodiments and / or claims of the present disclosure can be combined and / or combined in a variety of ways, even if such a combination or combination is not explicitly recorded in the present disclosure. In particular, without departing from the spirit and teaching of the present disclosure, the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in a variety of ways. All of these combinations and / or combinations fall within the scope of the present disclosure.

[0172] The embodiments of the present disclosure are described above. However, these embodiments are only for illustrative purposes and are not intended to limit the scope of the present disclosure. Although the embodiments are described above separately, this does not mean that the measures in the various embodiments cannot be used in combination to advantage. The scope of the present disclosure is defined by the attached claims and their equivalents. Without departing from the scope of the present disclosure, those skilled in the art may make a variety of substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims

1. A method for determining boost pressure of an engine, comprising: Extracting the operating condition data of the engine under all operating conditions to obtain the target operating condition parameters of the engine, wherein the operating condition data represents the relationship between the engine speed, torque and time; The genetic algorithm and the target engine simulation model are used to jointly solve the target boost parameters, including: When the target engine simulation model is operated under the target operating parameters, the engine simulation model is used to iteratively solve the engine fuel consumption rate and the maximum combustion pressure in the cylinder of the simple supercharger model in the target engine simulation model under different turbine equivalent nozzle areas, wherein the turbine equivalent nozzle area satisfies the preset nozzle constraint condition; Based on the preset combustion pressure constraint and the minimum fuel consumption rate, the input data is processed by the genetic algorithm to obtain the target turbine equivalent nozzle area, wherein the target boost parameter includes the target turbine equivalent nozzle area, and the input data includes a plurality of turbine equivalent nozzle areas, the engine fuel consumption rate corresponding to each of the turbine equivalent nozzle areas, and the maximum combustion pressure in the cylinder; Based on the target operating condition parameters, according to the target boost parameters and the target engine simulation model, determining a supercharger boundary condition; Determining a supercharger model corresponding to the engine according to the target supercharging parameter and the supercharger boundary condition; Wherein, the target engine simulation model is generated in the following manner: Obtaining configuration parameters of the engine; Using preset simulation software to construct an initial engine simulation model based on the configuration parameters, wherein the initial engine simulation model at least includes a supercharging system model, an engine model, and an intake air cooler model; The target engine simulation model is obtained by replacing the supercharging system model in the initial engine simulation model with a simple supercharger model, wherein the simple supercharger model is a supercharger model that can determine the supercharger operating state in a single working condition only by setting parameters without using a detailed supercharger map, and the setting parameters include compressor efficiency, turbine efficiency, turbine flow regulating bypass valve flow surface diameter and turbine equivalent nozzle area.

2. The method according to claim 1, before replacing the supercharging system model with the simplified supercharger model, further comprises: Running the initial engine simulation model and outputting operating parameters, wherein the operating parameters at least include fuel consumption rate, maximum combustion pressure in cylinder, intake flow and pressure, and exhaust pressure; When the difference between the operating parameters and the calibration parameters of the engine is greater than a preset error range, the model parameters of the initial engine simulation model are adjusted to obtain an adjusted initial engine simulation model, so as to replace the supercharging system model in the adjusted initial engine simulation model with the simple supercharger model.

3. The method according to claim 1, wherein: The target turbine equivalent nozzle area includes a turbine equivalent nozzle area applicable to a single-stage supercharger or a target high-pressure turbine equivalent nozzle area applicable to a high-pressure stage supercharger of a two-stage supercharger and a target low-pressure turbine equivalent nozzle area of ​​a low-pressure stage supercharger.

4. The method according to claim 1, further comprising: Replacing the simplified supercharger model in the target engine simulation model with a common supercharger model to obtain a verification engine simulation model, wherein the common supercharger model uses a supercharger map of a target supercharger corresponding to the supercharger model; Running the verification engine simulation model under all working conditions and outputting the running results; When the operation result indicates that both the common supercharger model and the engine model are operating normally, the target supercharger corresponding to the supercharger model is confirmed as a successfully matched supercharger.

5. The method according to claim 1, wherein the target boost parameters include a target high-pressure turbine equivalent nozzle area of ​​a high-pressure stage supercharger and a target low-pressure turbine equivalent nozzle area of ​​a low-pressure stage supercharger; in, Based on the target operating condition parameters, according to the target boost parameters and the target engine simulation model, determining a supercharger boundary condition includes: Inputting the target high-pressure turbine equivalent nozzle area and the target low-pressure turbine equivalent nozzle area into the target engine simulation model to obtain a modified target engine simulation model; The modified target engine simulation model is run under the target operating parameters to output the intake flow rate of the engine and the pressure ratio between the high-pressure stage supercharger and the low-pressure stage supercharger, wherein the supercharger boundary condition includes the intake flow rate and the pressure ratio.

6. The method according to claim 5, wherein: Determining a supercharger model corresponding to the engine according to the target supercharging parameter and the supercharger boundary condition includes: The supercharger models of the high-pressure stage supercharger and the low-pressure stage supercharger are determined respectively according to the target high-pressure turbine equivalent nozzle area, the target low-pressure turbine equivalent nozzle area and the supercharger boundary conditions.

7. The method according to claim 1, wherein: The engine is a fuel engine in a hybrid transportation device.

8. A boost pressure determination device for an engine, comprising: An extraction module, used for extracting the operating condition data of the engine under all operating conditions to obtain the target operating condition parameters of the engine, wherein the operating condition data represents the relationship between the engine speed, torque and time; The iteration module is used to jointly solve the target boost parameters using the genetic algorithm and the target engine simulation model, including: A solving unit is used for iteratively solving the engine fuel consumption rate and the maximum combustion pressure in the cylinder of the simple supercharger model in the target engine simulation model under different turbine equivalent nozzle areas by using the engine simulation model when the target engine simulation model is running under the target operating parameters, wherein the turbine equivalent nozzle area satisfies the preset nozzle constraint condition; a first determination unit, configured to process input data using a genetic algorithm based on a preset combustion pressure constraint and a minimum fuel consumption rate to obtain a target turbine equivalent nozzle area, wherein the target boost parameter includes a target turbine equivalent nozzle area, and the input data includes a plurality of turbine equivalent nozzle areas, an engine fuel consumption rate corresponding to each turbine equivalent nozzle area, and a maximum combustion pressure in a cylinder; A first determination module, configured to determine a supercharger boundary condition based on the target operating condition parameter, the target boost parameter and the target engine simulation model; A second determination module, configured to determine a supercharger model corresponding to the engine according to the target supercharging parameter and the supercharger boundary condition; Wherein, the target engine simulation model is generated by acquiring a unit, constructing a unit, and obtaining a unit; The acquisition unit is used to acquire configuration parameters of the engine; The construction unit is used to construct an initial engine simulation model based on the configuration parameters using preset simulation software, wherein the initial engine simulation model at least includes a supercharging system model, an engine model and an intake air cooler model; The obtaining unit is used to replace the supercharging system model in the initial engine simulation model with a simple supercharger model to obtain a target engine simulation model, wherein the simple supercharger model is a supercharger model that does not require a detailed supercharger map and can determine the supercharger operating state in a single working condition only by setting parameters, and the setting parameters include compressor efficiency, turbine efficiency, turbine flow regulating bypass valve flow surface diameter and turbine equivalent nozzle area.

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