Intelligent calibration method and device, electronic equipment, storage medium and vehicle
By optimizing parameter variables and DOE tests, an engine model was established, and automated calibration was performed using the algorithm model. This solved the problems of long time cycles and high costs in the diesel engine calibration process, and achieved an efficient and reliable calibration process.
Patent Information
- Application Number
- CN202511782023.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-29
- Publication Date
- 2026-01-23
AI Technical Summary
During the diesel engine calibration process, the number and dimensions of control parameters explode, resulting in a huge workload for testing and verification, a long time cycle, high development costs, and extremely high requirements for the experience and technical level of calibration engineers.
By optimizing the target parameters and their range, DOE tests are conducted to establish an engine model. The algorithm model is then used for calibration to automatically balance engine performance and function, achieving a fully automated calibration process.
It reduces calibration time, lowers development costs, improves R&D efficiency, and ensures the authenticity and reliability of calibration data and system optimization.
Smart Images
Figure CN121384476A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of diesel engine calibration application technology, and in particular to intelligent calibration methods, devices, electronic equipment, storage media, and vehicles. Background Technology
[0002] Diesel engine calibration technology is a crucial part of modern diesel engine development, serving as the core bridge connecting advanced hardware and the final product. It involves meticulously adjusting a vast number of parameters within the Electronic Control Unit (ECU) to comprehensively optimize engine power, economy, emissions, reliability, and driving smoothness across the entire operating range, thereby finding the optimal balance among conflicting performance indicators. Crucially, accurate calibration is the only way to ensure diesel engines meet increasingly stringent requirements, enabling complex after-treatment systems to work efficiently and collaboratively. This is a prerequisite for legally launching a product and a decisive factor in unlocking hardware potential, defining product competitiveness, and enhancing user experience.
[0003] The number and dimensions of control parameters have exploded, requiring the calibration of tens of thousands of MAPs (data maps). The testing and verification workload is enormous. It necessitates conducting "three-high" tests globally—high-altitude, high-temperature, and high-cold—as well as countless Real Driving Emissions (RDE) tests, totaling tens or even millions of kilometers. This demands extremely high levels of experience, technical expertise, and systems engineering thinking from calibration engineers, resulting in long development cycles and extremely high development costs. Summary of the Invention
[0004] The purpose of this invention is to provide an intelligent calibration method, intelligent calibration device, electronic device, storage medium, and vehicle, at least solving one of the technical problems of how to reduce the time cycle of calibration control parameters and how to reduce development costs.
[0005] This invention provides the following solution:
[0006] According to one aspect of the present invention, an intelligent calibration method is provided, comprising:
[0007] Obtain the optimization target to be calibrated for the target engine, and set the parameter variables related to the optimization target and the range of the parameter variables corresponding to the parameter variables;
[0008] Based on the parameter variables and their ranges, conduct DOE experiments and record the experimental data;
[0009] Based on the test data, an engine model corresponding to the target engine is established, and the optimization target is calibrated using the engine model.
[0010] Furthermore, a first parameter variable corresponding to the performance optimization target and a range of the first parameter variable corresponding to the first parameter variable are set;
[0011] Set the second parameter variable corresponding to the function optimization goal, and the range of the second parameter variable corresponding to the second parameter variable.
[0012] Furthermore, based on the performance optimization objective, the type of performance optimization is determined, and based on the type of performance optimization, the test conditions for the DOE test are determined;
[0013] Based on the first parameter variable and its corresponding first parameter variable range, the second parameter variable and its corresponding second parameter variable range, determine the execution variables of each actuator required to execute the test condition, as well as the working range of the execution variables;
[0014] The DOE experiment is performed based on the execution variables and the working scope, and the experiment data is recorded.
[0015] Furthermore, based on the first parameter variable and its corresponding first parameter variable range, the second parameter variable and its corresponding second parameter variable range, multiple algorithm models for establishing the engine model are initialized;
[0016] Train multiple preset algorithm models based on the experimental data, and determine the accuracy result corresponding to each algorithm model;
[0017] Among the multiple algorithm models, the first algorithm model corresponding to the optimal accuracy result is determined;
[0018] An engine model corresponding to the target engine is established based on the first algorithm model.
[0019] Furthermore, based on the performance optimization objective and the engine model, the cost function and optimization algorithm are determined;
[0020] Based on the cost function and the optimization algorithm, the optimal solution for the performance optimization objective is determined, and the performance optimization objective is calibrated based on the optimal solution.
[0021] The performance optimization target was adjusted through bench testing to determine the calibration result of the performance optimization target.
[0022] Furthermore, the calibration order of the functional optimization objectives is determined, and the optimization algorithm corresponding to each functional optimization objective is determined;
[0023] Using the engine model, the corresponding functional optimization objectives are calibrated according to the calibration order and the optimization algorithm.
[0024] The calibration results of the functional optimization target are determined by conducting bench tests to test and adjust the calibrated functional optimization target.
[0025] According to a second aspect of the present invention, an intelligent calibration device is provided, comprising:
[0026] The variable setting module is used to obtain the optimization target to be calibrated for the target engine, and to set the parameter variables related to the optimization target and the parameter variable range corresponding to the parameter variables;
[0027] The testing module is used to conduct DOE tests based on the parameter variables and the range of the parameter variables, and to record the test data;
[0028] The intelligent calibration module is used to establish an engine model corresponding to the target engine based on the test results, and to calibrate the optimization target through the engine model.
[0029] According to three aspects of the present invention, an electronic device is provided, comprising: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;
[0030] The memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of the intelligent calibration method.
[0031] According to four aspects of the present invention, a computer-readable storage medium is provided, comprising: storing a computer program executable by an electronic device, wherein when the computer program is run on the electronic device, the electronic device performs the steps of an intelligent calibration method.
[0032] According to five aspects of the present invention, a vehicle is provided, comprising:
[0033] Electronic equipment used to implement steps of intelligent calibration methods;
[0034] The processor runs a program, and when the program runs, it executes the steps of the intelligent calibration method based on data output from the electronic device.
[0035] Storage medium used to store programs that, when run, execute intelligent calibration methods on data output from electronic devices.
[0036] The above solution achieves the following beneficial technical effects:
[0037] This application optimizes the target parameters and their ranges to conduct DOE experiments, thereby reducing the number of experiments through structured experimental design, improving R&D efficiency, shortening trial and error time, and making the R&D process more efficient.
[0038] This application establishes an engine model corresponding to the target engine based on experimental results, which makes the established engine model closer to the target engine and makes the simulated data more realistic and reliable.
[0039] This application calibrates the optimization target using an engine model, automatically balancing engine performance and functions such as fuel consumption and exhaust temperature to achieve system optimization. Furthermore, the calibration process is fully automated, requiring no manual calibration. After system self-verification, calibration data is automatically generated, thereby reducing calibration time and development costs. Attached Figure Description
[0040] Figure 1 This is a flowchart of an intelligent calibration method provided by one or more embodiments of the present invention.
[0041] Figure 2 This is a schematic diagram of an intelligent calibration algorithm provided in a specific embodiment of the present invention.
[0042] Figure 3 This is a schematic diagram of the architecture for intelligent calibration of a diesel engine provided in a specific embodiment of the present invention.
[0043] Figure 4 This is a schematic diagram of intelligent calibration provided in a specific embodiment of the present invention.
[0044] Figure 5 This is a structural diagram of an intelligent calibration device provided in one or more embodiments of the present invention.
[0045] Figure 6 This is a block diagram of an electronic device structure for an intelligent calibration method provided in one or more embodiments of the present invention. Detailed Implementation
[0046] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0047] Figure 1 This is a flowchart of an intelligent calibration method provided by one or more embodiments of the present invention.
[0048] like Figure 1 The intelligent calibration methods shown include:
[0049] Step S1: Obtain the optimization target to be calibrated for the target engine, and set the parameter variables related to the optimization target and the range of the parameter variables.
[0050] Figure 2 This is a schematic diagram of an intelligent calibration algorithm provided in a specific embodiment of the present invention. For example... Figure 2 As shown, the algorithm includes a calibration guidance algorithm, a configuration settings GUI, a DOE automatic testing algorithm, an engine modeling system, a performance optimization algorithm, a performance result optimization algorithm, a function optimization algorithm, and a function result optimization algorithm. The optimization target is calibrated step-by-step through each algorithm. The following examples will illustrate how the optimization target is calibrated step-by-step through each algorithm.
[0051] In this embodiment, before defining the performance optimization goals and functional optimization goals, it is necessary to set the performance optimization goals and their corresponding parameter variables, as well as the functional optimization goals and their corresponding parameter variables. Furthermore, boundary conditions can be set for the parameter variables, i.e., the corresponding parameter variable ranges can be defined.
[0052] The optimization objectives to be calibrated include performance optimization objectives and functional optimization objectives. Further, a first parameter variable corresponding to the performance optimization objective and a range of the first parameter variable corresponding to the first parameter variable are set, and a second parameter variable corresponding to the functional optimization objective and a range of the second parameter variable corresponding to the second parameter variable are set.
[0053] It should be noted that the selection of functional optimization goals can be adjusted based on performance optimization goals.
[0054] Among them, parameter variables and their ranges can be set through a pre-configured graphical user interface (GUI).
[0055] This embodiment can set all parameter variable options, including engine parameters, based on the graphical user interface. This allows users to select parameter variables corresponding to the optimization target in the graphical user interface as needed, and further set the parameter variable range corresponding to the parameter variables based on the graphical user interface.
[0056] Step S2: Conduct a DOE experiment based on the parameter variables and their ranges, and record the experimental data.
[0057] Among them, DOE experiment is a systematic experimental design method.
[0058] Based on the optimization objective, its parameter variables, and their ranges, the parameters and ranges for the DOE experiment are further set, and the DOE experiment is conducted and the test data is recorded. The recorded test data is used to build an engine model corresponding to the target engine.
[0059] Furthermore, based on the performance optimization objective, the type of performance optimization is determined, and the test conditions for the DOE experiment are determined accordingly. Specifically, a corresponding DOE algorithm can be selected based on the performance optimization type, and the test condition design is determined based on the selected DOE algorithm, thus defining the DOE test conditions. The test condition design can include designing typical experiments related to the performance optimization objective.
[0060] Next, based on the first parameter variable and its corresponding range, and the second parameter variable and its corresponding range, the execution variables of each actuator required for the test conditions, as well as the working range of the execution variables, are determined. DOE tests are then conducted based on the execution variables and working ranges, and the test data is recorded.
[0061] Step S3: Based on the experimental data, establish an engine model corresponding to the target engine, and calibrate the optimization target using the engine model.
[0062] In this embodiment, multiple algorithm models for building the engine model are initialized based on the first parameter variable and its corresponding range, and the second parameter variable and its corresponding range. That is, the input and output variables for each algorithm model are determined, and the algorithm model is parameterized.
[0063] Multiple pre-set algorithm models are trained based on experimental data. The accuracy result corresponding to each algorithm model is determined. Among the multiple algorithm models, the first algorithm model corresponding to the optimal accuracy result is determined. Then, an engine model corresponding to the target engine is established based on the first algorithm model. The engine model includes data such as fuel consumption, exhaust temperature, and after-treatment emissions.
[0064] Based on the performance optimization objective and the engine model, the cost function and optimization algorithm are determined. After setting the performance optimization objective through the graphical user interface, the corresponding cost function is defined. An example of its execution code is as follows:
[0065] def hierarchical_cost_function(intake_throttle, exhaust_throttle, post_injection_params, target_temperature):
[0066] # Obtain actual performance metrics
[0067] actual_fuel_consumption = get_fuel_consumption(intake_throttle,exhaust_throttle, post_injection_params)
[0068] actual_temperature = get_exhaust_temperature(intake_throttle,exhaust_throttle, post_injection_params)
[0069] # Normalized fuel consumption
[0070] ref_fuel = 250 # g / kWh
[0071] normalized_fuel = actual_fuel_consumption / ref_fuel
[0072] # Stratification processing
[0073] if actual_temperature < target_temperature:
[0074] temperature_error = (target_temperature - actual_temperature) / target_temperature
[0075] cost = 10 + temperature_error
[0076] else
[0077] temperature_excess = (actual_temperature - target_temperature) / target_temperature
[0078] cost = normalized_fuel - 0.05 * temperature_excess
[0079] return cost
[0080] The optimization algorithm can be a non-dominated sorting genetic algorithm II (NSGA-II), a multi-objective particle swarm optimization algorithm (MOPSO), or similar algorithms. Based on the cost function and the optimization algorithm, the optimal solution for the performance optimization objective is determined, and the performance optimization objective is calibrated based on the optimal solution. For example, the optimal intake throttle valve, exhaust throttle valve, and rear injection angle are calculated to generate a mean average precision (MAP) map, resulting in a preliminary MAP map.
[0081] This embodiment can connect the engine bench test system and the calibration system of the electronic control unit, monitor the engine parameters measured by the bench test system, and control the calibration system of the electronic control unit according to system instructions.
[0082] Furthermore, bench tests are used to experimentally adjust the calibrated performance optimization targets, determine the calibration results of the performance optimization targets, and obtain the final calibration MAP. This experimental adjustment of the calibrated performance optimization targets through bench tests can involve online local optimization of the preliminary calibration MAP, thereby performing small-scale experimental adjustments to obtain the final calibration MAP.
[0083] It should be noted that if the final MAP plot does not meet expectations, the performance optimization target, the corresponding parameter variables and their ranges need to be readjusted and recalibrated.
[0084] In this embodiment, functional optimization targets can also be defined, and there can be one or more functional optimization targets.
[0085] If there is only one functional optimization objective, then the corresponding optimization algorithm is determined based on that functional optimization objective, and the corresponding functional optimization objective is calibrated based on the engine model and its optimization algorithm.
[0086] Among them, the optimization algorithm corresponding to the functional optimization objective can be Particle Swarm Optimization (PSO), Genetic Algorithm, Differential Evolution (DE), etc.
[0087] If there are multiple functional optimization objectives, determine the calibration order of the functional optimization objectives and the optimization algorithm corresponding to each functional optimization objective. The functional optimization objectives can be models in the Model-Based Component (MBC) or functions corresponding to sub-functional modules in the Electronic Control Unit (ECU). The MBC is a model-based optimization tool, and the sub-functional modules in the ECU can be sub-modules such as the inflation module and the exhaust temperature management module.
[0088] Using an engine model, and following the calibration sequence, the corresponding functional optimization objectives are calibrated according to the optimization algorithm, resulting in a preliminary MAP (Map of Functional Optimization Objectives). Bench tests are then conducted to experimentally adjust the calibrated functional optimization objectives and determine the calibration results.
[0089] Among them, bench testing can be used to test and adjust the calibrated functional optimization target. This can be done by performing online local optimization on the preliminary MAP map of the calibrated functional optimization target through bench testing, thereby making small-scale test adjustments, and finally calibrating the MAP map of the functional optimization target.
[0090] It should be noted that if the final MAP diagram of the functional optimization target does not meet expectations, the performance optimization target, the corresponding parameter variables and their ranges need to be readjusted and recalibrated.
[0091] Furthermore, for cases with multiple functional optimization objectives, after each objective is calibrated, a bench test must be conducted for that objective to adjust its corresponding MAP (Map of Objectives) until the MAP meets the expected requirements. Only then can the calibration of the next objective be performed. This avoids the accumulation of errors, which could lead to increased calibration errors.
[0092] The intelligent calibration method provided in this embodiment Figure 3 This is a schematic diagram of the architecture for intelligent calibration of a diesel engine provided in a specific embodiment of the present invention. Figure 3 As shown, the execution modules corresponding to each step include a diesel engine intelligent calibration system, a diesel engine testing system, a calibration system, an ECU, a diesel engine, and a communication module. The diesel engine intelligent calibration system is connected to the communication module and the calibration system. ECUS4 is connected to the calibration system and the diesel engine. The diesel engine testing system is connected to the communication module and the diesel engine.
[0093] Furthermore, the diesel engine intelligent calibration system transmits and receives signals from the communication module to acquire parameters such as engine fuel consumption, engine exhaust temperature, and engine emissions. It internally calculates the optimization target to be calibrated and controls the ECU's internal calibration parameters through the calibration system. These internal calibration parameters of the ECU act on the actuators of the diesel engine, generating different torques at different positions of the actuators to meet the control requirements of the diesel engine testing system.
[0094] Figure 4 This is a schematic diagram of intelligent calibration provided in a specific embodiment of the present invention. For example... Figure 4As shown, after the intelligent calibration system is connected and debugged with the communication and calibration systems, the performance optimization objectives, DOE test variables, and some boundary conditions are set through the GUI user interface of the intelligent calibration system, and the input and output variables required for modeling are extracted. Once prepared, the intelligent calibration program is started to begin automated calibration. The DOE test acquires modeling data and automatically builds models of the engine and aftertreatment. Performance calibration is performed according to the performance calibration objectives, and performance calibration data is output. The calibration guidance algorithm guides the calibration sequence of different functional modules, automatically calibrating the functional modules one by one, and outputting functional calibration data.
[0095] The intelligent calibration method provided in the above embodiments automatically balances engine fuel consumption and exhaust temperature to optimize the system. It automatically optimizes the calibration parameters of engine control sub-functions, such as the intake system, fuel supply system, and aftertreatment system. This achieves intelligent ECU calibration, with a fully automated calibration process and no manual intervention. After system self-verification, calibration data is automatically generated.
[0096] Figure 5 This is a structural diagram of an intelligent calibration device provided in one or more embodiments of the present invention.
[0097] like Figure 5 The intelligent calibration device shown includes: a variable setting module, an experimental module, and an intelligent calibration module;
[0098] The variable setting module is used to obtain the optimization target to be calibrated for the target engine, and to set the parameter variables related to the optimization target and the corresponding parameter variable ranges.
[0099] The test module is used to perform DOE tests based on parameter variables and their ranges, and to record the test data.
[0100] The intelligent calibration module is used to establish an engine model corresponding to the target engine based on the test results, and to calibrate the optimization target through the engine model.
[0101] The variable setting module is used to set the first parameter variable corresponding to the performance optimization goal and the range of the first parameter variable corresponding to the first parameter variable; and to set the second parameter variable corresponding to the function optimization goal and the range of the second parameter variable corresponding to the second parameter variable.
[0102] The testing module is used to determine the type of performance optimization based on the performance optimization objective, and to determine the test conditions for the DOE test based on the type of performance optimization; to determine the execution variables of each actuator required to execute the test conditions, and the working range of the execution variables, based on the first parameter variable and its corresponding first parameter variable range, the second parameter variable and its corresponding second parameter variable range; to conduct the DOE test based on the execution variables and working range, and to record the test data.
[0103] The intelligent calibration module is used to initialize multiple algorithm models for building an engine model based on the first parameter variable and its corresponding range, the second parameter variable and its corresponding range; train multiple preset algorithm models based on experimental data, and determine the accuracy result corresponding to each algorithm model; determine the first algorithm model corresponding to the optimal accuracy result among the multiple algorithm models; and build an engine model corresponding to the target engine based on the first algorithm model.
[0104] The intelligent calibration module is used to determine the cost function and optimization algorithm based on the performance optimization objective and the engine model; determine the optimal solution of the performance optimization objective based on the cost function and optimization algorithm, and calibrate the performance optimization objective based on the optimal solution; and conduct test adjustments to the calibrated performance optimization objective through bench tests to determine the calibration result of the performance optimization objective.
[0105] The intelligent calibration module is used to determine the calibration order of functional optimization targets and the corresponding optimization algorithm for each functional optimization target; using the engine model, the corresponding functional optimization targets are calibrated according to the calibration order and the optimization algorithm; the calibrated functional optimization targets are tested and adjusted through bench tests to determine the calibration results of the functional optimization targets.
[0106] Figure 6 This is a block diagram of an electronic device structure for an intelligent calibration method provided in one or more embodiments of the present invention.
[0107] like Figure 6 As shown, this application provides an electronic device, including: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;
[0108] The memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of an intelligent calibration method.
[0109] This application also provides a computer-readable storage medium storing a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of an intelligent calibration method.
[0110] This application also provides a vehicle, including:
[0111] Electronic equipment used to implement steps based on intelligent calibration methods;
[0112] The processor runs a program, and when the program runs, it executes the steps of the intelligent calibration method based on data output from the electronic device.
[0113] Storage medium used to store programs that, when run, execute intelligent calibration methods on data output from electronic devices.
[0114] The communication bus mentioned in the above electronic devices can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not mean that there is only one bus or one type of bus.
[0115] The electronic device comprises a hardware layer, an operating system layer running on top of the hardware layer, and an application layer running on the operating system. The hardware layer includes hardware such as a central processing unit (CPU), a memory management unit (MMU), and memory. The operating system can be any one or more computer operating systems that control the electronic device through processes, such as Linux, Unix, Android, iOS, or Windows. Furthermore, in this embodiment of the invention, the electronic device can be a smartphone, tablet computer, or other handheld device, or a desktop computer, portable computer, or other electronic device; there is no particular limitation in this embodiment.
[0116] In this embodiment of the invention, the executing entity for electronic device control can be an electronic device itself, or a functional module within an electronic device capable of calling and executing a program. The electronic device can obtain the firmware corresponding to the storage medium. This firmware is provided by the supplier, and different storage media may have the same or different firmware; no limitation is made here. After obtaining the firmware corresponding to the storage medium, the electronic device can write this firmware into the storage medium; specifically, it burns the firmware corresponding to the storage medium into the storage medium. The process of burning the firmware into the storage medium can be implemented using existing technology, and will not be elaborated upon in this embodiment of the invention.
[0117] Electronic devices can also obtain reset commands corresponding to storage media. These reset commands are provided by the supplier, and the reset commands for different storage media can be the same or different, which is not limited here.
[0118] At this time, the storage medium of the electronic device is a storage medium on which the corresponding firmware has been written. The electronic device can respond to the reset command corresponding to the storage medium on which the corresponding firmware has been written, thereby resetting the storage medium on which the corresponding firmware has been written according to the reset command. The process of resetting the storage medium according to the reset command can be implemented by existing technology and will not be described in detail in this embodiment of the invention.
[0119] For ease of description, the above devices are described separately according to their functions, divided into various units and modules. Of course, in implementing this application, the functions of each unit and module can be implemented in one or more software and / or hardware.
[0120] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the meaning consistent with their meaning in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined.
[0121] For the sake of simplicity, the method embodiments are described as a series of actions. However, those skilled in the art should understand that the embodiments of the present invention are not limited to the described order of actions, because according to the embodiments of the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions involved are not necessarily essential to the embodiments of the present invention.
[0122] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of this application.
[0123] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.
Claims
1. An intelligent calibration method, characterized in that, The method includes: Obtain the optimization target to be calibrated for the target engine, and set the parameter variables related to the optimization target and the range of the parameter variables corresponding to the parameter variables; Based on the parameter variables and their ranges, conduct DOE experiments and record the experimental data; Based on the test data, an engine model corresponding to the target engine is established, and the optimization target is calibrated using the engine model.
2. The intelligent calibration method according to claim 1, characterized in that, The setting of parameter variables related to the optimization objective and the corresponding parameter variable ranges include: Set the first parameter variable corresponding to the performance optimization goal and the range of the first parameter variable corresponding to the first parameter variable; Set the second parameter variable corresponding to the function optimization goal, and the range of the second parameter variable corresponding to the second parameter variable.
3. The intelligent calibration method according to claim 2, characterized in that, The step of conducting DOE experiments based on the parameter variables and their ranges, and recording the experimental data, includes: Based on the performance optimization objectives, determine the types of performance optimization, and based on the types of performance optimization, determine the test conditions for the DOE test; Based on the first parameter variable and its corresponding first parameter variable range, the second parameter variable and its corresponding second parameter variable range, determine the execution variables of each actuator required to execute the test condition, as well as the working range of the execution variables; The DOE experiment is performed based on the execution variables and the working scope, and the experiment data is recorded.
4. The intelligent calibration method according to claim 3, characterized in that, The step of establishing an engine model corresponding to the target engine based on the test data includes: Based on the first parameter variable and its corresponding first parameter variable range, the second parameter variable and its corresponding second parameter variable range, initialize multiple algorithm models for establishing the engine model; Train multiple preset algorithm models based on the experimental data, and determine the accuracy result corresponding to each algorithm model; Among the multiple algorithm models, the first algorithm model corresponding to the optimal accuracy result is determined; An engine model corresponding to the target engine is established based on the first algorithm model.
5. The intelligent calibration method according to claim 4, characterized in that, The calibration of the optimization objective using the engine model includes: Based on the performance optimization objective and the engine model, determine the cost function and optimization algorithm; Based on the cost function and the optimization algorithm, the optimal solution for the performance optimization objective is determined, and the performance optimization objective is calibrated based on the optimal solution. The performance optimization target was adjusted through bench testing to determine the calibration result of the performance optimization target.
6. The intelligent calibration method according to claim 4, characterized in that, The calibration of the optimization objective using the engine model includes: Determine the calibration order of the functional optimization objectives, and determine the optimization algorithm corresponding to each functional optimization objective; Using the engine model, the corresponding functional optimization objectives are calibrated according to the calibration order and the optimization algorithm. The calibration results of the functional optimization target are determined by conducting bench tests to test and adjust the calibrated functional optimization target.
7. An intelligent calibration device, characterized in that, The intelligent calibration device includes: The variable setting module is used to obtain the optimization target to be calibrated for the target engine, and to set the parameter variables related to the optimization target and the parameter variable range corresponding to the parameter variables; The testing module is used to conduct DOE tests based on the parameter variables and the range of the parameter variables, and to record the test data; The intelligent calibration module is used to establish an engine model corresponding to the target engine based on the test results, and to calibrate the optimization target through the engine model.
8. An electronic device, characterized in that, include: The processor, communication interface, memory, and communication bus are connected, with the processor, communication interface, and memory communicating with each other via the communication bus. The memory stores a computer program that, when executed by a processor, causes the processor to perform the steps of the intelligent calibration method as described in any one of claims 1 to 6.
9. A computer-readable storage medium, characterized in that, The device stores a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of the smart calibration method as described in any one of claims 1 to 6.
10. A vehicle, characterized in that, include: An electronic device for implementing the steps of the intelligent calibration method as described in any one of claims 1 to 6; A processor that runs a program, which, when running, performs the steps of the intelligent calibration method as described in any one of claims 1 to 6 from data output by the electronic device. A storage medium for storing a program that, when running, performs the steps of the intelligent calibration method as described in any one of claims 1 to 6 on data output from an electronic device.