Method and system for improving engine torque control precision
By obtaining engine operating conditions parameters in real time and using neural network algorithms to correct the engine target ignition advance angle, the problem of low engine torque accuracy is solved, high-precision torque control is achieved, and the car performance and environmental protection are improved.
Patent Information
- Application Number
- CN202410156584.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-02-04
- Publication Date
- 2025-07-25
AI Technical Summary
In the prior art, the engine torque accuracy is relatively low, especially in hybrid vehicles, and it is difficult to achieve control requirements of less than ±3%, which affects power and fuel economy.
By obtaining the engine operating condition parameters in real time, the neural network algorithm is used to calculate the target ignition advance angle correction value, and based on this, the target ignition advance angle of the engine is corrected, and the real torque and model torque are adjusted to reduce the difference value.
It improves the engine torque control accuracy, improves the power and fuel economy of the car, and reduces emission pollution, and meets the requirements of energy conservation and emission reduction.
Smart Images
Figure CN120367732A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of engine control, and particularly to a method and system for improving the torque control accuracy of an engine. Background Art
[0002] The engine torque accuracy is an important parameter for measuring the performance of an engine. It represents the difference between the actual torque of the engine and the calculated value of the torque model, and can be expressed as (model torque - actual torque) / model torque × 100%. Due to the manufacturing scatter of the engine and the intake and exhaust systems, this deviation is usually large, resulting in the engine torque accuracy generally being around ±10%. With the continuous development of hybrid vehicle technology, the requirement for engine torque accuracy is getting higher and higher, and it is now generally required to be around ±3%. Therefore, how to improve the torque accuracy of the engine in a hybrid vehicle has become an important technical challenge. Summary of the Invention
[0003] To solve the above technical problems, the present invention provides a method and system for improving the torque control accuracy of an engine to improve the torque control accuracy of the engine.
[0004] The present invention provides a method for improving the torque control accuracy of an engine, and the method includes:
[0005] Step S1: Obtain the working condition parameters of the engine in real time;
[0006] Step S2: Calculate the correction value of the target ignition advance angle of the engine according to the working condition parameters when the engine is in the starting state or the stable state;
[0007] Step S3: Based on the neural network algorithm, use the correction value of the target ignition advance angle of the engine to correct the target ignition advance angle of the engine to obtain the corrected target ignition advance angle of the engine;
[0008] Step S4: Adjust the actual torque and the model torque of the engine according to the corrected target ignition advance angle of the engine so that the difference between the actual torque and the model torque is less than a preset difference.
[0009] Preferably, the working condition parameters include: engine speed, engine load, intake pressure, throttle opening, cooling water temperature, oil temperature, and ambient temperature.
[0010] Preferably, the step S2 includes:
[0011] When the engine is in the starting state, calculate the correction value of the target ignition advance angle in the starting state of the engine according to the engine speed and the throttle opening, and the formula is:
[0012] Δθ start = b0 + b1N e + b2TP,
[0013] where Δθ start is the target ignition advance angle correction value in the engine starting state, N e is the engine speed, TP is the throttle opening, and b0, b1, b2 are the target ignition advance angle correction adjustment coefficients in the starting state;
[0014] In the engine stable state, according to the engine speed, engine load, intake pressure, throttle opening, coolant temperature, oil temperature, and ambient temperature, calculate the target ignition advance angle correction value in the engine stable state. The formula is:
[0015] Δθ stable = a0 + a1N e β1 + a2P i β2 i + a3TP β3 + a4T w β4 + a5T o β5 + a6T a β6 ,
[0016] where a0, a1, a2, a3, a4, a5, a6 are the target ignition advance angle correction adjustment coefficients in the stable state, and β1, β2, β3, β4, β 5、 β6 are the target ignition advance angle correction adjustment index coefficients in the stable state, and Δθ i is the target ignition advance angle correction value in the engine stable state, N e is the engine speed, P i is the intake pressure, TP is the throttle opening, T w is the coolant temperature, T o is the oil temperature, T a is the ambient temperature;
[0017] The formula for calculating the engine target ignition advance angle correction value is: Δθ = Δθ start + Δθ stable .
[0018] Preferably, the step S3 includes:
[0019] Construct a recurrent neural network model;
[0020] Use the working condition parameters and the engine target ignition advance angle correction value as the training set to train the recurrent neural network model;
[0021] Based on the trained recurrent neural network model, the target ignition advance angle of the engine is corrected to obtain the corrected target ignition advance angle of the engine.
[0022] Compared with the prior art, a method for improving the engine torque control accuracy provided by the present invention has the following beneficial effects: By obtaining the operating parameters of the engine in real time and calculating the correction value of the target ignition advance angle, using the neural network algorithm to correct the target ignition advance angle, and adjusting the actual torque and model torque of the engine according to the corrected target ignition advance angle, the control accuracy of the engine torque can be greatly improved. Moreover, it can improve the power performance and fuel economy of the vehicle, and can also reduce emissions pollution, meeting the environmental protection requirements of energy conservation and emission reduction.
[0023] The present invention also provides a system for improving the engine torque control accuracy, and the system includes:
[0024] A parameter acquisition module for obtaining the operating parameters of the engine in real time;
[0025] A calculation module for calculating the correction value of the target ignition advance angle of the engine according to the operating parameters when the engine is in the starting state or the stable state;
[0026] A correction module for correcting the target ignition advance angle of the engine based on the neural network algorithm by using the correction value of the target ignition advance angle of the engine to obtain the corrected target ignition advance angle of the engine;
[0027] An adjustment module for adjusting the actual torque and model torque of the engine according to the corrected target ignition advance angle of the engine so that the difference between the actual torque and the model torque is less than a preset difference.
[0028] Preferably, the operating parameters include: engine speed, engine load, intake pressure, throttle opening, coolant temperature, oil temperature, and ambient temperature.
[0029] Preferably, the calculation module includes:
[0030] A starting state calculation unit for calculating the correction value of the target ignition advance angle in the engine starting state according to the engine speed and the throttle opening when the engine is in the starting state, and the formula is:
[0031] Δθ start =b0 + b1N e +b2TP,
[0032] where, Δθ start is the correction value of the target ignition advance angle in the engine starting state, N e is the engine speed, TP is the throttle opening, and b0, b1, b2 are the correction adjustment coefficients of the target ignition advance angle in the starting state;
[0033] A steady state calculation unit, configured to calculate a target ignition advance angle correction value under the engine steady state according to the engine speed, engine load, intake pressure, throttle opening, coolant temperature, oil temperature, and ambient temperature. The formula is as follows:
[0034]
[0035] wherein, a0, a1, a2, a3, a4, a5, a6 are target ignition advance angle correction adjustment coefficients under the steady state, β1, β2, β3, β4, β 5、 β6 are target ignition advance angle correction adjustment index coefficients under the steady state, Δθ i is the target ignition advance angle correction value under the engine steady state, N e is the engine speed, P i is the intake pressure, TP is the throttle opening, T w is the coolant temperature, T o is the oil temperature, T a is the ambient temperature;
[0036] The calculation formula for the engine target ignition advance angle correction value is: Δθ = Δθ start +Δθ stable .
[0037] Preferably, the correction module includes:
[0038] A model construction unit, configured to construct a recurrent neural network model;
[0039] A training unit, configured to use the operating condition parameters and the engine target ignition advance angle correction value as a training set to train the recurrent neural network model;
[0040] A correction unit, configured to correct the engine target ignition advance angle based on the trained recurrent neural network model to obtain a corrected engine target ignition advance angle.
[0041] Compared with the prior art, the beneficial effects of the system for improving the engine torque control accuracy provided by the present invention are the same as those of the method for improving the engine torque control accuracy described in the above technical solution, and will not be elaborated herein.
[0042] The present invention further provides an electronic device, including a bus, a transceiver, a memory, a processor, and a computer program stored on the memory and executable on the processor. The transceiver, the memory, and the processor are connected through the bus. When the computer program is executed by the processor, the steps in any one of the methods for improving the engine torque control accuracy described above are implemented.
[0043] Compared with the prior art, the beneficial effects of the electronic device provided by the present invention are the same as those of the method for improving the engine torque control accuracy described in the above technical solution, and will not be elaborated herein.
[0044] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps in any one of the above-mentioned methods for improving the engine torque control accuracy are implemented.
[0045] Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present invention are the same as those of the method for improving the engine torque control accuracy described in the above technical solution, and will not be elaborated herein.
[0046] To make the above objects, features and advantages of the present invention more obvious and understandable, the following specific preferred embodiments are given in conjunction with the accompanying drawings and described in detail as follows. Brief Description of the Drawings
[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.
[0048] Figure 1 Shows a flowchart of a method for improving the engine torque control accuracy provided by an embodiment of the present invention. Detailed Embodiments
[0049] In the description of the present invention, it should be understood that the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present invention, "a plurality" means two or more unless otherwise specifically defined.
[0050] The term "a plurality" mentioned in this embodiment means two or more. "And / or" describes the association relationship of associated objects and indicates that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist simultaneously, and B exists alone. Words such as "exemplary" or "for example" are used to represent examples, illustrations or explanations, aiming to present relevant concepts in a specific manner and should not be construed as being more preferred or having more advantages than other embodiments or design solutions.
[0051] Figure 1 The flowchart of a method for improving the engine torque control accuracy provided by an embodiment of the present invention is shown. As Figure 1 shown, the method includes:
[0052] Step S1: Obtain the operating condition parameters of the engine in real time.
[0053] It should be noted that the operating condition parameters include: engine speed, engine load, intake pressure, throttle opening, coolant temperature, oil temperature, and ambient temperature.
[0054] Step S2: Calculate the engine target ignition advance angle correction value according to the operating condition parameters when the engine is in the starting state or the stable state.
[0055] It should be noted that when the engine is in the starting state, calculate the target ignition advance angle correction value in the engine starting state according to the engine speed and throttle opening. The formula is:
[0056] Δθ start = b0 + b1N e + b2TP,
[0057] where, Δθ start is the target ignition advance angle correction value in the engine starting state, N e is the engine speed, TP is the throttle opening, and b0, b1, b2 are the target ignition advance angle correction adjustment coefficients in the starting state;
[0058] When the engine is in the stable state, calculate the target ignition advance angle correction value in the engine stable state according to the engine speed, engine load, intake pressure, throttle opening, coolant temperature, oil temperature, and ambient temperature. The formula is:
[0059]
[0060] where, a0, a1, a2, a3, a4, a5, a6 are the target ignition advance angle correction adjustment coefficients in the stable state, β1, β2, β3, β4, β5, β6 are the target ignition advance angle correction adjustment index coefficients in the stable state, Δθ i is the target ignition advance angle correction value in the engine stable state, N e is the engine speed, P i is the intake pressure, TP is the throttle opening, T w is the coolant temperature, T o is the oil temperature, T a is the ambient temperature;
[0061] The calculation formula of the engine target ignition advance angle correction value is: Δθ = Δθ start + Δθstable 。
[0062] Step S3: Based on the neural network algorithm, use the engine target ignition advance angle correction value to correct the engine target ignition advance angle, and obtain the corrected engine target ignition advance angle.
[0063] It should be noted that first, a recurrent neural network model is constructed; then, the operating condition parameters and the engine target ignition advance angle correction value are used as the training set to train the recurrent neural network model; based on the trained recurrent neural network model, the engine target ignition advance angle is corrected to obtain the corrected engine target ignition advance angle.
[0064] Step S4: Adjust the actual torque and the model torque of the engine according to the corrected engine target ignition advance angle, so that the difference between the actual torque and the model torque is less than the preset difference.
[0065] It should be noted that by obtaining the actual torque measurement value of the engine, calculating the difference between the actual torque and the model torque, and then adjusting the operating condition parameters of the engine according to the difference to reduce the difference until the difference is less than or equal to the preset difference.
[0066] Compared with the prior art, a method for improving the engine torque control accuracy provided by an embodiment of the present invention has the following beneficial effects: By obtaining the operating condition parameters of the engine in real time and calculating the target ignition advance angle correction value, using the neural network algorithm to correct the target ignition advance angle, and adjusting the actual torque and the model torque of the engine according to the corrected target ignition advance angle, the control accuracy of the engine torque can be greatly improved. Moreover, it can improve the power performance and fuel economy of the vehicle, and can also reduce the emission pollution, meeting the environmental protection requirements of energy conservation and emission reduction.
[0067] An embodiment of the present invention further provides a system for improving the engine torque control accuracy, and the system includes:
[0068] A parameter acquisition module, configured to acquire the operating condition parameters of the engine in real time.
[0069] It should be noted that the operating condition parameters include: engine speed, engine load, intake pressure, throttle opening, coolant temperature, oil temperature, and ambient temperature.
[0070] A calculation module, configured to calculate the engine target ignition advance angle correction value according to the operating condition parameters when the engine is in the starting state or the stable state.
[0071] It should be noted that the calculation module includes:
[0072] A starting state calculation unit, configured to calculate a target ignition advance angle correction value in the engine starting state according to the engine speed and throttle opening degree when the engine is in the starting state. The formula is as follows:
[0073] Δθ start = b0 + b1N e + b2TP,
[0074] where, Δθ start is the target ignition advance angle correction value in the engine starting state, N e is the engine speed, TP is the throttle opening degree, and b0, b1, b2 are the target ignition advance angle correction adjustment coefficients in the starting state;
[0075] A stable state calculation unit, configured to calculate a target ignition advance angle correction value in the engine stable state according to the engine speed, engine load, intake pressure, throttle opening degree, cooling water temperature, oil temperature and ambient temperature when the engine is in the stable state. The formula is as follows:
[0076]
[0077] where, a0, a1, a2, a3, a4, a5, a6 are the target ignition advance angle correction adjustment coefficients in the stable state, β1, β2, β3, β4, β5, β6 are the target ignition advance angle correction adjustment index coefficients in the stable state, Δθ i is the target ignition advance angle correction value in the engine stable state, N e is the engine speed, P i is the intake pressure, TP is the throttle opening degree, T w is the cooling water temperature, T o is the oil temperature, T a is the ambient temperature;
[0078] The formula for calculating the engine target ignition advance angle correction value is: Δθ = Δθ start + Δθ stable .
[0079] A correction module, configured to correct the engine target ignition advance angle based on a neural network algorithm by using the engine target ignition advance angle correction value to obtain the corrected engine target ignition advance angle.
[0080] It should be noted that the correction module includes:
[0081] A model construction unit, configured to construct a recurrent neural network model;
[0082] A training unit, configured to use the operating condition parameters and the engine target ignition advance angle correction value as a training set to train the recurrent neural network model;
[0083] A correction unit, configured to correct the target ignition advance angle of the engine based on the trained recurrent neural network model to obtain the corrected target ignition advance angle of the engine.
[0084] An adjustment module, configured to adjust the actual torque and the model torque of the engine according to the corrected target ignition advance angle of the engine, so that the difference between the actual torque and the model torque is less than a preset difference.
[0085] It should be noted that by obtaining the actual torque measurement value of the engine, calculating the difference between the actual torque and the model torque, and then adjusting the operating parameters of the engine according to the difference to reduce the difference until the difference is less than or equal to the preset difference.
[0086] Compared with the prior art, the beneficial effects of a system for improving the torque control accuracy of an engine provided by an embodiment of the present invention are the same as those of the method for improving the torque control accuracy of an engine described in the above technical solution, and will not be elaborated here.
[0087] In addition, an embodiment of the present invention further provides an electronic device, including a bus, a transceiver, a memory, a processor, and a computer program stored on the memory and executable on the processor. The transceiver, the memory, and the processor are respectively connected through the bus. When the computer program is executed by the processor, each process of the method embodiment for improving the torque control accuracy of an engine described above is implemented, and the same technical effects can be achieved. To avoid repetition, it will not be elaborated here.
[0088] In addition, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by the processor, each process of the method embodiment for improving the torque control accuracy of an engine described above is implemented, and the same technical effects can be achieved. To avoid repetition, it will not be elaborated here.
[0089] A computer-readable storage medium includes permanent and non-permanent, removable and non-removable media, and is a tangible device that can retain and store instructions for use by an instruction execution device. The computer-readable storage medium includes electronic storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, and any suitable combination thereof. The computer-readable storage medium includes phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), non-volatile random access memory (NVRAM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette tape storage, magnetic disk tape storage or other magnetic storage devices, memory sticks, mechanical encoding devices (such as punched cards or raised structures in grooves on which instructions are recorded), or any other non-transmission medium that can be used to store information accessible by a computing device. As defined in the embodiments of the present invention, a computer-readable storage medium does not include transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (such as light pulses passing through an optical fiber cable), or electrical signals transmitted through wires.
[0090] In several embodiments provided in the present application, it should be understood that the disclosed devices, electronic devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the modules or units is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Additionally, the shown or discussed couplings or direct couplings or communication connections to each other can be indirect couplings or communication connections through some interfaces, devices, or units, and can also be in electrical, mechanical, or other forms of connection.
[0091] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units. They can be located in one position or distributed to multiple network units. Some or all of the units can be selected according to actual needs to solve the problems to be solved by the solution of the embodiments of the present invention.
[0092] In addition, in each embodiment of the present invention, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-integrated units can be implemented in the form of hardware or in the form of software functional units.
[0093] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the embodiments of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (including a personal computer, a server, a data center, or other network devices) to execute all or part of the steps of the methods described in the various embodiments of the present invention. And the above storage medium includes various media that can store program codes as enumerated above.
[0094] As described above, the foregoing is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technical solution that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention should be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims
1. A method for improving the accuracy of engine torque control, characterized in that Including: Step S1: Obtain the operating parameters of the engine in real time; Step S2: Calculate the correction value of the target ignition advance angle of the engine according to the operating parameters when the engine is in the starting state or the stable state; Step S3: Based on the neural network algorithm, use the correction value of the target ignition advance angle of the engine to correct the target ignition advance angle of the engine to obtain the corrected target ignition advance angle of the engine; Step S4: Adjust the actual torque and the model torque of the engine according to the corrected target ignition advance angle of the engine so that the difference between the actual torque and the model torque is less than the preset difference.
2. The method for improving the torque control accuracy of an engine according to claim 1, wherein the operating parameters include: engine speed, engine load, intake pressure, throttle opening, coolant temperature, oil temperature, and ambient temperature.
3. The method for improving the torque control accuracy of an engine according to claim 2, wherein Step S2 includes: In the engine starting state, calculate the correction value of the target ignition advance angle in the engine starting state according to the engine speed and the throttle opening, and the formula is: Δθ start = b0 + b1N e + b2TP, Among them, Δθ start is the target ignition advance angle correction value under the engine starting state, N e is the engine speed, TP is the throttle opening, and b0, b1, and b2 are the target ignition advance angle correction adjustment coefficients under the starting state; In the engine stable state, calculate the correction value of the target ignition advance angle in the engine stable state according to the engine speed, engine load, intake pressure, throttle opening, coolant temperature, oil temperature, and ambient temperature, and the formula is: Among them, a0, a1, a2, a3, a4, a5, a6 are the target ignition advance angle correction adjustment coefficients in the stable state, and β1, β2, β3, β4, β 5、 β6 are the target ignition advance angle correction adjustment exponential coefficients in the stable state, Δθ i is the target ignition advance angle correction value in the stable state of the engine, N e is the engine speed, P i is the intake pressure, TP is the throttle opening, T w is the coolant temperature, T o is the oil temperature, T a is the ambient temperature; The calculation formula for the correction value of the engine target ignition advance angle is: Δθ = Δθ start + Δθ stable .
4. The method for improving the torque control accuracy of an engine according to claim 1, wherein Step S3 includes: Construct a recurrent neural network model; Use the operating parameters and the correction value of the target ignition advance angle of the engine as the training set to train the recurrent neural network model; Based on the trained recurrent neural network model, correct the target ignition advance angle of the engine to obtain the corrected target ignition advance angle of the engine.
5. A system for improving the accuracy of engine torque control, characterized in that, Including: A parameter acquisition module for obtaining the operating parameters of the engine in real time; A calculation module for calculating the correction value of the target ignition advance angle of the engine according to the operating parameters when the engine is in the starting state or the stable state; A correction module for correcting the target ignition advance angle of the engine by using the correction value of the target ignition advance angle of the engine based on the neural network algorithm to obtain the corrected target ignition advance angle of the engine; An adjustment module for adjusting the actual torque and the model torque of the engine according to the corrected target ignition advance angle of the engine so that the difference between the actual torque and the model torque is less than the preset difference.
6. The system for improving the torque control accuracy of an engine according to claim 5, wherein the operating parameters include: engine speed, engine load, intake pressure, throttle opening, coolant temperature, oil temperature, and ambient temperature.
7. The system for improving the torque control accuracy of an engine according to claim 6, wherein the calculation module includes: A starting state calculation unit for calculating the correction value of the target ignition advance angle in the engine starting state according to the engine speed and the throttle opening in the engine starting state, and the formula is: Δθ start = b0 + b1N e + b2TP, where, Δθ start is the target ignition advance angle correction value in the engine starting state, N e is the engine speed, TP is the throttle opening, and b0, b1, b2 are the target ignition advance angle correction adjustment coefficients in the starting state; A steady-state calculation unit, which is used to calculate a target ignition advance angle correction value in the steady state of the engine according to the engine speed, engine load, intake pressure, throttle opening, coolant temperature, oil temperature, and ambient temperature. The formula is: Among them, a0, a1, a2, a3, a4, a5, a6 are the target ignition advance angle correction adjustment coefficients in the stable state, and β1, β2, β3, β4, β 5、 β6 are the target ignition advance angle correction adjustment exponential coefficients in the stable state, Δθ i is the target ignition advance angle correction value in the stable state of the engine, N e is the engine speed, P i is the intake pressure, TP is the throttle opening, T w is the coolant temperature, T o is the engine oil temperature, T a is the ambient temperature; The calculation formula for the correction value of the engine target ignition advance angle is: Δθ = Δθ start + Δθ stable .
8. The system for improving the engine torque control accuracy according to claim 5, wherein the correction module includes: a model construction unit, which is used to construct a recurrent neural network model; a training unit, which is used to use the working condition parameters and the engine target ignition advance angle correction value as a training set to train the recurrent neural network model; a correction unit, which is used to correct the engine target ignition advance angle based on the trained recurrent neural network model to obtain a corrected engine target ignition advance angle.
9. An electronic device, comprising a bus, a transceiver, a memory, a processor, and a computer program stored on the memory and executable on the processor, the transceiver, the memory, and the processor being connected via the bus, characterized in that When the computer program is executed by the processor, it implements the steps in a method for improving the engine torque control accuracy according to any one of claims 1-4.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps in a method for improving the engine torque control accuracy according to any one of claims 1-4.