CN117932941B - Deviation correction method and system based on torque prediction model - Google Patents
Deviation correction method and system based on torque prediction model Download PDFInfo
- Publication number
- CN117932941B CN117932941B CN202410118306.0A CN202410118306A CN117932941B CN 117932941 B CN117932941 B CN 117932941B CN 202410118306 A CN202410118306 A CN 202410118306A CN 117932941 B CN117932941 B CN 117932941B
- Authority
- CN
- China
- Prior art keywords
- engine
- torque
- constructing
- air
- value output
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 22
- 238000012937 correction Methods 0.000 title claims abstract description 18
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 8
- 239000000446 fuel Substances 0.000 claims description 10
- 238000000354 decomposition reaction Methods 0.000 claims description 9
- 238000002347 injection Methods 0.000 claims description 8
- 239000007924 injection Substances 0.000 claims description 8
- 238000004590 computer program Methods 0.000 claims description 6
- 238000012545 processing Methods 0.000 claims description 6
- 230000002000 scavenging effect Effects 0.000 claims description 4
- 238000011144 upstream manufacturing Methods 0.000 claims description 4
- 238000004364 calculation method Methods 0.000 claims description 3
- 238000010276 construction Methods 0.000 claims 1
- 230000008859 change Effects 0.000 abstract description 4
- 239000007789 gas Substances 0.000 description 7
- 238000002485 combustion reaction Methods 0.000 description 5
- 230000007613 environmental effect Effects 0.000 description 5
- 230000009286 beneficial effect Effects 0.000 description 4
- 239000003921 oil Substances 0.000 description 4
- 239000012530 fluid Substances 0.000 description 2
- 239000000295 fuel oil Substances 0.000 description 2
- 239000000203 mixture Substances 0.000 description 2
- 230000001133 acceleration Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000009499 grossing Methods 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000010705 motor oil Substances 0.000 description 1
- 230000010355 oscillation Effects 0.000 description 1
- 238000005381 potential energy Methods 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 238000011084 recovery Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 239000000243 solution Substances 0.000 description 1
- 230000001052 transient effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/14—Fourier, Walsh or analogous domain transformations, e.g. Laplace, Hilbert, Karhunen-Loeve, transforms
- G06F17/148—Wavelet transforms
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2113/00—Details relating to the application field
- G06F2113/08—Fluids
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/08—Thermal analysis or thermal optimisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Computational Mathematics (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Pure & Applied Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Software Systems (AREA)
- Databases & Information Systems (AREA)
- Algebra (AREA)
- Operations Research (AREA)
- Evolutionary Biology (AREA)
- Bioinformatics & Computational Biology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Probability & Statistics with Applications (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- Combined Controls Of Internal Combustion Engines (AREA)
Abstract
The invention provides a deviation correction method and a system based on a torque prediction model, wherein the method comprises the following steps: collecting an ambient temperature using an ambient sensor; constructing an intake manifold pressure system model according to the ambient temperature; constructing an engine torque prediction model by using an intake manifold pressure system model; calculating a torque value output by a theoretical engine by using an engine torque prediction model; when the deviation between the torque value output by the engine and the torque value output by the theoretical engine is not in the preset range, the deviation between the torque value output by the current engine and the torque value output by the theoretical engine is kept in the preset range through a PID algorithm. According to the invention, the environment sensor is used for collecting the environment temperature and constructing the corresponding model, so that the change of the environment temperature can be sensed in real time, and the engine torque can be adjusted in time so as to adapt to the working states at different temperatures.
Description
Technical Field
The invention belongs to the technical field of engine torque control, and particularly relates to a deviation correction method and system based on a torque prediction model.
Background
Engine torque control refers to adjusting the torque output by an engine according to the working state of the engine and the running condition of the vehicle so as to balance the power performance and the fuel economy of the vehicle. At present, the existing engine torque control method is mainly based on parameters such as vehicle speed, accelerator position, engine speed and the like, but the influence of ambient temperature on the engine performance is usually ignored.
The environmental temperature has important influence on the working performance of the engine, the combustion efficiency of the engine is reduced in a low-temperature environment, the viscosity of engine oil is increased, and the problems of difficult starting, incomplete combustion and the like of the engine are caused; the engine is easy to overheat and knock in high temperature environment. Therefore, the engine torque control method based on the ambient temperature is becoming a research hotspot in the current engine control field.
There have been some studies on engine control at ambient temperature, but most remain in the theoretical stage of investigation, lacking practical feasibility and reliability.
Disclosure of Invention
In order to solve the above problems, an object of the present invention is to provide a deviation correction method and system based on a torque prediction model.
In order to achieve the above purpose, the invention adopts the following technical scheme:
a deviation correction method based on a torque prediction model comprises the following steps:
Step 1: collecting an ambient temperature using an ambient sensor;
Step 2: constructing an intake manifold pressure system model according to the ambient temperature;
Step 3: constructing an engine torque prediction model by using an intake manifold pressure system model;
step 4: calculating a torque value of a theoretical engine output by using the engine torque prediction model;
step 5: judging whether the deviation between the torque value output by the current engine and the torque value output by the theoretical engine is in a preset range or not;
step 6: if the deviation between the torque value output by the current engine and the torque value output by the theoretical engine is not in the preset range, the deviation between the torque value output by the current engine and the torque value output by the theoretical engine is kept in the preset range through a PID algorithm.
Preferably, the step 2: constructing an intake manifold pressure system model according to the ambient temperature, comprising:
Step 2.1: constructing an air mass flow equation at a throttle valve based on the flow function; wherein the flow function is:
Wherein, As a flow function, κ represents the air flow rate, p m represents the intake manifold pressure, p a represents the throttle upstream pressure,
Step 2.2: constructing an air mass flow equation entering a cylinder by using the rotating speed of an engine;
Step 2.3: and constructing an intake manifold pressure system model by using the air mass flow equation at the throttle valve and the air mass flow equation of the air entering the cylinder.
Preferably, the air mass flow equation at the throttle valve is:
Where c d represents the specific heat capacity of air, T in represents the ambient temperature at the throttle valve, and R represents the air gas constant.
Preferably, the step 2.2: constructing an air mass flow equation into the cylinder using the rotational speed of the engine, comprising:
The formula is adopted:
constructing an air mass flow equation entering the air cylinder; where η denotes volumetric efficiency, V d denotes scavenging volume, T m denotes ambient temperature at the cylinder, ω denotes engine speed.
Preferably, the step 3: constructing an engine torque output model using the intake manifold pressure system model, comprising:
step 3.1: solving the oil injection quantity by utilizing an air mass flow equation entering the air cylinder;
Step 3.2: calculating an indication power by using the oil injection quantity;
step 3.3: calculating an average indicated torque using the indicated power;
step 3.4: and constructing an actual output torque equation of the engine by using the average indicated torque.
Preferably, in the step 3.4, the engine actual output torque equation is:
where λ represents an air-fuel ratio constant, H l represents an air-fuel ratio constant, η l represents an indicated efficiency, T e represents an engine actual output torque, and T f represents a friction torque.
Preferably, the step 1: collecting an ambient temperature using an ambient sensor, comprising:
step 1.1: acquiring a temperature signal acquired by an environment sensor;
step 1.2: decomposing the temperature signal by using a wavelet basis function to obtain wavelet coefficients under different scales;
Step 1.3: constructing wavelet threshold according to wavelet coefficients under different scales; wherein the wavelet threshold is:
Where λ j represents the wavelet threshold, σ j represents the standard deviation of the wavelet coefficients at the j-th decomposition scale, and N j represents the length of the temperature signal at the j-th decomposition scale;
Step 1.4: constructing a threshold function by utilizing the wavelet threshold;
Step 1.5: processing each wavelet coefficient by using the threshold function to obtain a processed wavelet coefficient;
Step 1.6: and carrying out reconstruction processing on the processed wavelet coefficient to obtain the environment temperature after denoising.
Preferably, the threshold function is:
Wherein W j,k represents the kth wavelet coefficient at the jth decomposition scale, Representing the processed wavelet coefficients, sgn (·) is a sign function, α represents the approximation coefficient, and β represents the cutoff coefficient.
The invention also provides a deviation correction system based on the torque prediction model, which comprises the following steps:
the environment temperature acquisition module is used for acquiring the environment temperature by using the environment sensor;
The pressure system model building module is used for building an intake manifold pressure system model according to the ambient temperature;
the torque prediction module is used for constructing an engine torque prediction model by utilizing the intake manifold pressure system model;
the theoretical torque calculation module is used for calculating a torque value output by a theoretical engine by using the engine torque prediction model;
The judging module is used for judging whether the deviation between the torque value output by the current engine and the torque value output by the theoretical engine is in a preset range or not;
And the PID control module is used for keeping the deviation between the torque value output by the current engine and the torque value output by the theoretical engine within a preset range through a PID algorithm if the deviation between the torque value output by the current engine and the torque value output by the theoretical engine is not within the preset range.
The present invention also provides a computer readable storage medium having a computer program stored thereon, wherein the computer program when executed by a processor implements the steps of a method for correcting a deviation based on a torque prediction model as described above.
The deviation correction method and system based on the torque prediction model provided by the invention have the beneficial effects that: compared with the prior art, the invention can sense the change of the ambient temperature in real time by using the ambient sensor to collect the ambient temperature and constructing the corresponding model, thereby being capable of adjusting the torque of the engine in time so as to adapt to the working states at different temperatures.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments or the description of the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flowchart of a deviation correction method based on a torque prediction model according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a deviation correction system based on a torque prediction model according to an embodiment of the present invention.
Detailed Description
In order to make the technical problems, technical schemes and beneficial effects to be solved more clear, the invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Referring to fig. 1, a deviation correction method based on a torque prediction model includes:
Step 1: collecting an ambient temperature using an ambient sensor;
Step 2: constructing an intake manifold pressure system model according to the ambient temperature;
The premise of torque output is that the combustion process is completed in the cylinder, the piston does work to drive the crankshaft to rotate to generate torque, the combustion process needs to be completed by fully mixing fuel oil and air and then igniting the mixture to generate a high-temperature and high-pressure environment to push the piston to do work, and therefore the air temperature has an important influence on the working performance of the engine. The intake manifold pressure system model of the present invention adopts an isothermal model, i.e., it is assumed that the temperature of the gas flowing through the manifold does not change or changes slowly and weakly.
Further, step 2 includes:
for compressible gases, the most important and common flow control module is the isothermal manifold. When modeling such devices, the key assumption is that the flow characteristics can be divided into two assumptions: firstly, there is no loss in the acceleration section up to the narrowest point (pressure drop). All potential energy stored in the fluid (pressure as its state quantity) is isentropically converted into kinetic energy; second, after the narrowest point, the flow is entirely turbulent, and all the kinetic energy obtained in the first section is converted (dissipated) into thermal energy. In addition, no pressure recovery occurs. The result of these key assumptions is that the pressure at the narrowest point of the valve is (approximately) equal to the downstream pressure, and that the fluid temperatures before and after the manifold are approximately the same.
Step 2.1: according to the theory, the invention can construct an air mass flow equation at the throttle valve based on a flow function by adopting the thermodynamic relationship of isentropic expansion; wherein the flow function is:
Wherein, As a flow function, κ represents the air flow rate, p m represents the intake manifold pressure, p a represents the throttle upstream pressure,
The air mass flow equation at the throttle valve is as follows:
Where c d represents the specific heat capacity of air, T in represents the ambient temperature at the throttle valve, and R represents the air gas constant.
Step 2.2: constructing an air mass flow equation entering a cylinder by using the rotating speed of an engine;
For a typical gasoline engine, the mass air flow from the manifold is actually determined by the difference between the intake manifold pressure and the individual cylinder inlet pressure. According to the mean modeling principle, the intake transient characteristics among different cylinders are ignored, and the mass air flow entering the cylinders is an equation related to the engine speed and the intake manifold pressure:
where η denotes volumetric efficiency, V d denotes scavenging volume, T m denotes ambient temperature at the cylinder, ω denotes engine speed.
Step 2.3: and constructing an intake manifold pressure system model by using the air mass flow equation at the throttle valve and the air mass flow equation of the air entering the cylinder.
And constructing an intake manifold pressure system model according to the law of conservation of mass energy:
V m is a constant of 22.4.
And obtaining parameters such as the air mass flow entering the cylinder, the air mass flow at the throttle valve, the air manifold pressure and the like by using a least square identification method through an air mass flow equation at the throttle valve, an air mass flow equation entering the cylinder and an air manifold pressure system model.
Step 3: constructing an engine torque prediction model by using an intake manifold pressure system model;
further, the step3 includes:
step 3.1: solving the oil injection quantity by utilizing an air mass flow equation entering the air cylinder;
Step 3.2: calculating an indication power by using the oil injection quantity;
step 3.3: calculating an average indicated torque using the indicated power;
step 3.4: and constructing an actual output torque equation of the engine by using the average indicated torque.
The gas intake manifold is distributed into the cylinder, the gas intake manifold is mixed with fuel oil in the cylinder to complete the combustion process, namely, the combustible gas mixture is combusted under a proper air-fuel ratio to form a high-temperature high-pressure environment, the piston is pushed to move to drive the crankshaft to rotate, and torque is generated, namely, the actual output torque equation of the engine is as follows:
where λ represents an air-fuel ratio constant, H l represents an air-fuel ratio constant, η l represents an indicated efficiency, T e represents an engine actual output torque, and T f represents a friction torque.
Step 4: calculating a torque value of a theoretical engine output by using the engine torque prediction model;
step 5: judging whether the deviation between the torque value output by the current engine and the torque value output by the theoretical engine is in a preset range or not;
step 6: if the deviation between the torque value output by the current engine and the torque value output by the theoretical engine is not in the preset range, the deviation between the torque value output by the current engine and the torque value output by the theoretical engine is kept in the preset range through a PID algorithm.
The invention keeps the deviation between the torque value output by the current engine and the torque value output by the theoretical engine in the preset range through the PID algorithm, so that the engine of the automobile can adapt to different environments and working conditions, and the system has stronger adaptability and stability.
The invention also carries out denoising treatment on the environmental temperature before acquiring the environmental temperature, and filters out noise signals in the environmental temperature, so that the acquired environmental temperature data is more accurate and reliable.
Further, step 1: collecting an ambient temperature using an ambient sensor, comprising:
step 1.1: acquiring a temperature signal acquired by an environment sensor;
step 1.2: decomposing the temperature signal by using a wavelet basis function to obtain wavelet coefficients under different scales;
Step 1.3: constructing wavelet threshold according to wavelet coefficients under different scales; wherein the wavelet threshold is:
Where λ j represents the wavelet threshold, σ j represents the standard deviation of the wavelet coefficients at the j-th decomposition scale, and N j represents the length of the temperature signal at the j-th decomposition scale;
Step 1.4: constructing a threshold function by utilizing the wavelet threshold;
Wherein the threshold function is:
Where W j,k represents the kth wavelet coefficient at the jth decomposition scale, Representing the processed wavelet coefficients, sgn (·) is a sign function, α represents the approximation coefficient, and β represents the cutoff coefficient.
The common wavelet denoising threshold functions include a hard threshold function and a soft threshold function, and the soft threshold function generally performs smoothing on wavelet coefficients to reduce noise, however, the smoothness is too strong, which causes loss of detail information of signals, and thus excessive denoising is caused. Also, there is always a constant deviation of the actual wavelet coefficients from the processed wavelet coefficients, which may reduce the quality of the reconstructed signal. The hard threshold function will zero wavelet coefficients less than the threshold, resulting in a complete cancellation of the small amplitude signal, resulting in a loss of valid information. In addition, since the hard threshold function directly cuts off the wavelet coefficient, an oscillation phenomenon occurs in the signal reconstruction process, and a pseudo Gibbs phenomenon further occurs. The threshold function provided by the invention can be controlled more conveniently by adjusting the approximation coefficient and the cutoff coefficient, the function is enabled to be more rapidly close to the expected position while the discontinuity of the threshold function is eliminated, and the continuity of the threshold function is ensured, so that the occurrence of the pseudo Gibbs phenomenon is avoided, and the smoothness of the original signal can be maintained after noise reduction.
Step 1.5: processing each wavelet coefficient by using the threshold function to obtain a processed wavelet coefficient;
Step 1.6: and carrying out reconstruction processing on the processed wavelet coefficient to obtain the environment temperature after denoising.
According to the invention, the environment sensor is used for collecting the environment temperature and constructing the corresponding model, so that the change of the environment temperature can be sensed in real time, and the engine torque can be adjusted in time so as to adapt to the working states at different temperatures.
Referring to fig. 2, the present invention further provides a deviation correction system based on a torque prediction model, including:
the environment temperature acquisition module is used for acquiring the environment temperature by using the environment sensor;
The pressure system model building module is used for building an intake manifold pressure system model according to the ambient temperature;
the torque prediction module is used for constructing an engine torque prediction model by utilizing the intake manifold pressure system model;
the theoretical torque calculation module is used for calculating a torque value output by a theoretical engine by using the engine torque prediction model;
The judging module is used for judging whether the deviation between the torque value output by the current engine and the torque value output by the theoretical engine is in a preset range or not;
And the PID control module is used for keeping the deviation between the torque value output by the current engine and the torque value output by the theoretical engine within a preset range through a PID algorithm if the deviation between the torque value output by the current engine and the torque value output by the theoretical engine is not within the preset range.
Compared with the prior art, the deviation correction system based on the torque prediction model has the same beneficial effects as the deviation correction method based on the torque prediction model described in the technical scheme, and is not repeated herein.
The present invention also provides a computer readable storage medium having a computer program stored thereon, wherein the computer program when executed by a processor implements the steps of a method for correcting a deviation based on a torque prediction model as described above.
Compared with the prior art, the beneficial effects of the computer readable storage medium provided by the invention are the same as those of the deviation correction method based on the torque prediction model described in the technical scheme, and are not repeated here.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.
Claims (5)
1. A deviation correction method based on a torque prediction model, comprising:
Step 1: collecting an ambient temperature using an ambient sensor;
Step 2: constructing an intake manifold pressure system model according to the ambient temperature;
the step 2: constructing an intake manifold pressure system model according to the ambient temperature, comprising:
Step 2.1: constructing an air mass flow equation at a throttle valve based on the flow function; wherein the flow function is:
Wherein, As a flow function, κ represents the air flow rate, p m represents the intake manifold pressure, p a represents the throttle upstream pressure,
Step 2.2: constructing an air mass flow equation entering a cylinder by using the rotating speed of an engine;
The step 2.2: constructing an air mass flow equation into the cylinder using the rotational speed of the engine, comprising:
The formula is adopted:
Constructing an air mass flow equation entering the air cylinder; where η denotes volumetric efficiency, V d denotes scavenging volume, T m denotes ambient temperature at the cylinder, ω denotes engine speed;
Step 2.3: constructing an intake manifold pressure system model by utilizing the air mass flow equation at the throttle valve and the air mass flow equation of the air entering the cylinder;
The air mass flow equation at the throttle valve is as follows:
Wherein c d represents the specific heat capacity of air, T in represents the ambient temperature at the throttle valve, and R represents the air gas constant;
Step 3: constructing an engine torque prediction model by using an intake manifold pressure system model;
The step 3: constructing an engine torque prediction model using the intake manifold pressure system model, comprising:
step 3.1: solving the oil injection quantity by utilizing an air mass flow equation entering the air cylinder;
Step 3.2: calculating an indication power by using the oil injection quantity;
step 3.3: calculating an average indicated torque using the indicated power;
Step 3.4: constructing an actual output torque equation of the engine by using the average indicated torque;
in said step 3.4, the engine actual output torque equation is:
Where λ represents an air-fuel ratio constant, H l represents an air-fuel ratio constant, η l represents an indicated efficiency, T e represents an engine actual output torque, and T f represents a friction torque;
step 4: calculating a torque value of a theoretical engine output by using the engine torque prediction model;
step 5: judging whether the deviation between the torque value output by the current engine and the torque value output by the theoretical engine is in a preset range or not;
step 6: if the deviation between the torque value output by the current engine and the torque value output by the theoretical engine is not in the preset range, the deviation between the torque value output by the current engine and the torque value output by the theoretical engine is kept in the preset range through a PID algorithm.
2. The deviation correcting method based on a torque prediction model according to claim 1, wherein the step 1: collecting an ambient temperature using an ambient sensor, comprising:
step 1.1: acquiring a temperature signal acquired by an environment sensor;
step 1.2: decomposing the temperature signal by using a wavelet basis function to obtain wavelet coefficients under different scales;
Step 1.3: constructing wavelet threshold according to wavelet coefficients under different scales; wherein the wavelet threshold is:
Where λ j represents the wavelet threshold, σ j represents the standard deviation of the wavelet coefficients at the j-th decomposition scale, and N j represents the length of the temperature signal at the j-th decomposition scale;
Step 1.4: constructing a threshold function by utilizing the wavelet threshold;
Step 1.5: processing each wavelet coefficient by using the threshold function to obtain a processed wavelet coefficient;
Step 1.6: and carrying out reconstruction processing on the processed wavelet coefficient to obtain the environment temperature after denoising.
3. The deviation correcting method based on a torque prediction model according to claim 2, wherein the threshold function is:
Wherein W j,k represents the kth wavelet coefficient at the jth decomposition scale, Representing the processed wavelet coefficients, sgn (·) is a sign function, α represents the approximation coefficient, and β represents the cutoff coefficient.
4. A torque prediction model-based bias correction system, comprising:
the environment temperature acquisition module is used for acquiring the environment temperature by using the environment sensor;
The pressure system model building module is used for building an intake manifold pressure system model according to the ambient temperature;
wherein, construct an intake manifold pressure system model according to the ambient temperature, comprising:
Step 2.1: constructing an air mass flow equation at a throttle valve based on the flow function; wherein the flow function is:
Wherein, As a flow function, κ represents the air flow rate, p m represents the intake manifold pressure, p a represents the throttle upstream pressure,
Step 2.2: constructing an air mass flow equation entering a cylinder by using the rotating speed of an engine;
The step 2.2: constructing an air mass flow equation into the cylinder using the rotational speed of the engine, comprising:
The formula is adopted:
Constructing an air mass flow equation entering the air cylinder; where η denotes volumetric efficiency, V d denotes scavenging volume, T m denotes ambient temperature at the cylinder, ω denotes engine speed;
Step 2.3: constructing an intake manifold pressure system model by utilizing the air mass flow equation at the throttle valve and the air mass flow equation of the air entering the cylinder;
The air mass flow equation at the throttle valve is as follows:
Wherein c d represents the specific heat capacity of air, T in represents the ambient temperature at the throttle valve, and R represents the air gas constant;
the torque prediction module is used for constructing an engine torque prediction model by utilizing the intake manifold pressure system model;
The construction of the engine torque prediction model by using the intake manifold pressure system model comprises the following steps:
step 3.1: solving the oil injection quantity by utilizing an air mass flow equation entering the air cylinder;
Step 3.2: calculating an indication power by using the oil injection quantity;
step 3.3: calculating an average indicated torque using the indicated power;
Step 3.4: constructing an actual output torque equation of the engine by using the average indicated torque;
in said step 3.4, the engine actual output torque equation is:
Where λ represents an air-fuel ratio constant, H l represents an air-fuel ratio constant, η l represents an indicated efficiency, T e represents an engine actual output torque, and T f represents a friction torque;
the theoretical torque calculation module is used for calculating a torque value output by a theoretical engine by using the engine torque prediction model;
The judging module is used for judging whether the deviation between the torque value output by the current engine and the torque value output by the theoretical engine is in a preset range or not;
And the PID control module is used for keeping the deviation between the torque value output by the current engine and the torque value output by the theoretical engine within a preset range through a PID algorithm if the deviation between the torque value output by the current engine and the torque value output by the theoretical engine is not within the preset range.
5. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of a torque prediction model based bias correction method as claimed in any one of claims 1-3.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410118306.0A CN117932941B (en) | 2024-01-29 | 2024-01-29 | Deviation correction method and system based on torque prediction model |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410118306.0A CN117932941B (en) | 2024-01-29 | 2024-01-29 | Deviation correction method and system based on torque prediction model |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117932941A CN117932941A (en) | 2024-04-26 |
| CN117932941B true CN117932941B (en) | 2024-07-26 |
Family
ID=90750533
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202410118306.0A Active CN117932941B (en) | 2024-01-29 | 2024-01-29 | Deviation correction method and system based on torque prediction model |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117932941B (en) |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110987452A (en) * | 2019-11-26 | 2020-04-10 | 东北大学 | Internal combustion engine torque soft measurement method based on rotation speed signal |
| CN113153543A (en) * | 2021-03-18 | 2021-07-23 | 联合汽车电子有限公司 | Air intake load model correction method and vehicle |
Family Cites Families (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5577474A (en) * | 1995-11-29 | 1996-11-26 | General Motors Corporation | Torque estimation for engine speed control |
| US7236869B2 (en) * | 2004-04-30 | 2007-06-26 | General Motors Corporation | Blended torque estimation for automatic transmission systems |
| JP2007126996A (en) * | 2005-11-01 | 2007-05-24 | Toyota Motor Corp | Engine output computing method and arithmetic unit |
| CN105683548B (en) * | 2013-11-01 | 2019-05-31 | 卡明斯公司 | For realizing the engine control system and method for torque value |
| KR102502016B1 (en) * | 2020-12-21 | 2023-02-22 | 주식회사 현대케피코 | Engine modeling torque error learning method in hybrid vehicle |
| CN115111078B (en) * | 2022-07-22 | 2024-03-19 | 浙江吉利控股集团有限公司 | Engine torque monitoring method, equipment and storage medium |
| CN117261858A (en) * | 2023-11-10 | 2023-12-22 | 格陆博科技有限公司 | Start control method and system for AVH and idle speed start and stop simultaneously |
-
2024
- 2024-01-29 CN CN202410118306.0A patent/CN117932941B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110987452A (en) * | 2019-11-26 | 2020-04-10 | 东北大学 | Internal combustion engine torque soft measurement method based on rotation speed signal |
| CN113153543A (en) * | 2021-03-18 | 2021-07-23 | 联合汽车电子有限公司 | Air intake load model correction method and vehicle |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117932941A (en) | 2024-04-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Fu et al. | Energy and exergy analysis on gasoline engine based on mapping characteristics experiment | |
| Jung et al. | Parameterization and transient validation of a variable geometry turbocharger for mean-value modeling at low and medium speed-load points | |
| Chiara et al. | Development and experimental validation of a control-oriented Diesel engine model for fuel consumption and brake torque predictions | |
| CN105408604A (en) | Method and device for operating an internal combustion engine | |
| Yang et al. | Performance prediction and optimization of an organic rankine cycle using back propagation neural network for diesel engine waste heat recovery | |
| Canova | Development and validation of a control-oriented library for the simulation of automotive engines | |
| Gonca | An optimization study on an eco-friendly engine cycle named as dual-miller cycle (DMC) for marine vehicles | |
| Liu et al. | Effects of working parameters on gasoline engine exergy balance | |
| CN117932941B (en) | Deviation correction method and system based on torque prediction model | |
| Yan et al. | In-cylinder oxygen mass fraction cycle-by-cycle estimation via a lyapunov-based observer design | |
| Pipitone et al. | The potential of a separated electric compound spark-ignition engine for hybrid vehicle application | |
| Aghaali et al. | Demonstration of air-fuel ratio role in one-stage turbocompound diesel engines | |
| Unver et al. | Modeling and validation of turbocharged diesel engine airpath and combustion systems | |
| Broomhead et al. | Model reduction of diesel mean value engine models | |
| Weber et al. | Control oriented modeling of a pressure wave supercharger | |
| Storset et al. | Adaptive air charge estimation for turbocharged diesel engines without exhaust gas recirculation | |
| Olsen et al. | Development of the tracer gas method for large bore natural gas engines—part II: measurement of scavenging parameters | |
| Elmoselhy et al. | Validated analytical modelling of supercharging centrifugal compressors with vaneless diffusers for H2-biodiesel dual-fuel engines with cooled EGR | |
| Ketata et al. | 1D gas dynamic code for performance prediction of one turbocharger radial turbine with different finite difference schemes | |
| Li et al. | A prediction model of compressor with variable-geometry diffuser based on elliptic equation and partial least squares | |
| Wu et al. | Mean value engine modeling for a diesel engine with GT-Power 1D detail model | |
| Mollenhauer et al. | History and fundamental principles of the diesel engine | |
| Walke et al. | NOx, soot, and fuel consumption predictions under transient operating cycle for common rail high power density diesel engines | |
| Wahlström et al. | Modeling of a diesel engine with VGT and EGR capturing sign reversal and non-minimum phase behaviors | |
| Wang et al. | Control oriented dynamic modeling of a turbocharged diesel engine |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |