CN107061032B - A kind of prediction technique and forecasting system of engine operating state - Google Patents
A kind of prediction technique and forecasting system of engine operating state Download PDFInfo
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- CN107061032B CN107061032B CN201710379976.8A CN201710379976A CN107061032B CN 107061032 B CN107061032 B CN 107061032B CN 201710379976 A CN201710379976 A CN 201710379976A CN 107061032 B CN107061032 B CN 107061032B
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
- F02D—CONTROLLING COMBUSTION ENGINES
- F02D41/00—Electrical control of supply of combustible mixture or its constituents
- F02D41/02—Circuit arrangements for generating control signals
- F02D41/14—Introducing closed-loop corrections
- F02D41/1401—Introducing closed-loop corrections characterised by the control or regulation method
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
- F02D—CONTROLLING COMBUSTION ENGINES
- F02D29/00—Controlling engines, such controlling being peculiar to the devices driven thereby, the devices being other than parts or accessories essential to engine operation, e.g. controlling of engines by signals external thereto
- F02D29/02—Controlling engines, such controlling being peculiar to the devices driven thereby, the devices being other than parts or accessories essential to engine operation, e.g. controlling of engines by signals external thereto peculiar to engines driving vehicles; peculiar to engines driving variable pitch propellers
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
- F02D—CONTROLLING COMBUSTION ENGINES
- F02D41/00—Electrical control of supply of combustible mixture or its constituents
- F02D41/02—Circuit arrangements for generating control signals
- F02D41/14—Introducing closed-loop corrections
- F02D41/1401—Introducing closed-loop corrections characterised by the control or regulation method
- F02D2041/1433—Introducing closed-loop corrections characterised by the control or regulation method using a model or simulation of the system
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
- F02D—CONTROLLING COMBUSTION ENGINES
- F02D41/00—Electrical control of supply of combustible mixture or its constituents
- F02D41/02—Circuit arrangements for generating control signals
- F02D41/14—Introducing closed-loop corrections
- F02D41/1401—Introducing closed-loop corrections characterised by the control or regulation method
- F02D2041/1433—Introducing closed-loop corrections characterised by the control or regulation method using a model or simulation of the system
- F02D2041/1437—Simulation
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- Engineering & Computer Science (AREA)
- Chemical & Material Sciences (AREA)
- Combustion & Propulsion (AREA)
- Mechanical Engineering (AREA)
- General Engineering & Computer Science (AREA)
- Combined Controls Of Internal Combustion Engines (AREA)
Abstract
The present invention discloses a kind of method and system for predicting engine operating state, method includes: the non-linear order and memory span that each impact factor is determined according to the spindle adjustment value of engine and the height above sea level of working environment, and impact factor includes: throttle opening, atmospheric pressure and atmospheric temperature；The nonlinear model of engine is determined according to non-linear order and memory span；Engine is motivated, acquires the sample data of the revolving speed of throttle opening, atmospheric pressure, atmospheric temperature and engine respectively；The object module that engine is determined according to sample data and nonlinear model, for predicting the operating status of engine.The present invention is directed to piston-engined nonlinear characteristic, using the nonlinear model that can accurately react real system, it establishes with throttle opening, atmospheric pressure and atmospheric temperature as input, take the revolving speed of engine as the nonlinear object module of multiple input single output of output, can accurately predict the operating status of engine.
Description
Technical field
The present invention relates to engine arts, more particularly to the prediction technique and forecasting system of engine operating state.
Background technique
With the fast development of modern science and technology, unmanned plane becomes " favorite " of science and technology in recent years, in the military and people
With etc. multiple fields have been favored by people.Miniature self-service power plants are the core apparatus of all kinds of UAV system, are being related to
And the research such as the total system of unmanned plane and subsystem emulation, Control System Design, state of flight prediction and safe condition detection and
In, require to carry out accurate modeling to miniature self-service power plants.
Current small drone generally uses piston aviation engine and constant pitch airscrew as power device.It is existing
Method is when modeling it, the method that generallys use linear modelling.Specific steps are as follows: 1) establish with engine throttle opening
For input, engine speed is the single-input single-output linear model of output；2) it acquires engine throttle opening and engine turns
The experimental data of speed；3) linear model established in step 1) is fitted using least square method using experimental data, is obtained
To the mathematical model of power device.
Since piston engine is a natural nonlinear system, linear model itself can not accurately describe piston engine
The dynamic property of machine, and model in the prior art is with engine throttle opening for input, and engine speed is output
Single-input single-output system, and the working condition of actually engine is also influenced by elements such as atmospheric pressure, atmospheric temperatures,
Especially flight in the sky when, the variation of atmospheric pressure has more significant influence to piston engine, therefore, using existing skill
Art establish power device mathematical model precision it is lower, can not Accurate Prediction engine operating status.
Therefore, how a kind of method and system that can accurately predict engine operating state are provided, this field skill is become
The technical issues of art personnel's urgent need to resolve.
Summary of the invention
The object of the present invention is to provide a kind of methods for predicting engine operating state, can accurately predict the fortune of engine
Row state.
To achieve the above object, the present invention provides following schemes:
A method of prediction engine operating state, which comprises
The non-linear order of each impact factor is determined according to the height above sea level of the spindle adjustment value of engine and working environment
And memory span, wherein the impact factor includes: throttle opening, atmospheric pressure and atmospheric temperature；
The nonlinear model of the engine is determined according to the non-linear order and memory span；
The engine is motivated, acquire respectively the throttle opening, the atmospheric pressure, the atmospheric temperature and
The sample data of the revolving speed of the engine；
The object module that the engine is determined according to the sample data and the nonlinear model, it is described for predicting
The operating status of engine.
Optionally, the engine is motivated using random multi-tone signal, the function of the random multi-tone signal are as follows:
Wherein, s (t) is random multi-tone signal, and t is time variable, A0For the mean value of excitation amplitude, fmaxIt is intended to motivate
Maximum frequency, K are the frequency dividing quantity of the maximum frequency to be motivated, Ak′For the random change of independent identically distributed excitation amplitude
Amount,For obedience [0,2 π) on equally distributed random phase.
Optionally, the nonlinear model are as follows:
Wherein, y (t) indicates that the revolving speed of the engine, u (t) indicate input vector, u (t)=(u1(t) u2(t) u3
(t))T, u1(t) throttle opening, u are indicated2(t) atmospheric pressure, u are indicated3(t) atmospheric temperature is indicated, t is indicated
Time variable, gn(τ) indicates that the nonlinear response function of model, m indicate the memory span, and p indicates the non-linear order.
Optionally, the object module of the engine is determined using batch processing identification algorithm under line.
The object of the invention is also to provide a kind of systems for predicting engine operating state, can accurately predict engine
Operating status.
To achieve the above object, the present invention provides following schemes:
A kind of system for predicting engine operating state, the system comprises:
Parameter determination module, for determining each influence according to the spindle adjustment value of engine and the height above sea level of working environment
The non-linear order and memory span of the factor, wherein the impact factor includes: throttle opening, atmospheric pressure and atmospheric temperature；
Nonlinear model module, for determining the non-linear of the engine according to the non-linear order and memory span
Model；
Sample data module acquires the throttle opening, the atmospheric pressure for motivating to the engine respectively
The sample data of the revolving speed of power, the atmospheric temperature and the engine；
Object module determining module, for determining the engine according to the sample data and the nonlinear model
Object module, for predicting the operating status of the engine.
Optionally, the sample data module motivates the engine using random multi-tone signal, described random
The function of multi-tone signal are as follows:
Wherein, s (t) is random multi-tone signal, and t is time variable, A0For the mean value of excitation amplitude, fmaxIt is intended to motivate
Maximum frequency, K are the frequency dividing quantity of the maximum frequency to be motivated, Ak′For the random change of independent identically distributed excitation amplitude
Amount,For obedience [0,2 π) on equally distributed random phase.
Optionally, the nonlinear model that the nonlinear model module determines are as follows:
Wherein, y (t) indicates that the revolving speed of the engine, u (t) indicate input vector, u (t)=(u1(t) u2(t) u3
(t))T, u1(t) throttle opening, u are indicated2(t) atmospheric pressure, u are indicated3(t) atmospheric temperature is indicated, t is indicated
Time variable, gn(τ) indicates that the nonlinear response function of model, m indicate the memory span, and p indicates the non-linear order.
Optionally, the object module determining module determines the target of the engine using batch processing identification algorithm under line
Model.
The specific embodiment provided according to the present invention, the invention discloses following technical effects:
The method and system of prediction engine operating state provided by the invention, for piston-engined non-linear spy
Property, using the nonlinear model that can accurately react real system, establish with throttle opening, atmospheric pressure and atmospheric temperature
It take the revolving speed of engine as the nonlinear object module of multiple input single output of output for input, the precision of object module is high, because
This, can accurately predict the operating status of engine.
Detailed description of the invention
It in order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, below will be to institute in embodiment
Attached drawing to be used is needed to be briefly described, it should be apparent that, the accompanying drawings in the following description is only some implementations of the invention
Example, for those of ordinary skill in the art, without creative efforts, can also obtain according to these attached drawings
Obtain other attached drawings.
Fig. 1 is the flow chart of the embodiment of the present invention 1；
Fig. 2 is the structural block diagram of the embodiment of the present invention 2；
Fig. 3 is the structure chart of 3 multiple input single output nonlinear model of the embodiment of the present invention；
Fig. 4 is the time domain and frequency domain characteristic figure of the random multi-tone signal of the embodiment of the present invention 3.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
The object of the present invention is to provide a kind of method and system for predicting engine operating state, can accurately predict to start
The operating status of machine.
In order to make the foregoing objectives, features and advantages of the present invention clearer and more comprehensible, with reference to the accompanying drawing and specific real
Applying mode, the present invention is described in further detail.
Embodiment 1:
As shown in Figure 1, the method for prediction engine operating state includes:
Step 11: the non-thread of each impact factor is determined according to the height above sea level of the spindle adjustment value of engine and working environment
Property order and memory span, wherein impact factor includes: throttle opening, atmospheric pressure and atmospheric temperature；
Step 12: the nonlinear model of engine is determined according to non-linear order and memory span；
Step 13: engine being motivated, acquires throttle opening, atmospheric pressure, atmospheric temperature and engine respectively
The sample data of revolving speed；
Step 14: the object module of engine is determined according to sample data and nonlinear model, for predicting engine
Operating status.
Specifically, step 12: according to the nonlinear model for the engine that non-linear order and memory span determine are as follows:
Wherein, y (t) indicates that the revolving speed of the engine, u (t) indicate input vector, u (t)=(u1(t) u2(t) u3
(t))T, u1(t) throttle opening, u are indicated2(t) atmospheric pressure, u are indicated3(t) atmospheric temperature is indicated, t is indicated
Time variable, gn(τ) indicates that the nonlinear response function of model, m indicate the memory span, and p indicates the non-linear order.
Engine is motivated using random multi-tone signal in step 13, the function of random multi-tone signal are as follows:
Wherein, s (t) is random multi-tone signal, and t is time variable, A0For the mean value of excitation amplitude, fmaxIt is intended to motivate
Maximum frequency, K are the frequency dividing quantity of the maximum frequency to be motivated, Ak′For the random change of independent identically distributed excitation amplitude
Amount,For obedience [0,2 π) on equally distributed random phase.
The object module of engine is determined in step 14 using batch processing identification algorithm under line.
Existing linear modeling approach there are aiming at the problem that, the present invention is used with engine throttle opening, atmospheric pressure, big
Temperature degree is input, and engine speed is that the multiple input single output nonlinear model of output builds the dynamic characteristic of engine
Mould improves the precision of engine mockup, establishes unmanned plane dynamical system model more more accurate than conventional linear method.
The nonlinear model of engine provided by the invention cannot be only used for replacing traditional in unmanned plane analogue system move
Force system model can significantly improve the fidelity of analogue system, provide support for unmanned plane emulation；And it can online in real time
It predicts the future state of unmanned plane dynamical system, realizes the on-line prediction of unmanned plane future state of flight, and then reach to nobody
Machine safe condition real time monitoring is the state of flight prediction and safety of unmanned plane to the purpose that the following flight risk is prejudged
Condition monitoring provides support；Can also according to control instruction Accurate Prediction engine speed, thus be accurately controlled power and
Control moment can reduce the number of iterations of Control System Design, improve the design efficiency of control system.
Embodiment 2:
As shown in Fig. 2, a kind of system for predicting engine operating state includes:
Parameter determination module 21, for determining each shadow according to the spindle adjustment value of engine and the height above sea level of working environment
Ring the non-linear order and memory span of the factor, wherein impact factor includes: throttle opening, atmospheric pressure and atmospheric temperature；
Nonlinear model module 22, for determining the nonlinear model of engine according to non-linear order and memory span；
Sample data module 23 acquires throttle opening, atmospheric pressure, big temperature for motivating to engine respectively
The sample data of the revolving speed of degree and engine；
Object module determining module 24, for determining the object module of engine according to sample data and nonlinear model,
For predicting the operating status of engine.
Specifically, the nonlinear model that nonlinear model module 22 determines are as follows:
Wherein, y (t) indicates that the revolving speed of the engine, u (t) indicate input vector, u (t)=(u1(t) u2(t) u3
(t))T, u1(t) throttle opening, u are indicated2(t) atmospheric pressure, u are indicated3(t) atmospheric temperature is indicated, t is indicated
Time variable, gn(τ) indicates that the nonlinear response function of model, m indicate the memory span, and p indicates the non-linear order.
Sample data module 23 motivates engine using random multi-tone signal, the function of random multi-tone signal are as follows:
Wherein, s (t) is random multi-tone signal, and t is time variable, A0For the mean value of excitation amplitude, fmaxIt is intended to motivate
Maximum frequency, K are the frequency dividing quantity of the maximum frequency to be motivated, Ak′For the random change of independent identically distributed excitation amplitude
Amount,For obedience [0,2 π) on equally distributed random phase.
Object module determining module 24 determines the object module of engine using batch processing identification algorithm under line.
The invention proposes the non-linear modeling method of multiple input single output Hammerstein series model, the present embodiment
The multiple input single output nonlinear model of miniature self-service power plants is established using this method.According to the power device established
Model devises System Discrimination algorithm and recognizes to the multiple input single output nonlinear model shape parameter, and entire identification process can
To descend batch processing to complete online.Miniature self-service power plants nonlinear model simulation essence with higher provided by the invention
Degree, can accurately predict the operating status of engine.
Embodiment 3: the method for predicting engine operating state includes:
Step 31: the non-thread of each impact factor is determined according to the height above sea level of the spindle adjustment value of engine and working environment
Property order and memory span, wherein impact factor includes: throttle opening, atmospheric pressure and atmospheric temperature:
Engine throttle opening, atmospheric pressure, the respective non-linear order of three variables of atmospheric temperature and memory span are 1
It is selected between~3.
If engine operation height above sea level is in ten thousand metres hereinafter, atmospheric pressure and the non-linear order of atmospheric temperature may be selected
It is 2, memory span is selected as 1；If work is more than height above sea level ten thousand metres, the non-linear order of atmospheric pressure and atmospheric temperature
It may be selected to be 2, memory span is selected as 2.
The non-linear order and memory span of engine throttle opening are related to the factors such as engine model and spindle adjustment,
Therefore usually starting is selected as non-linear order 2, memory span 2.If final mask precision meet demand, can reduce non-linear
Order and memory span, it is on the contrary then increase non-linear order and memory span.Target is to make the model of foundation in meet demand essence
There is the smallest non-linear order and memory span in the case where degree.
Step 32: the nonlinear model of engine is determined according to non-linear order and memory span:
The nonlinear model of following form is known as Hammerstein series model by the present invention:
Wherein, u (t) is mode input vector, and y (t) is model output vector, function gn(τ) is the non-linear sound of model
Answer function, n=1,2 ....
As shown in figure 3, step 31 has determined that the non-linear order of the model and memory span carry out, according to non-linear order
With memory span determine, the nonlinear model based on Hammerstein series model it is as follows:
Wherein, wherein y (t) indicates the revolving speed of engine, is scalar, and unit is Radian per second, u (t) indicate input to
Amount, u (t)=(u1(t) u2(t) u3(t))T, u1(t) throttle opening is indicated, unit is fractional value, u2(t) atmospheric pressure is indicated,
Unit is Pascal, u3(t) indicate that atmospheric temperature, unit are Kelvin, t indicates time variable, gn(τ) indicates the non-thread of model
Property receptance function, m indicates memory span, and p indicates non-linear order.
Step 33: engine being motivated, acquires throttle opening, atmospheric pressure, atmospheric temperature and engine respectively
The sample data of revolving speed:
The random multi-tone signal that the present embodiment uses can motivate the various characteristics of mode for being identified object comprehensively, be a kind of
Ideal identification pumping signal.(a) of the time domain of machine multi-tone signal and frequency domain characteristic such as Fig. 4 be partially and shown in the part (b),
The function of random multi-tone signal is as follows:
Wherein, s (t) is random multi-tone signal, and t is time variable, A0For the mean value of excitation amplitude, fmaxIt is intended to motivate
Maximum frequency, K are the frequency dividing quantity of the maximum frequency to be motivated, Ak′For the random change of independent identically distributed excitation amplitude
Amount,For obedience [0,2 π) on equally distributed random phase.
Step 34: the object module of engine is determined according to sample data and nonlinear model, for predicting engine
Operating status:
The present embodiment determines the object module of engine, multiple input single output using batch processing identification algorithm under line
Hammerstein series model identification algorithm the following steps are included:
After obtaining experiment sample data, parameter identification is carried out to object module.Write object module as matrix form such as
Shown in lower:
Y=Φ θ (4)
Wherein, Y is the data vector of the engine speed of acquisition, and θ is the model parameter matrix to be recognized, and Φ is acquisition
The data matrix of impact factor, is defined as follows:
Φ=(X1 X2 ... Xp) (5)
Wherein, XkFor the non-linear excitation matrix that the sample data of the impact factor of acquisition is formed, k=1,2,3..., p tool
Body is defined as follows:
Wherein, N indicates sample data number, and the model parameter matrix θ to be recognized is defined as follows in formula (4):
θ=(g1 g2 ... gp)T (7)
Wherein gkFor the nonlinear parameter vector of different orders, gkIt is defined as follows:
gk=(gk(0) gk(1) ... gk(m))T (8)
Therefore the least-squares estimation of model parameter matrix to be recognized can be obtained according to formula (4)
Above-mentioned discrimination method successively can construct input data matrix according to formula (5)~(6) after obtaining sample data,
The least-squares estimation of model parameter matrix to be recognized can be obtained using formula (9) then in conjunction with output data vector, thus
Determine the nonlinear response function g of modeln(τ), and then determine the multiple input single output nonlinear model of engine.
Miniature self-service power plants modeling method provided by the invention uses the nonlinear model closer to real system
Type, and consider in addition to conventional control amount --- other than engine throttle opening, the environment that engine condition is affected is become
Amount: the atmospheric pressure and atmospheric temperature of engine operation, combined using multiple input single output Hammerstein model come
The multiple input single output nonlinear model for establishing miniature self-service power plants, with traditional based on the linear mould of single-input single-output
The prediction technique of type is compared, precision of prediction with higher.
Each embodiment in this specification is described in a progressive manner, the highlights of each of the examples are with other
The difference of embodiment, the same or similar parts in each embodiment may refer to each other.For system disclosed in embodiment
For, since it is corresponded to the methods disclosed in the examples, so being described relatively simple, related place is said referring to method part
It is bright.
Used herein a specific example illustrates the principle and implementation of the invention, and above embodiments are said
It is bright to be merely used to help understand method and its core concept of the invention；At the same time, for those skilled in the art, foundation
Thought of the invention, there will be changes in the specific implementation manner and application range.In conclusion the content of the present specification is not
It is interpreted as limitation of the present invention.
Claims (8)
1. a kind of method for predicting engine operating state, which is characterized in that the described method includes:
The non-linear order and note of each impact factor are determined according to the height above sea level of the spindle adjustment value of engine and working environment
Recall length, wherein the impact factor includes: throttle opening, atmospheric pressure and atmospheric temperature；
The nonlinear model of the engine is determined according to the non-linear order and memory span；
The engine is motivated, acquires the throttle opening, the atmospheric pressure, the atmospheric temperature and described respectively
The sample data of the revolving speed of engine；
The object module that the engine is determined according to the sample data and the nonlinear model, for predicting described start
The operating status of machine.
2. the method for prediction engine operating state according to claim 1, which is characterized in that use random multi-tone signal
The engine is motivated, the function of the random multi-tone signal are as follows:
Wherein, s (t) is random multi-tone signal, and t is time variable, A0For the mean value of excitation amplitude, fmaxFor the maximum frequency to be motivated
Rate, K are the frequency dividing quantity of the maximum frequency to be motivated, Ak′For the stochastic variable of independent identically distributed excitation amplitude,For
Obey [0,2 π) on equally distributed random phase, k ' is the multiplier parameter for the maximum frequency to be motivated.
3. the method for prediction engine operating state according to claim 1, which is characterized in that the nonlinear model
Are as follows:
Wherein, y (t) indicates that the revolving speed of the engine, u (t) indicate input vector, u (t)=(u1(t) u2(t) u3(t))T,
u1(t) throttle opening, u are indicated2(t) atmospheric pressure, u are indicated3(t) atmospheric temperature is indicated, t indicates that the time becomes
Amount, gn(τ) indicates that the nonlinear response function of model, m indicate the memory span, and p indicates the non-linear order.
4. the method for prediction engine operating state according to claim 1, which is characterized in that distinguished using batch processing under line
Know the object module that algorithm determines the engine.
5. a kind of system for predicting engine operating state, which is characterized in that the system comprises:
Parameter determination module, for determining each impact factor according to the spindle adjustment value of engine and the height above sea level of working environment
Non-linear order and memory span, wherein the impact factor includes: throttle opening, atmospheric pressure and atmospheric temperature；
Nonlinear model module, for determining the nonlinear model of the engine according to the non-linear order and memory span
Type；
Sample data module, for being motivated to the engine, acquire respectively the throttle opening, the atmospheric pressure,
The sample data of the revolving speed of the atmospheric temperature and the engine；
Object module determining module, for determining the target of the engine according to the sample data and the nonlinear model
Model, for predicting the operating status of the engine.
6. the system of prediction engine operating state according to claim 5, which is characterized in that the sample data module
The engine is motivated using random multi-tone signal, the function of the random multi-tone signal are as follows:
Wherein, s (t) is random multi-tone signal, and t is time variable, A0For the mean value of excitation amplitude, fmaxFor the maximum frequency to be motivated
Rate, K are the frequency dividing quantity of the maximum frequency to be motivated, Ak′For the stochastic variable of independent identically distributed excitation amplitude,For
Obey [0,2 π) on equally distributed random phase, the multiplier parameter of the k ' expression maximum frequency to be motivated.
7. the system of prediction engine operating state according to claim 5, which is characterized in that the nonlinear model pattern
The nonlinear model that block determines are as follows:
Wherein, y (t) indicates that the revolving speed of the engine, u (t) indicate input vector, u (t)=(u1(t) u2(t) u3(t))T,
u1(t) throttle opening, u are indicated2(t) atmospheric pressure, u are indicated3(t) atmospheric temperature is indicated, t indicates that the time becomes
Amount, gn(τ) indicates that the nonlinear response function of model, m indicate the memory span, and p indicates the non-linear order.
8. the system of prediction engine operating state according to claim 5, which is characterized in that the object module determines
Module determines the object module of the engine using batch processing identification algorithm under line.
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| CN108762089B (en) * | 2018-06-15 | 2021-02-19 | 大连理工大学 | Model prediction-based aero-engine online optimization and multivariable control design method |
| CN113447271A (en) * | 2020-11-30 | 2021-09-28 | 中国人民解放军火箭军工程大学 | Online monitoring method for gas circuit of aero-engine based on corrected partial derivative |
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| CN101892914A (en) * | 2010-07-14 | 2010-11-24 | 中国第一汽车集团公司 | Engine transient air inflow estimation method based on model |
| CN204877693U (en) * | 2015-08-18 | 2015-12-16 | 宜春学院 | Motor gasoline machine inlet flow controlling means |
| CN105221282A (en) * | 2015-08-25 | 2016-01-06 | 重庆邮电大学 | Based on the hcci engine burning timing control method of linear model and sliding mode controller |
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