CN113255116A - Splitting parallel simulation method for modeling of aircraft electromechanical system - Google Patents
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Abstract
The invention discloses a split parallel simulation method for modeling an electromechanical system of an airplane, which analyzes modal complex eigenvalue and frequency response of the electromechanical system model of the airplane through a frequency domain analysis principle, calculates and finds the split position of the system model, splits the system model into a plurality of models with independent input quantity and output quantity, strips and extracts the input quantity and the output quantity of each split model to form a single data variable, defines one end of each split model as an output end and the other end as an input end, respectively arranges an input module and an output module at the input end and the output end, writes variable data in the input module and the output module, adds an adaptation module, integrates and unifies models modeled by different software to realize parallel simulation without simplifying the models and sacrificing the simulation precision, making the architecture of the system clear.
Description
Technical Field
The invention relates to the field of airplane simulation, in particular to a split parallel simulation method for modeling an electromechanical system of an airplane.
Background
The existing system simulation, especially the electromechanical system of the airplane, generally adopts a professional modeling tool to model, for example, a hydraulic system adopts AMESim, MWorks, DSHplus and the like; the environment control system adopts FloMASTER, Dymola, AMESim and the like, the fuel system adopts AMESim, Dymola, FloMASTER and the like, the transmission system adopts SimulinX, AMESim and the like, the dynamic simulation adopts ADAMS, virtual. Labmotion, Simpack and the like, the needed system simulation model is more and more complex along with the requirement of the simulation, on one hand, the related professional subjects are more and more, on the other hand, the units of the model are more and more complicated, the calculation efficiency is more and more slow, the calculation is not easy to converge, the system simulation requires the cooperation and parallel simulation of multiple subjects while the simulation efficiency and the simulation precision are improved, at present, different systems of the aircraft electromechanical system are modeled by using different modeling software, the related fields are more, the established models are more complex, the physical coupling is stronger and the parallel simulation is difficult, and the aircraft electromechanical system is seriously influenced.
Disclosure of Invention
Aiming at the problems, the invention provides a split parallel simulation method for modeling an electromechanical system of an airplane, which has the advantages of integrating different software models and realizing collaborative parallel simulation.
The technical scheme of the invention is as follows:
a split parallel simulation method for modeling an aircraft electromechanical system, the steps comprising:
s1, analyzing modal complex eigenvalue and frequency response of the aircraft electromechanical system model through a frequency domain analysis principle, calculating and finding a detachable position of the system model, detaching the detachable position into a plurality of models with independent input interface modules and output interface modules, wherein each input interface module and each output interface module can independently output input quantity and output quantity;
s2, stripping and extracting the input quantity and the output quantity of each split model to obtain a single data variable;
s3, defining one end of each split model as an output end, defining the other end as an input end, connecting an output interface module at the output end, extracting the stripped output quantity in real time, creating variable data identical to the output quantity, writing the variable data into the input quantity of the output end in real time, connecting an input end interface module at the input end, extracting the stripped input quantity in real time, creating variable data identical to the input quantity, and writing the variable data into the input quantity of the input end in real time;
s4, adding capacitive links or inertial weight at the output interface module and the input interface module of each split model;
s5, adding an adaptation module in the split model, wherein the adaptation module is used for solver numerical range adaptation and frequency adaptation;
and S6, performing cooperation of one or more input interface modules, one or more output interface modules and one or more adapter modules of the split model to complete simulation iteration and combination calculation, and obtaining a final model.
In S1, the frequency domain analysis of the electromechanical system of the aircraft first needs to be linearized, and is generally converted into a jacobian matrix:
where F' (x), the derivative of the function at point x, is the Jacobian matrix JF (x);
x∈Rn；
f (x) is equal to Rm, JF (x) is m × n;
and then performing modal complex eigenvalue and frequency response analysis on the established main nonlinear working condition moments of the airplane electromechanical system model, wherein the analysis adopts a computer numerical integration method.
In S2, an API function is used to strip and extract the input and output quantities of the model.
In S3, the output interface module and the input interface module adopt the following method to ensure that the split model equation is complete and can be compiled, the method is as follows:
1) and calling an Add input put () function to Add a co-simulation input port for the model. And calling an Add output put () function to Add a co-simulation output port for the model. The required mapping variables are added. Thus, the consistency of the variable number and the equation number is ensured;
2) the input module and the output module adopt a compiler which is the same as the source tool software to compile during packaging, and are hung in an application library of the tool software, so that unified compilation can be ensured after connection.
In S4, a capacitive link or an inertial weight is added to increase the convergence efficiency of the model solution, and the existing capacitive link or the existing inertial weight link needs to unify all capacitive links or inertial weights at the interface.
In the step S5, the adaptation module is a second-order transfer function, then opens the frequency parameter and the amplitude parameter, and then encapsulates the second-order transfer function into an application library in the same manner as the input and output modules, and the application library is hung in the tool software platform and used as a library of the tool software to be called when the model is built. When the tool software solver solves the module, the solver has to reduce the maximum simulation step length and adapt to the precision range due to the convergence requirement.
The invention has the beneficial effects that:
1. the model which is difficult to carry out real-time simulation or semi-physical simulation before is used in a real-time simulation environment, the model is not required to be simplified, and the simulation precision is not sacrificed;
2. by splitting the model, the model which is too large in the prior art and has very low calculation efficiency even can be stably and efficiently calculated due to unconvergence;
3. by splitting the model, the rigidity matrix of the model is divided into modules, and the calculation efficiency is accelerated by several times;
4. the model collaborative simulation between different versions is easy through splitting;
5. the model cross-platform collaborative simulation is easy to realize through splitting;
6. the system model is divided into modules, so that the architecture of the system becomes clear.
Drawings
Fig. 1 is a schematic split flow diagram of a split parallel simulation method for modeling an aircraft electromechanical system according to an embodiment of the present invention.
Detailed Description
The embodiments of the present invention will be further described with reference to the accompanying drawings.
Example (b):
as shown in fig. 1, a split parallel simulation method for modeling an electromechanical system of an aircraft includes the following steps:
s1, analyzing modal complex eigenvalue and frequency response of the aircraft electromechanical system model through a frequency domain analysis principle, calculating and finding the detachable position of the system model, and detaching the detachable position into a plurality of models with independent input quantity and output quantity;
the frequency domain analysis of the electromechanical system of the airplane, which needs to be linearized first, is generally converted into a Jacobian matrix:
where F' (x), the derivative of the function at point x, is the Jacobian matrix JF (x);
x∈Rn；
f (x) is equal to Rm, JF (x) is m × n;
and then performing modal complex eigenvalue and frequency response analysis on the established main nonlinear working condition moments of the airplane electromechanical system model, wherein the analysis adopts a computer numerical integration method.
In order to guarantee the stability of numerical integration, the simulation step size needs to be limited to the order of the minimum time constant (equivalent to the reciprocal of the maximum eigenvalue norm). This is because, according to the derivation, the product of the numerical integration step size and the modulus of the feature root is a single digit.
An approximate stable condition can be deduced through a system characteristic equation, taking an Euler method as an example:
y'＝A y；
[y(n+1)-y(n)]/dt＝A y(n)；
y(n+1)＝(1+A*dt)y(n)；
the stage number stable convergence condition is |1+ a × dt | < 1; consider a as a component of a vector of eigenvalues (a1, a 2.., Am).
I1 + Aidt I <1, i belongs to [1, m ]
Further, | Ai | <2 can be derived.
And (4) expanding the constraint condition, and limiting the simulation step length to be on the order of magnitude of the reciprocal of the maximum eigenvalue modulus when a stable approximate condition is obtained.
The minimum time constant in the model equation can be considered to be determined in an empirical mode, and the step length is (0.2-0.05) Tmin. Wherein Tmin is the smallest time constant in the state space, i.e. the state with the fastest change.
The step size may also be set according to the shear frequency point of the frequency response, taking into account the relation between the time constant and the frequency response. In most cases, according to the result of system identification, the open-loop frequency response of the object can be acquired more directly. Therefore, the method has more practical engineering significance.
In this case, the step size is 1/[ (5 ~ 20) wc ], where wc is the shear frequency in the open loop frequency response.
For a modeling object which changes rapidly, the time constant is generally smaller, the frequency response is higher, the coupling degree is higher due to the stability influence of simulation data, and the modeling object cannot be split at the position. On the contrary, for a modeling object with slow change, generally, the time constant is large, the frequency response is low, the splitting can be considered here, the modal complex eigenvalue and the frequency response of the aircraft electromechanical system model system are analyzed in the frequency domain, the relative frequency response at the cavity and the short axis is low, and the main point is selected for the splitting position. But the split position cannot be determined immediately. The simulation step length calculated in the process is larger than the parallel distributed collaborative simulation step length, and the step length is the position where the splitting can be carried out.
S2, stripping and extracting the input quantity and the output quantity of each split model to form a single data variable, calling an API function of simulation tool software through C/C + + to extract physical quantity, calling an Add input put () function to acquire model port input interface information and store the model port input interface information in a data stream file, calling an Add output put () function to acquire model port output interface information and store the model port output interface information in the data stream file, wherein the data file structurally comprises initialization, cyclic calculation and exit stages. When the port information is acquired, Add output () or Add input () type functions can be directly written in the initialization paragraph, and the data types in table 1 are formed after stripping:
TABLE 1
The API function operates as follows:
a) and calling an Add input put () function to Add a co-simulation input port for the model. And calling an Add output put () function to Add a co-simulation output port for the model. Calling the AddParameter () function adds a co-simulation parameter port to the model. Calling an AddSignal () function to add a collaborative simulation signal port for the model;
b) calling a GetCS input putData () function in the while loop body to obtain corresponding input port data on the simulation soft bus;
c) calling a GetCSParaData () function to obtain corresponding parameter port data on the simulation soft bus;
d) and the split model code is in a ToDo: the model run is controlled to operate under the input g;
e) the SetCS output putData () function is called by the split model code to send the output port data to the simulation soft bus;
s3, defining one end of each split model as an output end, defining the other end as an input end, connecting an output interface module at the output end, extracting the stripped output quantity in real time, creating variable data which is the same as the output quantity, writing the variable data into the input quantity of the output end, connecting an input interface module at the input end, extracting the stripped input quantity in real time, creating variable data which is the same as the input quantity, writing the variable data into the input quantity of the input end, and ensuring that the split model equation is complete and can be compiled by the output interface module and the input interface module by the following method:
1) and calling an Add input put () function to Add a co-simulation input port for the model. And calling an Add output put () function to Add a co-simulation output port for the model. The required mapping variables are added. Thus, the consistency of the variable number and the equation number is ensured;
2) the input module and the output module adopt a compiler which is the same as the source tool software to compile during packaging, and are hung in an application library of the tool software, so that unified compilation can be ensured after connection;
s4, adding a capacitive link or an inertial weight at the output interface module and the input interface module of each split model, so that the convergence efficiency of model solution can be effectively increased, and all capacitive links or inertial weights at the interface need to be integrated and unified in the existing capacitive link or inertial weight link;
capacitive links, as illustrated below:
for the dynamic closed cavity, when the pressure in the closed cavity is P, the volume is V; at increasing pressure P + Δ P, the volume is V- Δ V, whereby:
ΔP＝Ee×Δq×t/V
in the formula: ee: effective bulk modulus of elasticity
V: the total volume of the enclosed volume;
Δ q: during time t, the difference between the flow rates of the liquid into and out of the closed volume (no longer a change in volume)
Δ P: during time t, the pressure of the enclosed volume changes (either increases or decreases);
and (ap/t) is known as the pressure rise rate (change in pressure per unit time). It can be seen that there are three main factors, namely Ee, V and Δ q, that affect the pressure change in the closed volume.
As V increases, Δ P becomes smaller, that is, the frequency response becomes slower;
inertial mass, illustrated below:
for the short axis, the moment T is equal to the moment of inertia I multiplied by the angular acceleration α: and (T) is I, and the relation of the moment angle is found in an integral mode:
T＝I*d^2θ/dt^2
in the formula: t: moment of force;
i: moment of inertia;
d ^2 theta/dt ^ 2: change of angle during time t;
also as I increases, the rotational frequency response of the shaft slows;
and S5, connecting an adaptation module at the output end of the split model, wherein the adaptation module is used for numerical range adaptation and frequency adaptation, the adaptation module is a second-order transfer function, then opening frequency parameters and amplitude parameters, and then packaging into an application library in the same way as the input and output modules, hanging in a tool software platform, serving as a tool software library, and calling when the model is built. When the tool software solver solves the module, the solver has to reduce the maximum simulation step length and adapt to the precision range due to the convergence requirement, the adaptation module has two adaptation modes, one is numerical range adaptation, the problem of large and small number matching calculation precision loss during calculation of the solver is solved, and the other is frequency adaptation, and the problem of step length self-adaptation during calculation of the solver is solved;
and S6, performing cooperative completion of variable data of input quantity and output quantity of one or more split models and the adaptive model to perform simulation iterative merging calculation, wherein n split models can be respectively put into n computers to perform parallel distributed simulation. The original model adopts a computer, the split system model carries out collaborative simulation calculation through the computer 1 and the computer 2 …, the data flow of the split parallel distributed simulation task model is designed to be (control flow, clock flow and data flow) only belonging to the same domain, and the domains are isolated, so different simulation tasks occupy different regions of the simulation soft bus and are not influenced with each other, and multi-user concurrent simulation is realized through the design of the data domain of the distributed simulation soft bus, and the final system model is obtained.
The above-mentioned embodiments only express the specific embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention.
Claims (6)
1. A split parallel simulation method for modeling an aircraft electromechanical system is characterized by comprising the following steps:
s1, analyzing modal complex eigenvalue and frequency response of the aircraft electromechanical system model through a frequency domain analysis principle, calculating and finding the detachable position of the system model, and detaching the detachable position into a plurality of models with independent input quantity and output quantity;
s2, stripping and extracting the input quantity and the output quantity of each split model to obtain a single data variable;
s3, defining one end of each split model as an output end, defining the other end as an input end, connecting an output interface module at the output end, extracting the stripped output quantity in real time, creating variable data which are the same as the output quantity, writing the variable data into the input quantity of the output end, connecting an input end interface module at the input end, extracting the stripped input quantity in real time, creating variable data which are the same as the input quantity, and writing the variable data into the input quantity of the input end;
s4, adding capacitive links or inertial weight at the output interface module and the input interface module of each split model;
s5, adding a solver adaptation module in the split model, wherein the adaptation module is used for numerical value range adaptation and frequency adaptation;
and S6, performing cooperative completion of the output interface module, the input interface module and the adaptation module of the single or multiple split models to perform simulation iterative computation, and obtaining a final model.
2. The method of claim 1, wherein in the step S1, the frequency domain analysis of the electromechanical system of the aircraft, which first needs to be linearized, is generally converted into a jacobian matrix:
where F' (x), the derivative of the function at point x, is the Jacobian matrix JF (x);
x∈Rn；
f (x) is equal to Rm, JF (x) is m × n;
and then performing modal complex eigenvalue and frequency response analysis on the established main nonlinear working condition moments of the airplane electromechanical system model, wherein the analysis adopts a computer numerical integration method.
3. The method for split-parallel simulation of aircraft electromechanical system modeling according to claim 1, wherein in S2, API functions are used for stripping and extracting the input quantity and the output quantity of the model.
4. The method for split parallel simulation of aircraft electromechanical system modeling according to claim 1, wherein in S3, the output interface module and the input interface module use the following method to ensure that the split model equation is complete and can be compiled, and the method is as follows:
1) and calling an Add input put () function to Add a co-simulation input port for the model. And calling an Add output put () function to Add a co-simulation output port for the model. The required mapping variables are added. Thus, the consistency of the variable number and the equation number is ensured;
2) the input module and the output module adopt a compiler which is the same as the source tool software to compile during packaging, and are hung in an application library of the tool software, so that unified compilation can be ensured after connection.
5. The method for split parallel simulation of aircraft electromechanical system modeling according to claim 1, wherein in S4, a capacitive link or an inertial weight is added for increasing convergence efficiency of model solution, and an existing capacitive link or an existing inertial weight link needs to unify all capacitive links or inertial weights at an interface.
6. The method for split parallel simulation of aircraft electromechanical system modeling according to claim 1, wherein in S5, the adaptation module is a second-order transfer function, then opens the frequency parameter and the amplitude parameter, then encapsulates the second-order transfer function into an application library in the same manner as the input and output modules, hangs the application library in a tool software platform, and uses the application library as a tool software library to be called when building the model. When the tool software solver solves the module, the solver has to reduce the maximum simulation step length and adapt to the precision range due to the convergence requirement.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114048610A (en) * | 2021-11-15 | 2022-02-15 | 中科三清科技有限公司 | Data output method and device |
Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5629845A (en) * | 1995-08-17 | 1997-05-13 | Liniger; Werner | Parallel computation of the response of a physical system |
| CN101315649A (en) * | 2008-07-17 | 2008-12-03 | 西北工业大学 | Order reduction modeling method of micro electro-mechanical system containing considerable input ports |
| US7487078B1 (en) * | 2002-12-20 | 2009-02-03 | Cadence Design Systems, Inc. | Method and system for modeling distributed time invariant systems |
| CN102929158A (en) * | 2012-10-30 | 2013-02-13 | 北京华力创通科技股份有限公司 | Multi-core multi-model parallel distributed type real-time simulation system |
| US20130179142A1 (en) * | 2012-01-09 | 2013-07-11 | Pusan National University Industry- University Cooperation Foundation | Distributed parallel simulation method and recording medium for storing the method |
| CN105159140A (en) * | 2015-08-11 | 2015-12-16 | 中国航空工业集团公司西安飞机设计研究所 | Real time control system simulation method and apparatus |
| CN106096194A (en) * | 2016-06-28 | 2016-11-09 | 沈阳航空航天大学 | Fixed Wing AirVehicle rapid modeling method for designing based on plug type interface |
| CN109814990A (en) * | 2018-12-24 | 2019-05-28 | 四川知周科技有限责任公司 | A kind of distributed parallel collaborative simulation framework |
| US20190286086A1 (en) * | 2016-11-10 | 2019-09-19 | Rowanalytics Ltd | Control apparatus and method for processing data inputs in computing devices therefore |
| US20190326982A1 (en) * | 2016-04-21 | 2019-10-24 | University Of Louisiana At Lafayette | Experimental Smartphone Ground Station Grid System |
| CN110968118A (en) * | 2019-12-18 | 2020-04-07 | 中国科学院长春光学精密机械与物理研究所 | Control method for six-degree-of-freedom adjusting rotary table |
| CN111507020A (en) * | 2020-05-12 | 2020-08-07 | 中国民航大学 | Graphical display method for distributed simulation results of electromechanical systems of multi-electric aircraft |
| CN111985102A (en) * | 2020-08-19 | 2020-11-24 | 西安中锐创联科技有限公司 | Distributed integrated simulation method and system for multi-source heterogeneous model |
| CN112103982A (en) * | 2020-08-27 | 2020-12-18 | 中国南方电网有限责任公司超高压输电公司检修试验中心 | MMC small-signal impedance modeling method based on Fourier decomposition |
-
2021
- 2021-05-11 CN CN202110512439.2A patent/CN113255116B/en active Active
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5629845A (en) * | 1995-08-17 | 1997-05-13 | Liniger; Werner | Parallel computation of the response of a physical system |
| US7487078B1 (en) * | 2002-12-20 | 2009-02-03 | Cadence Design Systems, Inc. | Method and system for modeling distributed time invariant systems |
| CN101315649A (en) * | 2008-07-17 | 2008-12-03 | 西北工业大学 | Order reduction modeling method of micro electro-mechanical system containing considerable input ports |
| US20130179142A1 (en) * | 2012-01-09 | 2013-07-11 | Pusan National University Industry- University Cooperation Foundation | Distributed parallel simulation method and recording medium for storing the method |
| CN102929158A (en) * | 2012-10-30 | 2013-02-13 | 北京华力创通科技股份有限公司 | Multi-core multi-model parallel distributed type real-time simulation system |
| CN105159140A (en) * | 2015-08-11 | 2015-12-16 | 中国航空工业集团公司西安飞机设计研究所 | Real time control system simulation method and apparatus |
| US20190326982A1 (en) * | 2016-04-21 | 2019-10-24 | University Of Louisiana At Lafayette | Experimental Smartphone Ground Station Grid System |
| CN106096194A (en) * | 2016-06-28 | 2016-11-09 | 沈阳航空航天大学 | Fixed Wing AirVehicle rapid modeling method for designing based on plug type interface |
| US20190286086A1 (en) * | 2016-11-10 | 2019-09-19 | Rowanalytics Ltd | Control apparatus and method for processing data inputs in computing devices therefore |
| CN109814990A (en) * | 2018-12-24 | 2019-05-28 | 四川知周科技有限责任公司 | A kind of distributed parallel collaborative simulation framework |
| CN110968118A (en) * | 2019-12-18 | 2020-04-07 | 中国科学院长春光学精密机械与物理研究所 | Control method for six-degree-of-freedom adjusting rotary table |
| CN111507020A (en) * | 2020-05-12 | 2020-08-07 | 中国民航大学 | Graphical display method for distributed simulation results of electromechanical systems of multi-electric aircraft |
| CN111985102A (en) * | 2020-08-19 | 2020-11-24 | 西安中锐创联科技有限公司 | Distributed integrated simulation method and system for multi-source heterogeneous model |
| CN112103982A (en) * | 2020-08-27 | 2020-12-18 | 中国南方电网有限责任公司超高压输电公司检修试验中心 | MMC small-signal impedance modeling method based on Fourier decomposition |
Non-Patent Citations (4)
| Title |
|---|
| A. GEE等: "Integration of a real-time parallel transputer-based helicopter simulation with real flight control hardware", 《IET》 * |
| B.R. GIVENS等: "A scalable architecture for the rapid prototyping of aircraft cockpits", 《IEEE》 * |
| 吴颖等: "基于模型的飞机机电系统综合仿真技术研究", 《第21届中国系统仿真技术及其应用学术年会论文集》 * |
| 陈娟等: "飞机多机电系统综合仿真的研究", 《仪器仪表学报》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114048610A (en) * | 2021-11-15 | 2022-02-15 | 中科三清科技有限公司 | Data output method and device |
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