A method for modeling and simulating multidisciplinary complex products that natively supports physical simulation

Abstract

The present invention discloses a method for modeling and simulating multidisciplinary complex products that natively supports physical simulation. In a specific implementation, the method includes: S1, describing the functional model and the logical model based on the SysML language, and conducting analysis and verification of the functional level and the logical level; S2, expanding the SysML language to refine the functional model and the logical model, and realizing the conversion to a consistent description of the physical model; S3, directly compiling the refined physical model, the functional model, and the logical model as a whole to generate executable code; S4, performing simulation and solving according to the continuous discrete simulation criterion. This implementation solves the problem of refining the description and solving the physical model in the system engineering modeling and analysis tool, and realizes the joint simulation of multidisciplinary physical models directly in a system engineering modeling and analysis tool, improves the consistency of the physical models involved in the joint simulation, and improves the efficiency of joint simulation integration and debugging.

Description

Technical Field

[0001] The present invention relates to the field of model system engineering technology, and more specifically, to a method for modeling and simulating multidisciplinary complex products that natively supports physical simulation. Background Art

[0002] According to the definition of the International Council for Systems Engineering (INCOSE): Model-based systems engineering is the formal application of modeling to support system requirements, design, analysis, verification and validation activities, starting from the conceptual design stage and extending to development and subsequent life cycle stages.

[0003] The three elements of model-based system engineering are: language, method, and tool. Language: SysML and DSL are usually used to accurately describe and express the overall system design and business elements of each sub-discipline. Method: Follow a certain framework method to carry out detailed design, verification and iteration step by step (such as HarmonySE method, which describes and analyzes from the aspects of requirements, functions, logic, and physical architecture). Tools: Commonly used tools include Raphsody, MagicDraw and other system modeling and analysis tools, as well as Dymola, SimulationX and other (multi) discipline digital design and simulation verification tools.

[0004] At present, complex products involve many disciplines. In the process of implementation, model-based system engineering faces the gap between the functional and logical models in the overall design field and the physical models in each sub-discipline field, insufficient design consistency, and difficulty in joint simulation in verification. For example, the use of digital design and simulation verification tools in the discipline field to refine the physical model of the concerned part involves model integration debugging between the two tools, especially the integration debugging of black box models, which is highly complex, time-consuming and labor-intensive. The use of digital design and simulation verification tools in the discipline field to refine the physical model of each part has the problem of difficulty in ensuring the consistency between the physical model established by the digital design and simulation verification tools in each discipline field and the functional and logical model established by the system modeling and analysis tools, lack of reuse and transfer, etc. Summary of the invention

[0005] An object of the present invention is to provide a method for modeling and simulating multidisciplinary complex products that natively supports physical simulation.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] A method for modeling and simulating multidisciplinary complex products with native support for physical simulation, the method comprising:

[0008] S1. Describe the functional model and logical model based on SysML language, and conduct analysis and verification at the functional level and logical level;

[0009] S2. Expand SysML language to refine functional model and logical model, and realize the transformation to consistent description of physical model;

[0010] S3, directly compile the refined physical model, functional model and logical model as a whole to generate executable code;

[0011] S4. Perform simulation and solution according to the continuous discrete simulation criterion.

[0012] Optionally, the S1 includes:

[0013] The functions and logic of the model are described based on the module definition diagram, internal block diagram, parameter diagram and state machine diagram of the SysML language, and simulation verification based on the functional model and logical model is carried out to ensure the correctness of the model function and logic.

[0014] Optionally, the S2 includes:

[0015] For those models without reusable basic models in the model library, the model is described by directly writing scripts based on the extended SysML language. On the basis of the SysML language, its parameter diagram is expanded, and the functions of describing differential equations, algebraic equations and conditional judgment are added to facilitate the description of physical properties.

[0016] Optionally, the S2 further includes:

[0017] For reusable basic models in the model library, the existing basic models are directly introduced into the model to describe the model, and the module definition diagram and internal block diagram of SysML are expanded. The non-causal interface is expanded based on its own interface. There are potential variables and flow variables in the non-causal interface. The flow variable orientation is positive inside the model. When the non-causal interface is connected, the potential variables of the two interfaces are equal, and the sum of the flow variables is 0. By expanding the non-causal interface, the connection structure between the basic models is the same as the actual physical connection structure.

[0018] Optionally, the S3 includes:

[0019] Based on the DEVS specification, the detailed physical model, functional model and logical model are compiled into executable code that complies with the DEVS specification;

[0020] The DEVS model is:

[0021] AtomicDevs= <X,Y,S,ta,δ int , δ ext ,λ>

[0022] Among them, AtomicDevs is the atomic model; X is the input port set; Y is the output port set; S is the set of state variables and parameters; ta is the time advancement function; δ int is the internal transfer function; δ ext is the external transfer function; λ is the output function;

[0023] The CoupledDevs model is:

[0024] CoupledDevs= <X,Y,D,{M d |d∈D},EIC,EOC,IC,select>

[0025] Among them, CoupledDevs is a composite model; X is the input port set; Y is the output port set; D is the member name set; {M d |d∈D} is the set of members, EIC is the relationship between the coupling model input and the member input, EOC represents the relationship between the member output and the coupling model output, IC is the relationship between the member output and the member input, and select is the arbiter;

[0026] The module without components in SysML corresponds to the atomic model AtomicDevs in DEVS; if the module has no constraint attributes, it corresponds to the discrete atomic model, and if it has constraint attributes, it corresponds to the continuous atomic model; the port of the module corresponds to the DEVS port X, Y; the state machine state and other state variables of the module correspond to the state set S in DEVS; the time event of the state machine corresponds to the time event ta of DEVS; the change event of the state machine corresponds to the state event δ of DEVS int ; The signal event of the state machine corresponds to the external transfer of DEVSδ ext ; The state machine sends a signal corresponding to the output function λ of DEVS;

[0027] The modules with components in SysML correspond to the composite model CoupledDevs in DEVS; the module components correspond to {M d |d∈D}; the ports of the module correspond to the DEVS ports X, Y; the connection relationship defined in the internal block diagram of the composite module corresponds to the three connection relationships EIC, EOC and IC in the composite model of DEVS; for components connected together using non-causal interfaces, these components need to be regarded as an atomic model during compilation, the equations of each component need to be combined in an atomic model, and the Kirchhoff equations corresponding to the non-causal interface connections need to be supplemented in the atomic model.

[0028] Optionally, the S4 includes:

[0029] In the same tool, simulation and solving are performed according to the continuous discrete simulation criteria. The model of each child node has a corresponding simulator, which is used to calculate differential algebraic equations, state transitions, outputs, and the time of the next state change; each leaf node has a corresponding coordinator, which is used to filter the child nodes whose states are about to change; the root node has a corresponding general coordinator, which is responsible for advancing the simulation time.

[0030] The beneficial effects of the present invention are as follows:

[0031] The technical solution described in the present invention provides a method for modeling and simulating multidisciplinary complex products that natively supports physical simulation, solves the problem of detailed description and solution of physical models in system engineering modeling and analysis tools, and realizes joint simulation including multidisciplinary physical models directly in a system engineering modeling and analysis tool, thereby improving the consistency of physical models involved in the joint simulation and improving the efficiency of joint simulation integration and debugging. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The specific implementation modes of the present invention are further described in detail below in conjunction with the accompanying drawings.

[0033] Figure 1 A flow chart of a method for modeling and simulating a multidisciplinary complex product that natively supports physical simulation provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0034] In order to more clearly illustrate the present invention, the present invention is further described below in conjunction with preferred embodiments and accompanying drawings. Similar components in the accompanying drawings are represented by the same reference numerals. It should be understood by those skilled in the art that the content specifically described below is illustrative rather than restrictive, and should not be used to limit the scope of protection of the present invention.

[0035] Currently, complex products involve many disciplines. Model-based system engineering faces the problem of disconnection between the functional and logical models in the overall design field and the physical models in each sub-discipline field during implementation. The consistency of design is insufficient, and joint simulation is difficult in verification. The current solutions are as follows:

[0036] (1) Use digital design and simulation verification tools in the subject area to refine the physical model of the focus area.

[0037] Then, 1) either import the original system modeling and analysis tool through FMI integration specifications for joint simulation with other functional and logical models (e.g., Modelica model output as FMU, imported into SysML tool for joint simulation verification between subsystems);

[0038] 2) Either export other models in the original system modeling and analysis tool for joint simulation based on the FMI integration specification (e.g., export the SysML control model as FMU and import it into the Modelica tool for joint simulation verification within the subsystem).

[0039] The problem is that the model integration debugging between the two tools, especially the integration debugging of the black box model, is highly complex, time-consuming and labor-intensive.

[0040] (2) The physical model of each part is refined through the digital design and simulation verification tools in the subject area (generally involving multiple tools), and then joint simulation is carried out through the integration and interoperability of various tools.

[0041] The existing problem is that it is difficult to ensure the consistency between the physical models established by digital design and simulation verification tools in various disciplines and the functional and logical models established by system modeling and analysis tools, and there is a lack of reuse and transfer.

[0042] In view of this, if Figure 1 As shown, an embodiment of the present invention provides a method for modeling and simulating a multidisciplinary complex product that natively supports physical simulation, the method comprising:

[0043] S1. Describe the functional model and logical model based on SysML language, and conduct analysis and verification at the functional level and logical level.

[0044] In a specific example, the S1 includes:

[0045] The functions and logic of the model are described based on the module definition diagram, internal block diagram, parameter diagram and state machine diagram of the SysML language, and simulation verification based on the functional model and logical model is carried out to ensure the correctness of the model function and logic.

[0046] S2. Expand the SysML language to refine the functional model and logical model, and achieve a consistent description transformation to the physical model.

[0047] In a specific example, the S2 includes:

[0048] For those models without reusable basic models in the model library, the model is described by directly writing scripts based on the extended SysML language. On the basis of the SysML language, its parameter diagram is expanded, and the functions of describing differential equations, algebraic equations and conditional judgment are added to facilitate the description of physical properties.

[0049] In a specific example, the S2 further includes:

[0050] For reusable basic models in the model library, the existing basic models are directly introduced into the model to describe the model, and the module definition diagram and internal block diagram of SysML are expanded. The non-causal interface is expanded based on its own interface. There are potential variables and flow variables in the non-causal interface. The flow variable orientation is positive inside the model. When the non-causal interface is connected, the potential variables of the two interfaces are equal, and the sum of the flow variables is 0. By expanding the non-causal interface, the connection structure between the basic models is the same as the actual physical connection structure.

[0051] S3. Compile the refined physical model, functional model and logical model as a whole directly to generate executable code.

[0052] In a specific example, the S3 includes:

[0053] Based on the DEVS specification, the detailed physical model, functional model and logical model are compiled into executable code that complies with the DEVS specification;

[0054] The DEVS model is:

[0055] AtomicDevs= <X,Y,S,ta,δ int , δ ext ,λ>

[0056] Among them, AtomicDevs is the atomic model; X is the input port set; Y is the output port set; S is the set of state variables and parameters; ta is the time advancement function; δ int is the internal transfer function; δ ext is the external transfer function; λ is the output function;

[0057] The CoupledDevs model is:

[0058] CoupledDevs= <X,Y,D,{M d |d∈D},EIC,EOC,IC,select>

[0059] Among them, CoupledDevs is a composite model; X is the input port set; Y is the output port set; D is the member name set; {M d |d∈D} is the set of members, EIC is the relationship between the coupling model input and the member input, EOC represents the relationship between the member output and the coupling model output, IC is the relationship between the member output and the member input, and select is the arbiter;

[0060] The module without components in SysML corresponds to the atomic model AtomicDevs in DEVS; if the module has no constraint attributes, it corresponds to the discrete atomic model, and if it has constraint attributes, it corresponds to the continuous atomic model; the port of the module corresponds to the DEVS port X, Y; the state machine state and other state variables of the module correspond to the state set S in DEVS; the time event of the state machine corresponds to the time event ta of DEVS; the change event of the state machine corresponds to the state event δ of DEVS int ; The signal event of the state machine corresponds to the external transfer of DEVSδ ext ; The state machine sends a signal corresponding to the output function λ of DEVS;

[0061] The modules with components in SysML correspond to the composite model CoupledDevs in DEVS; the module components correspond to {M d |d∈D}; the ports of the module correspond to DEVS ports X, Y; the connection relationship defined in the internal block diagram of the composite module corresponds to the three connection relationships EIC, EOC and IC in the composite model of DEVS. In particular, for components connected together using non-causal interfaces, these components need to be treated as an atomic model during compilation, the equations of each component need to be combined in an atomic model, and the Kirchhoff equations corresponding to the non-causal interface connection need to be supplemented in the atomic model.

[0062] S4. Perform simulation and solution according to the continuous discrete simulation criterion.

[0063] In a specific example, the S4 includes:

[0064] In the same tool, simulation and solving are performed according to the continuous discrete simulation criteria. The model of each child node has a corresponding simulator, which is used to calculate differential algebraic equations, state transitions, outputs, and the time of the next state change; each leaf node has a corresponding coordinator, which is used to filter the child nodes whose states are about to change; the root node has a corresponding general coordinator, which is responsible for advancing the simulation time.

[0065] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not limitations on the implementation methods of the present invention. For ordinary technicians in the relevant field, other different forms of changes or modifications can be made based on the above description. It is impossible to list all the implementation methods here. All obvious changes or modifications derived from the technical solution of the present invention are still within the protection scope of the present invention.

Claims

1. A method for modeling and simulating multidisciplinary complex products that natively supports physical simulation, characterized by: The method includes: S1. Describe the functional model and logical model based on SysML language, and conduct analysis and verification at the functional level and logical level; S2. Expand the SysML language to refine the functional model and logical model, and achieve the transformation of the consistent description into the physical model; S3. Compile the refined physical model, functional model, and logical model as a whole to generate executable code; S4. Perform simulation and solution according to the continuous-discrete simulation criterion; The S3 includes: Based on the DEVS specification, the detailed physical model, functional model and logical model are compiled into executable code that complies with the DEVS specification; The DEVS model is: AtomicDevs= <X,Y,S,ta,δ int ,δ ext ,λ> Among them, AtomicDevs is the atomic model; X is the input port set; Y is the output port set; S is the set of state variables and parameters; ta is the time advancement function; δ int is the internal transfer function; δ ext is the external transfer function; λ is the output function; The CoupledDevs model is: CoupledDevs=<X,Y,D,{M d |d∈D},EIC,EOC,IC,select> Among them, CoupledDevs is a composite model; X is the input port set; Y is the output port set; D is the member name set; {M d |d∈D} is the set of members, EIC is the relationship between the coupling model input and the member input, EOC represents the relationship between the member output and the coupling model output, IC is the relationship between the member output and the member input, and select is the arbiter; A module without components in SysML corresponds to the atomic model AtomicDevs in DEVS; a module without constraints corresponds to a discrete atomic model, and a module with constraints corresponds to a continuous atomic model; the module's ports correspond to DEVS ports X and Y; the module's state machine states and other state variables correspond to the state set S in DEVS; the state machine's time events correspond to the DEVS's time events ta; and the state machine's change events correspond to the DEVS's state events δ. int ; The signal event of the state machine corresponds to the external transfer of DEVS δ ext ;The state machine sends a signal corresponding to the output function λ of DEVS; The modules with components in SysML correspond to the composite model CoupledDevs in DEVS; the components of the modules correspond to {M d |d∈D}; the ports of the module correspond to the DEVS ports X, Y; the connection relationship defined in the internal block diagram of the composite module corresponds to the three connection relationships EIC, EOC and IC in the composite model of DEVS; for components connected together using non-causal interfaces, these components need to be regarded as an atomic model during compilation, the equations of each component need to be combined in an atomic model, and the Kirchhoff equations corresponding to the non-causal interface connections need to be supplemented in the atomic model.

2. The method according to claim 1, characterized in that Said S1 comprises: The model's functions and logic are described based on the module definition diagram, internal block diagram, parameter diagram, and state machine diagram of the SysML language, and simulation verification is performed based on the functional model and logic model to ensure the correctness of the model's functions and logic.

3. The method according to claim 1, characterized in that The S2 includes: For models without reusable basic models in the model library, the model is described by directly writing scripts based on the extended SysML language. On the basis of the SysML language, its parameter diagram is expanded, and the functions of describing differential equations, algebraic equations and conditional judgment are added to facilitate the description of physical characteristics.

4. The method according to claim 1, wherein Said S2 further comprises: For reusable basic models in the model library, the existing basic models are directly introduced into the model to describe the model, and the SysML module definition diagram and internal block diagram are expanded. The non-causal interface is expanded based on its own interface. There are potential variables and flow variables in the non-causal interface. The flow variable orientation is positive inside the model. When the non-causal interface is connected, the potential variables of the two interfaces are equal, and the sum of the flow variables is 0. By expanding the non-causal interface, the connection structure between the basic models is made the same as the actual physical connection structure.

5. The method according to claim 1, wherein The S4 includes: In the same tool, simulation and solution are performed according to the continuous-discrete simulation criteria. Each sub-node model has a corresponding simulator for calculating differential algebraic equations, state transitions, outputs, and the time for the next state change; each leaf node has a corresponding coordinator for screening sub-nodes whose states are about to change; and the root node has a corresponding general coordinator responsible for advancing the simulation time.

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