A method for generating automobile mechanical simulation model based on graph theory

Abstract

The present invention provides a method for generating an automobile mechanical simulation model based on graph theory, which expands the initial mechanical design scheme based on graph theory, and evaluates the optimal mechanical design scheme from the expanded multiple mechanical design schemes through weight matrix conversion to generate a corresponding mathematical physical model for simulation, including designing the initial mechanical design scheme, expanding the design scheme, constructing a weight table, constructing a model adjacency matrix, and evaluating the optimal design scheme. The present invention has the beneficial effects of realizing the automatic construction of a physical model, greatly improving the R&D efficiency of designers while ensuring the optimization of the design scheme to the greatest extent.

Description

Technical Field

[0001] The invention belongs to the technical field of automobile mechanical design, and in particular relates to a method for generating an automobile mechanical simulation model based on graph theory. Background Art

[0002] The intelligent design of mechanical equipment mainly involves the product design process, and its core is to carry out continuous simulation iteration and modification during the design stage. The general design simulation process includes: after the preliminary design, design multiple schemes for the predetermined indicators and build corresponding models; then simulate each model, and calculate the model performance according to the simulation results, and adjust and optimize the design scheme based on this; then build a new model for further simulation testing, and finally determine the optimal design scheme through this iterative method. Although this process is cumbersome and time-consuming, it is an essential link to evaluate and optimize the scheme before physical verification. Some automated tools have been used in the current design process to reduce the time of simulation and evaluation. However, designers need to repeatedly modify and reconstruct models for multiple schemes, which still occupies most of the time in the design process. Summary of the invention

[0003] In view of this, the present invention aims to propose a method for generating an automobile mechanical simulation model based on graph theory to realize the automatic construction of a physical model, which greatly improves the R&D efficiency of designers while ensuring the optimization of the design scheme to the greatest extent.

[0004] To achieve the above object, the technical solution of the present invention is achieved as follows:

[0005] A method for generating automobile mechanical simulation models based on graph theory.

[0006] Furthermore, the initial mechanical design scheme is expanded based on graph theory, and the optimal mechanical design scheme is evaluated from the expanded multiple mechanical design schemes through weighted matrix transformation to generate the corresponding mathematical and physical model for simulation. The generation method includes:

[0007] T1. Design the first version of the mechanical design plan: determine the plan requirements and evaluation indicators, and draw a schematic diagram of the mechanism through simulation design software;

[0008] T2. Extended design plan: Expand the mechanism graph theory diagram according to different design ideas and generate multiple mechanism graph theory diagrams;

[0009] T3. Construct a weighting table: assign values ​​to each edge in the graph theory diagrams of various organizations to form a corresponding weighting table;

[0010] T4. Construct model adjacency matrix: convert all these weighted tables into symmetric model adjacency matrix and verify the feasibility of the model adjacency matrix;

[0011] T5. Evaluate the optimal design solution: Evaluate the performance of the model adjacency matrix according to the preset evaluation indicators to select the optimal mechanical design solution and generate the corresponding mathematical and physical model;

[0012] T6. Conduct simulation and optimization verification on mathematical and physical models to ensure that the design meets the target indicators.

[0013] Furthermore, each node in the T1 mechanism graph diagram represents a corresponding element, and each edge represents a connection between elements.

[0014] Furthermore, in said T2, according to the principle concept of automobile mechanical design, the same component is designed using different elements or different connection methods of the same element to generate a variety of mechanism graph diagrams.

[0015] Furthermore, in T4, the model adjacency matrix is ​​a symmetric matrix, and the steps of constructing the model adjacency matrix include:

[0016] T41. Assign a unique number to each node of the organizational graph diagram;

[0017] T42. Create an n*n matrix, where n is the total number of nodes and all elements of the matrix are 0;

[0018] T43. According to the connection relationship between each node, the node number is used to anchor the element position in the matrix, and the element value is the weighted value.

[0019] Further, the step T5 comprises the following steps:

[0020] T51. Invert the connection relationship of all model adjacency matrices into a path search problem through the inversion algorithm;

[0021] T52, use the shortest path algorithm and minimum spanning tree algorithm to perform superposition interference judgment on the path;

[0022] T53, filter out infeasible model adjacency matrices, and evaluate the performance of the remaining model adjacency matrices according to preset evaluation indicators to find the optimal model adjacency matrix and the corresponding mechanical design solution;

[0023] T54. Generate the corresponding mathematical and physical model based on the optimal model adjacency matrix.

[0024] Furthermore, in T52, the shortest path algorithm is used to ensure the most effective connection between nodes, and the minimum spanning tree algorithm is used to find the minimum weight tree connecting all nodes.

[0025] Furthermore, the model adjacency matrix filtered by T53 includes invalid, inefficient, and node-conflicting model adjacency matrices.

[0026] Further, the T55 generates a mathematical physical model including, according to the element represented by the node, finding the corresponding physical element from the physical element library, converting it, and generating the corresponding model code;

[0027] Automatically connect related components according to the connection relationship of the matrix, determine the connection interface by judging the interface type, and generate the corresponding connection code;

[0028] Eliminate invalid components, optimize the model layout by flipping components, regularizing connections, etc., and generate the final mathematical and physical model.

[0029] Furthermore, an electronic device includes a processor and a memory that is in communication with the processor and is used to store instructions executable by the processor, and the processor is used to execute the graph theory-based automobile mechanical simulation model generation method.

[0030] Furthermore, a computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for generating an automobile mechanical simulation model based on graph theory is implemented.

[0031] Compared with the prior art, the method for generating an automobile mechanical simulation model based on graph theory according to the present invention has the following beneficial effects:

[0032] By expanding and evaluating multiple mechanical design schemes, it is possible to quickly evaluate and select the optimal scheme among multiple design schemes, thereby improving design efficiency and accuracy; in addition, by utilizing graph theory models and weighted matrix transformation, through inversion algorithms and path search algorithms, as well as optimal path and minimum spanning tree algorithms, it is possible to quickly evaluate and select the optimal design scheme, thereby achieving efficient automation of mechanical design. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The accompanying drawings constituting a part of the present invention are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the accompanying drawings:

[0034] Figure 1 A schematic diagram of a flow chart of a method for generating an automobile mechanical simulation model according to an embodiment of the present invention;

[0035] Figure 2 A schematic diagram of a fuel cell system model structure according to an embodiment of the present invention;

[0036] Figure 3 A schematic diagram of a fuel cell system model mechanism diagram according to an embodiment of the present invention;

[0037] Figure 4A schematic diagram of an adjacency matrix of a fuel cell system model according to an embodiment of the present invention;

[0038] Figure 5 A schematic diagram of a hybrid power system architecture model according to an embodiment of the present invention;

[0039] Figure 6 It is a schematic diagram of the structure diagram of the hybrid power system architecture model described in an embodiment of the present invention. DETAILED DESCRIPTION

[0040] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0041] The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0042] The method for generating an automobile mechanical simulation model based on graph theory is to expand the initial mechanical design scheme based on graph theory, and evaluate the optimal mechanical design scheme from the expanded multiple mechanical design schemes through weighted matrix transformation to generate the corresponding mathematical and physical model for simulation. The generation method includes:

[0043] T1. Design the first version of the mechanical design plan: determine the plan requirements and evaluation indicators, and draw a schematic diagram of the mechanism through simulation design software;

[0044] T2. Extended design plan: Expand the mechanism graph theory diagram according to different design ideas and generate multiple mechanism graph theory diagrams;

[0045] T3. Construct a weighting table: assign values ​​to each edge in the graph theory diagrams of various organizations to form a corresponding weighting table;

[0046] T4. Construct model adjacency matrix: convert all these weighted tables into symmetric model adjacency matrix and verify the feasibility of the model adjacency matrix;

[0047] T5. Evaluate the optimal design solution: Evaluate the performance of the model adjacency matrix according to the preset evaluation indicators to select the optimal mechanical design solution and generate the corresponding mathematical and physical model.

[0048] Finally, it is determined whether the mathematical and physical model corresponding to the optimal mechanical design scheme can meet the design indicators. If it does, the design scheme is determined. If not, it returns to T2 to redraw the mechanism diagram or T5 to select another model adjacency matrix.

[0049] Specifically, each node in the T1 mechanism graph diagram represents a corresponding component, and each edge represents a connection between components.

[0050] Specifically, in T2, according to the principles and concepts of automobile mechanical design, the same component is designed using different elements or different connection methods of the same elements to generate a variety of mechanism graph theory diagrams.

[0051] Specifically, in T4, the model adjacency matrix is ​​a symmetric matrix. For example, the node numbered 1 has one edge connected to the node numbered 3, and the weighted value of the edge is 3. Then the element values ​​of the first row and third column of the matrix and the element values ​​of the third row and first column are both changed to 3. The specific construction steps include:

[0052] T41. Assign a unique number to each node of the organizational graph diagram;

[0053] T42. Create an n*n matrix, where n is the total number of nodes and all elements of the matrix are 0;

[0054] T43. According to the connection relationship between each node, the node number is used to anchor the element position in the matrix, and the element value is the weighted value.

[0055] Specifically, T5 includes the following steps:

[0056] T51. Invert the connection relationship of all model adjacency matrices into a path search problem through the inversion algorithm;

[0057] T52, use the shortest path algorithm and the minimum spanning tree algorithm to perform superposition interference judgment on the path, specifically use the shortest path algorithm to ensure that the nodes are connected most effectively, and use the minimum spanning tree algorithm to find the minimum weight tree connecting all nodes;

[0058] T53, filter out infeasible model adjacency matrices, including invalid, inefficient, and node-conflicting model adjacency matrices, and evaluate the performance of the remaining model adjacency matrices according to preset evaluation indicators to find the optimal model adjacency matrix and the corresponding mechanical design solution;

[0059] T54. Generate the corresponding mathematical and physical model based on the optimal model adjacency matrix.

[0060] Specifically, T55 generates mathematical and physical models by finding the corresponding physical components from the physical component library according to the components represented by the nodes, converting them, and generating corresponding model codes; automatically connecting related components according to the connection relationship of the matrix, determining the connection interface by judging the interface type, and generating corresponding connection codes; eliminating invalid components, optimizing the model layout by flipping components, regularizing connections, etc., and generating the final mathematical and physical model.

[0061] Embodiment 1: A simulation model is designed for a fuel cell system model using a method for generating an automobile mechanical simulation model based on graph theory.

[0062] T1. Design the initial mechanical design plan: In the early stage of fuel cell system design, the evaluation indicators of the overall system, such as electrode power density, rated power, etc., are clarified, and the mechanism diagram is drawn through simulation design software. Figure 3 As shown, the battery system can be divided into three paths: cooling water path, air path and hydrogen path, which are combined with the battery stack for reaction. In the air path, the humidifier, gas-liquid separator and turbine are optional. In the hydrogen path, the proportional valve and the ejector are optional, and there are multiple combinations of hydrogen pumps and ejectors.

[0063] T2. Extended design scheme: In this case, the fuel cell system has the following rules for reference, which can form 40 types of model adjacency matrices:

[0064] Air path: 1. Humidifier is optional. The humidifier has two pairs of interfaces, one for the dry gas side before entering the stack and the other for the wet gas side after leaving the stack; 2. Gas-liquid separator is optional. Generally, the gas-liquid separator and the turbine are paired. 3. Turbine is optional. There is a mechanical connection port between the turbine and the air compressor for torque input;

[0065] Hydrogen circuit: 1. Choose one between proportional valve and ejector; 2. The combinations of hydrogen pump and ejector are: ① single ejector; ② single hydrogen pump; ③ hydrogen pump and ejector in series; ④ hydrogen pump and ejector in parallel; ⑤ ejectors and ejectors in parallel.

[0066] T3. Construct a weighting table: assign different values ​​to each edge to express different associations. You can select characters from numbers and letters in order or at random to assign weights without repetition. Repetition represents the same weight. Label the edges on the graph model with their respective weights. The weighting table for this case is shown in the following table:

[0067] Table 1 Fuel cell system model weighting table

[0068] Join relationship Weight Connection between cooling water circuit and fuel cell stack 1 Connection between NEDC load and DC / DC 2 Connection between DC / DC and battery stack 3 Inter-component humidifier connection 4 Connection of gas-liquid separator and turbine combination to air pressure source 5 Connection between fuel cell stack and gas pressure source 6 Connection between hydrogen pump and ejector assembly and fuel cell stack 7 Connection between hydrogen pump and ejector combination and proportional valve and injector combination 8 Connection of proportional valve and ejector combination with pressure reducing valve 9 Connection between pressure reducing valve and hydrogen source 10 Connection between hydrogen pump and gas pressure source 11 Connection between hydrogen pump and ejector a Connection between ejectors b

[0069] T4. Construct the model adjacency matrix: According to the weight table and the mechanism graph theory diagram, use simulation software to convert the graph theory model into the model adjacency matrix. The graph theory model of the fuel cell system in this implementation has 13 nodes, so a 13*13 matrix with all zeros is established. Then, starting from node 1, sort out the edges connected to node 1, and assign the weights on the corresponding edges to the corresponding positions of the model adjacency matrix. For example, node 1 is only connected to node 7, and the weight is 1, so the values ​​at the [1,7] and [7,1] positions of the matrix are changed from 0 to 1, such as Figure 4 As shown. In the graph theory model of this case, the air path has a gas-liquid separator and a turbine combination, the hydrogen path selects a proportional valve, and the hydrogen pump and ejector combination selects a hydrogen pump and an ejector in series. The result is as follows Figure 2 shown.

[0070] T5. Evaluate the optimal design solution: Evaluate the performance of the model adjacency matrix according to the preset evaluation indicators to select the optimal mechanical design solution and generate the corresponding mathematical and physical model.

[0071] Finally, according to the initial fuel cell design goals, the optimization module of the simulation software is used to calibrate and optimize the parameters of the mathematical and physical model, and then the simulation is solved to obtain the actual output parameters of the model, calculate the performance indicators such as electrode power density and rated power, and determine whether the design indicators can be met. If they are met, the design scheme is determined. If not, the mechanism diagram is redrawn or another model adjacency matrix is ​​selected.

[0072] Embodiment 2: A method for generating an automobile mechanical simulation model based on graph theory is used to design a simulation model for a hybrid power system architecture model.

[0073] The hybrid system includes multiple power sources such as the engine and the motor. There are also many different design schemes for the power transmission paths of the engine and the motor. According to the requirements, the following schematic diagram is designed. The simplified hybrid system is as follows: Figure 5 As shown, through the method for generating a mechanical simulation model of an automobile, main components are represented by solid circles as nodes, connection relationships are represented by lines as edges, dashed lines or components are optional, and lines of different colors represent different connection categories. In this embodiment, the connection relationships of several hybrid power systems are integrated as follows Figure 6 shown.

[0074] Furthermore, construct the weighting table:

[0075] Table 2 Weighting table of hybrid power system architecture model

[0076] Join relationship Weight Battery and motor connection 1 Connection between generator and motor 2 Connection between generator and battery 3 Connection between generator and engine 4 Engine and motor connection 5 Connection between engine and clutch 1 6 Connection between clutch 1 and gearbox 1 7 Connection between clutch 1 and motor 8 Connection between gearbox 1 and motor 9 Connection between clutch 2 and motor 10 Connection between gearbox 2 and motor 11 Connection between reducer and motor 12 Connection between clutch 2 and gearbox 2 13 Connection between reducer and gearbox 2 14

[0077] Furthermore, according to the weighted graph, the graph theory model is converted into a model adjacency matrix using simulation software. Optionally, three rules are set to screen the feasibility of the scheme: ① Set required nodes, such as node 1, node 2, node 6, and node 9; ② ​​Set required edges, such as edges with a weight of 1; ③ Set nodes that must be associated, such as node 1 and node 2 must be associated, and node 2 and node 9 must be associated. Then, the simulation software uses a built-in inversion algorithm to invert the connection relationship into a possible path search problem to ensure path accessibility, thereby ensuring the feasibility of the model connection.

[0078] Those of ordinary skill in the art will appreciate that the units and method steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0079] In the several embodiments provided in the present application, it should be understood that the disclosed methods and systems can be implemented in other ways. For example, the division of the units described above is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. The above-mentioned units may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of the present invention.

[0080] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

[0081] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for generating an automobile mechanical simulation model based on graph theory, characterized in that: The first version of the mechanical design scheme is expanded based on graph theory, and the optimal mechanical design scheme is evaluated from the expanded multiple mechanical design schemes through weighted matrix transformation to generate the corresponding mathematical and physical model for simulation. The generation method includes: T1. Design the first version of the mechanical design plan: determine the plan requirements and evaluation indicators, and draw a schematic diagram of the mechanism through simulation design software; Each node in the T1 mechanism graph theory diagram represents a corresponding element, and each edge represents a power transmission relationship between elements; T2. Extended design plan: Expand the mechanism graph theory diagram according to different design ideas and generate multiple mechanism graph theory diagrams; In T2, according to the principles and concepts of automobile mechanical design, the same component is designed using different elements or different connection methods of the same element to generate a variety of mechanism graph theory diagrams; T3. Construct a weighting table: assign values ​​or letters to each edge in the various mechanism graph diagrams to form a corresponding weighting table; T4. Construct model adjacency matrix: convert all these weighted tables into symmetric model adjacency matrix and verify the feasibility of the model adjacency matrix; In T4, the model adjacency matrix is ​​a symmetric matrix. The steps to construct the model adjacency matrix include: T41. Assign a unique number to each node of the organizational graph diagram; T42. Create an n*n matrix, where n is the total number of nodes and all elements of the matrix are 0; T43. According to the connection relationship between each node, the node number is used to anchor the element position in the matrix, and the element value is the weighted value; T5. Evaluate the optimal design solution: Evaluate the performance of the model adjacency matrix according to the preset evaluation indicators to select the optimal mechanical design solution and automatically generate the corresponding mathematical and physical model; T5 includes the following steps: T51. Invert the connection relationship of all model adjacency matrices into a path search problem through the inversion algorithm; T52, use the shortest path algorithm and minimum spanning tree algorithm to perform superposition interference judgment on the path; In T52, the shortest path algorithm is used to ensure that the nodes are connected in the most effective way, and the minimum spanning tree algorithm is used to find the minimum weight tree connecting all nodes; T53, filter out infeasible model adjacency matrices, and evaluate the performance of the remaining model adjacency matrices according to preset evaluation indicators to find the optimal model adjacency matrix and the corresponding mechanical design solution; The model adjacency matrix filtered by T53 includes invalid, inefficient, and node-conflicting model adjacency matrices; T54. Generate the corresponding mathematical and physical model according to the optimal model adjacency matrix; The T54 generates a mathematical physical model including, according to the element represented by the node, finding the corresponding physical element from the physical element library, converting it, and generating the corresponding model code, wherein the physical element includes an engine, a generator, a battery, a motor, a gearbox, and a reducer; Automatically connect related components according to the connection relationship of the matrix, determine the connection interface by judging the interface type, and generate the corresponding connection code; Eliminate invalid components, optimize the model layout by flipping components and tidying up the wiring, and generate the final mathematical and physical model; T6. Conduct simulation and optimization verification on mathematical and physical models to ensure that the design meets the target indicators.

2. An electronic device, comprising a processor and a memory connected to the processor for storing instructions executable by the processor, characterized in that: The processor is used to execute the method for generating an automobile mechanical simulation model based on graph theory as described in claim 1 above.

3. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method for generating an automobile mechanical simulation model based on graph theory as claimed in claim 1 is implemented.

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