Parameter optimization method and device, electronic equipment and storage medium
By decoupling the model and operating conditions, storing and optimizing it separately, the problem of waste of storage space and large amount of operating conditions in vehicle development is solved, and efficient parameter optimization and multiple applications are achieved Coordinated optimization under working conditions.
Patent Information
- Application Number
- CN202411627310.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-14
- Publication Date
- 2025-02-18
AI Technical Summary
During the development of the vehicle, the existing technology has wasted storage space and large model modification operations due to the high complexity of the dynamic model and the large number of working conditions, and it is difficult to achieve collaborative optimization under multi-work conditions.
By decoupling the model and the working conditions and storing them separately, avoiding storing a model for each working condition. Use the optimization solver to optimize the target parameter value based on the data of each working condition index, adjust the model, and update the working condition index according to the adjusted model data until optimization goals are met.
It realizes saving storage space, improving model reusability and simulation optimization efficiency, and can be applied to a variety of working conditions, improving the efficiency and accuracy of parameter optimization.
Smart Images
Figure CN119475595A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of simulation technology, and in particular to a parameter optimization method and device, an electronic device, and a storage medium. Background Art
[0002] When developing a whole vehicle, the dynamics model is mainly established, and the overall performance indicators are obtained by calculation and simulation under different working conditions, so as to verify the influence of design parameters on the performance of the whole vehicle. For example, taking the optimization of automobile suspension structure as an example, according to the given optimization parameter values, a dynamic model is established for each working condition and the corresponding indicators are defined. The corresponding indicator data is extracted from the result file corresponding to each working condition, and the optimal set of indicator data is selected as the optimization parameter value by comparing the indicator data. When the complexity of the dynamics model is high and the number of working conditions is large, a large amount of storage space will be wasted. Summary of the invention
[0003] In order to solve the above problems, the embodiments of the present application provide a parameter optimization method and device, an electronic device, and a storage medium.
[0004] In a first aspect, an embodiment of the present application provides a parameter optimization method, including: determining a target object model, the target object model is determined based on design parameter data of the target object, wherein the design parameter data includes parameter values corresponding to multiple design parameters, and at least one design parameter is a target parameter; determining at least one target operating condition and one or more operating condition indicators corresponding to each target operating condition; based on each target operating condition and the target object model, determining indicator data for each operating condition indicator corresponding to each target operating condition; and determining a target parameter value for the target parameter based on the indicator data for each operating condition indicator corresponding to each target operating condition.
[0005] In combination with the first aspect, based on the indicator data of each operating condition indicator corresponding to each target operating condition, the target parameter value of the target parameter is determined, including: based on the indicator data of each operating condition indicator corresponding to each target operating condition, the target parameter is optimized using an optimization solver to obtain the optimized parameter value of the target parameter; based on the optimized parameter value of the target parameter, the target object model is adjusted; based on the adjusted target object model and each target operating condition, the indicator data of each operating condition indicator is updated; when the indicator data of at least one updated operating condition indicator does not meet the optimization target, the step of updating the indicator data of each operating condition indicator is repeated; when the indicator data of each updated operating condition indicator meets the optimization target, the optimized parameter value of the target parameter is determined as the target parameter value of the target parameter.
[0006] In combination with the first aspect, when the indicator data of each updated operating condition indicator meets the optimization target, before determining the optimized parameter value of the target parameter as the target parameter value of the target parameter, the parameter optimization method also includes: determining whether the optimized parameter value of the target parameter meets the constraint conditions, and the constraint conditions include at least the parameter value range of the target parameter; when the optimized parameter value of the target parameter meets the constraint conditions, determining the optimized parameter value of the target parameter as the target parameter value of the target parameter; when the optimized parameter value of the target parameter does not meet the constraint conditions, repeating the step of updating the indicator data of each operating condition indicator until the optimized parameter value of the target parameter meets the constraint conditions and the indicator data of each operating condition indicator meets the optimization target.
[0007] In combination with the first aspect, the target operating condition includes operating condition information; based on each target operating condition and the target object model, the index data of each operating condition indicator corresponding to each target operating condition is determined, including: based on the operating condition information included in each target operating condition, the target object model is simulated and analyzed to obtain the simulation results corresponding to each target operating condition; based on the simulation results corresponding to each target operating condition, the index data of each operating condition indicator is determined.
[0008] In combination with the first aspect, based on the simulation results corresponding to each target working condition, the indicator data of each working condition indicator is determined, including: based on each working condition indicator corresponding to each target working condition, a topological relationship diagram of the working condition indicator is determined; based on the topological relationship diagram, multiple target simulation results are determined in the simulation results to obtain a target simulation result set; based on one or more target simulation results in the target simulation result set, the indicator data of each working condition indicator is determined.
[0009] In combination with the first aspect, the target object model is stored in a first file, each target operating condition is stored in a respective second file, the first file also stores multiple general indicators, and the second file also stores specific indicators corresponding to the target operating condition; determining the operating condition indicator corresponding to each target operating condition includes: obtaining the specific indicator corresponding to the target operating condition in the second file corresponding to the target operating condition; and selecting the general indicator corresponding to the target operating condition from the multiple general indicators in the first file.
[0010] In combination with the first aspect, after determining the target parameter value of the target parameter based on the indicator data of each operating condition indicator corresponding to each of the target operating conditions, the parameter optimization method also includes: sending the target parameter value of the target parameter to the user end for the user to view; if a new parameter to be optimized is received from the user end, the new parameter to be optimized is determined as the target parameter, and the step of determining the target parameter value of the target parameter based on the indicator data of each operating condition indicator corresponding to each target operating condition is repeated; or, if a new parameter value range of the target parameter is received from the user end, the step of determining the target parameter value of the target parameter based on the indicator data of each operating condition indicator corresponding to each target operating condition is repeated.
[0011] In a second aspect, an embodiment of the present application provides a parameter optimization device, comprising: a determination module; the determination module is used to determine a target object model, wherein the target object model is determined based on design parameter data of the target object, wherein the design parameter data includes parameter values corresponding to multiple design parameters, and at least one design parameter is a target parameter; the determination module is also used to determine at least one target operating condition and one or more operating condition indicators corresponding to each target operating condition; the determination module is also used to determine, based on each target operating condition and the target object model, indicator data of each operating condition indicator corresponding to each target operating condition; the determination module is also used to determine the target parameter value of the target parameter based on the indicator data of each operating condition indicator corresponding to each target operating condition.
[0012] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a processor; a memory, the memory being connected to the processor, the memory being used to store a computer program, and the computer program implementing the above-mentioned parameter optimization method when executed by the processor.
[0013] In a fourth aspect, an embodiment of the present application provides a storage medium having a computer program stored thereon. When the computer program is executed by a processor, the above-mentioned parameter optimization method is implemented.
[0014] In a fifth aspect, an embodiment of the present application provides a computer program product, including computer program instructions, which implement the above-mentioned parameter optimization method when executed by a processor.
[0015] Through the above technical solution, the model and the working condition are decoupled and stored separately. There is no need to store a model for each working condition, which can save storage space and improve the reusability of the model. On the other hand, when performing parameter optimization, only the model needs to be changed to be applicable to a variety of working conditions, thereby improving the efficiency of simulation optimization. In addition, in an embodiment of the present application, general indicators are stored in a first file related to the model, and specific indicators are stored in a second file related to the corresponding working condition, which can avoid repeated definition and storage of general indicators, save storage space, and realize flexible definition of specific indicators. In addition, in an embodiment of the present application, only simulation results related to working condition indicators need to be stored, and the minimized set of simulation results is determined based on the working condition indicators, thereby greatly saving disk space and improving optimization efficiency. BRIEF DESCRIPTION OF THE DRAWINGS
[0016] Figure 1 It is a flow chart of a parameter optimization method provided in one embodiment of the present application.
[0017] Figure 2 It is a flowchart of a method for determining indicator data of each operating condition indicator provided in an embodiment of the present application.
[0018] Figure 3 A schematic diagram of a topological relationship diagram is shown.
[0019] Figure 4a It is a schematic diagram of the model and working condition coupling of the four-bar linkage structure in the prior art.
[0020] Figure 4b It is a schematic diagram of the model and working condition decoupling of the four-bar linkage structure of the present application.
[0021] Figure 5 It is a flow chart of a parameter optimization method provided in yet another embodiment of the present application.
[0022] Figure 6 It is a flow chart of a parameter optimization method provided in yet another embodiment of the present application.
[0023] Figure 7 It is a structural block diagram of a parameter optimization device provided in one embodiment of the present application.
[0024] Figure 8 It is a schematic diagram of the structure of an electronic device provided in one embodiment of the present application. DETAILED DESCRIPTION
[0025] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.
[0026] In the existing scheme, a dynamic model needs to be built for each working condition, that is, the model information and the working condition information are coupled and saved together; when the complexity of the dynamic model is high and the number of working conditions is large, a lot of storage space will be wasted. When the design parameters need to be optimized, the dynamic model needs to be changed during the optimization process. At this time, the dynamic model corresponding to each working condition needs to be modified synchronously, which increases the amount of calculation for modifying the model; if the dynamic model under a certain working condition is changed incorrectly, the simulation results may be invalid.
[0027] In the face of the above technical problems, an embodiment of the present application provides a parameter optimization method, which is particularly suitable for collaborative optimization under multiple working conditions. The parameter optimization method includes: determining a target object model, the target object model is determined based on the design parameter data of the target object, wherein the design parameter data includes parameter values corresponding to multiple design parameters, and at least one design parameter is a target parameter; determining at least one target working condition and one or more working condition indicators corresponding to each target working condition; based on each target working condition and the target object model, determining the index data of each working condition indicator corresponding to each target working condition; based on the index data of each working condition indicator corresponding to each target working condition, determining the target parameter value of the target parameter. In an embodiment of the present application, the model and the working condition are decoupled and stored separately. There is no need to store a model for each working condition, which can save storage space and improve the reusability of the model; on the other hand, when performing parameter optimization, only the model needs to be changed to be applicable to a variety of working conditions, thereby improving the efficiency of simulation optimization.
[0028] Figure 1 1 is a flow chart of a parameter optimization method provided in an embodiment of the present application. The parameter optimization method in the embodiment of the present application is particularly suitable for parameter optimization under multiple working conditions. The method can be executed on a model building system, and the model building system is used to generate a multi-body dynamics model and optimize the multi-body dynamics model (i.e., parameter optimization). Figure 1 As shown, the method includes the following steps.
[0029] Step S110, determining the target object model.
[0030] In the embodiment of the present application, the target object model is determined based on the design parameter data of the target object.
[0031] In an embodiment of the present application, the target object includes a vehicle, a vehicle component (e.g., a shock absorber, a suspension, a hood, etc.), or other mechanical structural parts, and the present application is not limited. Optionally, the design parameter data of the target object includes parameter values corresponding to each of the multiple design parameters, for example, the initial parameter values of the design parameters set by the user. Exemplarily, for a vehicle, the design parameters may include parameters such as spring stiffness, frame stiffness, suspension size, door panel size, tire mechanical properties, mass, center of mass, inertia, etc. Optionally, at least one design parameter is a target parameter, and the target parameter is a parameter that needs to be optimized. In an embodiment of the present application, the design parameter data and the target parameter are both defined by the user, and the design parameter data and the target parameter are obtained from the user's user terminal (e.g., a mobile phone, a computer, etc., or other input device).
[0032] The target object model is constructed according to the design parameter data. In the embodiment of the present application, the target object model only includes intrinsic properties. Intrinsic properties refer to properties that will not change under the action of external forces, such as component shape, component size, connection relationship between components, and physical properties such as mass / rigidity. When modifying the design parameters of the model later, only the corresponding parameter values need to be modified without considering the working conditions.
[0033] Step S120, determining at least one target operating condition and one or more operating condition indicators corresponding to each target operating condition.
[0034] In an embodiment of the present application, at least one target working condition is obtained from a user terminal of a user, and the target working condition includes working condition information. Optionally, working condition information corresponding to the target working condition can be obtained from the user terminal of the user, or working condition information corresponding to the target working condition can be queried in a working condition information database. The working condition information database is used to indicate the corresponding relationship between the working condition and the working condition information, and the working condition information database is generated in advance.
[0035] In the embodiment of the present application, the operating condition information can be understood as including information that can affect the performance of the target object under the target operating condition. Optionally, the operating condition information includes boundary conditions, such as force boundary conditions, displacement boundary conditions, whether the connection relationship is activated, etc. Exemplarily, the target operating condition is a bump-crossing condition, and the corresponding operating condition information includes the driving speed of the car, the displacement boundary conditions of the wheels, etc. For another example, the target operating condition is a waist stiffness condition, and the corresponding operating condition information includes the inner panel waist loading point information and the outer panel waist loading point information. For another example, the target operating condition can be an exterior rearview mirror mounting point stiffness condition, and the corresponding operating condition information includes the exterior rearview mirror mounting point information, etc.
[0036] In an embodiment of the present application, the target object model is stored in a first file, and each target working condition is stored in a respective second file. In this way, the decoupling and separate storage of the model and the working condition can be achieved. The first file also stores a plurality of general indicators, and the second file also stores specific indicators corresponding to the target working condition. In an embodiment of the present application, the general indicator refers to an indicator required for various working conditions, which does not depend on the working condition information and can be stored in the first file, so that the repeated definition (or modification) and storage of the general indicator can be avoided. For example, when it is necessary to modify the calculation method of a certain general indicator, it is only necessary to change the general indicator in the first file, without having to modify it one by one in the corresponding working condition, which can avoid missing or wrong modification, and thus avoid errors in the simulation results. The specific indicator is related to the specific working condition, so the specific indicator is directly stored in the second file of the corresponding target working condition. In this way, the indicator cannot be accessed under other working conditions, thereby ensuring that illegal operations will not occur, and flexible definition of specific indicators can also be performed.
[0037] Optionally, the specific index corresponding to the target working condition is obtained in the second file corresponding to the target working condition, that is, all the specific indexes corresponding to the target working condition are selected. Since the general indexes of multiple working conditions are stored in the first file, determining the general index of any target working condition includes: selecting the general index corresponding to the target working condition from the multiple general indexes in the first file. The general index and the specific index constitute the working condition index corresponding to the target working condition.
[0038] Step S130 , based on each target operating condition and the target object model, determining the index data of each operating condition index corresponding to each target operating condition.
[0039] Optionally, the method for determining the index data of each working condition index is specifically referred to Figure 2 .like Figure 2 As shown, the method comprises the following steps:
[0040] Step S210 , performing simulation analysis on the target object model based on the operating condition information included in each target operating condition, and obtaining simulation results corresponding to each target operating condition.
[0041] In the embodiment of the present application, under each target working condition, the target object model is simulated and analyzed according to the working condition information to obtain multiple simulation results under the target working condition. The index data of the working condition index is calculated from the corresponding simulation results.
[0042] Step S220, determining the index data of each operating condition index based on the simulation results corresponding to each target operating condition.
[0043] In an embodiment of the present application, the simulation results include the full simulation results of the target object (i.e., the simulation results of multiple components), for example, including the simulation results of the vehicle suspension, the simulation results of the shock absorber, the simulation results of the door panel, the simulation results of the hood, etc. However, when determining the index data of the working condition index, it is only necessary to select the simulation results corresponding to the working condition index. If the full simulation results are stored, storage space will be wasted and the simulation efficiency will be reduced. For example, when performing parameter optimization, it is necessary to simulate thousands of times, and the number of related working condition indicators is generally between 3 and 20. The number of simulation results required for each working condition indicator is generally not more than 10, that is, when calculating the working condition index, only a small part of all simulation results needs to be used. Therefore, in an embodiment of the present application, it is only necessary to store the simulation results related to the working condition indicators, and determine the minimized set of simulation results based on the working condition indicators, thereby greatly saving disk space and improving optimization efficiency.
[0044] Optionally, based on each operating condition indicator corresponding to each target operating condition, a topological relationship diagram of the operating condition indicators is determined, and the topological relationship diagram shows the relationship between the simulation results and the operating condition indicators, and between the operating condition indicators. Then, based on the topological relationship diagram, multiple target simulation results are determined in the simulation results to obtain a target simulation result set. The target simulation result set is a minimized set of all simulation results used to calculate the operating condition indicators. In an embodiment of the present application, only the target simulation result set needs to be stored, and the full amount of simulation results does not need to be stored, which can save storage space and improve optimization efficiency. Based on one or more target simulation results in the target simulation result set, the indicator data of each operating condition indicator is determined. For each operating condition indicator, the target simulation result corresponding to the operating condition indicator is determined, and the target simulation result is calculated to obtain the indicator data of the operating condition indicator.
[0045] Figure 3 A schematic diagram of a topological relationship diagram is shown. Figure 3 As shown, the simulation result corresponding to index 5 is calculated by the simulation results corresponding to index 1 and index 4 and the simulation result corresponding to number 310. The simulation results of index 1, index 4 and number 310 are taken as the union to obtain the simulation result of index 5, which is the simulation result set corresponding to index 1 and index 4. The simulation result corresponding to index 3 is calculated by the simulation result corresponding to index 2 and the simulation result corresponding to number 320. The simulation results corresponding to index 1, index 2, index 3, index 4 and index 5 are taken as the union to obtain the simulation result set, that is, Figure 3 The black part on the straight line 30 in FIG. After each simulation analysis, only the simulation results corresponding to the working condition indicators need to be stored, which can greatly save storage space and improve optimization efficiency.
[0046] Step S140, determining a target parameter value of a target parameter based on the indicator data of each operating condition indicator corresponding to each target operating condition.
[0047] In an embodiment of the present application, after determining the index data of each operating condition indicator, the difference between the index data of each operating condition indicator and the optimization target (i.e., the expected index data) can be judged to determine the optimization direction of the target parameter until the index data of each operating condition indicator meets the optimization target.
[0048] Specifically, based on the index data of each operating condition index corresponding to each target operating condition, the target parameters are optimized using an optimization solver to obtain the optimized parameter values of the target parameters, and the target object model is adjusted based on the optimized parameter values of the target parameters; based on the adjusted target object model and each target operating condition, the index data of each operating condition index is updated. Determine whether the index data of the updated operating condition index meets the optimization target, and when the index data of at least one updated operating condition index does not meet the optimization target, repeat the step of updating the index data of each operating condition index; when the index data of each updated operating condition index meets the optimization target, determine the optimized parameter value of the target parameter as the target parameter value of the target parameter. For more description on determining the target parameter value of the target parameter, please refer to this application Figure 5 The relevant description in will not be repeated here.
[0049] Optionally, after determining the target parameter value of the target parameter, the method further includes: sending the target parameter value of the target parameter to the user terminal for the user to view. If the user is satisfied with the current design, the optimization is terminated. For example, an instruction to terminate the optimization can be sent to the model modeling system. If the user is not satisfied with the current design, a new parameter to be optimized is determined, or a new parameter value range of the currently optimized parameter is determined and sent to the model modeling system. If the model modeling system receives the parameter to be optimized sent by the user terminal, the new parameter to be optimized is determined as the target parameter, and the step of determining the target parameter value of the target parameter based on the indicator data of each operating condition indicator corresponding to each target operating condition is repeated (i.e., step S140). If the model modeling system receives a new parameter value range of the target parameter sent by the user terminal, the step of determining the target parameter value of the target parameter based on the indicator data of each operating condition indicator corresponding to each target operating condition is repeated (i.e., step S140).
[0050] In an embodiment of the present application, the model and the working condition are decoupled and stored separately. There is no need to store a model for each working condition, which can save storage space and improve the reusability of the model. On the other hand, when performing parameter optimization, only the model needs to be changed to be applicable to a variety of working conditions, thereby improving the efficiency of simulation optimization. In addition, in an embodiment of the present application, general indicators are stored in a first file related to the model, and specific indicators are stored in a second file related to the corresponding working condition, which can avoid repeated definition and storage of general indicators, save storage space, and enable flexible definition of specific indicators. In addition, in an embodiment of the present application, only simulation results related to working condition indicators need to be stored, and the minimized set of simulation results is determined based on the working condition indicators, thereby greatly saving disk space and improving optimization efficiency.
[0051] Figure 4a It is a schematic diagram of the model and working condition coupling of the four-bar linkage structure in the prior art. Figure 4bSchematic diagram of the model and working condition decoupling of the four-bar linkage structure of the present application. Figure 4a As shown in the figure, the modeling process includes: first create three rods, then create constraint pairs at the connections between the rods, then create drives based on the constraint pairs, and finally select the corresponding time integrator for simulation calculation. If you want to change the drive rod from rod 1 to rod 3 (that is, change the working condition), you need to manually delete the drive on the current rod 1, then add a new drive on rod 3, and finally manually submit a new simulation calculation task. Figure 4b As shown, in an embodiment of the present application, the model (e.g., physical properties) and the working condition (e.g., boundary conditions) are decoupled: the model only retains the intrinsic properties of the four-bar linkage physical model, namely the shape, density, spatial position of each rod and the constraint pairs (connection relationships) between the rods; the working condition includes boundary conditions, such as force elements, drives, and activation / invalidation of connection relationships. In this embodiment, working condition 1 applies a corresponding drive to the rotation pair between rod 1 and the ground; working condition 2 applies a corresponding drive to the rotation pair between rod 3 and the ground. The decoupling of the model and the working condition improves the reusability of the model, greatly saves disk storage space (otherwise all model information needs to be saved for each working condition), and facilitates the debugging of the model.
[0052] Figure 5 is a flow chart of a parameter optimization method provided by another embodiment of the present application. The parameter optimization method of the embodiment of the present application is particularly suitable for parameter optimization under multiple working conditions. Optionally, the method is executed by a model building system. Figure 5 As shown, the method includes the following steps.
[0053] Step S510, determining a target object model.
[0054] In the embodiment of the present application, the target object model is determined based on the design parameter data of the target object.
[0055] Step S520: determine at least one target operating condition and one or more operating condition indicators corresponding to each target operating condition.
[0056] Step S530 , based on each target operating condition and the target object model, determine the indicator data of each operating condition indicator corresponding to each target operating condition.
[0057] In the embodiment of the present application, steps S510-S530 are the same as steps S110-S130. The specific steps of steps S510-S530 can refer to steps S110-S130 and will not be repeated here.
[0058] Step S540, based on the index data of each operating condition index corresponding to each target operating condition, the target parameter is optimized using an optimization solver to obtain an optimized parameter value of the target parameter.
[0059] In an embodiment of the present application, the difference between the index data of each operating condition index and the optimization target (for example, the expected index data of each operating condition index) is compared, the optimization direction of the target parameter is determined, and the target parameter is optimized using the optimization solver to obtain the optimized parameter value of the target parameter. In an embodiment of the present application, the optimization solver can call an optimization algorithm to perform an optimization operation. Optionally, the optimization algorithm includes at least one of Design Of Experiment (DOE), Sequential Least Squares Programming (SLSQP), and Non-dominated Sorting Genetic Algorithm (NSGA). Optionally, the optimization algorithm can be defined in advance by the user.
[0060] Step S550: adjusting the target object model based on the optimized parameter value of the target parameter.
[0061] Optionally, the target object model is adjusted using the optimized parameter value of the target parameter to obtain an adjusted target object model. In the embodiment of the present application, since the working condition and the model are decoupled, the target object model does not depend on the working condition information, and the target object model only needs to be adjusted once, thereby improving the simulation efficiency and accuracy.
[0062] Step S560: updating the index data of each operating condition index based on the adjusted target object model and each target operating condition.
[0063] Optionally, based on the working condition information included in each target working condition, the adjusted target object model is simulated and analyzed to obtain a simulation result corresponding to each target working condition; based on the simulation result corresponding to each target working condition, the index data of each working condition index is determined. In this step, the index data of the working condition index determined is the updated index data, which is different from the index data of the working condition index determined in step S530.
[0064] Step S570, determining whether the indicator data of each updated operating condition indicator meets the optimization target.
[0065] Compare the difference between the index data of the updated working condition index and the optimization target. If the index data of at least one updated working condition index does not meet the optimization target, return to step S540 to continue optimizing the target parameter. If the index data of each updated working condition index meets the optimization target, execute step S580. In step S580, the optimized parameter value of the target parameter is determined as the target parameter value of the target parameter.
[0066] In an embodiment of the present application, the model and the operating condition are decoupled and stored separately. When performing parameter optimization, only the model needs to be changed to be applicable to a variety of operating conditions, thereby improving the efficiency and accuracy of simulation optimization.
[0067] In some embodiments, the target parameter value of the target parameter also needs to satisfy the constraint condition, otherwise it will cause the size of the components of the generated model to be inappropriate or there will be interference between the components. Figure 6 shown.
[0068] Figure 6 is a flow chart of a parameter optimization method provided by another embodiment of the present application. The parameter optimization method in the embodiment of the present application is particularly suitable for parameter optimization under various working conditions. Optionally, the method is executed by a model building system. Figure 6 As shown, the method includes the following steps.
[0069] Step S610, determining a target object model.
[0070] In the embodiment of the present application, the target object model is determined based on the design parameter data of the target object.
[0071] Step S620: determine at least one target operating condition and one or more operating condition indicators corresponding to each target operating condition.
[0072] Step S630: determining the index data of each operating condition index corresponding to each target operating condition based on each target operating condition and the target object model.
[0073] Step S640, based on the index data of each operating condition index corresponding to each target operating condition, the target parameter is optimized using an optimization solver to obtain an optimized parameter value of the target parameter.
[0074] Step S650: adjusting the dynamics model based on the optimized parameter value of the target parameter.
[0075] Step S660: updating the index data of each operating condition index based on the adjusted dynamic model and each target operating condition.
[0076] In the embodiment of the present application, steps S610-660 are the same as steps S510-S560 and are not described again here.
[0077] Step S670, determining whether the indicator data of each updated operating condition indicator meets the optimization target.
[0078] In the embodiment of the present application, when the index data of at least one updated operating condition index does not meet the optimization target, the process returns to step S640. When the index data of each updated operating condition index meets the optimization target, the process executes step S680.
[0079] In step S680, it is determined whether the optimized parameter value of the target parameter satisfies the constraint condition. The constraint condition includes at least the parameter value range of the target parameter. Optionally, the constraint condition can be defined by the user and sent to the model building system through the client. When the optimized parameter value of the target parameter does not satisfy the constraint condition, return to step S640. When the optimized parameter value of the target parameter satisfies the constraint condition, step S690 is executed, in which the optimized parameter value of the target parameter is determined as the target parameter value of the target parameter.
[0080] In an embodiment of the present application, before determining the optimized parameter value of the target parameter as the target parameter value of the target parameter, it also includes: determining whether the optimized parameter value of the target parameter satisfies the constraint conditions. In this way, it is possible to avoid inappropriate component sizes of the generated model or interference between components, thereby improving the simulation accuracy of the model.
[0081] In the embodiments of the present application, in order to fully understand the technical solution of the present application, the optimization of vehicle handling stability is used as an example for explanation. When the vehicle is in a turning condition, it is hoped that the steering wheel can be accurately and quickly controlled, and the corresponding spring stiffness coefficient of the suspension is required to be larger and the damping coefficient is smaller; however, when the vehicle is in a bump-crossing condition, it is hoped that the vehicle body has no vibration to provide a better riding experience, and at this time, the spring stiffness coefficient of the suspension is required to be smaller and the damping coefficient is larger.
[0082] The user defines the design parameter data of the vehicle model, and determines one or more design parameters to be optimized (i.e., target parameters) and the parameter value range of the target parameters (i.e., constraints). In an embodiment of the present application, the target parameters include the stiffness coefficient and damping coefficient of the spring. The user also needs to define the corresponding target operating conditions and determine the operating condition indicators corresponding to each target operating condition. In an embodiment of the present application, the target operating conditions include steady-state turning conditions, step steering conditions, parallel wheel hop conditions, and bump-crossing conditions. Exemplarily, the operating condition indicators include the maximum vehicle speed or maximum radius under steady-state turning conditions, the maximum displacement of the vehicle body under parallel wheel hop conditions, and the disappearance time of the oscillation. In addition, the user also needs to define the optimization algorithm.
[0083] The model building system obtains the design parameter data sent by the user end, and generates a vehicle model based on the design parameter data. The vehicle model only includes the intrinsic properties of the vehicle. The vehicle model is simulated and analyzed under each target working condition to obtain the index data of the working condition index under each target working condition. According to the index data of each working condition index under each target working condition, the target parameter (i.e., spring stiffness coefficient, damping coefficient) is optimized using an optimization solver to obtain the optimized parameter value of the target parameter. Based on the optimized parameter value of the target parameter, the vehicle model is adjusted, and the index data of each working condition index is updated based on the adjusted vehicle model and each target working condition. It is judged whether the index data of the updated working condition index meets the optimization target and whether the optimized parameter value of the target parameter meets the constraint condition. If not, it is necessary to repeat the step of updating the index data of each working condition index; if satisfied, the optimized parameter value of the target parameter is determined as the target parameter value of the target parameter. The model building system sends the target parameter value of the target parameter to the user end for the user to view.
[0084] If the user is satisfied with the current result, the current optimization task is completed; if the user is not satisfied with the current result, the user can redefine the parameters to be optimized, or redefine the parameter value range of the parameters to be optimized, and perform the optimization task again.
[0085] Figure 7 is a structural block diagram of a parameter optimization device provided in an embodiment of the present application. Figure 7 As shown, the parameter optimization device 700 includes a determination module 710 .
[0086] The determination module 710 is used to determine a target object model, where the target object model is determined based on design parameter data of the target object, wherein the design parameter data includes parameter values corresponding to a plurality of design parameters, and at least one design parameter is a target parameter.
[0087] The determination module 710 is used to determine at least one target operating condition and one or more operating condition indicators corresponding to each target operating condition.
[0088] Optionally, the determination module 710 is further configured to obtain a specific indicator corresponding to the target operating condition in a second file corresponding to the target operating condition; and select a general indicator corresponding to the target operating condition from a plurality of general indicators in the first file.
[0089] The determination module 710 is further configured to determine the index data of each operating condition index corresponding to each target operating condition based on each target operating condition and the target object model.
[0090] Optionally, the determination module 710 is further used to perform simulation analysis on the target object model based on the operating condition information included in each target operating condition to obtain a simulation result corresponding to each target operating condition; and determine the indicator data of each operating condition indicator based on the simulation result.
[0091] Optionally, the determination module 710 is also used to determine a topological relationship diagram of the operating condition indicators based on each operating condition indicator corresponding to each target operating condition; based on the topological relationship diagram, determine multiple target simulation results in the simulation results to obtain a target simulation result set; based on one or more target simulation results in the target simulation result set, determine the indicator data of each operating condition indicator.
[0092] The determination module 710 is further configured to determine a target parameter value of a target parameter based on the indicator data of each operating condition indicator corresponding to each target operating condition.
[0093] Optionally, the determination module 710 is also used to optimize the target parameters using an optimization solver based on the index data of each operating condition index corresponding to each target operating condition to obtain the optimized parameter values of the target parameters; adjust the target object model based on the optimized parameter values of the target parameters; update the index data of each operating condition index based on the adjusted target object model and each target operating condition; when the index data of at least one updated operating condition index does not meet the optimization target, repeat the step of updating the index data of each operating condition index; when the index data of each updated operating condition index meets the optimization target, determine the optimized parameter value of the target parameter as the target parameter value of the target parameter.
[0094] Optionally, the determination module 710 is also used to determine whether the optimized parameter value of the target parameter satisfies the constraint conditions, and the constraint conditions include at least the parameter value range of the target parameter; when the optimized parameter value of the target parameter satisfies the constraint conditions, the optimized parameter value of the target parameter is determined as the target parameter value of the target parameter; when the optimized parameter value of the target parameter does not satisfy the constraint conditions, repeat the step of updating the indicator data of each operating condition indicator until the optimized parameter value of the target parameter satisfies the constraint conditions and the indicator data of each operating condition indicator meets the optimization target.
[0095] Optionally, the determination module 710 is also used to send the target parameter value of the target parameter to the user end for the user to view; if a new parameter to be optimized is received from the user end, the new parameter to be optimized is determined as the target parameter, and the step of determining the target parameter value of the target parameter based on the indicator data of each operating condition indicator corresponding to each target operating condition is repeated; or, if a new parameter value range of the target parameter is received from the user end, the step of determining the target parameter value of the target parameter based on the indicator data of each operating condition indicator corresponding to each target operating condition is repeated.
[0096] The specific working principle and benefits of the parameter optimization device provided in the embodiment of the present application are similar to the specific working principle and benefits of the parameter optimization method provided in the embodiment of the present application, and will not be repeated here.
[0097] Below, reference Figure 8To describe an electronic device according to an embodiment of the present application. Figure 8 It is a schematic diagram of the structure of an electronic device provided in one embodiment of the present application.
[0098] like Figure 8 As shown, the electronic device 800 includes one or more processors 801 and a memory 802 .
[0099] The processor 801 may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device 800 to perform desired functions.
[0100] The memory 802 may include one or more computer program products, and the computer program product may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may include, for example, a read-only memory (ROM), a hard disk, a flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 801 may run the program instructions to implement the parameter optimization method and / or other desired functions of the various embodiments of the present application described above. Various contents such as design parameter data, operating condition information, and operating condition indicators may also be stored in the computer-readable storage medium.
[0101] In one example, the electronic device 800 may further include: an input device 803 and an output device 804 , and these components are interconnected via a bus system and / or other forms of connection mechanisms (not shown).
[0102] The input device 803 may include, for example, a keyboard, a mouse, etc.
[0103] The output device 804 can output various information to the outside, including indicator data of working condition indicators, target parameter values of target parameters, etc. The output device 804 can include, for example, a display, a speaker, a printer, a communication network and its connected remote output device, etc.
[0104] Of course, to simplify, Figure 8 Only some of the components related to the present application in the electronic device 800 are shown, and components such as a bus, an input / output interface, etc. are omitted. In addition, according to specific application situations, the electronic device 800 may also include any other appropriate components.
[0105] In addition to the above-mentioned methods and devices, an embodiment of the present application may also be a computer program product, which includes computer program instructions, which, when executed by a processor, enable the processor to execute the steps of the parameter optimization method according to various embodiments of the present application described above in this specification.
[0106] The computer program product may be written in any combination of one or more programming languages to write program codes for performing the operations of the embodiments of the present application, including object-oriented programming languages, such as Java, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as an independent software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server.
[0107] In addition, an embodiment of the present application may also be a computer-readable storage medium on which computer program instructions are stored. When the computer program instructions are executed by a processor, the processor executes the steps of the parameter optimization method according to various embodiments of the present application described above in this specification.
[0108] The computer readable storage medium can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can include, for example, but is not limited to, a system, device or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.
[0109] The basic principles of the present application are described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, effects, etc. mentioned in the present application are only examples and not limitations, and it cannot be considered that these advantages, strengths, effects, etc. are required by each embodiment of the present application. In addition, the specific details disclosed above are only for the purpose of illustration and ease of understanding, not for limitation, and the above details do not limit the present application to being implemented by adopting the above specific details.
[0110] The block diagrams of the devices, apparatuses, equipment, and systems involved in this application are only illustrative examples and are not intended to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagram. As will be appreciated by those skilled in the art, these devices, apparatuses, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "including", "comprising", "having", etc. are open words, referring to "including but not limited to", and can be used interchangeably with them. The words "or" and "and" used here refer to the words "and / or" and can be used interchangeably with them, unless the context clearly indicates otherwise. The words "such as" used here refer to the phrase "such as but not limited to", and can be used interchangeably with them.
[0111] It should also be noted that in the apparatus, device and method of the present application, each component or each step can be decomposed and / or recombined. Such decomposition and / or recombination should be regarded as equivalent solutions of the present application.
[0112] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of the present application. Therefore, the present application is not intended to be limited to the aspects shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.
[0113] The above description has been given for the purpose of illustration and description. In addition, this description is not intended to limit the embodiments of the present application to the forms disclosed herein. Although multiple example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions and sub-combinations thereof.
Claims
1. A parameter optimization method, characterized in that: include: Determine a target object model, wherein the target object model is determined based on design parameter data of the target object, wherein the design parameter data includes parameter values corresponding to each of a plurality of design parameters, and at least one of the design parameters is a target parameter; Determine at least one target operating condition and one or more operating condition indicators corresponding to each of the target operating conditions; Based on each of the target operating conditions and the target object model, determining the indicator data of each of the operating condition indicators corresponding to each of the target operating conditions; Based on the indicator data of each operating condition indicator corresponding to each target operating condition, a target parameter value of the target parameter is determined.
2. The parameter optimization method according to claim 1, characterized in that: The step of determining the target parameter value of the target parameter based on the indicator data of each operating condition indicator corresponding to each target operating condition includes: Based on the index data of each operating condition index corresponding to each target operating condition, the target parameter is optimized using an optimization solver to obtain an optimized parameter value of the target parameter; based on the optimized parameter value of the target parameter, the target object model is adjusted; based on the adjusted target object model and each target operating condition, the index data of each operating condition index is updated; When the index data of at least one of the updated operating condition indicators does not meet the optimization target, repeating the step of updating the index data of each of the operating condition indicators; When the index data of each updated operating condition index meets the optimization target, the optimized parameter value of the target parameter is determined as the target parameter value of the target parameter.
3. The parameter optimization method according to claim 2, characterized in that: When the index data of each of the updated operating condition indicators meets the optimization target, before determining the optimized parameter value of the target parameter as the target parameter value of the target parameter, the parameter optimization method further includes: Determining whether the optimized parameter value of the target parameter satisfies a constraint condition, wherein the constraint condition at least includes a parameter value range of the target parameter; When the optimized parameter value of the target parameter satisfies the constraint condition, determining the optimized parameter value of the target parameter as the target parameter value of the target parameter; When the optimized parameter value of the target parameter does not satisfy the constraint condition, the step of updating the index data of each operating condition index is repeated until the optimized parameter value of the target parameter satisfies the constraint condition and the index data of each operating condition index satisfies the optimization target.
4. The parameter optimization method according to claim 1, characterized in that: The target operating condition includes operating condition information; The step of determining the index data of each of the operating condition indicators corresponding to each of the target operating conditions based on each of the target operating conditions and the target object model includes: Performing simulation analysis on the target object model based on the operating condition information included in each target operating condition to obtain a simulation result corresponding to each target operating condition; Based on the simulation results corresponding to each of the target operating conditions, indicator data of each of the operating condition indicators is determined.
5. The parameter optimization method according to claim 4, characterized in that: Determining the index data of each of the operating condition indicators based on the simulation results corresponding to each of the target operating conditions includes: Based on each of the operating condition indicators corresponding to each target operating condition, determining a topological relationship diagram of the operating condition indicators; Based on the topological relationship diagram, determining a plurality of target simulation results in the simulation results to obtain a target simulation result set; Based on one or more of the target simulation results in the target simulation result set, indicator data of each of the operating condition indicators is determined.
6. The parameter optimization method according to claim 1, characterized in that: The target object model is stored in a first file, each target working condition is stored in a respective second file, the first file further stores a plurality of general indicators, and the second file further stores specific indicators corresponding to the target working condition; Determining the operating condition index corresponding to each target operating condition includes: Obtaining a specific indicator corresponding to the target operating condition in a second file corresponding to the target operating condition; A general indicator corresponding to the target operating condition is selected from a plurality of general indicators in the first file.
7. The parameter optimization method according to claim 1, characterized in that: After determining the target parameter value of the target parameter based on the indicator data of each operating condition indicator corresponding to each target operating condition, the parameter optimization method further includes: Sending the target parameter value of the target parameter to the user terminal for the user to view; If a new parameter to be optimized is received from the user terminal, the new parameter to be optimized is determined as the target parameter, and the step of determining the target parameter value of the target parameter based on the indicator data of each operating condition indicator corresponding to each target operating condition is repeated; or, If a new parameter value range of the target parameter sent by the user terminal is received, the step of determining the target parameter value of the target parameter based on the indicator data of each operating condition indicator corresponding to each target operating condition is repeated.
8. A parameter optimization device, characterized in that: include: A determination module, configured to determine a target object model, wherein the target object model is determined based on design parameter data of the target object, wherein the design parameter data includes parameter values corresponding to each of a plurality of design parameters, and at least one of the design parameters is a target parameter; The determination module is further used to determine at least one target operating condition and one or more operating condition indicators corresponding to each of the target operating conditions; The determination module is further used to determine the index data of each of the operating condition indicators corresponding to each of the target operating conditions based on each of the target operating conditions and the target object model; The determination module is further configured to determine a target parameter value of the target parameter based on the indicator data of each operating condition indicator corresponding to each target operating condition.
9. An electronic device, characterized in that: include: processor; A memory, wherein the memory is connected to the processor, and the memory is used to store a computer program, and when the computer program is executed by the processor, the parameter optimization method according to any one of claims 1 to 7 is implemented.
10. A storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by the processor, the parameter optimization method according to any one of claims 1 to 7 is implemented.