A vehicle dynamic performance simulation method and system under multiple working conditions and a storage medium

Abstract

The application provides a kind of multi-working condition vehicle dynamic performance simulation method, system and storage medium, method includes: obtaining vehicle production information, wherein, vehicle production information includes vehicle model and vehicle production parameter;Based on vehicle model, obtain the target part model corresponding to vehicle model from the preset database, wherein, a plurality of reference part models corresponding to each part are stored in the preset database;Based on vehicle production parameter, the target part model is constructed into vehicle simulation model;Obtain simulation task, determine the ordered simulation working condition information corresponding to simulation task, based on ordered simulation working condition information, use vehicle simulation model to carry out dynamic performance simulation, obtain simulation result.The application can improve the efficiency of completing the evaluation of vehicle dynamic performance.

Description

Technical Field

[0001] This application relates to the field of simulation technology, and in particular to a method, system and storage medium for simulating the dynamic performance of a vehicle under multiple operating conditions. Background Technology

[0002] To keep pace with the development of the automotive industry, it is necessary to accelerate research and development and shorten delivery cycles. However, ensuring delivery quality remains crucial, which inevitably requires performance simulation of the vehicle's dynamics before delivery. Through simulation technology, engineers can simulate various complex operating conditions in a virtual environment, thereby comprehensively evaluating the vehicle's dynamic performance.

[0003] Currently, dynamic performance simulation typically involves determining which vehicle model needs simulation, then creating a corresponding model for that model. Different operating conditions are then selected to simulate the vehicle's overall dynamic performance, yielding relevant simulation parameters and conclusions. While this method can evaluate vehicle dynamic performance, it requires building a model from scratch each time, which is time-consuming and reduces efficiency. Furthermore, existing databases only store the entire vehicle model, preventing the reuse of individual component models and failing to account for discrepancies between actual production dimensions and drawings, resulting in low simulation model accuracy. Summary of the Invention

[0004] To improve the efficiency of completing vehicle dynamic performance evaluation, this application provides a method, system, and storage medium for simulating vehicle dynamic performance under multiple operating conditions.

[0005] Firstly, a method for simulating the dynamic performance of a vehicle under multiple operating conditions is provided, the method comprising: Obtain vehicle production information, wherein the vehicle production information includes vehicle model and vehicle production parameters; Based on the vehicle model, the target part model corresponding to the vehicle model is obtained from a preset database, wherein the preset database stores several reference part models corresponding to each part; Based on the vehicle production parameters, the target part model is constructed into a vehicle simulation model; The simulation task is obtained, the ordered simulation condition information corresponding to the simulation task is determined, and the vehicle simulation model is used to perform dynamic performance simulation based on the ordered simulation condition information to obtain the simulation results.

[0006] In some embodiments, the preset database includes several preset sub-databases, each storing several reference part models corresponding to a part, and the reference part models in each preset sub-database are different. Each reference part model corresponds to a structure of the part. The step of obtaining the target part model corresponding to the vehicle model from the preset database based on the vehicle model includes: Based on the vehicle model, obtain the part structure of each part of the vehicle, and determine whether there is a reference part model of the vehicle with respect to the part structure in each preset sub-database. If there is, determine the reference part model as the target part model of the part structure. If it does not exist, obtain the reference part principle of each reference part model in the preset sub-database, as well as the original part principle of the part structure, calculate the similarity between the original part principle and each reference part principle, and determine the reference part model corresponding to the maximum similarity among all similarities as the target part model of the part structure.

[0007] In some embodiments, the target part model is either a normal target part model or an abnormal target part model, and constructing the target part model into a vehicle simulation model based on the vehicle production parameters includes the following steps: Determine whether all target part models are normal target part models. If so, determine the connection relationship and connection parameters between all target part models according to the vehicle production parameters, and use the connection relationship and connection parameters to construct the target part models into a vehicle simulation model. If not, adjust the abnormal target part model using the original part principle of the part structure corresponding to the abnormal target part model to obtain an adjusted target part model that is the same as the original part principle; Based on the vehicle production parameters, determine the connection relationships and connection parameters between all the adjustment target part models and normal target part models, and use the connection relationships and connection parameters to construct all the adjustment target part models and normal target part models into a vehicle simulation model.

[0008] In some embodiments, the method further includes: The model of the target part to be adjusted is stored in the preset database.

[0009] In some embodiments, the connection parameters include several connection sub-parameters, the connection relationships include several sets of connection sub-relationships, each set of connection sub-relationships corresponds to a uniquely determined connection sub-parameter, and the step of using the connection relationships and connection parameters to construct the target part model into a vehicle simulation model includes: Obtain the actual connection parameters of the associated target part models corresponding to each set of connection sub-relationships, and determine whether the actual connection parameters are the same as the corresponding connection sub-parameters. If they are the same, directly connect the two target part models corresponding to the actual connection parameters to construct the vehicle sub-simulation model. If they are not the same, the construction parameters are determined based on the actual connection parameters and the corresponding connection sub-parameters. The construction parameters are then used to connect the two target part models corresponding to the actual connection parameters to construct the vehicle sub-simulation model. All vehicle sub-simulation models are combined into a vehicle simulation model.

[0010] In some embodiments, the simulation task includes several simulation sub-tasks, and determining the ordered simulation condition information corresponding to the simulation task includes: Determine whether the simulation task contains user requirements. If not, sort the simulation subtasks in the simulation task according to a preset order to obtain ordered simulation condition information. If so, obtain the requirement simulation subtask corresponding to the user requirement, as well as the associated simulation subtask associated with the requirement simulation subtask, and determine the arrangement position of the associated simulation subtask relative to the requirement simulation subtask by referring to a preset order, so as to obtain ordered sub-simulation working condition information. Obtain the estranged simulation subtasks from the simulation task, excluding the required simulation subtasks and related simulation subtasks. Based on the ordered sub-simulation condition information, arrange the estranged simulation subtasks before or after the ordered sub-simulation condition information in a preset order to obtain the ordered simulation condition information.

[0011] In some embodiments, the simulation results include several simulation sub-results, each corresponding to a simulation sub-task. The step of performing dynamic performance simulation using a vehicle simulation model based on the ordered simulation condition information includes: For each simulation subtask obtained, it is determined whether the simulation sub-result corresponding to the simulation subtask is a normal result. If it is, the vehicle simulation model is used to perform dynamic performance simulation for the next simulation subtask based on the simulation subtask. If it does not belong to the preset task, determine whether the simulation subtask belongs to the preset task; if so, generate an end command. Otherwise, continue with the next simulation subtask based on the aforementioned simulation subtask, using the vehicle simulation model to perform dynamic performance simulation.

[0012] In some embodiments, the method further includes: If the simulation subtask belongs to a preset task, the simulation sub-results corresponding to all simulation subtasks following the simulation subtask will be determined as abnormal results.

[0013] Secondly, a multi-condition vehicle dynamic performance simulation system is provided, comprising: an acquisition module, a model module, a construction module, and a simulation module; wherein... The acquisition module is used to acquire vehicle production information, wherein the vehicle production information includes vehicle model and vehicle production parameters; The model module is used to obtain the target part model corresponding to the vehicle model from a preset database based on the vehicle model. The preset database stores several reference part models corresponding to each part. The construction module is used to build a vehicle simulation model from the target part model based on the vehicle production parameters; The simulation module is used to acquire simulation tasks, determine the ordered simulation conditions information corresponding to the simulation tasks, and perform dynamic performance simulation using a vehicle simulation model based on the ordered simulation conditions information to obtain simulation results.

[0014] Thirdly, a computer-readable storage medium is provided, on which a computer program capable of running on a processor is stored, wherein when the computer program is executed by the processor, it implements a method for simulating the dynamic performance of a vehicle under multiple operating conditions as described in the first aspect.

[0015] By employing the above method, this application first obtains vehicle production information, including vehicle model and vehicle production parameters. Then, based on the vehicle model, it retrieves the target part model corresponding to the vehicle model from a pre-set database, where the database stores several reference part models for each part. Next, based on the vehicle production parameters, it constructs a vehicle simulation model from the target part model. Finally, it obtains the simulation task, determines the ordered simulation conditions corresponding to the simulation task, and uses the vehicle simulation model to perform dynamic performance simulation based on the ordered simulation conditions to obtain simulation results. This application can improve the efficiency of completing the dynamic performance evaluation of a vehicle. Attached Figure Description

[0016] Figure 1 This is a block diagram of a method for simulating the dynamic performance of a vehicle under multiple operating conditions, provided in an embodiment of this application.

[0017] Figure 2 This is a flowchart of a method provided in this application for obtaining a target part model corresponding to a vehicle model from a preset database based on the vehicle model.

[0018] Figure 3 This is a flowchart of the method provided in this application for constructing a vehicle simulation model from a target part model based on vehicle generation parameters.

[0019] Figure 4This is a flowchart of the method for determining the ordered simulation condition information corresponding to the simulation task provided in this application.

[0020] Figure 5 This is a schematic diagram of the connection of a vehicle dynamic performance simulation system under multiple operating conditions provided in an embodiment of this application. Detailed Implementation

[0021] To better understand the purpose, technical solutions, and advantages of this application, it has been described and illustrated below with reference to the accompanying drawings and embodiments. However, those skilled in the art should understand that this application can be implemented without these details. It will be apparent to those skilled in the art that various modifications can be made to the embodiments disclosed in this application, and the general principles defined in this application can be applied to other embodiments and application scenarios without departing from the principles and scope of this application. Therefore, this application is not limited to the illustrated embodiments, but is consistent with the broadest scope claimed in this application.

[0022] The embodiments of this application will now be described in further detail with reference to the accompanying drawings.

[0023] Figure 1 This is a block diagram of a vehicle dynamic performance simulation method under multiple operating conditions provided in an embodiment of this application. For example... Figure 1 As shown, a method for simulating the dynamic performance of a vehicle under multiple operating conditions includes the following steps: Step S100: Obtain vehicle production information, which includes vehicle model and vehicle production parameters.

[0024] This application describes the process from the perspective of the simulation end. The aforementioned vehicle production information refers to the production information of the vehicle to be simulated. This information includes the vehicle model and production parameters. This production information is standard information, specifically the vehicle model and production parameters from the drawings used during vehicle production. Each vehicle corresponds to a specific vehicle model, indicating the brand, series, and model. The production parameters specifically refer to the parameters used in the vehicle's production process, including the connection dimensions between different parts of the vehicle and how they are connected. Vehicles of the same model have the same production parameters. One method involves staff sending the information to the simulation end, allowing the simulation end to obtain the vehicle production information, including the model and production parameters. Another method involves using a camera located at the vehicle production site to first obtain the vehicle model, and then using that model to retrieve the vehicle's production parameters from the associated device or location storing the vehicle drawings. Other methods can also be used to obtain vehicle production information, which will not be elaborated upon here. The first method, where staff send the information, reduces the interaction between the hardware and the simulation end. The second method, which utilizes the existing camera equipment, can obtain vehicle production information efficiently and accurately without incurring additional costs. This reduces labor costs and minimizes issues such as untimely manual transmission.

[0025] Step S200: Obtain the target part model corresponding to the vehicle model from the preset database based on the vehicle model. The preset database stores several reference part models corresponding to each part.

[0026] The simulation platform also includes a preset database, which comprises several preset sub-databases. Each sub-database stores several reference part models corresponding to a specific part, and all reference part models in each sub-database are different, each corresponding to a specific structure of that part. Specifically, each sub-database stores only one standardized part model for a given part across different vehicle models on the market—that is, several reference part models, all corresponding to the same part. Each sub-database also has a name, which is the name of the part corresponding to the model stored in that sub-database.

[0027] If there is no matching model in the database, the closest reference model is selected by calculating the similarity of the parts and principles, and then adjusted to reuse the existing model and reduce the modeling cost.

[0028] Figure 2This is a flowchart illustrating the method provided in this application for retrieving target part models corresponding to vehicle models from a pre-defined database. For example... Figure 2 As shown, obtaining the target part model corresponding to the vehicle model from a preset database based on the vehicle model includes the following steps: Step S201: Based on the vehicle model, obtain the part structure of each part of the vehicle, and determine whether there is a reference part model for the part structure in each preset sub-database. If there is, determine the reference part model as the target part model of the part structure.

[0029] Step S202: If not, obtain the reference part principle of each reference part model in the preset sub-database, as well as the original part principle of the part structure, calculate the similarity between the original part principle and each reference part principle, and determine the reference part model corresponding to the maximum similarity among all similarities as the target part model of the part structure.

[0030] Each vehicle has corresponding blueprints before production. You can find the blueprints corresponding to the vehicle model and view them to obtain the structural details of each part of the vehicle.

[0031] Next, each part structure obtained above is used to find the corresponding preset sub-database. The reference part structure corresponding to each reference part model stored in the preset sub-database is checked to see if it is the same as the part structure obtained above. If they are the same, the preset sub-database stores the reference part model of the vehicle with respect to this part structure, and the reference part model corresponding to the reference part structure that is the same as the part structure obtained above is determined as the target part model of the part structure obtained above.

[0032] If they are different, then the preset sub-database does not store a reference part model of the vehicle for this structural component. After all, the vehicle for which dynamic performance simulation is required may contain structural components that were recently developed or components that were previously developed. Therefore, the preset sub-database may not store a reference part model of the vehicle for this structural component.

[0033] When the preset sub-database does not store a reference model for a specific part of the vehicle's structure, to minimize the high time cost of remodeling and shorten the time required to obtain a model of that part, reverse engineering software and dynamics software can be used to obtain the reference principles of each reference model in the preset sub-database, as well as the original principle of the obtained part structure. Then, NetworkX software is used to calculate the similarity between the original principle and each reference principle, resulting in multiple similarity scores. Finally, sorting or subtraction operations are used to obtain the maximum similarity score, and the reference model corresponding to the maximum similarity score is determined as the target part model for the obtained structure. Thus, when a part model of the vehicle to be simulated is stored in the preset database, that model is designated as the model for that part; when no such model is stored, the most similar simulation model from the existing models is selected as the model for that part. This avoids building a model from scratch, reduces modeling time, and provides a foundational part model for determining the final vehicle model.

[0034] Step S300: Based on the vehicle production parameters, construct the target part model into a vehicle simulation model.

[0035] The target part model can be either a normal target part model or an abnormal target part model. If the part structure corresponding to the target part model is the same as the part structure of the vehicle, then the target part model is a normal target part model. If the part structure corresponding to the target part model is different from the part structure of the vehicle, then the target part model is an abnormal target part model. This is because the part structure corresponding to the target part model obtained in step S200 may not necessarily be found in the preset database. Figure 3 This is a flowchart illustrating the method provided in this application for constructing a vehicle simulation model from a target part model based on vehicle production parameters. For example... Figure 3 As shown, constructing a vehicle simulation model from the target part model based on vehicle production parameters includes the following steps: Step S301: Determine whether all target part models are normal target part models. If so, determine the connection relationship and connection parameters between all target part models according to the vehicle production parameters, and use the connection relationship and connection parameters to construct the target part models into a vehicle simulation model.

[0036] Step S302: If not, adjust the abnormal target part model using the original part principle of the part structure corresponding to the abnormal target part model to obtain an adjusted target part model that is the same as the original part principle.

[0037] Step S303: Determine the connection relationships and connection parameters between all adjustment target part models and normal target part models according to the vehicle production parameters, and use the connection relationships and connection parameters to construct all adjustment target part models and normal part models into a vehicle simulation model.

[0038] You can determine whether all target part models are normal target part models by checking whether NetworkX software was used to calculate the similarity between the original part principle and the principle of each reference part. If NetworkX software was not used, then all target part models are normal target part models. If NetworkX software was used, then not all target part models are normal target part models.

[0039] If all target part models are normal target part models, it indicates that no further adjustments to the target part models are needed. In this case, connection relationships and connection dimensions can be used as keywords to extract information from vehicle production parameters to obtain the connection relationships and connection parameters between all target part models. The connection parameters include several connection sub-parameters, and the connection relationships include several sets of connection sub-relationships, each set of connection sub-relationships corresponding to a uniquely determined connection sub-parameter.

[0040] Once the connection relationships and parameters, which include the connections between all target part models, are obtained, these relationships and parameters can be used to construct a vehicle simulation model from all target part models. The process of constructing a vehicle simulation model from target part models using connection relationships and parameters includes the following steps: Step S301-1: Obtain the actual connection parameters of the associated target part models corresponding to each set of connection sub-relationships, and determine whether the actual connection parameters are the same as the corresponding connection sub-parameters. If they are the same, directly connect the two target part models corresponding to the actual connection parameters to construct the vehicle sub-simulation model.

[0041] Step S301-2: If they are not the same, determine the construction parameters based on the actual connection parameters and the corresponding connection sub-parameters, and use the construction parameters to connect the two target part models corresponding to the actual connection parameters to construct the vehicle sub-simulation model.

[0042] Step S301-3: Assemble all the vehicle sub-simulation models into a vehicle simulation model.

[0043] Although vehicles are manufactured according to the dimensions in the drawings, the actual dimensions of the manufactured vehicles may differ from those in the drawings. Therefore, a camera device installed at the vehicle production site can be used to capture information and send it to a simulation terminal. The simulation terminal can then process the image to obtain the actual connection parameters between the two parts that need to be connected. In other words, it can obtain the actual connection parameters of the associated target part model corresponding to each set of connection sub-relationships, with each connection sub-relationship corresponding to one actual connection parameter.

[0044] By comparing the corresponding actual connection parameter with the value of the connection sub-parameter, if they are equal, then the actual connection parameter is the same as the corresponding connection sub-parameter. If they are not equal, then the actual connection parameter is different from the corresponding connection sub-parameter.

[0045] Under the same conditions, it indicates that the connection dimensions of the two parts produced are the same as the connection dimensions in the drawing. At this time, the connection parts of the two target part models corresponding to the actual connection parameters are consistent with the actual part models of the vehicle. The two target part models corresponding to the actual connection parameters can be directly connected to obtain the vehicle sub-simulation models corresponding to these two parts. There is no need to adjust the connection parts of the models corresponding to these two parts. The vehicle sub-simulation models of these two parts that match the actual situation of the vehicle can be obtained.

[0046] In different situations, the connection dimensions of the two manufactured parts differ from those in the drawings. In this case, the connection between the two target part models corresponding to the actual connection parameters and the actual vehicle part models is inconsistent. The two target part models corresponding to these actual connection parameters cannot be directly connected to obtain the corresponding vehicle sub-simulation models. Direct connection would lead to inaccurate subsequent model construction. Instead, the actual connection parameters and their corresponding connection sub-parameters can be compared to determine how the connection sub-parameters need adjustment (i.e., constructing parameters). These constructed parameters are then used to connect the two target part models corresponding to the actual connection parameters, resulting in a vehicle sub-simulation model that accurately reflects the actual vehicle situation.

[0047] Once the vehicle sub-simulation model corresponding to each actual connection parameter is obtained, the corresponding vehicle simulation model is obtained. This way, after obtaining accurate models of each individual target part, when further connecting these models to form the complete vehicle model, the errors in the connection parameters between parts can be taken into account, making the final constructed complete vehicle model more accurate. After all, the connections between parts have a significant impact on the overall vehicle's dynamic performance. Furthermore, regardless of the structure of the vehicle to be simulated, existing individual part models can be quickly and accurately assembled, thus efficiently obtaining the complete vehicle simulation model without sacrificing accuracy.

[0048] When all target part models contain both normal and abnormal models, it indicates that the abnormal target part models need adjustment. This involves using modeling software deployed on the simulation end to adjust the abnormal target part model according to the original structural principles of the corresponding part, resulting in a normal target part model that matches the actual part – the adjusted target part model. This allows for subsequent connection work. This approach ensures that the simulation end only needs to adjust the modeling software based on the closest existing model when a model that accurately reflects the vehicle cannot be directly obtained. This allows for rapid acquisition of a model that accurately reflects the vehicle. Firstly, compared to comparing with the entire vehicle model, modeling of certain accurately reflecting vehicle parts can be omitted, saving modeling time and reducing the number of models needed, as comparing with the entire vehicle is more likely to require modeling. Secondly, it avoids remodeling; instead, it adjusts existing models, further reducing modeling time. This, in turn, shortens the time required to derive the entire vehicle model from accurately reflecting vehicle parts.

[0049] After obtaining the adjustment target part model corresponding to the abnormal target part model, refer to the method in step S301-1 above for constructing all target part models into a vehicle simulation model. Determine the connection relationships and parameters between all adjustment target part models and normal target part models according to vehicle production parameters. Use these connection relationships and parameters to construct all adjustment target part models and normal target part models into a vehicle simulation model. This will not be elaborated further here. Similarly, after obtaining each individual accurate part model, when further connecting the models to form the complete vehicle model, taking into account the errors in the connection parameters between parts can make the final constructed complete vehicle model more accurate, since the connections between parts have a significant impact on the overall vehicle's dynamic performance. Furthermore, regardless of the structure of the vehicle to be simulated, existing individual part models can be quickly and accurately assembled, thereby efficiently obtaining the complete vehicle simulation model without compromising accuracy.

[0050] Preferably, the simulation terminal will also adjust the target part model and store it in a preset database to expand the models in the preset database. This will facilitate the reduction of model time when performing multi-condition vehicle power performance simulations on other vehicles in the future, thereby improving the efficiency of completing the vehicle power performance evaluation.

[0051] Step S400: Obtain the simulation task, determine the ordered simulation condition information corresponding to the simulation task, and use the vehicle simulation model to perform dynamic performance simulation based on the ordered simulation condition information to obtain the simulation results.

[0052] The aforementioned simulation task refers to the simulation tests required to assess the vehicle's overall dynamic performance under various operating conditions. This task can be obtained by the simulation terminal through a method where staff send the simulation data. The simulation task comprises several sub-tasks, each corresponding to a specific operating condition. Figure 4 This is a block diagram of the method for determining the ordered simulation condition information corresponding to the simulation task provided in this application. For example... Figure 4 As shown, determining the ordered simulation condition information corresponding to the simulation task includes the following steps: Step S401: Determine whether the simulation task contains user requirements. If not, sort the simulation subtasks in the simulation task according to a preset order to obtain ordered simulation condition information.

[0053] Step S402: If applicable, obtain the requirement simulation subtask corresponding to the user requirement, as well as the associated simulation subtask associated with the requirement simulation subtask, and determine the arrangement position of the associated simulation subtask relative to the requirement simulation subtask by referring to the preset order, so as to obtain ordered sub-simulation condition information.

[0054] Step S403: Obtain the detached simulation subtasks from the simulation task, excluding the required simulation subtasks and related simulation subtasks. Based on the ordered sub-simulation condition information, insert the detached simulation subtasks into the ordered sub-simulation condition information in a preset order to obtain the ordered simulation condition information.

[0055] When staff send simulation tasks to the simulation platform, they may also send their own requirements as additional information. By checking whether the simulation task contains this additional information, it can be determined whether the simulation task includes user requirements. The presence of additional information indicates that the simulation task contains user requirements. The absence of additional information indicates that the simulation task does not contain user requirements.

[0056] When the simulation task does not include user requirements, it indicates that the user has no requirement on which operating condition the vehicle power performance simulation should be performed in the first place. In this case, the simulation subtasks in the simulation task can be sorted according to the preset order stored in the simulation terminal to obtain simulation operating condition information. Then, based on this ordered simulation operating condition information, the vehicle simulation model is used to perform power performance simulation to obtain the simulation results.

[0057] When a simulation task includes user requirements, it indicates the user's desired sequence for simulating the vehicle's dynamic performance under various operating conditions. Based on these requirements, the order of the simulation subtasks within the task can be determined, and these subtasks are marked as required simulation subtasks. Since different operating conditions may exhibit strong cohesion—meaning that completing the simulation of one condition before proceeding to another will shorten the time required for the latter—to improve efficiency, each required simulation subtask can be stored in the simulation's memory area. This memory area stores cohesive operating conditions; the cohesive simulation subtask refers to this specific cohesive operating condition.

[0058] To further determine the order between the requirement simulation subtask and its corresponding associated simulation subtask, the order of the two in the preset order can be used to obtain the position of the associated simulation subtask relative to the corresponding requirement simulation subtask, i.e., whether it is before or after it. This positional relationship is determined as the ordered sub-simulation condition information, which is a part of the ordered simulation condition information.

[0059] Then, the simulation subtasks within the simulation task, excluding the aforementioned requirement simulation subtasks and related simulation subtasks, are marked as alienated simulation subtasks. These alienated simulation subtasks are then placed before or after the ordered simulation subtask condition information according to a preset order to obtain ordered simulation condition information composed of all conditions, without changing the position of the ordered sub-simulation condition information in the final sequence. For example, if the simulation task has five simulation subtasks, with the requirement simulation subtask corresponding to the user's needs as the first position and its corresponding related simulation subtask as the second position, the remaining three simulation subtasks are sorted from third position according to a preset order to obtain the ordered simulation condition information composed of these five simulation subtasks. By taking user needs into account and the correlation between tasks, this approach maximizes the satisfaction of user needs while obtaining a condition sequence that allows for a shorter time to complete vehicle power performance simulations under multiple conditions. This facilitates subsequent simulations based on this condition sequence, reducing time and improving the efficiency of evaluating vehicle power performance.

[0060] The simulation results described above include several sub-results, each corresponding to a sub-task. The dynamic performance simulation using a vehicle simulation model based on ordered simulation condition information includes the following steps: Step S404: For each simulation subtask obtained, determine whether the simulation sub-result corresponding to the simulation subtask is a normal result. If it is, continue to use the vehicle simulation model to perform dynamic performance simulation based on the next simulation subtask.

[0061] Step S405: If it does not belong to the preset task, determine whether the simulation subtask belongs to the preset task. If it does, generate an end command.

[0062] Step S406, otherwise, continue with the next simulation subtask based on the simulation subtask, using the vehicle simulation model to perform dynamic performance simulation.

[0063] The simulation end first uses the first condition in the above ordered simulation condition information to simulate the vehicle's overall power performance, thereby obtaining a simulation sub-result. Then, it checks whether this simulation sub-result meets the set standard. If it does, then this simulation sub-result is a normal result. At this time, it continues to use the second condition in the above ordered simulation condition information to simulate the vehicle's overall power performance, and obtains another corresponding simulation sub-result. Then, it uses the above judgment method to determine whether the simulation sub-result is a correct result. If the simulation sub-result is a correct result, the above loop continues to be executed.

[0064] If a simulation sub-result does not meet the set standards, it is considered an abnormal result. In this case, it's necessary to check if the simulation sub-task belongs to a preset task. If it does, a termination command is generated. If it doesn't belong to a preset task, the simulation continues with the next simulation sub-task based on that sub-task, using the vehicle simulation model to perform dynamic performance simulation. The preset task refers to the operating condition that plays a decisive role in the vehicle's dynamic performance. If the simulation sub-result under this condition is incorrect, the vehicle cannot be definitively deemed undeliverable. The preset task is specifically determined by the staff. By using ordered simulation operating condition information to perform dynamic performance simulation on the vehicle simulation model, the simulation results can be obtained efficiently and accurately, enabling the evaluation of the vehicle's dynamic performance.

[0065] Preferably, if a simulation subtask belongs to a preset task, the simulation sub-results corresponding to all simulation subtasks following that simulation subtask are determined to be abnormal results. If it is determined that a simulation subtask belongs to a preset task and its corresponding simulation sub-result is incorrect, then performing corresponding simulation work on other simulation subtasks of that simulation subtask is meaningless, as it is known that the vehicle will definitely not meet the delivery requirements. This can indirectly improve the efficiency of completing the vehicle's power performance evaluation.

[0066] Figure 5 This is a schematic diagram of the connection of a vehicle dynamic performance simulation system under multiple operating conditions, provided in an embodiment of this application. Figure 5 As shown, a vehicle dynamic performance simulation system under multiple operating conditions includes: an acquisition module, a model module, a construction module, and a simulation module.

[0067] The system comprises the following modules: **Acquisition Module:** Acquires vehicle production information, including vehicle model and production parameters. **Model Module:** Retrieves target part models corresponding to the vehicle model from a pre-defined database. This database stores several reference part models for each part. **Build Module:** Constructs a vehicle simulation model from the target part models based on the vehicle production parameters. **Simulation Module:** Acquires simulation tasks, determines the ordered simulation conditions corresponding to the tasks, and performs dynamic performance simulation using the vehicle simulation model based on these ordered conditions to obtain simulation results. The ordered simulation conditions refer to a sequence of conditions ordered by execution priority.

[0068] The other functions performed by the acquisition module, model module, construction module, and simulation module, as well as the technical details of each function, are the same as or similar to the corresponding features in the multi-condition vehicle dynamic performance simulation method described above, so they will not be repeated here.

[0069] This application also provides a computer storage medium storing a computer program that, when run on a computer, enables the computer to execute the steps in the multi-condition vehicle dynamic performance simulation method described above.

[0070] It should be understood that although the steps in the flowcharts in the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order requirement for the execution of these steps, and they may be performed in other orders.

[0071] The above description is only a partial embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for simulating the dynamic performance of a vehicle under multiple operating conditions, characterized in that, The method includes: Obtain vehicle production information, wherein the vehicle production information includes vehicle model and vehicle production parameters; Based on the vehicle model, the target part model corresponding to the vehicle model is obtained from a preset database, wherein the preset database stores several reference part models corresponding to each part; Based on the vehicle production parameters, the target part model is constructed into a vehicle simulation model; Acquire a simulation task, determine the ordered simulation condition information corresponding to the simulation task, and use a vehicle simulation model to perform dynamic performance simulation based on the ordered simulation condition information to obtain simulation results. The preset database includes several preset sub-databases, each storing several reference part models corresponding to a part, and the reference part models in each preset sub-database are different. Each reference part model corresponds to a structure of the part. The step of obtaining the target part model corresponding to the vehicle model from the preset database based on the vehicle model includes: Based on the vehicle model, obtain the part structure of each part of the vehicle, and determine whether there is a reference part model of the vehicle with respect to the part structure in each preset sub-database. If there is, determine the reference part model as the target part model of the part structure. If it does not exist, obtain the reference part principle of each reference part model in the preset sub-database, as well as the original part principle of the part structure, calculate the similarity between the original part principle and each reference part principle, and determine the reference part model corresponding to the maximum similarity among all similarities as the target part model of the part structure. The simulation task includes several simulation sub-tasks, and determining the ordered simulation condition information corresponding to the simulation task includes: Determine whether the simulation task contains user requirements. If not, sort the simulation subtasks in the simulation task according to a preset order to obtain ordered simulation condition information. If so, obtain the requirement simulation subtask corresponding to the user requirement, as well as the associated simulation subtask associated with the requirement simulation subtask, and determine the arrangement position of the associated simulation subtask relative to the requirement simulation subtask by referring to a preset order, so as to obtain ordered sub-simulation working condition information. Obtain the estranged simulation subtasks from the simulation task, excluding the required simulation subtasks and related simulation subtasks. Based on the ordered sub-simulation condition information, arrange the estranged simulation subtasks before or after the ordered sub-simulation condition information in a preset order to obtain the ordered simulation condition information.

2. The method according to claim 1, characterized in that, The target part model is either a normal target part model or an abnormal target part model. The step of constructing a vehicle simulation model from the target part model based on the vehicle production parameters includes the following steps: Determine whether all target part models are normal target part models. If so, determine the connection relationship and connection parameters between all target part models according to the vehicle production parameters, and use the connection relationship and connection parameters to construct the target part models into a vehicle simulation model. If not, adjust the abnormal target part model using the original part principle of the part structure corresponding to the abnormal target part model to obtain an adjusted target part model that is the same as the original part principle; Based on the vehicle production parameters, determine the connection relationships and connection parameters between all the adjustment target part models and normal target part models, and use the connection relationships and connection parameters to construct all the adjustment target part models and normal target part models into a vehicle simulation model.

3. The method according to claim 2, characterized in that, The method further includes: The model of the target part to be adjusted is stored in the preset database.

4. The method according to claim 2, characterized in that, The connection parameters include several connection sub-parameters, and the connection relationships include several sets of connection sub-relationships. Each set of connection sub-relationships corresponds to a uniquely determined connection sub-parameter. The step of using the connection relationships and connection parameters to construct the target part model into a vehicle simulation model includes: Obtain the actual connection parameters of the associated target part models corresponding to each set of connection sub-relationships, and determine whether the actual connection parameters are the same as the corresponding connection sub-parameters. If they are the same, directly connect the two target part models corresponding to the actual connection parameters to construct the vehicle sub-simulation model. If they are not the same, the construction parameters are determined based on the actual connection parameters and the corresponding connection sub-parameters. The construction parameters are then used to connect the two target part models corresponding to the actual connection parameters to construct the vehicle sub-simulation model. All vehicle sub-simulation models are combined into a vehicle simulation model.

5. The method according to claim 1, characterized in that, The simulation results include several simulation sub-results, each corresponding to a simulation sub-task. The dynamic performance simulation based on the ordered simulation condition information using the vehicle simulation model includes: For each simulation subtask obtained, it is determined whether the simulation sub-result corresponding to the simulation subtask is a normal result. If it is, the vehicle simulation model is used to perform dynamic performance simulation for the next simulation subtask based on the simulation subtask. If it does not belong to the preset task, determine whether the simulation subtask belongs to the preset task; if so, generate an end command. Otherwise, continue with the next simulation subtask based on the aforementioned simulation subtask, using the vehicle simulation model to perform dynamic performance simulation.

6. The method according to claim 5, characterized in that, The method further includes: If the simulation subtask belongs to a preset task, the simulation sub-results corresponding to all simulation subtasks following the simulation subtask will be determined as abnormal results.

7. A vehicle dynamic performance simulation system under multiple operating conditions, characterized in that, The system includes: an acquisition module, a model module, a construction module, and a simulation module; wherein, The acquisition module is used to acquire vehicle production information, wherein the vehicle production information includes vehicle model and vehicle production parameters; The model module is used to obtain the target part model corresponding to the vehicle model from a preset database based on the vehicle model. The preset database stores several reference part models corresponding to each part. The construction module is used to build a vehicle simulation model from the target part model based on the vehicle production parameters; The simulation module is used to acquire simulation tasks, determine the ordered simulation conditions information corresponding to the simulation tasks, and use the vehicle simulation model to perform dynamic performance simulation based on the ordered simulation conditions information to obtain simulation results. The preset database includes several preset sub-databases, each storing several reference part models corresponding to a part, and the reference part models in each preset sub-database are different. Each reference part model corresponds to a structure of the part. The step of obtaining the target part model corresponding to the vehicle model from the preset database based on the vehicle model includes: Based on the vehicle model, obtain the part structure of each part of the vehicle, and determine whether there is a reference part model of the vehicle with respect to the part structure in each preset sub-database. If there is, determine the reference part model as the target part model of the part structure. If it does not exist, obtain the reference part principle of each reference part model in the preset sub-database, as well as the original part principle of the part structure, calculate the similarity between the original part principle and each reference part principle, and determine the reference part model corresponding to the maximum similarity among all similarities as the target part model of the part structure. The simulation task includes several simulation sub-tasks, and determining the ordered simulation condition information corresponding to the simulation task includes: Determine whether the simulation task contains user requirements. If not, sort the simulation subtasks in the simulation task according to a preset order to obtain ordered simulation condition information. If so, obtain the requirement simulation subtask corresponding to the user requirement, as well as the associated simulation subtask associated with the requirement simulation subtask, and determine the arrangement position of the associated simulation subtask relative to the requirement simulation subtask by referring to a preset order, so as to obtain ordered sub-simulation working condition information. Obtain the estranged simulation subtasks from the simulation task, excluding the required simulation subtasks and related simulation subtasks. Based on the ordered sub-simulation condition information, arrange the estranged simulation subtasks before or after the ordered sub-simulation condition information in a preset order to obtain the ordered simulation condition information.

8. A computer-readable storage medium having a computer program stored thereon that can run on a processor, characterized in that, When the computer program is executed by the processor, it implements a multi-condition vehicle dynamic performance simulation method as described in any one of claims 1 to 6.

Images