Digital twin system and construction method, vehicle-mounted air conditioner optimization and life prediction method

Abstract

The present application relates to the technical field of air conditioning, and particularly provides a digital twin system and a construction method, a vehicle-mounted air conditioner optimization and life prediction method, aiming to solve the problems that the existing parking air conditioner cannot timely find the risk of part fracture and cannot quickly and effectively avoid part fracture in the use process. For this purpose, the construction method of the digital twin system is mainly to first construct a bench test system, a multi-body dynamics model and a finite element analysis model according to the vehicle-mounted air conditioner and the vehicle, obtain the load spectrum of the vehicle under different roads, load the load spectrum to the bench test system and the multi-body dynamics model, compare and detect the results to optimize the multi-body dynamics model, obtain the power spectral density of the installation position of the vehicle-mounted air conditioner through the multi-body dynamics model and load it to the bench test system and the finite element analysis model, and optimize the finite element analysis model according to the detection results. In this way, the digital twin system is used to participate in the optimization design and life prediction of the vehicle-mounted air conditioner.

Description

Technical Field

[0001] This invention relates to the field of air conditioning technology, specifically providing a digital twin system and its construction method, as well as a method for optimizing and predicting the lifespan of vehicle air conditioning systems. Background Technology

[0002] Currently, parking air conditioners are mainly installed in commercial vehicles and special vehicles. Commercial vehicles and special vehicles typically operate under harsh conditions with severe vibrations, which can easily lead to pipe and other component breakage in the parking air conditioner. This results in excessive vibration and noise from the parking air conditioner, as well as refrigerant leaks due to broken refrigerant lines, ultimately causing a decrease in the air conditioning system's energy efficiency ratio.

[0003] To address the aforementioned issues, improvements to the parking air conditioner's structure are typically made during the design phase to reduce the risk of these problems during use. However, improvements to existing air conditioners usually involve structural reinforcement of the problematic areas. Whether this reinforcement effectively prevents the problems in actual use can only be determined based on market feedback after widespread use of the parking air conditioner. Further improvements can only be made based on market feedback. This approach cannot quickly and effectively prevent pipe and other component breakage during use, nor can it promptly detect impending breakage of pipes and other components during operation.

[0004] Therefore, a new technical solution is needed in this field to solve the above problems. Summary of the Invention

[0005] The present invention aims to solve the above-mentioned technical problems, namely, to solve the problem that existing parking air conditioners cannot detect the risk of component breakage in time during use and cannot quickly and effectively prevent component breakage.

[0006] In a first aspect, the present invention provides a method for constructing a digital twin system for vehicle air conditioning, the method comprising the following steps:

[0007] S1. Construct a bench test system, a multibody dynamics model, and a finite element analysis model based on the physical parameters of the vehicle air conditioner and the vehicle to which the vehicle air conditioner is applied.

[0008] S2. Obtain the load spectrum data of the vehicle under different types of roads and preprocess the load spectrum data;

[0009] S3. Load the preprocessed load spectrum data into the bench test system in order to obtain the detection results of the test points of the bench test system;

[0010] S4. Load the preprocessed load spectrum data into the multibody dynamics model in order to obtain the detection results of the corresponding test points of the multibody dynamics model;

[0011] S5. Compare the detection results of the test points of the bench test system with the detection results of the corresponding test points of the multibody dynamics model, and selectively adjust the parameters of the multibody dynamics model according to the comparison results to obtain the target multibody dynamics model.

[0012] S6. Load the preprocessed load spectrum data into the target multibody dynamics model to obtain the power spectral density at the installation location of the vehicle air conditioner in the target multibody dynamics model.

[0013] S7. The power spectral density is loaded onto the finite element analysis model and the bench test system to obtain the risk point data of the vehicle air conditioner in the finite element analysis model and the risk point data of the vehicle air conditioner in the bench test system.

[0014] S8. Adjust the parameters of the finite element analysis model according to the risk point data of the vehicle air conditioner in the finite element analysis model and the risk point data of the vehicle air conditioner in the bench test system to obtain the target finite element analysis model.

[0015] In the preferred embodiment of the above construction method, the step of "selectively adjusting the parameters of the multibody dynamics model according to the comparison results to obtain the target multibody dynamics model" includes:

[0016] If the error between the detection result of the test point of the bench test system and the detection result of the corresponding test point of the multibody dynamics model is not greater than 10%, then the current multibody dynamics model is taken as the target multibody dynamics model.

[0017] In the preferred embodiment of the above construction method, the step of "selectively adjusting the parameters of the multibody dynamics model according to the comparison results to obtain the target multibody dynamics model" includes:

[0018] If the error between the detection result of the test point of the bench test system and the detection result of the corresponding test point of the multibody dynamics model is greater than 10%, then the parameters of the multibody dynamics model are adjusted, and then the process returns to step S4.

[0019] In the preferred embodiment of the above construction method, the step of "obtaining load spectrum data of the vehicle under different types of roads" includes:

[0020] The load spectrum data of the vehicle under different types of roads is obtained based on Internet of Things (IoT) technology.

[0021] In the preferred embodiment of the above construction method, the detection result includes acceleration.

[0022] In the preferred embodiment of the above construction method, the preprocessing includes anomaly detection, symmetry detection, stationarity detection, filtering, calibration, resampling, and / or data compression.

[0023] In a second aspect, the present invention provides a digital twin system for vehicle air conditioning, wherein the digital twin system is constructed by the construction method for a digital twin system for vehicle air conditioning described in any of the preceding claims.

[0024] In the preferred technical solution of the above-mentioned digital twin system, the vehicle air conditioner is a parking air conditioner.

[0025] By adopting the above technical solution, the present invention constructs a digital twin system for vehicle air conditioning using the above method. This system can construct an accurate digital twin system, which can quickly and accurately analyze the stress of the vehicle air conditioning under various operating conditions. This allows for more accurate optimization and verification of the vehicle air conditioning structure during the design phase, avoiding the need for extensive experimental verification or mass production followed by extensive user practice to discover defects in the improved structure. Furthermore, the digital twin system can monitor the internal stress of vehicle air conditioning components in real time under various usage scenarios, thereby predicting the fracture risk and service life of vehicle air conditioning components in real time.

[0026] In a third aspect, the present invention provides a lifespan prediction method for an in-vehicle air conditioner, the lifespan prediction method being performed based on the aforementioned digital twin system for in-vehicle air conditioners, the prediction method comprising:

[0027] The load spectrum data of the vehicle equipped with the vehicle air conditioner is acquired in real time during the driving process and preprocessed.

[0028] The preprocessed load spectrum data of the vehicle equipped with the vehicle air conditioner during driving is loaded into the target multibody dynamics model in order to obtain the power spectral density of the installation position of the vehicle air conditioner in the target multibody dynamics model.

[0029] The power spectral density is loaded into the finite element analysis model to obtain the risk point data of the vehicle air conditioner in the finite element analysis model;

[0030] The service life of the vehicle air conditioner is predicted based on the risk point data of the vehicle air conditioner in the finite element analysis model.

[0031] By adopting the above technical solution, it is possible to monitor the internal stress of components of the vehicle air conditioner in real time under usage scenarios, and thus predict the breakage risk and service life of the vehicle air conditioner components in real time.

[0032] In a fourth aspect, the present invention provides an optimized design method for an in-vehicle air conditioner, the optimized design method being executed based on the aforementioned digital twin system for in-vehicle air conditioners, the optimized design method comprising:

[0033] Install the physical prototype of the vehicle air conditioner into the vehicle;

[0034] The vehicle is driven on different types of roads to acquire load spectrum data and perform preprocessing.

[0035] The preprocessed load spectrum data is loaded into the target multibody dynamics model to obtain the power spectral density at the installation location of the vehicle air conditioner in the target multibody dynamics model.

[0036] The power spectral density is loaded into the finite element analysis model to obtain the risk point data of the vehicle air conditioner in the finite element analysis model;

[0037] The structure of the physical prototype is adjusted based on the risk point data of the vehicle air conditioner in the finite element analysis model.

[0038] By adopting the above technical solution, the structure of the vehicle air conditioner can be more accurately optimized and further verified during the design phase, avoiding the situation where the vehicle air conditioner needs to undergo a large number of experimental verifications or mass production and extensive user practice before the defects of the improved structure can be discovered. Attached Figure Description

[0039] The preferred embodiments of the present invention are described below with reference to the accompanying drawings, in which:

[0040] Figure 1 This is a step diagram illustrating a method for constructing a digital twin system for a parking air conditioner in one embodiment of the present invention;

[0041] Figure 2 This is a flowchart illustrating the steps of a method for predicting the lifespan of a parking air conditioner in one embodiment of the present invention;

[0042] Figure 3 This is a flowchart illustrating the steps of an optimized design method for a parking air conditioner in one embodiment of the present invention. Detailed Implementation

[0043] First, those skilled in the art should understand that the embodiments described below are merely for explaining the technical principles of the present invention and are not intended to limit the scope of protection of the present invention. For example, the following embodiments are described in conjunction with a parking air conditioner, but this does not constitute a limitation on the scope of protection of the present invention. The vehicle air conditioner in the present invention can also be an air conditioner used while the vehicle is in motion.

[0044] It should be noted that in the description of this invention, the terms "first," "second," "third," and "fourth" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0045] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the term "connection" should be interpreted broadly. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium; and it can also refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0046] Based on the issues mentioned in the background technology regarding the inability to promptly detect the risk of component breakage during use and the inability to quickly and effectively prevent component breakage, this invention provides a method for constructing a digital twin system for vehicle air conditioning. This method can construct an accurate digital twin system, which can quickly and accurately analyze the stress conditions of the vehicle air conditioning under various operating conditions. This allows for more accurate optimization of the vehicle air conditioning structure during the design phase and further verification, avoiding the need for extensive experimental verification or mass production followed by extensive user practice to discover defects in the improved structure. Furthermore, the digital twin system can monitor the internal stress of components in the vehicle air conditioning in real time under various usage scenarios, thereby predicting the breakage risk and service life of vehicle air conditioning components in real time.

[0047] Reference Figure 1 The construction method of the digital twin system for vehicle air conditioning of the present invention is introduced in conjunction with the parking air conditioner. Among them, Figure 1 This is a flowchart illustrating the steps of constructing a digital twin system for a parking air conditioner in one embodiment of the present invention.

[0048] like Figure 1 As shown in the diagram, the construction method of the digital twin system for parking air conditioning of the present invention includes the following steps:

[0049] S100. Based on the physical parameters of the parking air conditioner and the vehicle in which it is applied, construct a bench test system, a multibody dynamics model, and a finite element analysis model.

[0050] Specifically, a bench test system, a multibody dynamics model, and a finite element analysis model are constructed based on the structure, size, material, and connection relationship of the parking air conditioner and the various components of the vehicle in which it is applied.

[0051] S200: Acquire load spectrum data of vehicles under different types of roads and preprocess the load spectrum data.

[0052] Specifically, a parking air conditioner is installed on the vehicle, and the vehicle is driven on different types of roads (such as ordinary roads, expressways, reinforced roads, mountain roads, etc.). Data is acquired through wheel six-component force sensors, body acceleration sensors, axle acceleration sensors, suspension displacement sensors, center of gravity acceleration sensors, GPS sensors, steering wheel angle sensors, and strain gauges / strain rosettes installed on the vehicle, thereby obtaining the load spectrum of the vehicle on different types of roads. The load spectrum is preprocessed, including anomaly detection, symmetry detection, stability detection, filtering, calibration, resampling, and data compression.

[0053] S300. Load the preprocessed load spectrum data into the bench test system in order to obtain the test results of the test points of the bench test system.

[0054] S400. Load the preprocessed load spectrum data into the multibody dynamics model in order to obtain the detection results of the corresponding test points of the multibody dynamics model.

[0055] It should be noted that the test results at the test point can be force, torque, displacement, velocity, acceleration, etc. Preferably, the test result at the test point is acceleration, which is more convenient to measure. In addition, steps S300 and S400 can be executed simultaneously or sequentially, and the execution order can be arbitrarily changed, which does not limit the scope of protection of this invention.

[0056] S510. Determine the error between the test results of the multibody dynamics model and the test points of the bench test system.

[0057] S520. Determine if the error is less than or equal to 10%. If yes, proceed to step S540; otherwise, proceed to step S530.

[0058] S530. Adjust the parameters of the multibody dynamics model, then return to step S400.

[0059] Specifically, adjust the mass, stiffness, damping, and component connection coefficients of the multibody dynamics model.

[0060] S540. Use the current multibody dynamics model as the target multibody dynamics model.

[0061] S600. Load the preprocessed load spectrum data into the target multibody dynamics model to obtain the power spectral density at the installation location of the parking air conditioner in the target multibody dynamics model.

[0062] S700: The power spectral density is applied to the finite element analysis model and the bench test system to obtain the risk point data of the parking air conditioner in the finite element analysis model and the risk point data of the parking air conditioner in the bench test system.

[0063] S800. Adjust the parameters of the finite element analysis model based on the risk point data of the parking air conditioner in the finite element analysis model and the risk point data of the parking air conditioner in the bench test system to obtain the target finite element analysis model.

[0064] By constructing a digital twin system for parking air conditioners using the above methods, a digital twin system that more closely resembles the physical structure can be obtained. Based on the constructed digital twin system, the stress conditions of the parking air conditioner under various operating conditions can be analyzed quickly and accurately. This allows for more accurate optimization of the parking air conditioner structure during the design phase and further verification, avoiding the need for extensive experimental verification or mass production followed by extensive user practice to discover defects in the improved structure. Furthermore, the constructed digital twin system can monitor the internal stress of parking air conditioner components in real time under various usage scenarios, thereby enabling real-time prediction of the breakage risk and service life of parking air conditioner components.

[0065] In step S520, the error between the multibody dynamics model and the detection results of the test points of the bench test system is compared with 10%. Based on the comparison result, the current multibody dynamics model is selectively used as the target multibody dynamics model, or the parameters of the multibody dynamics model are adjusted before returning to step S400. This allows for a more accurate target multibody dynamics model with fewer adjustments. It is understood that comparing the error between the multibody dynamics model and the detection results of the test points of the bench test system with 10% is only a preferred setting. In practical applications, it can be adjusted to adapt to specific application scenarios. For example, the error between the multibody dynamics model and the detection results of the test points of the bench test system can be compared with 5%, 8%, 12%, or 13%, etc.

[0066] Preferably, in step S200, load spectrum data of vehicles under different types of roads is acquired based on Internet of Things (IoT) technology. Specifically, IoT technology is used to monitor a large amount of vehicle data throughout its entire lifecycle in real time, thereby obtaining more comprehensive and richer load spectrum data, facilitating data collection. Furthermore, this can further improve the accuracy of the constructed digital twin system.

[0067] In addition, the present invention also provides a digital twin system for parking air conditioning constructed using the above method.

[0068] This digital twin system for parking air conditioners can be used to predict the lifespan of parking air conditioners during use, and also for the optimization design phase of parking air conditioners.

[0069] The following reference Figure 2 This paper introduces a method for predicting the lifespan of a parking air conditioner based on the aforementioned digital twin system for parking air conditioners. Specifically, Figure 2 This is a flowchart illustrating the steps of a method for predicting the lifespan of a parking air conditioner in one embodiment of the present invention.

[0070] like Figure 2 As shown, the method for predicting the lifespan of a parking air conditioner includes the following steps:

[0071] S110. Real-time acquisition and preprocessing of load spectrum data of vehicles equipped with parking air conditioners during driving.

[0072] Each parking air conditioner has a corresponding target multibody dynamics model and finite element analysis model. During the operation of the parking air conditioner, load spectrum data of the vehicle during the driving process is collected in real time. For example, the load spectrum data of the vehicle on the current road can be obtained by data detected by the vehicle body acceleration sensor, axle head acceleration sensor, suspension displacement sensor, center of gravity acceleration sensor, GPS sensor, steering wheel angle sensor, etc., and the load spectrum data is preprocessed.

[0073] S120. Load the preprocessed load spectrum data of the vehicle with the parking air conditioner installed during the driving process into the target multibody dynamics model so as to obtain the power spectral density of the installation position of the parking air conditioner in the target multibody dynamics model.

[0074] S130. Load the power spectral density into the finite element analysis model to obtain the risk point data of the parking air conditioner in the finite element analysis model.

[0075] S140. Predict the service life of the parking air conditioner based on the risk point data of the parking air conditioner in the finite element analysis model.

[0076] Specifically, when the number of risk points in the parking air conditioner increases in the finite element analysis model and the stress at the risk points reaches a preset value, a risk warning of fatigue fracture in the parking air conditioner can be issued, and information such as the specific location of the risk point and the probability of fracture can be displayed.

[0077] This lifespan prediction method can predict the breakage risk and lifespan of parking air conditioner components in real time, preventing situations where users are unaware of internal pipe or other component breakages during use, leading to more serious damage to the parking air conditioner.

[0078] The following reference Figure 3 This paper introduces an optimized design method for parking air conditioners based on the aforementioned digital twin system for parking air conditioners. Specifically, Figure 3 This is a flowchart illustrating the steps of an optimized design method for a parking air conditioner in one embodiment of the present invention.

[0079] like Figure 3 As shown, the optimized design method for parking air conditioners includes the following steps:

[0080] S210. Install the physical prototype of the parking air conditioner into the vehicle.

[0081] After addressing the shortcomings of existing parking air conditioners, the designers manufactured a physical prototype of the parking air conditioner based on the improved design and installed it in the vehicle.

[0082] S220: To enable vehicles to travel on different types of roads in order to acquire load spectrum data and perform preprocessing.

[0083] S230. Load the preprocessed load spectrum data into the target multibody dynamics model to obtain the power spectral density at the installation location of the parking air conditioner in the target multibody dynamics model.

[0084] S240. Predict the service life of the parking air conditioner based on the risk point data of the parking air conditioner in the finite element analysis model.

[0085] It should be noted that, in the process of building the digital twin system in this embodiment, the parking air conditioner used can be either a physical prototype of the parking air conditioner or the parking air conditioner before this improvement.

[0086] After optimizing the structure of the parking air conditioner during the design phase, a digital twin system was used to further verify the physical prototype of the parking air conditioner. This avoided the situation where the parking air conditioner needed to undergo a large number of experimental verifications or mass production and extensive user practice before the defects of the improved structure could be discovered, thus reducing design costs and improving design efficiency.

[0087] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A method for constructing a digital twin system for vehicle air conditioning, characterized in that, The construction method includes the following steps: S1. Construct a bench test system, a multibody dynamics model, and a finite element analysis model based on the physical parameters of the vehicle air conditioner and the vehicle to which the vehicle air conditioner is applied. S2. Obtain the load spectrum data of the vehicle under different types of roads and preprocess the load spectrum data; S3. Load the preprocessed load spectrum data into the bench test system in order to obtain the detection results of the test points of the bench test system; S4. Load the preprocessed load spectrum data into the multibody dynamics model in order to obtain the detection results of the corresponding test points of the multibody dynamics model; S5. Compare the detection results of the test points of the bench test system with the detection results of the corresponding test points of the multibody dynamics model, and selectively adjust the parameters of the multibody dynamics model according to the comparison results to obtain the target multibody dynamics model. S6. Load the preprocessed load spectrum data into the target multibody dynamics model to obtain the power spectral density at the installation location of the vehicle air conditioner in the target multibody dynamics model. S7. The power spectral density is loaded onto the finite element analysis model and the bench test system to obtain the risk point data of the vehicle air conditioner in the finite element analysis model and the risk point data of the vehicle air conditioner in the bench test system. S8. Adjust the parameters of the finite element analysis model according to the risk point data of the vehicle air conditioner in the finite element analysis model and the risk point data of the vehicle air conditioner in the bench test system to obtain the target finite element analysis model.

2. The construction method according to claim 1, characterized in that, The step of "selectively adjusting the parameters of the multibody dynamics model based on the comparison results to obtain the target multibody dynamics model" includes: If the error between the detection result of the test point of the bench test system and the detection result of the corresponding test point of the multibody dynamics model is not greater than 10%, then the current multibody dynamics model is taken as the target multibody dynamics model.

3. The construction method according to claim 2, characterized in that, The step of "selectively adjusting the parameters of the multibody dynamics model based on the comparison results to obtain the target multibody dynamics model" includes: If the error between the detection result of the test point of the bench test system and the detection result of the corresponding test point of the multibody dynamics model is greater than 10%, then the parameters of the multibody dynamics model are adjusted, and then the process returns to step S4.

4. The construction method according to claim 1, characterized in that, The steps for "obtaining load spectrum data of the vehicle under different types of roads" include: The load spectrum data of the vehicle under different types of roads is obtained based on Internet of Things (IoT) technology.

5. The construction method according to claim 1, characterized in that, The detection results include acceleration.

6. The construction method according to claim 1, characterized in that, The preprocessing includes anomaly detection, symmetry detection, stationarity detection, filtering, calibration, resampling, and / or data compression.

7. A digital twin system for vehicle air conditioning, characterized in that, The digital twin system is a digital twin system constructed using the construction method for a digital twin system for vehicle air conditioning as described in any one of claims 1 to 6.

8. The digital twin system according to claim 7, characterized in that, The vehicle air conditioner mentioned is a parking air conditioner.

9. A method for predicting the lifespan of a vehicle air conditioner, characterized in that, The lifespan prediction method is performed based on the digital twin system for vehicle air conditioning as described in claim 7, and the prediction method includes: The load spectrum data of the vehicle equipped with the vehicle air conditioner is acquired in real time during the driving process and preprocessed. The preprocessed load spectrum data of the vehicle equipped with the vehicle air conditioner during driving is loaded into the target multibody dynamics model in order to obtain the power spectral density of the installation position of the vehicle air conditioner in the target multibody dynamics model. The power spectral density is loaded into the finite element analysis model to obtain the risk point data of the vehicle air conditioner in the finite element analysis model; The service life of the vehicle air conditioner is predicted based on the risk point data of the vehicle air conditioner in the finite element analysis model.

10. An optimized design method for a vehicle air conditioner, characterized in that, The optimization design method is performed based on the digital twin system for vehicle air conditioning as described in claim 7, and the optimization design method includes: Install the physical prototype of the vehicle air conditioner into the vehicle; The vehicle is driven on different types of roads to acquire load spectrum data and perform preprocessing. The preprocessed load spectrum data is loaded into the target multibody dynamics model to obtain the power spectral density at the installation location of the vehicle air conditioner in the target multibody dynamics model. The power spectral density is loaded into the finite element analysis model to obtain the risk point data of the vehicle air conditioner in the finite element analysis model; The structure of the physical prototype is adjusted based on the risk point data of the vehicle air conditioner in the finite element analysis model.

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