Method for determining testability of a thermal system
Patent Information
- Application Number
- CN202610297418.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Priority Date
- 2025-03-12
- Filing Date
- 2026-03-12
- Publication Date
- 2026-09-15
Smart Images
Figure CN122753784A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to a method for determining the testability of a thermal system. Background Technology
[0002] Methods for determining the testability of thermal systems are known from the prior art. Summary of the Invention
[0003] The objective of this invention is to provide an improved method for determining the testability of a thermal system and an improved method for testing a thermal system.
[0004] This task is solved by the method according to the invention. Advantageous embodiments are set forth in the description.
[0005] According to one aspect, a computer-implemented method for determining the testability of a thermal system is provided, the method comprising: The thermal conductivity value of the receiving heat system; The dynamic behavior of a thermal system is determined based on its thermal conductivity value. Determine the linearity of the thermal behavior of the thermal system; and If the thermal behavior is identified as linear, then the thermal system is identified as testable; and If the thermal behavior is identified as nonlinear, the thermal system is identified as untestable.
[0006] The resulting technical advantage is that it provides an improved method for determining the testability of a thermal system. To this end, the dynamic behavior of the thermal system is first determined based on its thermal conductivity value. Then, the linearity of this thermal behavior is determined. Finally, the testability of the thermal system is determined based on the linearity of the thermal behavior. If the thermal behavior is linear, the thermal system is identified as testable. Conversely, if the thermal behavior is not linear, the thermal system is identified as untestable.
[0007] The testability of a thermal system can be determined by assessing the linearity of its thermal behavior. Compared to expensive simulation tools used to accurately map thermal behavior in order to determine the testability of a thermal system, this method requires significantly less computational power and time.
[0008] In the context of this application, the testability description of a thermal system refers to whether it is possible or meaningful to thermally test the system. Here, thermal testing of a thermal system is meaningful if it is expected that the thermal behavior of the current thermal system will remain within a predefined framework of thermal behavior for similar types of thermal systems.
[0009] Conversely, if the thermal behavior of the thermal system under study is found to have a nonlinear component according to the present invention, it is impossible to predict how the thermal system under study will behave during thermal testing. In this case, performing thermal testing should be considered meaningless.
[0010] Therefore, the method according to the invention can accurately estimate the testability of a thermal system based on the linearity of its thermal behavior. Compared to known simulation methods in the prior art, the method according to the invention requires significantly less computational effort.
[0011] In this context, the dynamic behavior of a thermal system is the evolution of its dynamic characteristics over time.
[0012] According to one implementation, determining the dynamic behavior includes: The heat flux (Wärmefluss) within the thermal system is determined for multiple boundary conditions and / or initial values, and multiple heat flux trajectories describing the heat flux are generated for the multiple boundary conditions and / or initial values, wherein the heat flux is determined taking into account the thermal conductivity of the thermal system.
[0013] The resulting technical advantage is that it enables the accurate determination of the thermal behavior of a thermal system based on its heat flux.
[0014] By generating heat flux trajectories, the dynamic behavior of a thermal system over time can be determined for different initial values and boundary conditions. This enables precise and detailed studies of the dynamic behavior.
[0015] According to one embodiment, the boundary conditions include at least one of the following: the number of thermal components in the thermal system, the size of the thermal components, the interaction between the thermal components, the thermal properties of the thermal components; and / or, wherein the initial values include the initial temperature of the thermal system.
[0016] The technical advantage that can be achieved in this way is that, by using different boundary conditions or initial values, convincing solutions for different situations of dynamic behavior can be provided in the form of corresponding heat flux trajectories.
[0017] According to one implementation, determining the linearity of thermal behavior includes: Attractor analysis was performed on multiple heat flux trajectories.
[0018] The resulting technical advantage is that the linearity of dynamic behavior can be accurately determined through attractor analysis of heat flux trajectories. Specifically, analyzing the attractors of multiple heat flux trajectories mapping dynamic behavior enables accurate, fast, and computationally efficient analysis of the linearity of dynamic behavior.
[0019] According to one implementation, performing attractor analysis includes: The heat flux trajectory is mapped to a multidimensional phase space and a phase space trajectory is generated within that phase space. Determine the correlation dimension of the phase space trajectory; If the correlation dimension of the phase space trajectory is greater than or equal to a predefined limit, the thermal behavior is identified as nonlinear behavior; and If the correlation dimension is less than a predefined limit, the thermal behavior is identified as linear behavior.
[0020] The resulting technical advantage is that, by calculating the correlation dimension of the phase space trajectory, accurate attractor analysis and, consequently, accurate analysis of the linearity of the dynamic behavior can be provided.
[0021] Here, if the correlation dimension is less than a predefined limit, the dynamic behavior is identified as linear. Conversely, if the correlation dimension is greater than or equal to the predefined limit, the dynamic behavior is identified as nonlinear.
[0022] Calculating the correlation dimension of phase space trajectories enables fast, accurate, and computationally efficient analysis of the linearity of dynamic behavior.
[0023] In the context of this application, correlation dimension is a term used for fractal dimension and represents the roughness (nonlinearity) of a self-similar signal.
[0024] According to one implementation, the heat flux trajectory is mapped into phase space using time delay coordinates.
[0025] The resulting technical advantage is that by mapping the heat flux trajectory to phase space using time-delay coordinates, the correlation dimension of the phase space trajectory can be accurately calculated.
[0026] According to one implementation, determining the thermal behavior includes: Divide the thermal system into multiple spatial elements; and Calculate the heat flux for the multiple spatial elements.
[0027] The technical advantage of this is that by dividing the thermal system into multiple spatial elements and calculating the heat flux of each spatial element, the heat flux of the entire thermal system can be accurately determined.
[0028] Furthermore, dividing the thermal system into multiple spatial regions and calculating the heat flux separately for each region can reduce the complexity of heat flux calculation. This can further reduce the required computing power.
[0029] According to one implementation, the thermal behavior is determined by taking into account Fourier's law of heat flux.
[0030] The resulting technical advantage is that the dynamic behavior of the thermal system can be accurately determined based on its heat flux. Therefore, Fourier's law can be considered in the form of differential equations.
[0031] According to one embodiment, the thermal conductivity value is determined based on the thermal components constructed in the thermal system.
[0032] The technical advantage that can be achieved is that the thermal system under study can be accurately described based on the thermal conductivity value.
[0033] According to one embodiment, the thermal system is formed from an electronic circuit board for a vehicle.
[0034] The resulting technical advantage is that this method allows for the determination of the testability of electronic circuit boards used in vehicles. Precise limits are set for the thermal load capacity of circuit boards used in the automotive field, particularly those applied to autonomous driving, and these limits restrict the dynamic behavior of the corresponding electronic components.
[0035] This method allows analysis of the circuit board under inspection to determine whether limits or regulations restricting its dynamic behavior can be met. Conversely, if the dynamic behavior of the circuit board under investigation is identified as nonlinear, it can be inferred that limits or guidelines regarding thermal development within circuit boards used in vehicles cannot be complied with.
[0036] In this case, the costly thermal testing of the circuit board can be omitted, since it can be inferred that the circuit board to be tested will not meet the test prerequisites.
[0037] According to one aspect, a method for testing a thermal system is provided, the method comprising: The testability of the thermal system is determined by implementing a method for determining the testability of a thermal system according to one of the above embodiments. If the thermal system is identified as testable, a thermal test of the thermal system is performed; and If the thermal system is identified as untestable, then aussetzen (abstain) from thermal testing of the thermal system.
[0038] According to one aspect, a computing unit is provided, the computing unit being configured to implement a method for determining the testability of a thermal system and / or a method for testing a thermal system according to one of the above embodiments.
[0039] According to one aspect, a computer program product including instructions is provided, which, when implemented by a data processing unit, cause the data processing unit to implement a method for determining the testability of a thermal system and / or a method for testing a thermal system according to one of the above embodiments. Attached Figure Description
[0040] Embodiments of the present invention are described with reference to the following accompanying drawings. The drawings show: Figure 1 A schematic diagram of a method for determining the testability of a thermal system according to one embodiment; Figure 2 A diagram illustrating the attractor analysis of the phase space trajectory of the thermal system according to another embodiment; Figure 3 A flowchart of a method for determining the testability of a thermal system according to one embodiment; Figure 4 Another flowchart of a method for determining the testability of a thermal system according to another embodiment; Figure 5 Another flowchart of a method for determining the testability of a thermal system according to another embodiment; Figure 6 A flowchart of a method for testing a thermal system according to one embodiment; and Figure 7 A schematic diagram of a computer program product. Detailed Implementation
[0041] Figure 1 A schematic diagram of a method for determining the testability of a thermal system 300 according to one embodiment is shown.
[0042] Figure 1 The various method steps of the method for determining the testability of a thermal system 300 according to the present invention are explained.
[0043] To determine testability, the thermal conductivity value 301 of the thermal system 300 to be inspected is first received by the analysis module 319, which can be implemented on the computing unit 317.
[0044] Subsequently, based on the thermal conductivity value 301, the dynamic behavior 303 of the thermal system 300 under study is obtained by the analysis module 319. The dynamic behavior 303 describes the evolution of the thermal properties of the dynamic system 300 over time.
[0045] Subsequently, the linearity 305 of the dynamic behavior 303 of the thermal system 300 is obtained by the analysis module 319.
[0046] Here, if the dynamic behavior 303 is identified as linear behavior, the thermal system 300 under investigation is identified as testable. Conversely, if the dynamic behavior 303 is identified as nonlinear behavior, the thermal system 300 under investigation is classified as untestable.
[0047] According to the present invention, the testability of the thermal system 300 under study is equivalent to the linearity of the corresponding dynamic behavior of the thermal system. Correspondingly, untestability is equivalent to the nonlinearity of the dynamic behavior.
[0048] In the illustrated embodiment, the thermal system 300 under study includes a plurality of thermal components 309. The thermal conductivity value 301 of the thermal system 300 describes the thermal conductivity characteristics of the different components 311.
[0049] According to the embodiment shown, the dynamic behavior 303 of the thermal system 300 under study is obtained while taking into account the heat flux 307 of the thermal system 300.
[0050] Heat flux 307 describes the amount of heat released per unit time through a unit area by the thermal system 300.
[0051] In the illustrated embodiment, in order to obtain the dynamic behavior 303 while taking into account the heat flux 307, the thermal system under study is divided into multiple spatial regions 315.
[0052] Spatial region 315 encloses the thermal system 300 and has multiple surface elements 321. In the illustrated embodiment, the heat flux 307 of the thermal system 300 is calculated for the multiple spatial regions 315.
[0053] In particular, heat flux can be calculated for each individual spatial region 315, especially as the heat flowing through the corresponding defined surface element 321 of the corresponding spatial region 315 per unit time.
[0054] According to one implementation, in order to obtain dynamic behavior, the heat flux 307 within the thermal system 300 can be calculated for multiple different boundary conditions and / or initial values.
[0055] Therefore, multiple heat flux trajectories describing the heat flux 307 can be calculated for different boundary conditions and / or initial values. Each heat flux trajectory describes the evolution of the heat flux over time for the corresponding set boundary conditions and / or initial values.
[0056] Boundary conditions may include at least one of the following: the number of thermal components 311 of the thermal system 300, the size of the thermal components 311, the interaction between the thermal components, and the thermal characteristics of the thermal components 311.
[0057] For example, the initial value could be a different initial temperature of the thermal system 300.
[0058] In the illustrated embodiment, the thermal system 300 is configured as a circuit board 327 for a vehicle. The plurality of thermal components 311 may be various electronic components of the circuit board 327.
[0059] Depending on the corresponding structure of each component, different thermal conductivity values 301 can be provided for different spatial regions 315 of the circuit board 327.
[0060] The thermal conductivity value 301 can be generated, for example, by corresponding measurements of different components 311 of the thermal system 300.
[0061] However, unlike the illustrated embodiment, the method of the present invention can also be applied to other thermal systems 300. The present invention should not be limited to circuit board 327.
[0062] Figure 2 A diagram illustrating the attractor analysis of the phase space trajectory 309 of a thermal system 300 according to another embodiment is shown.
[0063] According to one implementation, in order to obtain the dynamic behavior 303, the heat flux 307 is calculated using Fourier's law for heat flux.
[0064] Here: For temperature gradient In each unit of time Flow area The calories, of which, Where is the thermal conductivity coefficient, and The thickness is the layer thickness.
[0065] The specific equilibrium energy (spezifische Gleichgewichtsenergie) q (J / kg) is related to the temperature per unit volume: .
[0066] Taking Fourier's law into account, the accurate heat flux 307 can be calculated for the thermal system 300 under study. As described above, the heat flux 307 can be calculated for each individual spatial region 315.
[0067] According to the illustrated implementation, multiple heat flux trajectories are calculated for different boundary conditions and / or initial values, taking into account Fourier's law of heat flux 307. These heat flux trajectories describe the evolution of the dynamic characteristics of the system under study over time and, overall, describe the dynamic behavior 303 of the thermal system 300.
[0068] In the illustrated embodiment, in order to determine the linearity 305 of the dynamic behavior 303, attractor analysis is performed on multiple heat flux trajectories.
[0069] Therefore, multiple heat flux trajectories are mapped to a multidimensional phase space 313 using time-delay coordinates, and corresponding phase space trajectories 309 are generated.
[0070] In order to perform attractor analysis, in the embodiment shown, the correlation dimension of the phase space trajectory 309 in phase space 313 is determined.
[0071] Therefore, the correlation dimension is calculated using correlation integrals.
[0072] Related Integrals: , Where f is the number of phase space point pairs of phase space trajectory 309 in phase space 313, and the pair spacing between the phase space point pairs is less than or equal to r.
[0073] The correlation dimension D is derived here from the following relationship: C(r) ~ r D , This relationship is particularly applicable to small spacing r.
[0074] exist Figure 2 The diagram shows log-log plots of multiple phase space trajectories 309. Here, the different phase space trajectories 309 are derived based on heat flux trajectories, which are derived for different boundary conditions and / or initial values and represent the evolution of heat flux over time.
[0075] In order to determine the linearity of dynamic behavior 303, the correlation dimension d is now determined for different regions 329 within phase space 313.
[0076] exist Figure 2 Four distinct regions 329 are illustrated in the example. Here, two attractor regions 323 and two diverging regions 325 are labeled.
[0077] Here, the attractor region 323 is characterized in that the phase space points of the phase space trajectory 309 shown have a small spacing r between them and are shown compactly together.
[0078] Conversely, the divergence region 325 is characterized in that the phase space points of the phase space trajectory 309 shown have a relatively large distance r between each other.
[0079] Attractor region 323 indicates that different phase space trajectories 309 converge to a single point, said different phase space trajectories being based on the following heat flux trajectories: these heat flux trajectories represent different solutions of the Fourier equation for different frame conditions and / or initial values.
[0080] Conversely, the divergent region indicates that the phase space trajectories 309 are arranged at larger intervals to each other, thus exhibiting more divergent behavior.
[0081] Now, when calculating the correlation dimension D, the linearity 305 of the dynamic behavior 303 is calculated so that for the phase space region 325 where the correlation dimension D is less than a predetermined limit value, the dynamic behavior 303 is identified as a linear behavior.
[0082] exist Figure 2 In this process, this linear behavior is obtained within the indicated attractor region 323.
[0083] Conversely, for spatial regions 325 where the correlation dimension D is greater than or equal to a predefined limit value, the dynamic behavior 303 is identified as nonlinear behavior. This nonlinear behavior can be expected within the illustrated divergence region 325.
[0084] Experiments show that, for the thermal system 300, especially the circuit board 327 constructed for use in vehicles, the pre-defined limit of the correlation dimension D is equal to 1.28.
[0085] exist Figure 2 In the example shown, the dynamic behavior 303 represented by the phase space trajectory 309 will be identified as linear behavior in the attractor region 323 and as nonlinear behavior in the divergence region 325. Therefore, the corresponding thermal system 300 will be identified as untestable in the divergence region 325 and as testable in the attractor region 323.
[0086] Figure 3 A flowchart of a method 100 for determining the testability of a thermal system 300 according to one embodiment is shown.
[0087] To determine the testability of the thermal system 300, a thermal conductivity value 301 is first received in method step 101. In method step 103, the dynamic behavior 303 of the thermal system 300 is determined based on the thermal conductivity value 301.
[0088] In method step 105, the linearity 305 of the dynamic behavior 303 is obtained.
[0089] In method step 107, if the dynamic behavior 303 is identified as linear behavior, then the thermal system 300 is identified as testable.
[0090] Conversely, in method step 109, if the dynamic behavior 303 is identified as nonlinear, the thermal system 300 is identified as untestable.
[0091] Figure 4 Another flowchart of a method 100 for determining the testability of a thermal system 300 according to another embodiment is shown.
[0092] Figure 4 The implementation method in is based on Figure 3 The implementation methods described herein include all method steps.
[0093] In the illustrated embodiment, in method step 111, in order to obtain the dynamic behavior 303, the heat flux 307 of the thermal system 300 is obtained.
[0094] In order to obtain the linearity 305 of the dynamic behavior 303, in method step 113, attractor analysis is performed on the heat flux trajectory obtained for multiple different frame conditions and / or initial values.
[0095] Therefore, in method step 115, the heat flux trajectory is mapped to the multidimensional phase space 313 using time delay coordinates, and a phase space trajectory 309 is generated in the phase space 313.
[0096] In step 117 of the method, the correlation dimension D is calculated for multiple phase space trajectories 309 in phase space 313.
[0097] In method step 119, if the correlation dimension D is lower than a predefined limit, then dynamic behavior 303 is identified as linear behavior.
[0098] Conversely, in method step 121, if the correlation dimension D is greater than or equal to a predefined limit value, then the dynamic behavior 303 is identified as nonlinear behavior.
[0099] Figure 5 Another flowchart of a method 100 for determining the testability of a thermal system 300 according to another embodiment is shown.
[0100] Figure 5 The implementation method in is based on Figure 4 The implementation methods described herein include all method steps.
[0101] In the illustrated embodiment, in order to obtain the dynamic behavior 103, the thermal system 300 is divided into different spatial regions 315 in method step 123.
[0102] In method step 125, heat flux 307 is calculated for multiple spatial regions 315 of thermal system 300.
[0103] Figure 6 A flowchart of a method 200 for testing a thermal system 300 according to one embodiment is shown.
[0104] In order to test the thermal system 300, the testability of the thermal system 300 is first determined in the first method step 201 by implementing the method 100 for determining the testability of the thermal system 300 according to the present invention.
[0105] In another method step 203, if the thermal system 300 is identified as testable, a thermal test of the thermal system 300 is performed.
[0106] Conversely, in another method step 205, if the thermal system 300 is identified as untestable, the thermal test is abandoned.
[0107] Therefore, testing of the thermal system 300 may, for example, involve subjecting the thermal system 300 to a load and measuring the thermal evolution of the thermal system 300 over time.
[0108] In particular, the thermal development of each component 311 of the thermal system 300 can be considered by recording the corresponding measurements of temperature development.
[0109] Figure 7 A schematic diagram of a computer program product 400 is shown, which includes instructions that, when implemented by a data processing unit, cause the data processing unit to implement a method 100 for determining the testability of a thermal system 300 and / or a method 200 for testing the thermal system 300.
[0110] In the illustrated embodiment, the computer program product 400 is stored on a storage medium 401. This storage medium 401 can be any storage medium known from the prior art.
Claims
1. A computer-implemented method (100) for determining the testability of a thermal system (300), the method comprising: Receive (101) the thermal conductivity value (301) of the thermal system (300); The dynamic behavior (303) of the thermal system (300) is obtained (103) based on the thermal conductivity value (301). Determine the linearity (305) of the thermal behavior (303) of the thermal system (300) described in (105); and If the thermal behavior (303) is identified as linear thermal behavior (303), then the thermal system (300) is identified (107) as testable; and If the thermal behavior (303) is identified as nonlinear thermal behavior (303), then the thermal system (300) is identified (109) as untestable.
2. The method (100) according to claim 1, wherein, The dynamic behavior described in (103) includes: (111) The heat flux (307) within the thermal system (300) is determined for multiple boundary conditions and / or initial values, and multiple heat flux trajectories describing the heat flux (307) are generated for the multiple boundary conditions and / or initial values, wherein the heat flux (307) is determined taking into account the thermal conductivity value (301) of the thermal system (300).
3. The method (100) according to claim 2, wherein, The boundary conditions include at least one of the following: the number of thermal components (311) of the thermal system (300), the size of the thermal components (311), the interaction between the thermal components (311) and each other, the thermal properties of the thermal components (311); and / or, wherein the initial values include the initial temperature of the thermal system (300).
4. The method (100) according to claim 2 or 3, wherein, Determining the linearity (305) of the thermal behavior (303) described in (105) includes: Perform attractor analysis on the multiple heat flux trajectories (113).
5. The method (100) according to claim 4, wherein, Performing the attractor analysis described in (113) includes: The heat flux trajectory is mapped (115) into a multidimensional phase space (313) and a phase space trajectory (309) is generated in the phase space (313). Find the correlation dimension (117) used for multiple phase space trajectories (309); If the correlation dimension of the phase space trajectory (309) is less than a predetermined limit, then the thermal behavior (303) is identified (119) as linear behavior (303); and If the correlation dimension is greater than or equal to the predefined limit value, the thermal behavior (303) is identified (121) as nonlinear behavior (303).
6. The method (100) according to claim 5, wherein, The heat flux trajectory (309) is mapped into the phase space (313) using time-delay coordinates.
7. The method (100) according to any one of the preceding claims, wherein, Determining the thermal behavior (303) described in (103) includes: The thermal system (300) is divided (123) into multiple spatial regions (315); and The heat flux (307) is calculated (125) for the multiple spatial regions (315).
8. The method (100) according to any one of the preceding claims, wherein, The thermal behavior (303) is obtained by taking into account Fourier's law of the heat flux (307).
9. The method (100) according to any one of the preceding claims, wherein, The thermal conductivity value (301) is determined based on the thermal component (311) constructed in the thermal system (300).
10. The method (100) according to any one of the preceding claims, wherein, The thermal system (300) is formed by an electronic circuit board (327) for the vehicle.
11. A method (200) for testing a thermal system (300), the method comprising: The testability of the thermal system (300) is determined (201) by implementing the method (100) for determining the testability of the thermal system (300) according to any one of claims 1 to 10; If the thermal system (300) is identified as testable, then a thermal test of the thermal system (300) is performed (203); as well as If the thermal system (300) is identified as untestable, then the thermal test of the thermal system (300) is abandoned (205).
12. A computing unit (317) configured to implement a method (100) for testing an electronic circuit board according to any one of claims 1 to 10 and / or a method (200) for testing a thermal system (300) according to claim 11.
13. A computer program product (400) comprising instructions that, when implemented by a data processing unit, cause the data processing unit to implement a method (100) for testing an electronic circuit board according to any one of claims 1 to 10 and / or a method (200) for testing a thermal system (300) according to claim 11.