Method for condition monitoring, digital twin

Abstract

The invention relates to a method for the condition monitoring of at least one component (41, 42) of an electric drive system (2), wherein a digital twin (6) of the electric drive system (2) is formed based on an initial state of the drive system (2) and on at least one aging model of the drive system (2).

Description

[0001] 202417436

[0002] 1

[0003] Description

[0004] Condition monitoring methods, digital twin

[0005] The invention relates to a method for condition monitoring and a digital twin.

[0006] Data-based condition monitoring of an electric drive system with an inverter and a three-phase load, which relies on existing measurement data and intermediate parameters from the system's control, is a challenging task when monitoring the degradation of inverter components (especially semiconductor modules, sensors, DC link capacitors, and gate drivers). Degradation is usually detected by changes in the monitored parameters. Due to manufacturing tolerances, different assembly variants, and environmental influences such as temperature and cable lengths, varying initial values ​​are present. This complicates general parameterization in advance.

[0007] The invention is based on the objective of improving this.

[0008] The problem is solved by claim 1, i.e. a method for monitoring the condition of at least one component of an electric drive system, wherein a digital twin of the electric drive system is formed based on an initial state of the drive system and on at least one aging model of the drive system.

[0009] The invention enables the initial parameterization of data-based condition monitoring for a converter system. By combining it with a parallel-computing digital twin, detection capabilities can be increased to enable predictive maintenance. Unplanned downtime can thus be avoided.

[0010] A prediction of the remaining lifespan of the component is made here, in particular based on the collected data and the aging model.

[0011] An advantageous embodiment is one in which the aging model is based on end-of-life data and / or reliability tests. Advantage?

[0012] An advantageous embodiment is one in which the state of at least one component is determined at a real operating point by using rainflow counting to determine the state of the 202417436

[0013] 2

[0014] The digital twin is transferred from a simulated operating point to the real operating point.

[0015] Particularly advantageous is the continuous updating of the digital twin with real-time data from the electric drive system to ensure precise condition monitoring.

[0016] An advantageous embodiment is one in which the component is a semiconductor module or an element of a semiconductor module.

[0017] An advantageous embodiment involves simulating the drive system using the digital twin, detecting data changes at operating points, particularly when the data change exceeds a defined deviation.

[0018] An advantageous embodiment is one in which the aging of the component is taken into account when considering the data change.

[0019] An advantageous embodiment is one in which a warning message is provided if the data change exceeds a further or the defined deviation.

[0020] An advantageous embodiment is one in which the digital twin is modified based on the data change.

[0021] An advantageous embodiment is one in which the operation of the electric drive system takes place simultaneously with the operation of the digital twin.

[0022] An advantageous embodiment is one in which, upon reaching a certain operating point of the electric drive system, the digital twin is modified in such a way that state variables and / or measured values ​​of the digital twin correspond at least substantially to state variables and / or measured values ​​of the electric drive system.

[0023] Bidirectional communication between the digital twin and the real drive system can be provided, especially to make adjustments in real time.

[0024] An advantageous embodiment includes, for example, state variables and / or measured values ​​such as the forward voltage of the semiconductor, the thermal resistance of the semiconductor, ESR 202417436

[0025] 3

[0026] of the intermediate circuit capacitor, capacitance of the intermediate circuit capacitor, ohmic resistance of the load, temperature of the load, back EMF of the load and / or a switching point of the semiconductor.

[0027] An advantageous embodiment is one in which a degradation state of a component is determined based on the change in the digital twin and the aging model.

[0028] Fault diagnosis can be advantageously performed to identify potential sources of error in the component before an actual failure occurs.

[0029] Environmental conditions that could affect the aging of the component, such as temperature, humidity and vibrations, can also be taken into account.

[0030] An advantageous embodiment involves calculating a quality measure from the time since the last approach to a suitable operating point for modification and the respective identification quality of that operating point to quantify the current prediction accuracy of the digital twin. Advantage?

[0031] The problem can also be solved by using a digital twin of an electric drive system with at least one component, for monitoring the condition of the component using such a method.

[0032] The digital twin of an electric drive system is advantageous because it is a detailed, virtual model that represents the physical version of the drive in digital form. This digital twin effectively reflects the physical properties and behavior of the actual drive and can be connected to it in real time to collect and analyze data.

[0033] The main components and functions of a digital twin of an electric drive are preferably a physical model, i.e., an accurate replica of the mechanical, electrical, and thermal properties of the drive system.

[0034] Regarding data integration, it is advantageous if real-time data, including data from sensors and control units integrated into the physical drive system, is continuously fed into the digital model. 202417436

[0035] 4

[0036] Regarding simulation and analysis, the following is advantageous: The digital twin can be used to simulate different scenarios, perform performance analyses, and evaluate the behavior of the drive system under different conditions.

[0037] Error diagnosis and prediction are particularly successful with the digital twin: Based on the collected data and simulations, potential errors and signs of wear can be detected and predicted early.

[0038] In principle, the digital twin can also offer advantages in terms of optimization and control: The digital twin can be used to optimize the control strategies and operating parameters of the drive system in order to maximize efficiency and performance.

[0039] Implementing a digital twin can improve the performance and reliability of the drive system. Maintenance work can be optimized and downtime reduced.

[0040] Optimization of the operation of the electric drive system based on condition monitoring and operating points together with the digital twin is possible.

[0041] The digital twin can, for example, be operated in a cloud environment to enable convenient and flexible condition monitoring.

[0042] The task is solved by a computer program product comprising instructions which, when the program is executed by a computing unit, for example by a computing unit of the electric drive system, cause it to execute the procedure.

[0043] The task can also be solved using a computer-readable storage medium on which the computer program product is stored.

[0044] Furthermore, a user interface can be provided that visualizes the current state of the component and predicted maintenance intervals.

[0045] It is also possible to use machine learning to continuously improve the aging model and increase the accuracy of condition monitoring. 202417436

[0046] 5

[0047] The invention will now be described and explained in more detail with reference to the exemplary embodiments shown in the figures. The figures show:

[0048] FIG 1 advantageous steps of the process,

[0049] FIG 2 a drive system with an inverter and a dynamo-electric machine,

[0050] FIG 3 shows an alternative solution for a drive system in which the digital twin is operated in a cloud environment.

[0051] FIG 1 shows advantageous steps of the process.

[0052] In the first step, S1, a digital twin of the electric drive system is created. For the components to be subject to condition monitoring, aging models are advantageously stored alongside the initial state model. These aging models can be developed, for example, from data from end-of-life or reliability tests on the component test bench.

[0053] The transfer to the actual operating points takes place in a second step S2, for example using the method of rainflow counting.

[0054] For the semiconductor module, relevant parameters depend on aging, especially forward voltage, junction temperature, and DCB temperature. This is advantageously taken into account when modeling the digital twin.

[0055] In step S3, the digital twin is used in the simulation to investigate at which operating points, advantageously depending on the degradation state of the component or several components, a significant data change can be detected.

[0056] The data change allows for advantageous conclusions to be drawn about the underlying aging effect.

[0057] In step S4, the data change is used as input for the condition monitoring procedure. 202417436

[0058] 6

[0059] Thresholds can also be set for data changes that indicate an impending system failure, thus enabling predictive maintenance. A warning message can then be generated in step S5.

[0060] The identified operating points are advantageously stored in step S6 for later use as particularly suitable initialization points and / or update points for the digital twin.

[0061] The actual operation of the electric drive system with a parallel digital twin is advantageously carried out in the following way: Digital Twin is implemented as follows: After a defined time has elapsed, the initialization routine is carried out in step S7.

[0062] This approach advantageously involves visiting operational points that offer a high level of information. What does that mean?

[0063] The parameters of the parallel-running digital twin are adapted in step S8 such that the error between the measured values ​​or state variables of the real system and the simulated data of the digital twin approaches zero, i.e., is 0 or at least nearly 0.

[0064] In particular, this concerns the adaptation of the forward voltages and thermal resistances of the semiconductors, ESR and capacitance of the DC link capacitors, ohmic resistance, temperature and back EMF of the load, and switching times of the semiconductors.

[0065] This procedure is advantageously repeated at regular intervals upon reaching the previously identified, suitable operating points. The digital twin thus advantageously describes the state of the electric drive system immediately after the update processes.

[0066] By coupling with the previously created aging models, the degradation state of the components can be determined in one step S9.

[0067] In the time between two parameterization runs, the component parameters are further predicted more advantageously based on the aging models and the system data. 202417436

[0068] 7

[0069] Preferably in step S10, a quality measure is formed from the time since the last approach to an operating point suitable for re-parameterization and the respective identification quality of the operating point in order to quantify the current prediction quality of the digital twin.

[0070] The derived state of aging and the accuracy measure for the estimate are advantageously used to predict the impending failure of the system, thus enabling predictive maintenance without unplanned downtime.

[0071] The described method advantageously outlines the creation, initial parameterization, and real-world operation of a digital twin that monitors the aging of an electric drive system to enable predictive maintenance. Advantageously, the entire development cycle of the system is considered.

[0072] Linking aging models with the modeling of the real plant in the form of a digital twin is advantageous here. Ideally, operating points containing as much information as possible for condition monitoring are identified beforehand using the digital twin. This improves the robustness and reliability of the condition monitoring process.

[0073] Adapting the digital twin is preferably not performed at the same update rate, but rather at regular, well-known, and / or predefined, identifiable operating points. By coupling this with aging models, the system's state of degradation can also be determined in the periods between identification runs.

[0074] By introducing a quality measure, the uncertainty of the current degradation estimate can also be taken into account. Together, these enable predictive maintenance of the system without unplanned downtime.

[0075] FIG 2 shows a converter 4 and a dynamoelectric machine 5.

[0076] These form an electric drive system 2. Components 41 and 42 are shown in the inverter 4. Components 41 and 42 are shown as examples and could, for instance, represent a semiconductor module, sensors, or an intermediate capacitor. 202417436

[0077] 8

[0078] Furthermore, a computing unit 3 is shown, on which the digital twin 6 of the drive system, represented by the interaction of the inverter twin 4z and the motor twin 5z, runs.

[0079] FIG 3 shows an alternative solution in which the digital twin 6 is operated in a cloud environment 31.

[0080] The computing unit 3 is capable of executing a computer program product, which includes instructions that, when the program is executed by the computing unit 3, cause it to carry out the procedure.

[0081] This can also be achieved through Cloud 31.

[0082] The computing unit 3 preferably also includes a computer-readable storage medium on which the computer program product is stored.

Claims

202417436 9 Patent claims 1. Method for condition monitoring of at least one component (41, 42) of an electric drive system (2), wherein a digital twin (6) of the electric drive system (2) is formed based on an initial state of the drive system (2) and on at least one aging model of the drive system (2).

2. The method of claim 1, wherein the aging model is based on end-of-life data and / or reliability tests.

3. Method according to one of the preceding claims, wherein the state of the at least one component (41, 42) in a real operating point is determined by transferring the state of the digital twin (6) in a simulated operating point to the real operating point using rain flow counting.

4. Method according to any of the preceding claims, wherein the component (41, 42) is a semiconductor module or an element of a semiconductor module.

5. Method according to one of the preceding claims, wherein the drive system (2) is simulated using the digital twin (6), wherein a data change at operating points is detected, in particular when the data change exceeds a defined deviation.

6. Method according to one of the preceding claims, wherein the aging of the component (41, 42) is taken into account when considering the data change.

7. Method according to one of the preceding claims, wherein, if the data change exceeds a further or the defined deviation, a warning message is provided.

8. Method according to any of the preceding claims, wherein the digital twin (6) is modified based on the data change.

9. Method according to one of the preceding claims, wherein the operation of the electric drive system (2) takes place simultaneously with the operation of the digital twin (6). 202417436 10 10. Method according to one of the preceding claims, wherein, upon reaching a certain operating point of the electric drive system (2), the digital twin (6) is modified such that state variables and / or measured values ​​of the digital twin (6) correspond at least substantially to state variables and / or measured values ​​of the electric drive system (6).

11. Method according to claim 10, wherein state variables and / or measured values ​​are, for example, a forward voltage of the semiconductor, thermal resistance of the semiconductor, ESR of the intermediate circuit capacitor, capacitance of the intermediate circuit capacitor, ohmic resistance of the load, temperature of the load, back EMF of the load and / or a switching time of the semiconductor.

12. Method according to one of the preceding claims, wherein a degradation state of a component (41 , 42) is determined based on the change of the digital twin (6) and the aging model.

13. Method according to one of the preceding claims, wherein a quality measure is formed from the time since the last approach to an operating point suitable for modification and a respective identification quality of the operating point to quantify the current prediction quality of the digital twin (6).

14. Digital twin (6) of an electric drive system (2) with at least one component (41, 42), for condition monitoring of the component (41, 42) using a method according to one of claims 1 to 13.

15. Computer program product comprising instructions which, when the program is executed by a computing unit (3, 31), for example by a computing unit (3) of the electric drive system (2), cause it to execute the method according to one of claims 1 to 13.

16. Computer-readable storage medium on which the computer program product according to claim 15 is stored.

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