Method for providing temperature data of an electric machine

Abstract

A method (100) for providing temperature data of an electric machine is disclosed, comprising: acquiring provided parameter data (110) of the electric machine, wherein the parameter data comprise a PT1 temperature model and a PT2 temperature model of the electric machine; acquiring provided machine data (120) of the electric machine, wherein the machine data comprise a temperature measurement value of the electric machine, a speed value of the electric machine, and / or a torque value of the electric machine; and providing the temperature data (130), which comprise a temperature value determined based on the parameter data and the machine data, and / or a temperature deviation value determined based on the parameter data and the machine data. A computing unit configured and set up to execute the method is also disclosed.

Description

[0001] The present invention relates to a method for providing temperature data from an electric machine. The invention also relates to a computing unit configured and set up to execute the method.

[0002] In the prior art, methods for determining the temperature of an electric machine are known, particularly for determining the hotspot temperature of the stator, since the stator windings typically exhibit the highest temperature of the machine. The stator hotspot is located within the stator slots, making measurement, especially of the hotspot temperature, difficult. Therefore, measuring devices, particularly NTC sensors, are usually arranged at a star point within the electric machine, which is located outside the stator.

[0003] Methods are known for determining the hotspot temperature which determine the hotspot temperature either based on measured values ​​of the measuring device and temperature offset values ​​or based on a software model such as a PT1 temperature model.

[0004] Therefore, the hotspot temperature of the electric machine determined on the basis of known methods may deviate from the actual hotspot temperatures of the electric machine, so that for proper protection, especially against overheating of the stator, the electric machine can only be operated with a power output that is lower than a maximum possible power output.

[0005] The object of the present invention is therefore to provide a technology that is more advanced than the prior art. In particular, it aims to improve the accuracy of determining the hotspot temperature.

[0006] This problem is solved by articles with the features according to the independent claims. Advantageous embodiments are the subject of the dependent claims.

[0007] A method for providing temperature data of an electrical machine has been disclosed.

[0008] Furthermore, the method includes the acquisition of provided parameter data of the electric machine, wherein the parameter data includes a PT1 temperature model and a PT2 temperature model of the electric machine.

[0009] Furthermore, the method includes acquiring provided machine data of the electric machine, wherein the machine data includes a temperature measurement value of the electric machine, a speed value of the electric machine and / or a torque value of the electric machine.

[0010] Furthermore, the method discloses a provision of temperature data which includes a temperature value determined on the basis of the parameter data and the machine data, and / or a temperature deviation value determined on the basis of the parameter data and the machine data.

[0011] In other words, the method preferably uses a measured temperature of an electric machine's stator in combination with a temperature model, i.e., the PT1 temperature model and the PT2 temperature model, to determine the actual temperature value of the electric machine more accurately. By combining measured values ​​with model-based values, the method can also be described as a hybrid method for determining the actual temperature value. This hybrid solution particularly improves the accuracy of a temperature value from the PT1 temperature model.

[0012] Furthermore, the complexity of a purely model-based estimation of the actual temperature value can be reduced by combining it with the measured stator temperature. Additionally, the initialization of the temperature model in operating states of the electric machine with residual stator temperature can be simplified or improved.

[0013] This method can improve the accuracy of determining the temperature of the electric machine. In particular, it can improve accuracy under different operating conditions.

[0014] In other words, the improved accuracy allows for better performance of the electric machine, since any threshold values ​​for protection, especially against overheating, of the electric machine no longer need to be included in the control of the electric machine for a system reduction of the electric machine.

[0015] This allows an electric machine to be controlled or used in an improved way based on specific temperature values, in particular controlling the power output of the electric machine depending on the temperature values.

[0016] Furthermore, the parameter data includes a PT2 temperature model of the electric machine.

[0017] Temperature differences between the determined temperature values, particularly of the stator, and the measured temperature values ​​can exhibit an overshoot that cannot be modeled by a PT1 temperature model, since PT1 temperature models do not include overshoots. Therefore, the method can particularly preferably determine the temperature values ​​based on a combination of the PT1 and PT2 temperature models, so that any overshoots of the measured temperature values ​​can be taken into account in the determined temperature values.

[0018] Furthermore, the parameter data may also include an adaptation value for the electric machine.

[0019] The adaptation value can, for example, depend on the type and / or model of the electrical machine. Furthermore, the adaptation value can be determined in advance, for example, using test procedures.

[0020] Furthermore, the machine data may also include a coolant temperature value of the electric machine and / or a coolant flow rate value of the electric machine.

[0021] Furthermore, the temperature data may also include a hotspot temperature value, which is determined based on the parameter data and the machine data.

[0022] The hotspot temperature value can, for example, indicate a temperature at an area of ​​the electrical machine that has the highest temperature of the electrical machine.

[0023] Furthermore, the respective determination can also be carried out on the basis of a provided computer algorithm.

[0024] The computer algorithm can, for example, be a self-learning algorithm and / or an artificial intelligence (AI) model. The computer algorithm can be pre-trained and / or trained through the application of the procedure. Preferably, the computer algorithm can be further trained through the application of the procedure.

[0025] Furthermore, the parameter data may include first look-up data for determining a first P-factor value for use with the PT1 temperature model and / or the PT2 temperature model. The parameter data may also include second look-up data for determining a second P-factor value for use with the PT1 temperature model and / or the PT2 temperature model. Finally, the parameter data may include third look-up data for determining a first K-factor value for use with the PT1 temperature model and / or the PT2 temperature model. The parameter data may also include fourth look-up data for determining a second K-factor value for use with the PT1 temperature model and / or the PT2 temperature model.

[0026] The lookup data can be structured, for example, as a loop-up table. Furthermore, the lookup data can be used to map specific values, such as input values, to a value in the lookup data. The lookup data can contain, for example, one value and / or multiple values.

[0027] The second p-factor value can, for example, be expressed as a differential p-factor value. The second k-factor value can, for example, be expressed as a differential k-factor value.

[0028] Furthermore, the first look-up data can determine the first P-factor using the speed value, the torque value, and / or the coolant temperature value. The second look-up data can determine the second P-factor using the speed value, the torque value, and / or the coolant temperature value. The third look-up data can determine the first K-factor using the speed value, the torque value, and / or the coolant temperature value. Finally, the fourth look-up data can determine the second K-factor using the speed value, the torque value, and / or the coolant temperature value.

[0029] Furthermore, the respective determination can be carried out on the basis of the first P-factor value, the second P-factor value, the first K-factor value, the second K-factor value, the coolant flow rate value, the PT1 temperature model, the PT2 temperature model, the adaptation value, the self-learning algorithm and / or the temperature value.

[0030] Alternatively or additionally, a third P-factor value can be determined based on the first P-factor value, the second P-factor value and the coolant flow rate value.

[0031] Alternatively or additionally, a K2 factor value can be determined based on the first K factor value, the second K factor value and the coolant flow rate value.

[0032] Alternatively or additionally, a PT1 factor value can be determined based on the PT1 temperature model, the third P factor value, the K2 factor value and the adjustment value.

[0033] Alternatively or additionally, a K1 factor value can be determined based on the third P factor value and the K2 factor value. Furthermore, a PT1 factor value can be determined based on the PT1 temperature model, the K1 factor value, and the adjustment value.

[0034] Alternatively or additionally, a PT2 factor value can be determined based on the PT2 temperature model, the K2 factor value and the adjustment value.

[0035] Alternatively or additionally, the temperature value, the temperature deviation value and / or the hotspot temperature value can be determined based on the PT1 factor value and the PT2 factor value.

[0036] Furthermore, the third P-factor value, the K2-factor value, the PT1-factor value and / or the PT2-factor value can be provided by the procedure.

[0037] Also disclosed is a computing unit that is designed and equipped to execute the disclosed procedure.

[0038] The present invention is described in detail below with reference to the figures. These show: Fig. 1. a sequence of a procedure for providing temperature data of an electrical machine; Fig. 2. A diagram with graphs of exemplary temperature profiles; and Fig. 3 a vehicle with a computing unit for providing temperature data.

[0039] The present invention is described below with reference to preferred embodiments and the figures. However, this description of the embodiment should not be considered exhaustive.

[0040] The Fig. Figure 1 shows the sequence of a procedure 100 for providing temperature data of an electric machine.

[0041] Method 100 comprises acquiring provided parameter data 110 of the electric machine, wherein the parameter data includes a PT1 temperature model and a PT2 temperature model of the electric machine. Method 100 further comprises acquiring provided machine data 120 of the electric machine, wherein the machine data includes a temperature measurement value of the electric machine, a speed value of the electric machine, and / or a torque value of the electric machine. Method 100 also comprises providing the temperature data 130, which includes a temperature value determined based on the parameter data and the machine data, and / or a temperature deviation value determined based on the parameter data and the machine data.

[0042] In particular, the temperature data may also include a hotspot temperature value, which is determined based on the parameter data and the machine data.

[0043] Preferably, the parameter data may include first look-up data for determining a first P-factor value for use with the PT1 temperature model and / or the PT2 temperature model. More preferably, the parameter data may include second look-up data for determining a second P-factor value for use with the PT1 temperature model and / or the PT2 temperature model. More preferably, the parameter data may include third look-up data for determining a first K-factor value for use with the PT1 temperature model and / or the PT2 temperature model. More preferably, the parameter data may include fourth look-up data for determining a second K-factor value for use with the PT1 temperature model and / or the PT2 temperature model.

[0044] Preferably, the first look-up data can determine the first P-factor using the speed value, the torque value, and / or the coolant temperature value. Furthermore preferably, the second look-up data can determine the second P-factor using the speed value, the torque value, and / or the coolant temperature value. Furthermore preferably, the third look-up data can determine the first K-factor using the speed value, the torque value, and / or the coolant temperature value. Furthermore preferably, the fourth look-up data can determine the second K-factor using the speed value, the torque value, and / or the coolant temperature value.

[0045] Furthermore, the parameter data may include an adaptation value for the electric machine. Additionally, the machine data may include a coolant temperature value and / or a coolant flow rate value for the electric machine. Furthermore, the respective determination may be carried out based on a provided computer algorithm.

[0046] Furthermore, the respective determination can be carried out on the basis of the first P-factor value, the second P-factor value, the first K-factor value, the second K-factor value, the coolant flow rate value, the PT1 temperature model, the PT2 temperature model, the adaptation value, the computer algorithm and / or the temperature value.

[0047] The Fig. Figure 2 shows a diagram 10 with graphs 11, 12, 13 of exemplary temperature profiles, the diagram comprising a first axis representing a temperature [K] of graphs 11, 12, 13 and a second axis representing a time value [s].

[0048] Diagram 10 shows a first graph 11, which represents a temperature profile based on a PT1 temperature model, depicting a rising temperature profile. The PT1 temperature model is particularly well-suited for modeling, especially rapidly rising, temperature profiles. Furthermore, the first graph 11 can represent a temperature profile based on specific temperature values ​​from known prior art methods.

[0049] Furthermore, diagram 10 shows a second graph 12, which represents a temperature profile based on a PT2 temperature model, depicting a decrease in temperature. The PT2 temperature model is particularly well-suited for modeling oscillating or settling temperature profiles.

[0050] Furthermore, diagram 10 shows a third graph 13, which represents an actual temperature profile of an electric machine.

[0051] Furthermore, diagram 10 shows a fourth graph 14, which represents a temperature profile determined based on the PT1 temperature model and the PT2 temperature model. As can be seen, the fourth graph 14 depicts a rise and a fluctuation of the temperature profile. Therefore, the fourth graph 14 can represent a temperature profile that, at certain temperature values, is determined by method 100 according to the Fig. 1 is based and approximates the actual temperature profile shown by the third graph 13.

[0052] The Fig. Figure 3 shows a setup of an exemplary vehicle 30 with a computing unit 31 for providing temperature data according to the method 100. Fig. 1. Furthermore, the vehicle comprises an electric machine 33 and a control unit 32, which is designed and equipped to control the electric machine 33.

[0053] The computing unit 31 can, for example, receive a measured temperature value from the control unit 32 and / or a measuring device of the electric machine 33. Furthermore, the computing unit 31 can provide the control unit 32 with specific temperature data according to method 100. The control unit 32 can then control the electric machine 33 based on the temperature data. It should be noted that the computing unit 31 and the control unit 32 can also be implemented as a single unit. Reference symbol list 10 Diagram 11 first graph 12 second graph 13 third graph 14 fourth graph 20 Device 21 computing unit 22 Control unit 23 electric machine 100 methods for providing temperature data 110 Capturing provided parameter data 120 Recording of provided machine data 130 Providing the temperature data

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