Power supply device, operating module and temperature measuring method thereof

Abstract

A power supply device includes a working circuit, a circuit sensor, and a processing circuit. The circuit sensor continuously senses the working circuit to acquire data that changes over time. The processing circuit is coupled to the circuit sensor. The processing circuit is used to: receive the data from the working circuit; substitute the data into a reduced-order model to obtain the simulated temperature of the working circuit, wherein the reduced-order model is established based on a complex set of physical quantities of the working circuit through a reduction-order operation; and determine whether the working circuit is malfunctioning based on the simulated temperature.

Description

Technical Field

[0001] The present invention relates to a power supply device, a computing module and a temperature measurement method thereof, and in particular to a power supply device, a computing module and a method thereof for estimating transient temperature. Prior Art

[0002] Thermal management systems in the prior art typically rely on basic thermal models and require manual calibration. This approach can be inefficient and potentially cause failures under varying operating conditions. Conventional technology also utilizes temperature sensors to measure the operating temperature of circuit devices. However, conventional temperature sensors primarily measure the steady-state temperature of circuit devices, such as the temperature change every 10 seconds during continuous operation. Such steady-state temperature measurements can only represent the overall operating temperature of the circuit device and cannot reflect the transient temperature of a core circuit in the circuit device at a specific moment (for example, measuring the channel interface temperature of a power inverter switch at the moment of switch switching).

[0003] Since conventional temperature sensors cannot instantly measure or calculate the transient temperature of a specific component within a circuit, this makes temperature monitoring difficult. Summary of the Invention

[0004] This disclosure provides a power supply device. The power supply device includes a working circuit, a circuit sensor, and a computing circuit. The circuit sensor is used to continuously sense the working circuit and obtain data that changes over time. The computing circuit is coupled to the circuit sensor. The computing circuit is used to: receive data from the working circuit; substitute the data into a reduced-order model to obtain a simulated temperature of the working circuit, wherein the reduced-order model is constructed based on multiple physical quantities of the working circuit through reduced-order operations; and determine whether the working circuit is abnormal based on the simulated temperature.

[0005] This disclosure provides a temperature measurement method for a power supply device comprising an operating circuit, a circuit sensor, and a computing circuit. The temperature measurement method comprises: continuously sensing the operating circuit to obtain data that changes over time; substituting the data into a reduced-order model to obtain a simulated temperature of the operating circuit, wherein the reduced-order model is constructed based on multiple physical quantities of the operating circuit through reduced-order operations; and determining whether the operating circuit is abnormal based on the simulated temperature.

[0006] This disclosure provides a computational module. The computational module includes a circuit sensor and a computational circuit. The circuit sensor is used to continuously sense an operating circuit and obtain data that changes over time. The computational circuit is coupled to the circuit sensor. The computational circuit is used to: receive data from the operating circuit; substitute the data into a reduced-order model to obtain a simulated temperature of the operating circuit, wherein the reduced-order model is constructed based on multiple physical quantities of the operating circuit through reduced-order operations; and determine whether the operating circuit is abnormal based on the simulated temperature.

[0007] In summary, through the use of a reduced-order model, the power supply device of this disclosure only needs to measure voltage variables, current variables, and coolant flow rate to infer the simulated temperature of the operating circuit, thereby achieving the advantageous technical benefit of saving computing power. It can also be understood that through the use of a reduced-order model, the computing circuitry within the power supply device does not need to possess high computing power, thereby reducing the manufacturing cost of the power supply device. Simple diagram description

[0008] FIG1 is a schematic diagram of a power supply device according to an embodiment of the present disclosure. FIG2 is a schematic diagram of the internal components of the working circuit in the embodiment according to FIG1. FIG3 is a first structure function curve diagram according to one embodiment of the present disclosure. FIG. 4 is a graph showing a first structure function and a second penetration function according to an embodiment of the present disclosure. FIG5 is a flow chart of a temperature measurement method according to an embodiment of the present disclosure. FIG6 is a schematic diagram of a computing module according to an embodiment of the present disclosure. Implementation Method

[0009] The following will illustrate the embodiments of the present disclosure with reference to the accompanying drawings. In the drawings, the same reference numerals represent the same or similar elements or method flows.

[0010] Please refer to FIG. 1 , which is a schematic diagram of a power supply device 100 according to an embodiment of the present disclosure. In the embodiment of FIG. 1 , power supply device 100 includes an operating circuit 110, a circuit sensor 120, and a computing circuit 130. Circuit sensor 120 includes a temperature sensor 125. Furthermore, power supply device 100 is coupled to an external computing device 140.

[0011] In this embodiment, the power supply device 100 can be used as a power supply system for an electric vehicle. However, this disclosure is not limited to this. The power supply device 100 can also be used in renewable energy systems (e.g., solar or wind energy) or in power supply devices that feed DC power (e.g., a storage battery) into an AC power grid. The operating circuit 110 can be used to convert DC power input (e.g., a storage battery, solar panels, or wind turbine) into a specific AC power output. The operating circuit 110 may include components such as a coupled inductor, inverter switches, and a water-cooled motor. The operating circuit 110 can achieve AC power output through these components.

[0012] In this embodiment, the measuring end of the circuit sensor 120 can be disposed within the working circuit 110 to measure the voltage and current of components within the working circuit 110. Furthermore, the circuit sensor 120 can also measure the coolant of a water-cooled motor within the working circuit 110. The circuit sensor 120 can continuously sense the working circuit 110 to obtain data that changes over time. This data can come from a single detected point within the working circuit 110. Alternatively, this data can come from multiple detected points within the working circuit 110. Furthermore, this data can include a voltage variable VV1, a current variable IV1, and a coolant flow rate CFV1. The present invention is not limited to the above description; the circuit sensor 120 of the present invention can also continuously sense the working circuit 110 to obtain various data such as ambient temperature and coolant temperature that change over time.

[0013] The measuring end of the temperature sensor 125 of the circuit sensor 120 can also be set in the working circuit 110 to measure the initial temperature TEM0 of the working circuit 110 at the moment when the power supply device 100 starts to operate (also called the "initial state").

[0014] The computing circuit 130 is coupled to the circuit sensor 120 and the external computing device 140. The computing circuit 130 can receive the voltage variable VV1, the current variable IV1, and the coolant flow rate CFV1 from the circuit sensor 120, and obtain the reduced-order model DFM1 from the external computing device 140. The reduced-order model DFM1 of the present invention is exemplified by a reduced-order matrix model.

[0015] The computation circuit 130 is a single-chip system, an embedded system, or a system on a chip (SoC). It is used to determine the simulated temperature of the operating circuit 110 during operation. However, since the computation circuit 130 may be a single-chip system, its capacity and computing power are limited, making it incapable of performing more complex computations. Therefore, the computation circuit 130 must use a reduced-order model (DFM1) to determine the simulated temperature. It is worth noting that the simulated temperature can be the maximum temperature within the operating circuit 110.

[0016] In some embodiments, the operation circuit 130 may bring the voltage variable VV1, the current variable IV1, and the coolant flow rate CFV1 into the reduced-order model DFM1 to calculate the simulated temperature of the working circuit 110 during operation.

[0017] In these embodiments, the computing circuit 130 can determine whether the operating circuit 110 is abnormal based on the simulated temperature. Furthermore, the computing circuit 130 can set a threshold based on the voltage variable VV1, the current variable IV1, the coolant flow rate CFV1, and the reduced-order model DFM1, or the user can pre-set a specific value as the threshold. When the simulated temperature calculated by the computing circuit 130 exceeds the threshold, the computing circuit 130 can determine that the operating circuit 110 is abnormal. In this case, the internal temperature of the operating circuit 110 may be too high, and the service life of the operating circuit 110 may be insufficient. The computing circuit 130 can quickly cut off the power supply by shutting down the operating circuit 110, thereby protecting the power supply device 100 from damage caused by overload or faults.

[0018] In other embodiments, the computation circuit 130 may further incorporate the initial temperature TEM0 measured by the temperature sensor 125 into the reduced-order model DFM1. The computation circuit 130 may calculate the transient power of the operating circuit 110 at a specific point in time based on the voltage variable VV1, the current variable IV1, and the coolant flow rate CFV1. After determining the transient power, the computation circuit 130 may infer the simulated temperature based on the initial temperature TEM0 and the transient power.

[0019] In the above embodiment, the reduced-order model DFM1 is established by the external computing device 140 using a reduced-order operation. The external computing device 140 can measure a plurality of physical quantities PQ[1]-PQ[M] from the working circuit 110 and perform a reduced-order operation on the physical quantities PQ[1]-PQ[M] to establish the reduced-order model DFM1.

[0020] Through order reduction operations, a complex three-dimensional model can be simplified into a form that is easier to handle, thereby improving simulation efficiency without losing too much accuracy. A plurality of first physical quantities can be reduced to a heat convection coefficient, and the heat convection coefficient can be obtained through a plurality of second physical quantities, and the number of second physical quantities is less than the number of first physical quantities. In other words, through order reduction operations, a plurality of first physical quantities (for example, a three-dimensional model) can be simplified into a plurality of second physical quantities (in numerical form). Corresponding to the above embodiment, the first physical quantity in this paragraph can be the physical quantity PQ[1]~PQ[M] measured by the external computing device 140. The external computing device 140 can simplify the first physical quantity (i.e., the physical quantity PQ[1]~PQ[M]) into a second physical quantity through order reduction operations. And through the first physical quantity and the second physical quantity, a reduced-order model DFM1 can be established.

[0021] In one embodiment, the first physical quantity may be physical quantities PQ[1]-PQ[M] measured by the external computing device 140 and input as a three-dimensional model, and the physical quantities PQ[1]-PQ[M] may at least include the coolant flow rate, coolant density, coolant isobaric specific heat, coolant thermal conductivity, coolant viscosity of the water-cooled motor in the working circuit 110, and the ambient temperature during operation of the working circuit 110. The second physical quantity may be a simple numerical value, or may be the voltage variable VV1, the current variable IV1, and the coolant flow rate CFV1 of the working circuit 110.

[0022] In some embodiments, the reduced-order model DFM1 can be implemented using multi-operation logic gates. In other embodiments, the reduced-order model DFM1 can be represented in the form of mechanical code.

[0023] It is worth mentioning that the external computing device 140 and the power supply device 100 are different devices. The external computing device 140 can be a conventional computer device installed in a laboratory. A use environment equivalent to the power supply device 100 can be constructed in the laboratory, and the ambient temperature of the use environment and the physical quantities PQ[1]~PQ[M] of the working circuit 110 can be adjusted as needed. The external computing device 140 can measure the working circuit 110 at different ambient temperatures, calculate the corresponding relationship between the ambient temperature, the physical quantities PQ[1]~PQ[M], the voltage variable VV1, the current variable IV1, and the coolant flow rate CFV1 of the working circuit 110, and establish a reduced-order model DFM1.

[0024] In summary, through the reduced-order model DFM1, the power supply device 100 only needs to measure the voltage variable VV1, the current variable IV1, and the coolant flow rate CFV1 to allow the computing circuit 130 to infer the simulated temperature of the working circuit 110, without having to measure and calculate each of the physical quantities PQ[1]-PQ[M], thereby achieving the advantageous technical effect of saving computing performance. It can also be understood that through the reduced-order model DFM1, the computing circuit 130 in the power supply device 100 does not need to have strong computing performance, thereby reducing the manufacturing cost of the power supply device 100.

[0025] Please refer to FIG. 2, which is a schematic diagram of the internal components of the operating circuit 110 according to the embodiment of FIG. In this embodiment, the operating circuit 110 may include cables SC1 and SC2, coupled inductors CID1 and CID2, capacitors C1-C6, inverter switches SW1-SW6, and motor MOT1.

[0026] Cables SC1 and SC2 can receive an input voltage and be coupled to ground GND. Cable SC1 can also be coupled to the first terminal of capacitor C1. The second terminal of capacitor C1 is coupled to ground GND and the first terminal of capacitor C2. Cable SC2 can also be coupled to the second terminal of capacitor C2. In one embodiment, cables SC1 and SC2 can be shielded cables coated with insulating material.

[0027] A first input terminal of coupled inductor CID1 is coupled to the first terminal of capacitor C1. A first output terminal of coupled inductor CID1 is coupled to the first terminal of capacitor C3 and the first terminal of capacitor C4. A second input terminal of coupled inductor CID1 is coupled to the second terminal of capacitor C2. A second output terminal of coupled inductor CID1 is coupled to the second terminal of capacitor C3 and ground GND. A second terminal of capacitor C4 is coupled to ground GND.

[0028] A first end of inverter switch SW1 is coupled to capacitor C4, capacitor C5, a first end of inverter switch SW2, capacitor C6, and a first end of inverter switch SW3. A second end of inverter switch SW1 is coupled to a first end of inverter switch SW4. A second end of inverter switch SW2 is coupled to a first end of inverter switch SW5. A second end of inverter switch SW3 is coupled to a first end of inverter switch SW6. The second ends of inverter switch SW4, inverter switch SW5, and inverter switch SW6 are all coupled to ground GND.

[0029] Inverter switches SW1-SW6 are insulated gate bipolar transistors (IGBTs) or metal oxide semiconductor field effect transistors (MOSFETs), respectively. Operational circuit 130 generates gate signals to drive inverter switches SW1-SW6, thereby controlling their operation. Inverter switches SW1-SW6 switch their switching states according to the gate signals to generate three-phase AC power. Precise switching control of inverter switches SW1-SW6 generates the desired frequency and voltage waveform. Three sets of inverter switches SW1-SW6 form a three-phase system, with each set controlling the voltage of one phase, thereby generating a balanced three-phase AC power. Adjusting the switching speed of inverter switches SW1-SW6 adjusts the output frequency, thereby controlling the motor speed (e.g., the rotational speed of motor MOT1).

[0030] The inverter switches SW1 - SW6 are coupled to the input terminals of the coupled inductor CID2 . The three-phase input terminals of the motor MOT1 are coupled to the output terminals of the coupled inductor CID2 .

[0031] In this embodiment, the simulated temperature calculated by the computation circuit 130 may be the ideal operating temperature of the inverter switches. When the ideal operating temperature of the inverter switches exceeds the threshold value mentioned above, it may indicate that the inverter switches SW1-SW6 have worn out or have a short service life. When the inverter switches SW1-SW6 are determined to have a short service life, the power supply device 100 may prompt maintenance personnel to replace them. In some embodiments, the power supply device 100 may identify the service life of a specific inverter switch among the inverter switches SW1-SW6 and issue a targeted replacement prompt.

[0032] Please refer to FIG. 3 , which is a graph of a first structure function according to an embodiment of the present disclosure. The first structure function curve is obtained by measuring the thermal resistance and thermal capacitance of the chip, substrate, solder joints, fin headers, and circuit operating environment used by the power supply device 100 using an external computing device 140. This curve can be used to represent the first structure function generated by the reduced-order model DFM1 based on the physical quantities PQ[1]-PQ[M] of the operating circuit 110 in FIG. It is worth noting that the first structure function can be a heat flow structure function.

[0033] By measuring the physical quantities PQ[1]-PQ[M] of the working circuit 110, the corresponding relationship between the thermal resistance and thermal capacitance of the power supply device 100 can be obtained.

[0034] Please refer to FIG. 4 , which is a graph showing the first structure function and the second structure function according to an embodiment of the present disclosure.

[0035] The first structure function curve in Figure 4 is identical to the first structure function curve in Figure 3. The difference between Figures 3 and 4 is that Figure 4 includes a second structure function curve. Like the first structure function, the second structure function can also be a heat flow structure function. The first and second structure function curves can partially overlap. As shown in Figure 4, the first and second structure function curves overlap in the "chip," "chip connection point," and "substrate" regions. The bifurcation point between the first and second structure function curves occurs in the "solder point" region.

[0036] In the embodiment of Figure 4, the external computing device 140 can read measured values, such as the voltage variable VV1, the current variable IV1, or the coolant flow rate CFV1, as well as the simulated temperature calculated using the reduced-order model DFM1, through the computing circuit 130. Based on the structure presented by the first structure function, the real-time temperature change of the component is obtained. Conversely, the computing circuit 130 repeatedly obtains specific temperature changes within a specific time period (i.e., the time points corresponding to the first structure function), derives thermal resistance values ​​based on the structure function, and then connects these thermal resistance values ​​to form a second structure function curve. As the measured object undergoes structural changes over time, the second structure function curve differs from the first structure function curve. Therefore, a second structure function curve, different from the first structure function curve, can be defined to represent the state of the object under test when an abnormality occurs.

[0037] Through the visual presentation in Figure 4, the user can clearly understand whether there is a difference between the actual state of the operating circuit 110 and the normal state. We can compare any point or points on the second structure function curve with a corresponding point or points on the first structure function curve (for example, thermal resistance values ​​of 0.04K / W, 0.05K / W, etc.) to determine whether the DUT is in an abnormal state, such as whether the corresponding solder joint of the DUT is abnormal. Furthermore, we can compare any line segment on the second structure function curve with a corresponding line segment on the first structure function curve (for example, a line segment with thermal resistance values ​​of 0.04K / W to 0.05K / W, corresponding to a solder joint), to determine whether the DUT's solder joint is in an abnormal state.

[0038] The present invention uses a structure function generated by measuring temperature changes over a short period of time. Therefore, it can measure the transient response (transient change) of the object under test to temperature changes. Therefore, the temperature inferred according to the present invention is more accurate than conventional techniques. Because the structure function of the present invention is derived from transient changes in a multi-layer structure, when an abnormality occurs in the object under test, the method of the present invention can identify which layer of the structure of the object under test the abnormality occurs, such as an abnormal solder joint. This invention can improve the misjudgment of conventional methods. In reality, it is possible that the surface temperature of the object under test is normal, but the temperature of its inner structure is excessively high. The present invention can improve measurement accuracy and ensure the safety of the object under test.

[0039] Please refer to FIG5 . FIG5 is a flow chart of a temperature measurement method 500 according to an embodiment of the present disclosure. The temperature measurement method 500 is used to illustrate the operation method of the power supply device 100 .

[0040] In step S510 , the circuit sensor 120 of the power supply device 100 may continuously sense the working circuit 110 to obtain the voltage variable VV1 , the current variable IV1 , and the coolant flow rate CFV1 that change with time.

[0041] In step S520, the computing circuit 130 of the power supply device 100 substitutes the voltage variable VV1, the current variable IV1, and the coolant flow rate CFV1 into the reduced-order model DFM1 to obtain the simulated temperature of the operating circuit 110. In this embodiment, the reduced-order model DFM1 is established based on a plurality of physical quantities PQ[1]-PQ[M] of the operating circuit 110 through a reduced-order operation.

[0042] In step S530, the operation circuit 130 may determine whether the working circuit 110 is abnormal according to the simulated temperature.

[0043] Please refer to Figures 1 and 6 simultaneously. Figure 6 is a schematic diagram of a computing module 600 according to an embodiment of the present disclosure. The computing module 600 in Figure 6 includes a circuit sensor 620 and a computing circuit 630. The circuit sensor 620 includes a temperature sensor 625. The circuit sensor 620 and computing circuit 630 in Figure 6 correspond to the circuit sensor 120 and computing circuit 130 in Figure 1. Furthermore, in Figure 6, the computing module 600 can be externally connected to a working circuit 610 and an external computing device 640. The working circuit 610 and external computing device 640 in Figure 6 correspond to the working circuit 110 and external computing device 140 in Figure 1.

[0044] In the embodiment of FIG. 6 , the operational details of circuit sensor 620 and computing circuit 630 also correspond to those of circuit sensor 120 and computing circuit 130 in FIG. The measuring terminal of circuit sensor 620 can be located within operating circuit 610 to measure the voltage and current of components within operating circuit 610 and obtain various time-varying data, such as voltage variable VV1, current variable IV1, and coolant flow rate CFV1. Temperature sensor 625 within circuit sensor 620 can measure and receive initial temperature TEM0 from operating circuit 610.

[0045] The computing circuit 630 receives the voltage variable VV1, the current variable IV1, and the coolant flow rate CFV1 from the circuit sensor 620, and obtains the reduced-order model DFM1 from the external computing device 640. The details of the reduced-order model DFM1 can be found in the embodiment of FIG.

[0046] The computation circuit 630 can substitute the voltage variable VV1, current variable IV1, and coolant flow rate CFV1 into the reduced-order model DFM1 to calculate the simulated temperature of the operating circuit 610 during operation. The computation circuit 130 can determine whether the operating circuit 110 is abnormal based on the simulated temperature and generate a control signal S_ctrl based on the determination result.

[0047] The computation circuit 630 can send a control signal S_ctrl to the operating circuit 610 to control the operating circuit 610. In this embodiment, the computation circuit 630 can set a threshold value based on the voltage variable VV1, the current variable IV1, the coolant flow rate CFV1, and the reduced-order model DFM1, or the user can pre-set a specific value as the threshold value. When the simulated temperature calculated by the computation circuit 630 exceeds the threshold value, the computation circuit 630 can determine that an abnormality has occurred in the operating circuit 610. In this case, the computation circuit 630 can shut down the operating circuit 610 via the control signal S_ctrl, thereby quickly powering off the operating circuit 610 and protecting the operating circuit 610 from damage caused by overload or faults.

[0048] It is worth mentioning that the computing module 600 can be adapted to a variety of different types of working circuits. The present invention does not limit the specific circuit type of the working circuit 610. The working circuit 610 only needs to allow the computing module 600 and the external computing device 640 to measure the required data.

[0049] In summary, through the reduced-order model DFM1, the power supply device 100 only needs to measure the voltage variable VV1, the current variable IV1, and the coolant flow rate CFV1, so that the computing circuit 130 can infer the simulated temperature of the working circuit 110, without having to measure and calculate each of the physical quantities PQ[1] to PQ[M], thereby achieving the advantageous technical effect of saving computing performance. It can also be understood that through the reduced-order model DFM1, the computing circuit 130 in the power supply device 100 does not need to have strong computing performance, thereby reducing the manufacturing cost of the power supply device 100. When the present invention is used in a power supply device or a metal test object with a multi-layer structure, it can quickly calculate the structure function curve of the test object or the curve of the transient thermal resistance changing with time, thereby improving work efficiency.

[0050] The above are merely preferred embodiments of this disclosure. Various modifications and equivalents may be made to this disclosure without departing from the scope or spirit of this disclosure. In summary, all modifications and equivalents of this disclosure within the scope of the following claims are intended to be covered by this disclosure.

[0051] 100: Power supply device 110, 610: Working circuit 120, 620: Circuit sensor 125, 625: Temperature sensor 130, 630: Operational circuit 140, 640: External computing device VV1: voltage variable IV1: Current variable CFV1: Coolant flow rate TEM0: initial temperature PQ[1]~PQ[M]: physical quantity DFM1: Reduced Order Model SW1, SW2, SW3, SW4, SW5, SW6: Inverter switches SC1, SC2: Cable GND: Ground terminal C1, C2, C3, C4, C5, C6: capacitors CID1, CID2: coupled inductors MOT1: Motor 500: Temperature measurement method S510, S520, S530: Steps 600: Computing module S_ctrl: control signal

Claims

1. A power supply device comprising: a working circuit; a circuit sensor for continuously sensing the working circuit and acquiring data that changes over time; and a processing circuit coupled to the circuit sensor for receiving the data from the working circuit; substituting the data into a reduced-order model to obtain a simulated temperature of the working circuit, wherein the reduced-order model is established based on a plurality of physical quantities of the working circuit through a reduced-order operation; and determining whether the working circuit is abnormal based on the simulated temperature, wherein the reduced-order model is established through the following steps: measuring a plurality of first physical quantities of the working circuit; performing the reduced-order operation to simplify the first physical quantities into a plurality of second physical quantities, wherein the number of the second physical quantities is less than the number of the first physical quantities; and establishing the reduced-order model based on the first physical quantities and the second physical quantities.

2. The power supply device as claimed in claim 1, wherein the data includes a voltage variable, a current variable, and a coolant flow rate.

3. The power supply device as claimed in claim 1, wherein the reduced-order model is a matrix model, and a first structure function of the operating circuit is generated based on the first physical quantities.

4. The power supply device as claimed in claim 1, wherein the first physical quantity includes at least a coolant flow rate, a coolant density, a coolant isobaric specific heat, a coolant thermal conductivity, and a coolant viscosity coefficient of the operating circuit.

5. The power supply device as claimed in claim 1, wherein the order reduction operation is used to reduce the first physical quantity to a thermal convection coefficient.

6. The power supply device as claimed in claim 2, wherein the circuit sensor includes a temperature sensor for measuring an initial temperature in an initial state of the power supply device, and the computing circuit is further used to obtain the simulated temperature through the initial temperature, the voltage variable, the current variable and the coolant flow rate.

7. A method for measuring the temperature of a power supply device, the power supply device comprising a working circuit, a circuit sensor, and a computing circuit, the method comprising: continuously sensing the working circuit to obtain data that changes over time; substituting the data into a reduced-order model to obtain a simulated temperature of the working circuit, wherein the reduced-order model is established based on a plurality of physical quantities of the working circuit through a reduced-order operation; and determining whether the working circuit is abnormal based on the simulated temperature, wherein the reduced-order model is established through the following steps: measuring a plurality of first physical quantities of the working circuit; performing the reduced-order operation to simplify the first physical quantities into a plurality of second physical quantities, wherein the number of second physical quantities is less than the number of first physical quantities; and establishing the reduced-order model based on the first physical quantities and the second physical quantities.

8. The temperature measurement method as described in claim 7, wherein the reduced-order model is a matrix model, and a first structure function of the operating circuit is generated based on the first physical quantities.

9. The temperature measurement method as described in claim 7, wherein the first physical quantity includes at least a coolant flow rate, a coolant density, a coolant isobaric specific heat, a coolant thermal conductivity, and a coolant viscosity coefficient of the operating circuit.

10. The temperature measurement method as described in claim 7, wherein the order reduction operation is used to reduce the first physical quantity to a thermal convection coefficient.

11. The temperature measurement method as claimed in claim 7, wherein the circuit sensor includes a temperature sensor, and the temperature measurement method further includes: measuring an initial temperature in an initial state of the power supply device through the temperature sensor; and obtaining the simulated temperature through the initial temperature, a voltage variable, a current variable and a coolant flow rate.

12. A computing module comprising: a circuit sensor for continuously sensing a working circuit to acquire data that varies over time; and a computing circuit coupled to the circuit sensor for: receiving the data from the working circuit; substituting the data into a reduced-order model to obtain a simulated temperature of the working circuit, wherein the reduced-order model is established based on a plurality of physical quantities of the working circuit through a reduced-order operation; and determining whether the working circuit is abnormal based on the simulated temperature, wherein the reduced-order model is established by: measuring a plurality of first physical quantities of the working circuit; performing the reduced-order operation to simplify the first physical quantities into a plurality of second physical quantities, wherein the number of the second physical quantities is less than the number of the first physical quantities; and establishing the reduced-order model based on the first physical quantities and the second physical quantities.

13. The computing module as described in claim 12, wherein the data is a voltage variable, a current variable, and a coolant flow rate.

14. The computation module as described in claim 12, wherein the reduced-order model is a matrix model, and a first structure function of the operating circuit is generated based on the first physical quantities.

15. The computing module as claimed in claim 12, wherein the first physical quantity includes at least a coolant flow rate, a coolant density, a coolant isobaric specific heat, a coolant thermal conductivity, and a coolant viscosity coefficient of the operating circuit.

16. The computation module as described in claim 12, wherein the order reduction operation is used to reduce the first physical quantity to a thermal convection coefficient.

17. The computing module as claimed in claim 13, wherein the circuit sensor includes a temperature sensor for measuring an initial temperature in an initial state of the computing module, and the computing circuit is further used to obtain the simulated temperature through the initial temperature, the voltage variation, the current variation and the coolant flow rate.

Images