IGBT aging monitoring method and device and electronic equipment

Abstract

The invention discloses an IGBT aging monitoring method and apparatus, and an electronic device. The method comprises the steps of obtaining a pre-established first junction temperature expression, a first shell temperature expression and a model parameter conversion model of a to-be-monitored IGBT; the actually measured junction temperature and the actually measured shell temperature of the IGBT to be monitored and initial values of model parameters of the four-order Cauer thermal network model are obtained; fitting the first junction temperature expression in combination with the actually measured junction temperature to obtain a junction temperature initial value coefficient and a time constant; inputting different values of the junction temperature initial value coefficient, the time constant and the model parameter into a model parameter conversion model to obtain a shell temperature initial value coefficient corresponding to each value; inputting each value of the model parameter and the initial value coefficient of the shell temperature into a first shell temperature expression to obtain the shell temperature corresponding to each value; and evaluating the aging state of the to-be-monitored IGBT according to the model parameter corresponding to the shell temperature closest to the actually measured shell temperature. According to the invention, the aging state can be accurately evaluated in real time in different states.

Description

Technical Field

[0001] This invention relates to the field of device monitoring technology, specifically to IGBT aging monitoring methods, devices, and electronic equipment. Background Technology

[0002] Currently, Insulated Gate Bipolar Transistors (IGBTs) are the mainstream semiconductor power devices in power conversion systems. They are commonly monitored by identifying fourth-order thermal network model parameters and establishing a unique mapping between these parameters and the IGBT's multilayer solder and thermally conductive materials. Due to the similarity in physical processes, thermal and electrical parameters also exhibit similarities; therefore, the thermal network model is typically analyzed as an equivalent RC circuit model. IGBT thermal impedance models generally have two structures: the Cauer model and the Foster model. While the Foster model can directly decompose the component into parallel or series RC circuits, making it easier to analyze and construct, it is not directly related to the device's physical properties. Therefore, the analysis results from the Foster model cannot be mapped to the actual aging condition of the IGBT. While the Cauer model can describe the actual distribution of thermal network parameters, and each parameter incorporates the material's physical properties, allowing for precise analysis of thermal parameter changes in each stack, this method is difficult to calculate quickly. Furthermore, when the IGBT is under dynamic conditions, its state constantly changes, making it difficult to efficiently and accurately assess the IGBT's aging state in real time. Summary of the Invention

[0003] This invention provides an IGBT aging monitoring method, device, and electronic device to address the current lack of a method that can quickly and accurately identify the aging status of IGBTs.

[0004] In a first aspect, the present invention provides an IGBT aging monitoring method, comprising: acquiring a pre-established first junction temperature expression, a first case temperature expression, and a model parameter conversion model for the IGBT to be monitored; the first junction temperature expression is used to characterize the relationship between the time constant, the initial junction temperature coefficient, and the junction temperature of the fourth-order Foster thermal network model of the IGBT to be monitored; the first case temperature expression is used to characterize the relationship between the time constant, the initial case temperature coefficient, and the case temperature of the IGBT to be monitored; the model parameter conversion model is used to characterize the correspondence between the model parameters of the fourth-order Cauer thermal network model of the IGBT to be monitored and the time constant, the initial junction temperature coefficient, and the initial case temperature coefficient; acquiring the measured junction temperature, the measured case temperature, and the initial values ​​of the model parameters of the fourth-order Cauer thermal network model of the IGBT to be monitored; fitting the first junction temperature expression with the measured junction temperature to obtain the initial junction temperature coefficient and the time constant; iteratively updating the initial values ​​of the model parameters within a preset range, and inputting the initial junction temperature coefficient, the time constant, and the updated model parameters into the model parameter conversion model to obtain the initial case temperature coefficient corresponding to different values ​​of the model parameters; Different values ​​of the model parameters and the corresponding initial shell temperature coefficients are input into the first shell temperature expression to obtain the shell temperature corresponding to different values ​​of the model parameters; the aging state of the material layer in the IGBT to be monitored is evaluated based on the value of the model parameter corresponding to the shell temperature that is closest to the measured shell temperature.

[0005] In one optional implementation, obtaining a pre-established first junction temperature expression, first case temperature expression, and model parameter conversion model for the IGBT to be monitored includes: constructing a fourth-order Cauer thermal network model of the IGBT to be monitored, and a fourth-order Foster thermal network model equivalent to the fourth-order Cauer thermal network model; constructing the first junction temperature expression and the first case temperature expression based on the zero-state response expression of the fourth-order Foster thermal network model; constructing a second junction temperature expression and a second case temperature expression based on the zero-state response expression of the fourth-order Cauer thermal network model, wherein the second junction temperature expression is used to characterize the relationship between the model parameters of the fourth-order Cauer thermal network model and the junction temperature of the IGBT to be monitored; the second case temperature expression is used to characterize the relationship between the model parameters of the fourth-order Cauer thermal network model and the case temperature of the IGBT to be monitored; and determining the model parameter conversion model based on the first junction temperature expression, the first case temperature expression, the second junction temperature expression, and the second case temperature expression.

[0006] In one optional implementation, in the next aging condition assessment cycle, the model parameter value corresponding to the shell temperature closest to the measured shell temperature is used as the initial value of the model parameter of the fourth-order Cauer thermal network model, and the steps of obtaining the measured junction temperature, measured shell temperature and the initial value of the model parameter of the fourth-order Cauer thermal network model of the IGBT to be monitored are returned to evaluate the aging condition of the IGBT to be monitored.

[0007] In one optional implementation, if this is the first assessment of the aging state of the IGBT to be monitored, the step of obtaining the initial values ​​of the model parameters of the fourth-order Cauer thermal network model includes: obtaining the initial junction temperature of the IGBT to be monitored during steady-state operation; fitting the first junction temperature expression with the initial junction temperature to obtain the initial junction temperature coefficients and time constant during the steady-state operation of the IGBT to be monitored; calculating the parameter values ​​of the model parameters of the fourth-order Foster thermal network model based on the initial junction temperature coefficients, time constant, and power loss generated during the steady-state operation of the IGBT to be monitored; and converting the model parameters of the fourth-order Foster thermal network model into the initial values ​​of the model parameters of the fourth-order Cauer thermal network model.

[0008] In one optional implementation, the aging state of the material layer in the IGBT to be monitored is evaluated based on the value of the model parameter corresponding to the shell temperature closest to the measured shell temperature. This includes: determining the mapping relationship between the model parameters of the fourth-order Cauer thermal network model and each material layer in the IGBT to be monitored; if the value of the model parameter corresponding to any material layer reaches the limit range boundary in two consecutive aging state evaluation cycles, the aging trend of the material layer is determined to be abnormal.

[0009] In one alternative implementation, the first junction temperature is expressed as:

[0010] in, β 1. β 3. β 5. β 7 represents the initial junction temperature coefficients for each order in the fourth-order Foster thermal network model. β 2. β 4. β 6. β 8 represents the time constants for each order in the fourth-order Foster thermal network model. T J (t) This is the junction temperature sequence of the IGBT to be monitored at different times within the time window, where t is the length of the time window; The expression for the first shell temperature is:

[0011] in, β 9. β 10 , β 11 , β 12These are the initial shell temperature coefficients for each order in the fourth-order Foster thermal network model. β 2. β 4. β 6. β 8 represents the time constants for each order in the fourth-order Foster thermal network model. T J This represents the shell temperature sequence of the IGBT to be monitored at different times within the time window, where t is the length of the time window.

[0012] In one alternative implementation, the second junction temperature is expressed as:

[0013] The expression for the second shell temperature is:

[0014] in, T J (t) This is the junction temperature sequence of the IGBT to be monitored at different times within the time window. T c3 (t) This is a sequence of the shell temperature of the IGBT to be monitored at different times within a time window, where,

[0015] R c1 R c4 and C c1 C c4 These represent the thermal resistance and thermal capacity parameters of different orders in the fourth-order Cauer thermal network model.

[0016] In one optional implementation, the model parameter transformation model is as follows:

[0017] in, β 1. β 3. β 5. β 7 represents the initial junction temperature coefficients for each order in the fourth-order Foster thermal network model. β 9. β 10 , β 11 , β 12 These are the initial shell temperature coefficients for each order in the fourth-order Foster thermal network model. β2. β 4. β 6. β 8 represents the time constants for each order in the fourth-order Foster thermal network model.

[0018] Secondly, the present invention provides an IGBT aging monitoring device, comprising: a model acquisition module, used to acquire a pre-established first junction temperature expression, a first case temperature expression, and a model parameter conversion model of the IGBT to be monitored; the first junction temperature expression is used to characterize the relationship between the time constant, the initial junction temperature coefficients of the fourth-order Foster thermal network model of the IGBT to be monitored, and the junction temperature of the IGBT to be monitored; the first case temperature expression is used to characterize the relationship between the time constant, the initial case temperature coefficients, and the case temperature of the IGBT to be monitored; the model parameter conversion model is used to characterize the relationship between the time constant, the initial case temperature coefficients, and the case temperature of the fourth-order Cauer thermal network model of the IGBT to be monitored. The system includes the following modules: a model parameter and time constant, junction temperature initial value coefficient, and shell temperature initial value coefficient; a data acquisition module for acquiring the measured junction temperature, measured shell temperature, and initial values ​​of the model parameters of the fourth-order Cauer thermal network model of the IGBT to be monitored; a coefficient calculation module for fitting the first junction temperature expression with the measured junction temperature to obtain the initial value coefficient and time constant; a coefficient optimization module for iteratively updating the initial values ​​of the model parameters within a preset range, and inputting the junction temperature initial value coefficient, time constant, and updated model parameters into the model parameter conversion model to obtain the shell temperature initial value coefficient corresponding to different values ​​of the model parameters; a shell temperature calculation module for inputting different values ​​of the model parameters and the corresponding shell temperature initial value coefficient into the first shell temperature expression to obtain the shell temperature corresponding to different values ​​of the model parameters; and an aging assessment module for assessing the aging state of the material layer in the IGBT to be monitored based on the model parameter value corresponding to the shell temperature closest to the measured shell temperature.

[0019] Thirdly, the present invention provides an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the IGBT aging monitoring method of the first aspect or any corresponding embodiment described above. Attached Figure Description

[0020] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0021] Figure 1 This is a schematic diagram of an application scenario according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of the IGBT to be monitored according to an embodiment of the present invention; Figure 3 This is a topology diagram of a fourth-order Cauer thermal network model constructed according to an embodiment of the present invention; Figure 4 This is a topology diagram of a fourth-order Foster thermal network model constructed from the IGBT to be monitored according to an embodiment of the present invention; Figure 5 This is a flowchart illustrating the IGBT aging monitoring method according to an embodiment of the present invention; Figure 6 This is a schematic diagram of the Miller voltage measurement principle according to an embodiment of the present invention; Figure 7 This is a schematic diagram of a heat sink surface temperature measuring device according to an embodiment of the present invention; Figure 8 This is a schematic diagram of a junction temperature and case temperature measurement system according to an embodiment of the present invention; Figure 9 This is a topology diagram of an inverter system according to an embodiment of the present invention; Figure 10 This is a schematic diagram of the current loop in the inverter system according to an embodiment of the present invention, where VT4 is the IGBT to be monitored and VT5 is the constant current control device. Figure 11 This is a schematic diagram of the current loop in the inverter system according to an embodiment of the present invention, where VT5 is the IGBT to be monitored and VT4 is the constant current control device. Figure 12 This is a structural block diagram of an IGBT aging monitoring device according to an embodiment of the present invention; Figure 13 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0024] As an optional application scenario of this invention, such as Figure 1 As shown, the system may include at least one terminal device and at least one server. Figure 1 The system is illustrated in the example, which includes a computer 101, a mobile terminal 102, and a server 103, and the terminal devices such as the computer 101 and the mobile terminal 102 are connected to the server 103 through a network 110.

[0025] Specifically, the terminal device can be a smartphone, tablet, laptop, PDA, desktop computer, game console, smart TV, smart wearable device, in-vehicle terminal, VR (Virtual Reality) device, AR (Augmented Reality) device, etc. Server 103 can be a standalone physical server, a server cluster, a distributed system, or a cloud server providing cloud services. Network 110 can be a wired or wireless network, examples of which include, but are not limited to, the Internet, corporate intranet, local area network, wide area network, mobile communication network, and combinations thereof.

[0026] According to an embodiment of the present invention, an embodiment of an IGBT aging monitoring method is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0027] As the mainstream semiconductor power device in converter systems, IGBTs are generally monitored for aging by identifying fourth-order thermal network model parameters and establishing a unique mapping between these parameters and the IGBT's multilayer solder and thermal conductive materials. For example... Figure 2 As shown, the IGBT to be monitored includes, from bottom to top, a heat sink, a thermally conductive material, a substrate solder layer, a lower copper layer, a ceramic layer, an upper copper layer, a chip solder layer, and an IGBT chip.

[0028] The topology diagram of the fourth-order Cauer thermal network model constructed based on the IGBT to be monitored is as follows: Figure 3 As shown, where, P loss (t) The power loss generated on the IGBT chip, R c1 R c4 and C c1 Cc4 These represent the thermal resistance and heat capacity parameters at different orders in the fourth-order Cauer thermal network model. T j (t) This is the junction temperature of the IGBT, which is the highest temperature of the chip under test. T h (t) The IGBT case temperature refers to the surface temperature of the heat sink directly beneath the chip being tested within the IGBT module. T 1c (t) , T 2c (t) These represent the temperatures of different intermediate layers in a fourth-order Cauer thermal network model.

[0029] In an optional embodiment, the mapping relationship between the thermal resistance parameters in the fourth-order Cauer thermal network model and the material layers in the IGBT to be monitored is shown in Table 1 below: Table 1: Mapping relationship between thermal resistance parameters and material layers

[0030] The fourth-order Foster thermal network model, which is equivalent to the fourth-order Cauer thermal network model, is as follows: Figure 4 As shown, where, P loss (t) This refers to the power loss generated on the IGBT chip. R 1 R 4 and C 1 C 4 represent the thermal resistance and heat capacity parameters of different orders in the fourth-order Foster thermal network model, respectively. T j (t) This is the junction temperature of the IGBT, which is the highest temperature of the chip under test. T 1f ( t ) -T 3f ( t ) represents the temperature of each intermediate layer in the fourth-order Foster thermal network model.

[0031] This embodiment provides an IGBT aging monitoring method, which combines the aforementioned fourth-order Foster thermal network model and fourth-order Cauer thermal network model to evaluate the aging state of the IGBT. Figure 5 This is a flowchart of an IGBT aging monitoring method according to an embodiment of the present invention, such as... Figure 5 As shown, the process includes the following steps: Step S501: Obtain the pre-established first junction temperature expression, first shell temperature expression, and model parameter conversion model of the IGBT to be monitored; the first junction temperature expression is used to characterize the relationship between the time constant, the initial junction temperature coefficient, and the junction temperature of the fourth-order Foster thermal network model of the IGBT to be monitored; the first shell temperature expression is used to characterize the relationship between the time constant, the initial shell temperature coefficient, and the shell temperature of the IGBT to be monitored; the model parameter conversion model is used to characterize the correspondence between the model parameters of the fourth-order Cauer thermal network model of the IGBT to be monitored and the time constant, the initial junction temperature coefficient, and the initial shell temperature coefficient.

[0032] In an optional embodiment, the first junction temperature expression and the first shell temperature expression are constructed based on the zero-state response expression of the fourth-order Foster thermal network model, which is used to characterize the process of the IGBT under monitoring entering cooling from thermal steady-state conditions.

[0033] In an optional embodiment, considering that device thermal aging is a slow process and that each operation of the converter is short with negligible changes, the cooling process can completely eliminate the complex calculations and identification errors caused by time-varying power losses. This process can be used as part of the power-on self-test procedure during traction system startup. The cooling process implies no power loss; for the time-domain response analysis of the RC circuit, it is essentially the zero-state response of a fourth-order Foster thermal network model, which can be expressed as:

[0034] Where C1-C4 represent the first heat capacity parameters of each order in the fourth-order Foster thermal network model, and R1-R4 represent the first thermal resistance parameters of each order in the fourth-order Foster thermal network model. T J , T 1. T 2. T The expression for 3 is:

[0035] in, T j This refers to the junction temperature of the IGBT. T 1f ( t ) -T 3f ( t () represents the temperature of each intermediate layer in the fourth-order Foster thermal network model. T a The ambient temperature.

[0036] The solution to the zero-state response expression of the fourth-order Foster thermal network model depends on the initial state of the equation. Let... k 1 k 4 is the initial value coefficient, and its physical meaning is: in the initial state, the temperature difference across the thermal resistance in each order RC structure can be defined as:

[0037] Therefore, the expressions for the junction temperature, initial coefficients, and time constant of the fourth-order Foster thermal network model of the IGBT to be monitored are obtained as follows: , in, τ 1 -τ 4 represents the time constants for each order in the fourth-order Foster thermal network model. k 1 -k 4 represents the initial value coefficients for each order in the fourth-order Foster thermal network model, and t represents the length of the time window. T J (t) This is the junction temperature sequence of the IGBT to be monitored at different times within the time window.

[0038] Because the Cauer model can be converted to the Foster model for fast computation, and the analytical expressions of the differential equations derived from the Foster model can be easily solved, the Cauer and Foster models... T J The expressions are completely equivalent. By redefining the unknown coefficients in the above expressions, we can obtain the first junction temperature expression as follows:

[0039] in, β 1. β 3. β 5. β 7 represents the initial junction temperature coefficients for each order in the fourth-order Foster thermal network model. β 2. β 4. β 6. β 8 represents the time constants for each order in the fourth-order Foster thermal network model. T J (t) This represents the junction temperature sequence of the IGBT to be monitored at different times within the time window, where t is the length of the time window.

[0040] The first expression for the shell temperature of the IGBT to be monitored, the initial shell temperature coefficient, and the time constant of the fourth-order Foster thermal network model is as follows:

[0041] in, β 9. β 10 , β 11 , β 12 These are the initial shell temperature coefficients for each order in the fourth-order Foster thermal network model. β 2. β 4. β 6. β 8 represents the time constants for each order in the fourth-order Foster thermal network model. T J This represents the shell temperature sequence of the IGBT to be monitored at different times within the time window, where t is the length of the time window.

[0042] In an optional embodiment, a second junction temperature expression and a second shell temperature expression can be constructed based on the zero-state response expression of the fourth-order Cauer thermal network model. The second junction temperature expression is used to characterize the relationship between the model parameters of the fourth-order Cauer thermal network model and the junction temperature of the IGBT to be monitored; the second shell temperature expression is used to characterize the relationship between the model parameters of the fourth-order Cauer thermal network model and the shell temperature of the IGBT to be monitored.

[0043] The zero-state response of the fourth-order Cauer thermal network model can be expressed as:

[0044] in, R c1 R c4 and C c1 C c4 These represent the RC network parameters of the fourth-order Cauer model. T J The definition and physical meaning are exactly the same as in the Foster model, but because the Cauer model can correspond to actual physical materials, therefore... T c1 , T c2 and T c3 The value of has a practical physical meaning, and its expression is:

[0045] in, T 1c, T 2c and T h These represent the temperatures of the intermediate layers in the Cauer model. T c3 This is the difference between the surface temperature of the radiator and the ambient temperature. T h Accurate data can be obtained by placing thermocouples on the heat sink.

[0046] The second junction temperature expression, obtained by solving the above zero-state response expression, characterizes the relationship between the model parameters of the fourth-order Cauer thermal network model and the junction temperature of the IGBT to be monitored. , The second shell temperature expression, obtained by solving the above zero-state response expression, characterizing the relationship between the model parameters of the fourth-order Cauer thermal network model and the shell temperature of the IGBT to be monitored, is as follows:

[0047] in, T J (t) This is the junction temperature sequence of the IGBT to be monitored at different times within the time window. T c3 (t) This is a sequence of the shell temperature of the IGBT to be monitored at different times within a time window, where,

[0048] R c1 R c4 and C c1 C c4 These represent the thermal resistance and thermal capacity parameters of different orders in the fourth-order Cauer thermal network model.

[0049] Substituting the first junction temperature expression and the first case temperature expression into the second junction temperature expression and the second case temperature expression, we can obtain:

[0050]

[0051] Since coefficients of the same power are equal, the coefficients can be written in matrix form as follows:

[0052] The above formula yields the model parameter transformation model, which represents the relationship between the model parameters of the fourth-order Cauer thermal network model used to characterize the IGBT under monitoring and the time constant, junction temperature initial coefficient, and shell temperature initial coefficient:

[0053] .

[0054] Step S502: Obtain the initial values ​​of the measured junction temperature, measured case temperature, and model parameters of the fourth-order Cauer thermal network model for the IGBT to be monitored.

[0055] In an alternative embodiment, due to the junction temperature T of the IGBT j Miller voltage V during the opening process GP It has extremely high correlation and linearity, therefore it can be derived from V GP The junction temperature for measuring Miller voltage is determined by the following circuit: Figure 6 As shown.

[0056] In an optional embodiment, the case temperature in this embodiment of the invention can be the surface temperature of the heat sink, which is measured by a thermocouple. The layout is shown in Figure 7, where the thermocouple is embedded between the thermally conductive material directly below the chip and the surface of the heat sink.

[0057] The measurement system for the two key parameters, junction temperature and shell temperature, is as follows: Figure 8 As shown, the measurements of Miller voltage and thermocouple sensors are sampled by the ADC, processed by the FPGA, and sent to the host computer. By configuring the numerical relationship between key parameters and the measured parameters on the host computer, all the required parameters for the following method can be accurately obtained.

[0058] Step S503: Fit the first junction temperature expression to the measured junction temperature to obtain the initial junction temperature coefficient and time constant.

[0059] In an optional embodiment, a nonlinear least squares regression operation can be used to fit the first junction temperature expression to obtain the initial junction temperature coefficients and the time constant.

[0060] In an optional embodiment, although the measured junction temperature and measured case temperature are obtained in step S502, and the first junction temperature expression and the first case temperature expression are obtained in step S501, considering that the junction temperature rise and measurement accuracy are both high, the fitting result is relatively accurate, while the case temperature is low and the noise is large, so the fitting result obtained by fitting it has a large deviation. Therefore, in this embodiment of the invention, the first junction temperature expression is used to fit and obtain the initial value coefficient of the junction temperature and the time constant. The initial value coefficient of the case temperature in the first case temperature expression is determined by the following steps.

[0061] Step S504: Iteratively update the initial values ​​of the model parameters within a preset range, and input the initial junction temperature coefficient, time constant, and updated model parameters into the model parameter conversion model to obtain the initial shell temperature coefficients corresponding to different values ​​of the model parameters.

[0062] In an optional embodiment, considering the measurement error and the changing trend of the IGBT to be monitored, the model parameters of the fourth-order Cauer thermal network model should fluctuate within a reasonable range. Therefore, in this embodiment of the invention, a preset range is set around the initial value, and the value of the model parameter is continuously adjusted within the preset range. By inputting the value of the model parameter, the initial value coefficient of the junction temperature and the time constant into the model parameter conversion model, the initial value coefficient of the shell temperature corresponding to different values ​​of the model parameter can be obtained.

[0063] Step S505: Input the different values ​​of the model parameters and the corresponding initial shell temperature coefficients into the first shell temperature expression to obtain the shell temperature corresponding to the different values ​​of the model parameters.

[0064] In an optional embodiment, the aging process of the thermal network model parameters is slow, and the parameter changes are relatively small. Therefore, the optimal value can be selected using an exhaustive method based on the initial value range. According to the above model parameter transformation model, parameter β9... β 12 Calculation and C c3 It is irrelevant; in this embodiment of the invention, only the thermal resistance in the thermal network parameters is considered, and parameter C is ignored. c3 The change in R can significantly reduce the computational cost of iterations. The optimization parameter is R. c1 R c3 and C c1 C c2 .

[0065] Step S506: Evaluate the aging state of the material layer in the IGBT to be monitored based on the values ​​of the model parameters corresponding to the shell temperature closest to the measured shell temperature.

[0066] In an optional embodiment, the sum of squared residuals between the shell temperature and the measured shell temperature corresponding to different values ​​of the model parameters can be calculated. The model parameters corresponding to the shell temperature with the smallest sum of squared residuals are determined as the parameter identification results of the fourth-order Cauer thermal network model. The aging state of the material layer in the IGBT to be monitored is evaluated based on the parameter identification results.

[0067] In an optional embodiment, since the fourth-order Cauer thermal network model can describe the actual distribution of thermal network parameters, and each parameter contains the physical properties of the material, the thermal parameter changes of each stack can be accurately analyzed. Therefore, the aging state of the material layer in the IGBT to be monitored can be evaluated through the model parameters of the fourth-order Cauer thermal network model.

[0068] The method provided in this invention first constructs the first junction temperature expression, the first case temperature expression, and the model parameter transformation model of the IGBT under monitoring using a fourth-order Foster thermal network model and a fourth-order Cauer thermal network model. Since the fourth-order Foster thermal network model can directly decompose the component into parallel or series RC circuits, it is easier to analyze and construct. Therefore, after obtaining the measured junction temperature of the IGBT at any given time, the initial junction temperature coefficients and time constant of the IGBT under monitoring can be calculated using the first junction temperature expression of the IGBT constructed using the fourth-order Foster thermal network model. The initial values ​​of the model parameters are then iteratively updated within a preset range, and the initial junction temperature coefficients, time constant, and updated... The model parameters are then input into the model parameter conversion model to obtain the initial shell temperature coefficients corresponding to different values ​​of the model parameters. Using the first shell temperature expression, the shell temperature corresponding to different values ​​of the model parameters and the initial shell temperature coefficients can be calculated. The shell temperature calculated for different values ​​of the model parameters is compared with the measured shell temperature to find the model parameter value that is closest to the actual value. At this time, the aging state of the material layer in the IGBT to be monitored can be evaluated through the model parameter values. In this embodiment of the invention, the method only needs to obtain the model parameter values ​​of the current fourth-order Foster thermal network model based on the real-time collected junction temperature, shell temperature, and initial values ​​of the model parameters, which has flexible application scenarios.

[0069] In an optional embodiment, the method provided by the present invention periodically monitors the IGBT to be monitored and evaluates its aging. After executing the above step S505, in the next aging state evaluation cycle, the value of the model parameter corresponding to the shell temperature closest to the measured shell temperature is used as the initial value of the model parameter of the fourth-order Cauer thermal network model, and the above steps S502-S505 are repeated to evaluate the aging state of the IGBT to be monitored.

[0070] In an optional embodiment, if this is the first time the aging state of the IGBT to be monitored is being assessed, the step of obtaining the initial values ​​of the model parameters of the fourth-order Cauer thermal network model includes: Step a1: Obtain the initial junction temperature of the IGBT under monitoring during its steady-state operation.

[0071] Step a2: Fit the first junction temperature expression to the initial junction temperature to obtain the initial junction temperature coefficient and time constant during the steady-state operation of the IGBT to be monitored.

[0072] In one optional embodiment, steady-state operation refers to the generation of constant power loss on the IGBT and the attainment of a thermal equilibrium state, i.e., the temperature of the IGBT remains constant under constant power loss conditions. The IGBT is not in steady-state condition when operating in the inverter system; it is in steady-state condition during system startup self-test and shutdown maintenance.

[0073] In an optional embodiment, to ensure that certain devices in the inverter system are in a steady state during power-on self-test and shutdown maintenance, the following method can be used: like Figure 9 As shown, current paths of the same color form a closed loop. When the inverter system is shut down, two IGBTs on adjacent phases but different arms form a circuit similar to a DC-DC converter. Utilizing the existing inverter topology, the two-phase stator of the motor acts as an inductive load, forming a constant current loop without generating a rotating magnetic field. For example, using... Figure 9 Taking the current loop formed by VT4 and VT5 as an example, when VT4 is the IGBT to be monitored, VT5 will act as a constant current control device and enter high-frequency switching mode, such as... Figure 10 As shown, when VT The duty cycle of 5 is D u At that time, according to the volt-second equilibrium principle, under steady-state conditions, we have:

[0074] The average current can be calculated using the above formula. Ic for:

[0075] The switching frequency can be selected according to the ripple requirements. VT 4. Constant current operating mode. Similarly, when VT 5 is used as the IGBT to be monitored. VT 4 will function as a constant current control device and enter high-frequency switching mode, such as... Figure 11As shown. Although the freewheeling paths are different, the expressions and results are the same. The constant current is the same under both measurement conditions, which can be selected according to the duty cycle and actual input and load conditions. Current closed-loop control can also be added to adapt to any operating condition and ensure constant current. Under constant current conditions, power losses on the IGBTs cause the devices to heat up rapidly. When the cooling system is working normally, the module will enter a thermally stable state within a few minutes, after which both IGBTs will be simultaneously turned off to enter the cooling process. This process can be used as part of the power-on self-test procedure for traction system startup or as part of the shutdown maintenance procedure.

[0076] Step a3: Calculate the parameter values ​​of the fourth-order Foster thermal network model based on the initial junction temperature coefficient, time constant, and power loss generated during the steady-state operation of the IGBT to be monitored.

[0077] Step a4: Convert the model parameters of the fourth-order Foster thermal network model into the initial values ​​of the model parameters of the fourth-order Cauer thermal network model.

[0078] In an optional embodiment, the initial values ​​in the zero-state response expression of the above fourth-order Foster thermal network model are determined by the initial values ​​of the last heating process before cooling, the losses, and the time, due to the power loss P under steady-state conditions. loss Since the initial temperature is a constant, the following formulas can be used to characterize the initial temperature of different intermediate layers:

[0079]

[0080]

[0081]

[0082] in, k 10 k 40 The initial value is the temperature rise caused by power loss on the IGBT to be monitored. τ heat Let the duration of the heating process be denoted as . Substituting the above formula into the zero-state response expression, we obtain the following expression:

[0083] From the above equation, we can see that the four initial value coefficients k 1 k 4 does not form a simple proportional relationship with the thermal resistance parameter, but if the heating time is long enough (exceeding 5 times the maximum value of the time constant), then:

[0084] From the above equation, it can be seen that solving the zero-state response expression of the fourth-order Foster thermal network model yields the functional relationship between the junction temperature of the IGBT to be monitored, the initial coefficients, and the time constant of the fourth-order Foster thermal network model. Among these, the four coefficients... k 1 k Essentially, the initial temperature difference across the four thermal resistances in a fourth-order Foster thermal network model under steady-state conditions is the initial temperature difference across the thermal resistances. Under a steady-state measurement strategy, according to Ohm's law, the initial temperature difference across the thermal resistances should be the product of the power loss and the corresponding thermal resistance value under steady-state operation. Therefore, this method is limited to steady-state conditions.

[0085] The coefficients derived from the above formula k 1 k 4. Regarding the relationship with power loss, after obtaining the initial coefficients and time constant through fitting in step a2 above, the first thermal resistance parameter and the first heat capacity parameter of the fourth-order Foster thermal network model can be calculated in step a3 using the following formula:

[0086] .

[0087] After obtaining the first thermal resistance parameter and the first thermal capacity parameter of the fourth-order Foster thermal network model using the above method, the first thermal resistance parameter and the first thermal capacity parameter can be converted into the second thermal resistance parameter and the second thermal capacity parameter in the model parameters of the fourth-order Cauer thermal network model using any correlation method.

[0088] Since the methods described in steps a1-a4 are only applicable to obtaining model parameters under steady-state conditions, and steps S501-S505 do not limit the IGBT to be monitored to steady-state conditions, steps a1-a4 cannot replace steps S501-S505 in obtaining model parameters of a fourth-order Cauer thermal network model under arbitrary conditions.

[0089] In an optional embodiment, in step S505 above, when evaluating the aging state of the material layer in the IGBT to be monitored based on the value of the model parameter corresponding to the shell temperature closest to the measured shell temperature, the mapping relationship between the model parameters of the fourth-order Cauer thermal network model and each material layer in the IGBT to be monitored is first determined. If the value of the model parameter corresponding to any material layer reaches the limit range boundary in two consecutive aging state evaluation cycles, the aging trend of the material layer is determined to be abnormal.

[0090] This embodiment also provides an IGBT aging monitoring device, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0091] This embodiment provides an IGBT aging monitoring device, such as... Figure 12 As shown, it includes: The model acquisition module 121 is used to acquire the pre-established first junction temperature expression, first shell temperature expression, and model parameter conversion model of the IGBT to be monitored. The first junction temperature expression is used to characterize the relationship between the time constant, the initial junction temperature coefficient, and the junction temperature of the fourth-order Foster thermal network model of the IGBT to be monitored. The first shell temperature expression is used to characterize the relationship between the time constant, the initial shell temperature coefficient, and the shell temperature of the IGBT to be monitored. The model parameter conversion model is used to characterize the correspondence between the model parameters of the fourth-order Cauer thermal network model of the IGBT to be monitored and the time constant, the initial junction temperature coefficient, and the initial shell temperature coefficient. The data acquisition module 122 is used to acquire the measured junction temperature, measured shell temperature, and initial values ​​of the model parameters of the fourth-order Cauer thermal network model of the IGBT to be monitored. The coefficient calculation module 123 is used to fit the first junction temperature expression with the measured junction temperature to obtain the initial junction temperature coefficient and time constant; The coefficient optimization module 124 is used to iteratively update the initial values ​​of the model parameters within a preset range, and input the initial junction temperature coefficients, time constants and updated model parameters into the model parameter conversion model to obtain the initial shell temperature coefficients corresponding to different values ​​of the model parameters. The shell temperature calculation module 125 inputs different values ​​of the model parameters and the corresponding initial shell temperature coefficients into the first shell temperature expression to obtain the shell temperature corresponding to different values ​​of the model parameters. The aging assessment module 126 is used to assess the aging state of the material layer in the IGBT to be monitored based on the values ​​of the model parameters corresponding to the shell temperature closest to the measured shell temperature.

[0092] The IGBT aging monitoring device provided in this embodiment of the invention can execute the IGBT aging monitoring method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for executing the method. Further functional descriptions of the various modules and units described above are the same as in the corresponding embodiments described above, and will not be repeated here.

[0093] Figure 13 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0094] The following is a detailed reference. Figure 13 The diagram illustrates a structural schematic suitable for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor (e.g., a central processing unit, a graphics processing unit, etc.) 131, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 132 or a program loaded from memory 138 into random access memory (RAM) 133. The RAM 133 also stores various programs and data required for the operation of the electronic device. The processor 131, ROM 132, and RAM 133 are interconnected via a bus 134. An input / output (I / O) interface 135 is also connected to the bus 134.

[0095] Typically, the following devices can be connected to I / O interface 135: input devices 136 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 137 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 138 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1313. Communication device 1313 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 13 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0096] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication device 1313, or installed from memory 138, or installed from ROM 132. When the computer program is executed by processor 131, it performs the functions defined in the IGBT aging monitoring method of the embodiments of the present invention.

[0097] Figure 13 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0098] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the IGBT aging monitoring method shown in the above embodiments is implemented.

[0099] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0100] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for monitoring IGBT aging, characterized in that, The method includes: Obtain the pre-established first junction temperature expression, first shell temperature expression, and model parameter conversion model of the IGBT to be monitored; the first junction temperature expression is used to characterize the relationship between the time constant, the initial junction temperature coefficient, and the junction temperature of the fourth-order Foster thermal network model of the IGBT to be monitored; the first shell temperature expression is used to characterize the relationship between the time constant, the initial shell temperature coefficient, and the shell temperature of the IGBT to be monitored; the model parameter conversion model is used to characterize the correspondence between the model parameters of the fourth-order Cauer thermal network model of the IGBT to be monitored and the time constant, the initial junction temperature coefficient, and the initial shell temperature coefficient; Obtain the initial values ​​of the measured junction temperature, measured case temperature, and model parameters of the fourth-order Cauer thermal network model for the IGBT to be monitored. By fitting the first junction temperature expression with the measured junction temperature, the initial junction temperature coefficients and time constant are obtained; The initial values ​​of the model parameters are iteratively updated within a preset range, and the initial junction temperature coefficient, time constant, and updated model parameters are input into the model parameter conversion model to obtain the initial shell temperature coefficients corresponding to different values ​​of the model parameters. By inputting different values ​​of the model parameters and the corresponding initial shell temperature coefficients into the first shell temperature expression, the shell temperature corresponding to different values ​​of the model parameters is obtained. The aging state of the material layer in the IGBT to be monitored is evaluated based on the values ​​of the model parameters corresponding to the shell temperature closest to the measured shell temperature.

2. The method according to claim 1, characterized in that, The process of obtaining the pre-established first junction temperature expression, first case temperature expression, and model parameter transformation model of the IGBT to be monitored includes: Construct a fourth-order Cauer thermal network model of the IGBT to be monitored, and a fourth-order Foster thermal network model that is equivalent to the fourth-order Cauer thermal network model. The first junction temperature expression and the first shell temperature expression are constructed based on the zero-state response expression of the fourth-order Foster thermal network model. Based on the zero-state response expression of the fourth-order Cauer thermal network model, a second junction temperature expression and a second shell temperature expression are constructed. The second junction temperature expression is used to characterize the relationship between the model parameters of the fourth-order Cauer thermal network model and the junction temperature of the IGBT to be monitored; the second shell temperature expression is used to characterize the relationship between the model parameters of the fourth-order Cauer thermal network model and the shell temperature of the IGBT to be monitored. The model parameters are determined and the model is transformed based on the first junction temperature expression, the first shell temperature expression, the second junction temperature expression, and the second shell temperature expression.

3. The method according to claim 1, characterized in that, Also includes: In the next aging condition assessment cycle, the model parameter value corresponding to the shell temperature closest to the measured shell temperature is used as the initial value of the model parameter of the fourth-order Cauer thermal network model. The steps of obtaining the measured junction temperature, measured shell temperature and the initial value of the model parameter of the fourth-order Cauer thermal network model of the IGBT to be monitored are returned to evaluate the aging condition of the IGBT to be monitored.

4. The method according to claim 1, characterized in that, If this is the first assessment of the aging state of the IGBT to be monitored, the steps for obtaining the initial values ​​of the model parameters of the fourth-order Cauer thermal network model include: The initial junction temperature of the IGBT under monitoring is obtained during its steady-state operation. By fitting the first junction temperature expression with the initial junction temperature, the initial junction temperature coefficient and time constant during the steady-state operation of the IGBT to be monitored are obtained; The parameter values ​​of the model parameters of the fourth-order Foster thermal network model are calculated based on the initial junction temperature coefficient, time constant, and power loss generated during the steady-state operation of the IGBT under monitoring. The model parameters of the fourth-order Foster thermal network model are equivalently converted to the initial values ​​of the model parameters of the fourth-order Cauer thermal network model.

5. The method according to claim 3, characterized in that, The evaluation of the aging state of the material layer in the IGBT to be monitored based on the values ​​of the model parameters corresponding to the shell temperature closest to the measured shell temperature includes: Determine the mapping relationship between the model parameters of the fourth-order Cauer thermal network model and each material layer in the IGBT to be monitored; If the model parameter corresponding to any material layer reaches the limit range boundary in two consecutive aging state assessment cycles, the aging trend of the material layer is determined to be abnormal.

6. The method according to claim 1 or 2, characterized in that, The first junction temperature expression is: in, β 1. β 3. β 5. β 7 represents the initial junction temperature coefficients for each order in the fourth-order Foster thermal network model. β 2. β 4. β 6. β 8 represents the time constants for each order in the fourth-order Foster thermal network model. T J (t) This is the junction temperature sequence of the IGBT to be monitored at different times within the time window, where t is the length of the time window; The first shell temperature expression is: in, β 9. β 10 , β 11 , β 12 These are the initial shell temperature coefficients for each order in the fourth-order Foster thermal network model. β 2. β 4. β 6. β 8 represents the time constants for each order in the fourth-order Foster thermal network model. T J This represents the shell temperature sequence of the IGBT to be monitored at different times within the time window, where t is the length of the time window.

7. The method according to claim 2, characterized in that, The second junction temperature expression is: The second shell temperature expression is: in, T J (t) This is the junction temperature sequence of the IGBT to be monitored at different times within the time window. T c3 (t) This is a sequence of the shell temperature of the IGBT to be monitored at different times within a time window, where, R c1 R c4 and C c1 C c4 These represent the thermal resistance and thermal capacity parameters of different orders in the fourth-order Cauer thermal network model.

8. The method according to claim 7, characterized in that, The model parameter conversion model is as follows: in, β 1. β 3. β 5. β 7 represents the initial junction temperature coefficients for each order in the fourth-order Foster thermal network model. β 9. β 10 , β 11 , β 12 These are the initial shell temperature coefficients for each order in the fourth-order Foster thermal network model. β 2. β 4. β 6. β 8 represents the time constants for each order in the fourth-order Foster thermal network model.

9. An IGBT aging monitoring device, characterized in that, The device includes: The model acquisition module is used to acquire the pre-established first junction temperature expression, first shell temperature expression, and model parameter conversion model of the IGBT to be monitored. The first junction temperature expression is used to characterize the relationship between the time constant, the initial junction temperature coefficient, and the junction temperature of the fourth-order Foster thermal network model of the IGBT to be monitored. The first shell temperature expression is used to characterize the relationship between the time constant, the initial shell temperature coefficient, and the shell temperature of the IGBT to be monitored. The model parameter conversion model is used to characterize the correspondence between the model parameters of the fourth-order Cauer thermal network model of the IGBT to be monitored and the time constant, the initial junction temperature coefficient, and the initial shell temperature coefficient. The data acquisition module is used to acquire the measured junction temperature, measured case temperature, and initial values ​​of the model parameters of the fourth-order Cauer thermal network model of the IGBT to be monitored. The coefficient calculation module is used to fit the first junction temperature expression with the measured junction temperature to obtain the initial junction temperature coefficient and the time constant; The coefficient optimization module is used to iteratively update the initial values ​​of the model parameters within a preset range, and input the initial junction temperature coefficient, time constant and updated model parameters into the model parameter conversion model to obtain the initial shell temperature coefficients corresponding to different values ​​of the model parameters. The shell temperature calculation module inputs different values ​​of the model parameters and the corresponding initial shell temperature coefficients into the first shell temperature expression to obtain the shell temperature corresponding to different values ​​of the model parameters. The aging assessment module is used to assess the aging state of the material layer in the IGBT to be monitored based on the values ​​of the model parameters corresponding to the shell temperature closest to the measured shell temperature.

10. An electronic device, characterized in that, include: The system includes a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to perform the IGBT aging monitoring method according to any one of claims 1 to 8.

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