This application claims the priority benefit of China application serial no. 201910069446.2, filed on Jan. 24, 2019. The entirety of the above-mentioned patent application is hereby incorporated by reference herein and made a part of this specification.
The invention belongs to the field of power electronics and electronic information science, and particularly relates to a method for estimating the junction temperature on-line on an IGBT power module, and uses the Kalman filter to obtain an optimal estimation value of the junction temperature.
Power converters are widely used in the fields related to smart grids, rail transit and new energy sources. Insulated gate bipolar transistors (IGBT) are the key components of power converter devices, and their reliability is the guarantee for safe operation of the system. Therefore, monitoring the condition and predicting the service life of IGBT is extremely important. There are many types of IGBT power module failure modes, and temperature is the main factor causing its failure. Therefore, thermal analysis is an important part of IGBT power module status evaluation. Real time measurement of the junction temperature of IGBT power module is of great significance for improving the reliability of the system.
Patent application number 201810036617.7 (publication number 108108573A) discloses a method for dynamically predicting the junction temperature of an IGBT power module. It calculates the junction temperature based on the method of a fixed thermal model, but cannot compensate for degradation of thermal path caused by the influence of aging and cooling conditions. Patent application number 201710334867.4 (publication number 107192934A) discloses a measurement method for the transient thermal impedance of the crust of a high-power IGBT, which uses the temperature sensitive electrical parameter method to measure the temperature drop curve of the junction temperature of the high-power IGBT during the cooling process, and also uses the thermocouple method to obtain the temperature drop curve of the IGBT shell temperature. However, the measurement error and the change of the operation conditions affect the estimated value, and failure rate of the thermocouple is high and the maintenance is difficult.
The technical problem to be solved by the present invention is to provide a method for estimating the junction temperature on-line on an IGBT power module to fix the above-mentioned deficiencies of the related art, and realizing electrical insulation without changing the control strategy of the power converter for measurement. The method of the present invention reduces noise and eliminates the intermittent effects of voltage measurements, and improves the accuracy of junction temperature measurements.
The technical solution adopted by the present invention to solve the above technical problems is:
A method for estimating junction temperature on-line on an IGBT power module includes the following steps:
Step 1: setting a full-bridge inverter circuit and a VCE(ON) on-line measuring circuit based on a power electronic simulation software Saber, connecting two input terminals of the VCE(ON) on-line measuring circuit to the collector and emitter of an IGBT of the full-bridge inverter circuit, thereby realizing the connection between the full-bridge inverter circuit and the VCE(ON) on-line measuring circuit;
Step 2: obtaining IGBT conduction voltage drop VCE(ON) for the connected full-bridge inverter circuit and the VCE(ON) on-line measuring circuit, using the temperature sensitive electrical parameter method to obtain the calibration curve and fitting relationship of IGBT conduction voltage drop VCE(ON) and an IGBT power module junction temperature Tj;
Step 3: based on the full-bridge inverter circuit set in step 1, setting the behavior model of the IGBT power module composed of an IGBT and a corresponding diode, wherein static and dynamic characteristics of the behavior model are simulated and analyzed to calculate the switching loss and conduction loss of the IGBT, reverse recovery loss and conduction loss of the diode;
Step 4: considering the coupling effect between the IGBT and the diode in the IGBT power module of step 3, and setting a thermal model of extended state space of the IGBT power module;
Step 5: setting a system model of the Kalman filter (i.e., the Kalman filter), the IGBT power module junction temperature obtained in the step 2, the switching loss and conduction loss of the IGBT obtained in the step 3, the reverse recovery loss and conduction loss of the diode obtained in the step 3 are used as filter inputs to calculate the optimal estimated value of junction temperature.
According to the above scheme, the specific method for setting the full-bridge inverter circuit in the step 1 comprises: firstly setting the sinusoidal pulse width modulation (SPWM) control circuit, setting the dead-zone time, and then setting the gate driving circuit, and the gate driving circuit is modulated by the SPWM control circuit, the input terminal of the gate driving circuit is connected to the output terminal of the SPWM control circuit, and the output terminal of the gate driving circuit is connected to the gate of the IGBT of the IGBT power module. The full-bridge inverter circuit has four bridge arms, each of the bridge arms is composed of an SPWM control circuit, a gate driving circuit, an IGBT and a diode. Then the VCE(ON) on-line measuring circuit is set, and finally the two input terminals of the VCE(ON) on-line measuring circuit are connected to the collector and emitter of the IGBT of one of the bridge arms of the full-bridge inverter circuit.
According to the above scheme, the specific method for monitoring the junction temperature on-line by the temperature sensitive electrical parameter method is as follows. First, the IGBT is placed in the incubator, and after the junction temperature of the IGBT power module is stabilized, the small current IC at 100 mA-1 A is injected into the collector of the IGBT; then the saturation conduction voltage drop VCE(ON) of IGBT is measured, the temperature of the incubator is changed, and the saturation conduction voltage drop VCE(ON) of the IGBT is repeatedly measured in the range of 20° C.-150° C., and finally the junction temperature Tj is taken as the dependent variable, and VCE(ON) is an independent variable, and the VCE(ON) is linearly fitted to obtain a fitting relationship Tj=f(VCE(ON)).
According to the above scheme, the switching loss and conduction loss of the IGBT, the reverse recovery loss and the conduction loss of the diode obtained through the calculation in the step 3 are specifically as follows.
The IGBT Level-1 Tool modeling toolbox in Saber is used to set the simulation model for the specific structure and process of the device, thereby accurately representing the static and dynamic characteristics of the device, simulating the dynamic switching process of the IGBT power module, and obtaining the voltage and current waveform of the IGBT when the IGBT is on and off, and reverse recovery voltage and current waveform of diode, and voltage and current waveforms when IGBT and diode are turned on.
The loss of the IGBT is calculated as follows:
In the above equations, Pon represents the turn-on loss of the IGBT; ton represents the turn-on time of the IGBT; vce(t) represents the collector-emitter voltage of the IGBT during turn-on; ic(t) represents the collector current of the IGBT during turn-on; Poff represents the IGBT turn-off loss; toff indicates the turn-off time of the IGBT; Pcond_I indicates the conduction loss of the IGBT; Vce(on) indicates the conduction voltage drop of the IGBT; IC indicates the conduction current of the IGBT; and δ1 indicates the duty ratio of the current operating state of the IGBT; PIGBT represents the total loss of the IGBT; t represents time.
The loss of the diode is calculated as follows:
In the above equations, Pcond_D represents the conduction loss of the diode; VF represents the conduction voltage drop of the diode; IF represents the conduction current of the diode; δD represents the duty ratio of the current operating state of the diode; Pres represents the reverse recovery loss of the diode; t represents the reverse recovery time of the diode; vf(t) represents the voltage of the diode in reverse recovery; and if(t) represents the current when the diode is in reverse recovery; t represents time.
According to the above scheme, the specific method for setting the space thermal model of extended state of the IGBT power module in the step 4 is the following.
First, the self-heating of the IGBT is simulated, and its thermal resistance is expressed by the following equation:
Zθja(t)=(Tj(t)−Ta)/PIGBT
In the above equation, Tj(t) represents the IGBT junction temperature; Ta represents the ambient temperature at which the IGBT power module is located; Zθja(t) represents the thermal resistance; PIGBT represents the total loss of the IGBT; t represents time.
The above equation is expressed by the equivalent RC network, which is replaced by the Foster thermal network model, which is an RC loop composed of N thermal resistances and N thermal capacitances connected in parallel. The time response is expressed by the following series of exponential items:
Zθja(t)=Σi=1nRi(1−e−t/R
The Laplace transform is performed on the above equation, and the thermal resistance in the frequency domain is expressed as a partial fractional form:
In the above two equations, i represents the network order of the Foster thermal network model; n represents the total network order of the Foster thermal network model; Ri represents the thermal resistance in the Foster thermal network model; Ci represents the thermal capacitances in the Foster thermal network model; ki=1/Ci; kn=1/Cn; pi=1/RiCi, pn=1/RnCn.
The state space expression for the partial fraction of the above partial fractional form is:
{dot over (x)}(t)=Ax(t)+Bu(t) (equation of state)
Tj(t)=Cx(t)+Du(t) (output equation)
Specifically, x(t) represents an n-dimensional state vector; An×n represents a system matrix of n rows and n columns, a diagonal matrix of which the main diagonal is pi; Bn×2 represents an input matrix of n rows and 2 columns with the first column is ki; Cl×n represents the output matrix of l row and n columns; D1×2 represents the feedforward matrix of 1 row and 2 columns. In addition,
represents the system input vector, wherein PD(t) represents power loss of the IGBT power module.
Considering the coupling effect of the diode, and the above state space model is extended (n-order means self-heating, extended m-order means coupling heat of diode) as follows:
Specifically, xs1, . . . , xsn represents the state of self-heating impedance, xc1, . . . , xcn represents the state of the coupling thermal impedance; PIGBT represents the power loss of the IGBT in the IGBT power module, PDIODE represents the power loss of the diode in the IGBT power module;
specifically, Rs1 . . . Rsn, Cs1 . . . Csn represent the thermal resistance thermal capacitances in the equivalent Foster thermal network model of the IGBT in the IGBT power module; Rc1 . . . Rcn, Cc1 . . . Ccn represent the thermal resistance thermal capacitances in the equivalent Foster thermal network model of the diode in the IGBT power module.
According to the above scheme, the specific method for setting the system model of the Kalman filter in the step 5 comprises the following.
A system of a discrete control process is introduced based on a space thermal model of the extended state as follows:
xk=Fxk−1+Guk+wk
Tk=Hxk+Juk+vk
In the above equation, k represents the time step; xk−1 represents the state variable, i.e., the thermal resistance of the IGBT power module, at time (k−1); xk represents the state variable, i.e., the thermal resistance of the IGBT power module, at time k; F and G respectively represent the system matrix and control matrix; uk represents the system input vector, including the IGBT power module loss and the ambient temperature of the IGBT power module; wk and vk respectively represent the process noise and measurement noise. Assuming that both are Gaussian white noise, the covariance of process noise wk and measurement noise vk are Q and R respectively; Tk represents the junction temperature observation value of IGBT power module at time k; H and J respectively represent the observation matrix and direct matrix.
The Kalman filtering algorithm flow is described as follows.
(1) Predict the thermal resistance value {circumflex over (x)}(k|k−1) of IGBT power module at time k from the optimal thermal resistance estimated value {circumflex over (x)}(k−1|k−1) of the IGBT power module at time (k−1):
{circumflex over (x)}(k|k−1)=F{circumflex over (x)}(k−1|k−1)+Guk
(2) Calculate the predicted value of the junction temperature of the IGBT power module at time k:
{circumflex over (T)}(k|k−1)=H{circumflex over (x)}(k|k−1)+Iuk
(3) Measure the covariance P(k|k−1) at time k by the covariance P(k−1|k−1) between the observed value and the predicted value of the IGBT power module junction temperature at time (k−1):
P(k|k−1)=FP(k−1|k−1)FT+Q
(4) Calculate the Kalman filter gain:
K(k)=P(k|k−1)HT[HP(k|k−1)−1HT+R]−1
Specifically, K(k) represents the Kalman filter gain.
(5) Calculate the optimal estimated value of the system:
{circumflex over (x)}(k|k)={circumflex over (x)}(k|k−1)+K(k)(Tk−{circumflex over (T)}(k|k−1))
Specifically, {circumflex over (x)}(k|k) represents the optimal estimated value of the thermal resistance of the IGBT power module at time k.
(6) Update the inverse operation of the optimal junction temperature value of the IGBT power module in the next step at time (k+1), that is, update the covariance:
P(k|k)=[I−K(k)H]P(k|k−1)
Specifically, P(k|k) represents the updated covariance after time k, and I represents the unity matrix.
(7) Return to step (1) from step (6), performing a loop until the final result achieves the desired effect.
Compared with the existing art, the advantageous effects of the present invention are:
1. The method for estimating the junction temperature on the IGBT power module provided by the present invention is implemented on a full-bridge inverter, and is simulated by the system simulation software Saber, so that the actual working condition of the IGBT can be better simulated. Further, the conduction voltage drop VCE(ON) is utilized as the temperature sensitive electrical parameter to obtain the junction temperature. The VCE(ON) on-line measuring circuit is designed, which improves the measurement accuracy and achieves electrical insulation, so that the control strategy of changing the power converter is not required to make measurements. The IGBT self-heating is utilized and the coupling heat of the diode is considered, the state space representation method of the thermal model is developed by measuring the thermal impedance of the junction to the environment to derive the Kalman filter.
2. The present invention applies a Kalman filter to estimate the obtained junction temperature Tj, and constrains the measurement signal to the thermal model by means of a predictive-corrective rewinding loop, thereby reducing noise and eliminating the intermittent effect of the measurement of VCE(ON).
3. The method of the present invention can form a part of a real-time health management or active control system for a power converter and can be easily integrated into existing power converter control elements.
The present invention will be further described below with reference to specific embodiments and the accompanying drawings.
As shown in
Step 1. Set up a full-bridge inverter circuit, a VCE(ON) on-line measuring circuit, a SPWM control circuit and a gate driving circuit in Saber, and connect the two input terminals of the VCE(ON) on-line measuring circuit to the collector and emitter of an IGBT of the full-bridge inverter, thereby implementing the connection of the full-bridge inverter circuit to the VCE(ON) on-line measuring circuit, as shown in
Specifically, step 1 in the embodiment includes the following process:
1-1. Referring to the schematic diagram showing the principle of the sinusoidal pulse width modulation shown in
1-2. Referring to the VCE(ON) on-line measuring circuit shown in
1-3,
Step 2: Obtain the IGBT conduction voltage drop VCE(ON) for the connected full-bridge inverter circuit and the VCE(ON) on-line measuring circuit, and obtain the calibration curve and fitting relationship of IGBT conduction voltage drop VCE(ON) and IGBT power module junction temperature Tj by using the temperature sensitive electrical parameter method. Firstly, the IGBT is placed in the incubator, and the small current IC (100 mA-1 A) is injected into the collector of the IGBT after the junction temperature of the IGBT power module is stabilized. Then, the saturation conduction voltage drop VCE(ON) of the IGBT is measured, and the temperature of the incubator is changed, the saturation conduction voltage drop VCE(ON) of the IGBT is repeatedly measured in the range of 20° C.-150° C. Finally the junction temperature Tj serves as the dependent variable, VCE(ON) serves as the independent variable, and the VCE(ON) is linearly fitted to obtain the fitting relationship Tj=f(VCE(ON)).
Step 3. Set up a full-bridge inverter model in Saber, set a behavior model of an IGBT power module composed of an IGBT and a corresponding diode, simulate and analyze its static and dynamic characteristics of the behavior model, and calculate the switch loss and conduction loss of the IGBT as well as reverse recovery loss and conduction loss of the diode.
The IGBT Level-1 Tool modeling toolbox in Saber is utilized to set the simulation model for the specific structure and process of the device, thereby accurately representing the static and dynamic characteristics of the device, simulating the dynamic switching process of the IGBT power module, and obtaining the voltage and current waveform of the IGBT when the IGBT is on and off, and reverse recovery voltage and current waveform of diode, and voltage and current waveforms when IGBT and diode are turned on.
The loss of the IGBT is calculated as follows:
In the above equations, Pon represents the turn-on loss of the IGBT; ton represents the turn-on time of the IGBT; vce(t) represents the collector-emitter voltage of the IGBT during turn-on; ic(t) represents the collector current of the IGBT during turn-on; Poff represents the IGBT turn-off loss; toff indicates the turn-off time of the IGBT; Pcond_I indicates the conduction loss of the IGBT; Vce(on) indicates the conduction voltage drop of the IGBT; IC indicates the conduction current of the IGBT; and δ1 indicates the duty ratio of the current operating state of the IGBT; PIGBT represents the total loss of the IGBT; t represents time.
The loss of the diode is calculated as follows:
In the above equations, Pcond_D represents the conduction loss of the diode; VF represents the conduction voltage drop of the diode; IF represents the conduction current of the diode; δD represents the duty ratio of the current operating state of the diode; Prec represents the reverse recovery loss of the diode; t represents the reverse recovery time of the diode; vf(t) represents the voltage of the diode in reverse recovery; and if(t) represents the current when the diode is in reverse recovery; t represents time.
Step 4. Consider the coupling effect between the IGBT and the diode in the IGBT power module of step 3, and set a space thermal model of extended state of the IGBT power module.
Zθja(t)=(Tj(t)−Ta)/PIGBT
In the equation, Tj(t) represents the IGBT junction temperature; Ta represents the ambient temperature at which the IGBT power module is located; Zθja(t) represents the IGBT thermal resistance; PIGBT represents the total loss of the IGBT; t represents time.
Zθja(t)=Σi=1nRi(1−e−t/R
The Laplace transform is performed on the above equation, and the thermal resistance in the frequency domain is expressed as a partial fractional form:
In the above two equations, i represents the network order of the Foster thermal network model; n represents the total network order of the Foster thermal network model; Ri represents the thermal resistance in the Foster thermal network model; Ci represents the thermal capacitances in the Foster thermal network model; t represents time; ki=1/Ci; kn=1/Cn; pi=1/RiCi, pn=1/RnCn.
The state space expression for the partial fraction of the above partial fractional form is:
Specifically, x(t) represents an n-dimensional state vector; t represents time; An×n represents a system matrix of n rows and n columns; Bn×2 represents an input matrix of n rows and 2 columns; Cl×n represents the output matrix of l row and n columns; D1×2 represents the feedforward matrix of 1 row and 2 columns. In addition,
represents the system input vector, wherein PD(t) represents power loss of the IGBT power module.
Consider the coupling effect of the diode, and the above state space model is extended as follows:
Specifically, xs1, . . . , xsn represents the state of self-heating impedance, xc1, . . . , xcn represents the state of the coupling thermal impedance; PIGBT represents the power loss of the IGBT in the IGBT power module, PDIODE represents the power loss of the diode in the IGBT power module;
specifically, Rs1 . . . Rsn, Cs1 . . . Csn represent the thermal resistance thermal capacitances in the equivalent Foster thermal network model of the IGBT in the IGBT power module; Rc1 . . . Rcn, Cc1 . . . Ccn represent the thermal resistance thermal capacitances in the equivalent Foster thermal network model of the diode in the IGBT power module.
Step 5. Set a system model of the Kalman filter (i.e., the Kalman filter):
A system of a discrete control process is introduced based on a space thermal model of the extended state in step 4 as follows:
xk=Fxk−1+Guk+wk
Tk=Hxk+Juk+vk
In the above equation, k represents the time step; xk−1 represents the state variable at time (k−1) (i.e., the thermal resistance of the IGBT power module); xk represents the state variable at time k (i.e., the thermal resistance of the IGBT power module); F and G respectively represent the system matrix and control matrix; uk represents the system input vector (the IGBT power module loss and the ambient temperature of the IGBT power module); wk and vk respectively represent the process noise and measurement noise. Assume that both are Gaussian white noise, the covariance of which are Q and R respectively; Tk represents the junction temperature observation value of IGBT power module at time k; H and J respectively represent the observation matrix and direct matrix.
As shown in
(1) Predict the thermal resistance value {circumflex over (x)}(k|k−1) of IGBT power module at time k from the optimal thermal resistance estimated value {circumflex over (x)}(k−1|k−1) of the IGBT power module at time (k−1):
{circumflex over (x)}(k|k−1)=F{circumflex over (x)}(k−1|k−1)+Guk
(2) Calculate the predicted value of the junction temperature of the IGBT power module at time k:
{circumflex over (T)}(k|k−1)=H{circumflex over (x)}(k|k−1)+Iuk
(3) Measure the covariance P(k|k−1) at time k by the covariance P(k−1|k−1) between the observed value and the predicted value of the IGBT power module junction temperature at time (k−1):
P(k|k−1)=FP(k−1|k−1)FT+Q
(4) Calculate the Kalman filter gain:
K(k)=P(k|k−1)HT[HP(k|k−1)−1HT+R]−1
Specifically, K(k) represents the Kalman filter gain.
(5) Calculate the optimal estimated value of the system:
{circumflex over (x)}(k|k)={circumflex over (x)}(k|k−1)+K(k)(Tk−{circumflex over (T)}(k|k−1))
Specifically, {circumflex over (x)}(k|k) represents the optimal estimated value of the thermal resistance of the IGBT power module at time k.
(6) Update the inverse operation of the optimal junction temperature value of the IGBT power module in the next step at time (k+1), that is, update the covariance:
P(k|k)=[I−K(k)H]P(k|k−1)
Specifically, P(k|k) represents the updated covariance after time k, and I represents the unity matrix.
Return to step (1) from step (6), perform a loop until the final result achieves the desired effect.
Table 1 compares the statistical error of estimated value of the junction temperature Tj before and after the application of the Kalman filter, which fully demonstrates the superiority of the present invention.
Table 1 statistical error of estimated value of the junction temperature Tj before and after the application of the Kalman filter
The equation for calculating the average absolute error is as follows:
The equation for calculating the standard deviation is as follows:
In the above two equations, MAE represents the average absolute error; a represents the standard deviation; t represents the serial number of each estimated value of junction temperature; N represents the total number of estimated values of junction temperature; xt represents each estimated value of junction temperature; and yt represents each junction temperature value obtained through measurement by the infrared thermal imager; μ represents the average of N estimated values of junction temperature.
It is apparent that the above-described embodiments are merely illustrative of the invention and are not intended to limit the embodiments of the invention. Other variations or modifications of the various forms may be made by those skilled in the art in light of the above description. Obvious changes or variations that come within the spirit of the invention are still within the scope of the invention.
Number | Date | Country | Kind |
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201910069446.2 | Jan 2019 | CN | national |
Number | Date | Country |
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107192934 | Sep 2017 | CN |
107219016 | Sep 2017 | CN |
108108573 | Jun 2018 | CN |
20170104735 | Sep 2017 | KR |
Entry |
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Chen et al., “Predicting IGBT Junction Temperature with Thermal Network Component Model”, 2011 Asia-Pacific Power and Energy Engineering Conference, Mar. 25-28, 2011 (Year: 2011). |
Wu et al., “Junction Temperature Prediction of IGBT Power Module Based on BP Neural Network”, Electr Eng Technol vol. 9, No. 3: 970-977, 2014 (Year: 2014). |
Number | Date | Country | |
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20200240850 A1 | Jul 2020 | US |