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CN113343463B - Method for predicting residual life of diode of subway traction rectifier by considering aging process - Google Patents

Method for predicting residual life of diode of subway traction rectifier by considering aging process Download PDF

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CN113343463B
CN113343463B CN202110637999.0A CN202110637999A CN113343463B CN 113343463 B CN113343463 B CN 113343463B CN 202110637999 A CN202110637999 A CN 202110637999A CN 113343463 B CN113343463 B CN 113343463B
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林圣�
黄宇剑
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Abstract

The invention discloses a method for predicting the residual life of a diode of a subway traction rectifier by considering an aging process, which specifically comprises the following steps: collecting forward conduction current, radiator temperature and environment temperature outside a rectifier cabinet of a subway traction substation rectifier diode within 24 hours of a day from a point 0; calculating the current diode thermal network model parameters by using a parameter identification method, and calculating the junction temperature of the diode at the 2 nd day according to the current diode thermal network model parameters; and updating the thermal resistance value of the diode according to the diode junction temperature damage value on the 2 nd day, and repeating the steps until the damage value is greater than or equal to 1 for the first time, so that the predicted value of the residual service life of the diode on the sampling day can be obtained. According to the method, the monitoring data of the temperature of the radiator in the rectifier temperature protection are utilized to identify the heat network model parameters to obtain the heat network model parameters of the diode in the current state, the thermal resistance is used as the aging characteristic quantity, the influence of aging damage on the junction temperature of the device is considered, and the accuracy of residual life prediction is improved.

Description

Method for predicting residual life of diode of subway traction rectifier by considering aging process
Technical Field
The invention belongs to the technical field of rectifier diode life prediction, and particularly relates to a subway traction rectifier diode residual life prediction method considering an aging process.
Background
The diode is used as a core component in the subway traction rectifier, and the accurate service life prediction of the diode is very important for the reliable operation of a traction power supply system. According to the reliability research of the power electronic system, the power device is the part with the highest failure rate in the converter system, which accounts for about 34%, and among various failure factors, about 55% of the failures of the power electronic system are mainly induced by temperature factors. Because the subway runs and is started and braked frequently, the output current of the rectifier has rapid fluctuation and large swing amplitude, and the junction temperature of the diode fluctuates severely; meanwhile, no fan is arranged in the subway rectifier cabinet, the cooling mode of the device is air natural convection heat exchange, and the heat dissipation condition is poor. These factors can cause fatigue damage to the rectifier diodes and even open and short circuit failure of the diodes. The design life of the subway traction rectifier is usually more than 30 years, and in order to prevent major accidents caused by aging and failure of a key component, namely a diode, along with the lapse of time in a longer service period, a method for predicting the residual life of the diode needs to be researched, so that guidance is provided for operation and maintenance and repair arrangement of a traction rectifier unit.
At present, a linear damage model is mainly adopted for predicting the service life of power devices such as diodes, only thermal parameters provided in a product data manual are used in the prediction process, and the thermal parameter change caused by device aging is not considered. Therefore, a method for predicting the residual service life of the diode of the subway traction rectifier by considering the aging process needs to be researched, and the accuracy of service life prediction is improved.
Disclosure of Invention
In order to take account of the influence of the aging process on the thermal resistance of the diode and improve the prediction precision of the residual service life. The invention provides a method for predicting the residual life of a diode of a subway traction rectifier by considering an aging process.
The invention discloses a method for predicting the residual life of a diode of a subway traction rectifier by considering an aging process, which comprises the following steps of:
step 1: collecting forward conduction current i of a diode of a rectifier of a subway traction substation within 24 hours from a point 0 by taking delta t as a sampling intervalF(T) radiator temperature Th(T) and the ambient temperature T outside the rectifier cabineta(t)。
Step 2: obtaining the forward conduction voltage i of the diode according to a forward voltage-current characteristic curve provided by a diode product data manualF(t) corresponding forward conduction voltage uF(t); according to a transient thermal impedance curve provided by a diode product data manual, fitting to obtain the thermal resistance R of the diode in an initial state1(0)Diode heat capacity C1(0)Heat radiator thermal resistance Rh(0)Heat capacity of heat sink Ch(0)(ii) a Calculating and obtaining the identification quantity theta in the initial state according to the formula (1)1(0)、θ2(0)、θ3(0)And theta4(0)。
Figure BDA0003105961320000021
And step 3: the diode conduction loss p (t) at time t is calculated according to equation (2):
P(t)＝iF(t)uF(t) (2)
and 4, step 4: using the diode conduction loss, the radiator temperature and the environment temperature data outside the rectifier cabinet within 24 hours from the 0 point, and according to the formula (3), obtaining the identification quantity theta at the 24 points of the day by using least square method identification1(d0)、θ2(d0)、θ3(d0)And theta4(d0)。
Th(t)＝θ1(d0)Th(t-1)+θ2(d0)Th(t-2)+θ3(d0)P(t-1)+θ4(d0)Ta(t-1) (3)
And 5: calculating the coefficient g of the change of the thermal resistance of the diode at 24 points1(d0)And coefficient of variation of thermal resistance g of heat sinkh(d0)。
Figure BDA0003105961320000022
Step 6: the thermal network model parameters at 24 points are calculated.
Figure BDA0003105961320000023
And 7: calculating the current diode damage value D(d0)。
Figure BDA0003105961320000024
And 8: and calculating the junction temperature of the diode one day after the sampling day according to the parameters of the heat network model at the time of 24 days.
Figure BDA0003105961320000031
And step 9: using a rain flow counting method to carry out statistical analysis on the junction temperature of the diode, simplifying the junction temperature change into a plurality of heat load cycles, and extracting the temperature amplitude fluctuation delta T in a single heat loadjiMean value of junction temperature T of one-time thermal loadjmiAnd number of times n of loading of different thermal loadsiAnd calculating the damage d to the diode under the single thermal loadi。
Figure BDA0003105961320000032
In the formula: parameters a and α are life model parameters obtained by fitting experimental test data, a is 97.2231, α is 3.1292, and EaTo excite an energy constant, Ea＝9.89×10-20J，kBIs Boltzmann constant, kB＝1.38×10-23J/K。
Step 10: calculating the diode damage value D one day after sampling(d1)：
Figure BDA0003105961320000033
Wherein: k is the number of thermal load classes.
Step 11: updating the thermal resistance R of the diode one day after the sampling day1(d1)：
R1(d1)＝R1(0)(1+a·D(d1)) (10)
Step 12: and calculating the damage value of the diode m days after sampling, wherein m is an integer more than or equal to 2.
Repeating the steps 8-9 to calculate the junction temperature of the diode m days after sampling and the damage to the diode under single thermal load;
calculating the diode damage value D m days after sampling by using the following formula(d1)And diode thermal resistance value R1(dm)。
Figure BDA0003105961320000034
R1(dm)＝R1(0)(1+a·D(dm)) (12)
When D is present(dm)When the first time is more than or equal to 1, m is the predicted value of the residual service life of the diode on the sampling day.
Further, the sampling interval Δ t is 0.1 s.
The beneficial technical effects of the invention are as follows:
the invention utilizes the monitoring data of the temperature of the radiator in the temperature protection of the rectifier to identify the parameters of the heat network model, and obtains the parameters of the heat network model in the current state of the diode, namely the current aging state of the diode. And then, taking the thermal resistance as an aging characteristic quantity, calculating the thermal resistance of the diode after aging through the damage value, dispersing the aging process of the diode into a plurality of stages, and carrying out segmented damage accumulation, wherein the influence of the aging damage on the junction temperature of the device is considered, and the prediction precision of the residual life is improved.
Drawings
Fig. 1 is a diode second-order continuous thermal network model of a subway traction rectifier, which is suitable for the invention.
Fig. 2 is a graph of the forward conduction current signal of the diode in the simulation experiment.
Fig. 3 is a graph of a heat sink temperature signal in a simulation experiment.
Fig. 4 is a graph of diode conduction loss in a simulation experiment.
Fig. 5 is a graph of diode junction temperature in a simulation experiment.
Fig. 6 is a graph of diode damage values in a simulation experiment.
Detailed Description
The invention is further explained in detail below with reference to the drawings and simulation experiments.
The invention discloses a method for predicting the residual life of a diode of a subway traction rectifier by considering an aging process, which comprises the following steps of:
step 1: collecting forward conduction current i of a diode of a rectifier of a subway traction substation within 24 hours from a point 0 by taking delta t as a sampling intervalF(T) radiator temperature Th(T) and the ambient temperature T outside the rectifier cabineta(t)。
Step 2: obtaining the forward conduction voltage i of the diode according to a forward voltage-current characteristic curve provided by a diode product data manualF(t) corresponding forward conduction voltage uF(t); according to a transient thermal impedance curve provided by a diode product data manual, fitting to obtain the thermal resistance R of the diode in an initial state1(0)Diode heat capacity C1(0)Heat radiator thermal resistance Rh(0)Heat capacity of heat sink Ch(0)(ii) a Calculating and obtaining the identification quantity theta in the initial state according to the formula (1)1(0)、θ2(0)、θ3(0)And theta4(0)。
Figure BDA0003105961320000041
And step 3: the diode conduction loss p (t) at time t is calculated according to equation (2):
P(t)＝iF(t)uF(t) (2)
and 4, step 4: using the diode conduction loss, the radiator temperature and the environment temperature data outside the rectifier cabinet within 24 hours from the 0 point, and according to the formula (3), obtaining the identification quantity theta at the 24 points of the day by using least square method identification1(d0)、θ2(d0)、θ3(d0)And theta4(d0)。
Th(t)＝θ1(d0)Th(t-1)+θ2(d0)Th(t-2)+θ3(d0)P(t-1)+θ4(d0)Ta(t-1) (3)
And 5: calculating the coefficient g of the change of the thermal resistance of the diode at 24 points1(d0)And coefficient of variation of thermal resistance g of heat sinkh(d0)。
Figure BDA0003105961320000051
Step 6: the thermal network model parameters at 24 points are calculated.
Figure BDA0003105961320000052
And 7: calculating the current diode damage value D(d0)。
Figure BDA0003105961320000053
And 8: and calculating the junction temperature of the diode one day after the sampling day according to the parameters of the heat network model at the time of 24 days.
Figure BDA0003105961320000054
And step 9: using a rain flow counting method to carry out statistical analysis on the junction temperature of the diode, simplifying the junction temperature change into a plurality of heat load cycles, and extracting the temperature amplitude fluctuation delta T in a single heat loadjiMean value of junction temperature T of one-time thermal loadjmiAnd number of times n of loading of different thermal loadsiAnd calculating the damage d to the diode under the single thermal loadi。
Figure BDA0003105961320000055
In the formula: parameters a and α are life model parameters obtained by fitting experimental test data, a is 97.2231, α is 3.1292, and EaTo excite an energy constant, Ea＝9.89×10-20J，kBIs Boltzmann constant, kB＝1.38×10-23J/K。
Step 10: calculating miningSample diode damage value D one day later(d1)：
Figure BDA0003105961320000056
Wherein: k is the number of thermal load classes.
Step 11: updating the thermal resistance R of the diode one day after the sampling day1(d1)：
R1(d1)＝R1(0)(1+a·D(d1)) (10)
Step 12: and calculating the damage value of the diode m days after sampling, wherein m is an integer more than or equal to 2.
Repeating the steps 8-9 to calculate the junction temperature of the diode m days after sampling and the damage to the diode under single thermal load;
calculating the diode damage value D m days after sampling by using the following formula(d1)And diode thermal resistance value R1(dm)。
Figure BDA0003105961320000061
R1(dm)＝R1(0)(1+a·D(dm)) (12)
When D is present(dm)When the first time is more than or equal to 1, m is the predicted value of the residual service life of the diode on the sampling day.
Further, the sampling interval Δ t is 0.1 s.
Simulation experiment:
to verify the effectiveness of the method of the invention, the following simulation experiments were performed.
The PLECS software is used for establishing a diode second-order continuous thermal network model of the subway traction rectifier as shown in figure 1.
Collecting forward conduction current i of a diode of a rectifier of a subway traction substation within 24 hours of a day from a point 0 by taking 0.1s as a sampling intervalF(T), radiator temperature Th(t) As shown in FIGS. 2 and 3, respectively, assuming ambient temperature outside the rectifier cabinetDegree Ta(t) is constant 25 ℃.
According to a transient thermal impedance curve provided by a product data manual, obtaining the thermal resistance R of the diode in an initial state by fitting1(0)0.1K/W, diode heat capacity C1(0)10J/K, heat sink thermal resistance Rh(0)0.2K/W, heat capacity of radiator Ch(0)20J/K. Calculating to obtain the identification amount theta in the initial state1(0)＝1.8489，θ2(0)＝-0.8511，θ3(0)＝4.2553×10-4，θ4(0)＝2.1277×10-3。
The diode conduction loss p (t) over a single sampling period is calculated as shown in fig. 4. Using the diode conduction loss, the radiator temperature and the environment temperature data outside the rectifier cabinet within 24 hours of a day from 0 point, and obtaining the identification quantity theta at 24 points of the day by utilizing least square method identification1(d0)＝1.8532，θ2(d0)＝-0.8551、θ3(d0)＝4.0997×10-4，θ4(d0)＝1.9300×10-3。
Calculating the coefficient g of thermal resistance change of the diode at the time t1(d0)1.1068, coefficient of variation of heat sink thermal resistance gh(d0)＝1.1075.
Calculating a thermal network model parameter R at time t1(d0)0.11068K/W, diode heat capacity C1(d0)10J/K, heat sink thermal resistance Rh(d0)0.2215K/W, heat capacity of radiator Ch(d0)＝20J/K。
Calculating the current diode damage value D(d0)＝0.534。
Calculating the diode junction temperature one day after the sampling day from the thermal network model parameters at 24 o' clock of the day is shown in fig. 5.
Method for extracting junction temperature amplitude fluctuation size delta T in single heat load by rain flow counting methodjiMean value of junction temperature T of one-time thermal loadjmiAnd number of times n of loading of different thermal loadsiCalculating the damage value D of the diode one day after sampling(d1)Updating the thermal resistance R of the diode one day after sampling1(d1)This procedure was repeated to calculate the diode damage value D m days after the sampling day (m 2, 3, 4 … …)(dm)As shown in fig. 6When m is 4249, D(dm)The first time is more than or equal to 1, namely the predicted value of the residual service life of the diode on the sampling day is 4249 days.

Claims (2)

1. A method for predicting the residual life of a diode of a subway traction rectifier in consideration of an aging process is characterized by comprising the following steps:
step 1: collecting forward conduction current i of a diode of a rectifier of a subway traction substation within 24 hours from a point 0 by taking delta t as a sampling intervalF(T) radiator temperature Th(T) and the ambient temperature T outside the rectifier cabineta(t)；
Step 2: obtaining the forward conduction current i of the diode according to a forward voltage-current characteristic curve provided by a diode product data manualF(t) corresponding forward conduction voltage uF(t); according to a transient thermal impedance curve provided by a diode product data manual, fitting to obtain the thermal resistance R of the diode in an initial state1(0)Diode heat capacity C1(0)Heat radiator thermal resistance Rh(0)Heat capacity of heat sink Ch(0)(ii) a Calculating and obtaining the identification quantity theta in the initial state according to the formula (1)1(0)、θ2(0)、θ3(0)And theta4(0)；
Figure FDA0003105961310000011
And step 3: the diode conduction loss p (t) at time t is calculated according to equation (2):
P(t)＝iF(t)uF(t) (2)
and 4, step 4: using the diode conduction loss, the radiator temperature and the environment temperature data outside the rectifier cabinet within 24 hours from the 0 point, and according to the formula (3), obtaining the identification quantity theta at the 24 points of the day by using least square method identification1(d0)、θ2(d0)、θ3(d0)And theta4(d0)；
Th(t)＝θ1(d0)Th(t-1)+θ2(d0)Th(t-2)+θ3(d0)P(t-1)+θ4(d0)Ta(t-1) (3)
And 5: calculating the coefficient g of the change of the thermal resistance of the diode at 24 points1(d0)And coefficient of variation of thermal resistance g of heat sinkh(d0)；
Figure FDA0003105961310000012
Step 6: calculating the thermal network model parameters at 24 points:
Figure FDA0003105961310000013
and 7: calculating the current diode damage value D(d0)：
Figure FDA0003105961310000021
And 8: calculating the junction temperature of the diode one day after the sampling day according to the heat network model parameters at the time of 24 o' clock of the day:
Figure FDA0003105961310000022
and step 9: using a rain flow counting method to carry out statistical analysis on the junction temperature of the diode, simplifying the junction temperature change into a plurality of heat load cycles, and extracting the temperature amplitude fluctuation delta T in a single heat loadjiMean value of junction temperature T of one-time thermal loadjmiAnd number of times n of loading of different thermal loadsiAnd calculating the damage d to the diode under the single thermal loadi：
Figure FDA0003105961310000023
In the formula: parameters A, alpha are the lifetimes obtained by fitting of experimental test dataModel parameters, a-97.2231, α -3.1292, EaTo excite an energy constant, Ea＝9.89×10-20J，kBIs Boltzmann constant, kB＝1.38×10-23J/K；
Step 10: calculating the diode damage value D one day after sampling(d1)：
Figure FDA0003105961310000024
Wherein: k is the number of hot load types;
step 11: updating the thermal resistance R of the diode one day after the sampling day1(d1)：
R1(d1)＝R1(0)(1+a·D(d1)) (10)
Step 12: calculating a diode damage value m days after sampling, wherein m is an integer more than or equal to 2;
repeating the steps 8-9 to calculate the junction temperature of the diode m days after sampling and the damage to the diode under single thermal load;
calculating the diode damage value D m days after sampling by using the following formula(dm)And diode thermal resistance value R1(dm)；
Figure FDA0003105961310000025
R1(dm)＝R1(0)(1+a·D(dm)) (12)
When D is present(dm)When the first time is more than or equal to 1, m is the predicted value of the residual service life of the diode on the sampling day.
2. A method for predicting the residual life of diodes of a subway traction rectifier according to claim 1, wherein said sampling interval Δ t is 0.1 s.
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