CN113343463A - 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

Info

Publication number
CN113343463A
CN113343463A CN202110637999.0A CN202110637999A CN113343463A CN 113343463 A CN113343463 A CN 113343463A CN 202110637999 A CN202110637999 A CN 202110637999A CN 113343463 A CN113343463 A CN 113343463A
Authority
CN
China
Prior art keywords
diode
day
calculating
rectifier
temperature
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202110637999.0A
Other languages
Chinese (zh)
Other versions
CN113343463B (en
Inventor
林圣�
黄宇剑
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Southwest Jiaotong University
Original Assignee
Southwest Jiaotong University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Southwest Jiaotong University filed Critical Southwest Jiaotong University
Priority to CN202110637999.0A priority Critical patent/CN113343463B/en
Publication of CN113343463A publication Critical patent/CN113343463A/en
Application granted granted Critical
Publication of CN113343463B publication Critical patent/CN113343463B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/26—Testing of individual semiconductor devices
    • G01R31/2607—Circuits therefor
    • G01R31/2632—Circuits therefor for testing diodes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
    • G06F2119/02—Reliability analysis or reliability optimisation; Failure analysis, e.g. worst case scenario performance, failure mode and effects analysis [FMEA]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
    • G06F2119/04—Ageing analysis or optimisation against ageing

Landscapes

  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Hardware Design (AREA)
  • Evolutionary Computation (AREA)
  • Geometry (AREA)
  • General Engineering & Computer Science (AREA)
  • Testing Of Individual Semiconductor Devices (AREA)

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 the diode damage value D one day after sampling(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, assume an ambient temperature T outside the rectifier cabineta(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 methodjiSingle heat of reactionMean value of junction temperature T of 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. 6, when 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 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 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: diode conduction loss within 24 hours from use at 0, heat sink temperature, and ambient temperature outside the rectifier cabinetAnd (3) identifying the identification quantity theta of the day at 24 points by using a least square method according to the formula (3)1(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 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 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(d1)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.
CN202110637999.0A 2021-06-08 2021-06-08 Method for predicting residual life of diode of subway traction rectifier by considering aging process Active CN113343463B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110637999.0A CN113343463B (en) 2021-06-08 2021-06-08 Method for predicting residual life of diode of subway traction rectifier by considering aging process

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110637999.0A CN113343463B (en) 2021-06-08 2021-06-08 Method for predicting residual life of diode of subway traction rectifier by considering aging process

Publications (2)

Publication Number Publication Date
CN113343463A true CN113343463A (en) 2021-09-03
CN113343463B CN113343463B (en) 2022-04-29

Family

ID=77474922

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110637999.0A Active CN113343463B (en) 2021-06-08 2021-06-08 Method for predicting residual life of diode of subway traction rectifier by considering aging process

Country Status (1)

Country Link
CN (1) CN113343463B (en)

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20040023422A1 (en) * 2002-05-20 2004-02-05 Finisar Corporation Laser production and product qualification via accelerated life testing based on statistical modeling
CN102356478A (en) * 2009-02-12 2012-02-15 香港城市大学 Method and numerical tool for optimizing light emitting diode systems
US20180013259A1 (en) * 2016-07-08 2018-01-11 Fanuc Corporation Laser apparatus enabling calculation of effective driving time and remaining lifetime taking account of drive conditions including temperature
US20190197203A1 (en) * 2017-12-27 2019-06-27 Imec Vzw Simulation of Photovoltaic Systems
CN112487651A (en) * 2020-12-07 2021-03-12 广东电网有限责任公司江门供电局 Method for detecting service life of power device of photovoltaic converter

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20040023422A1 (en) * 2002-05-20 2004-02-05 Finisar Corporation Laser production and product qualification via accelerated life testing based on statistical modeling
CN102356478A (en) * 2009-02-12 2012-02-15 香港城市大学 Method and numerical tool for optimizing light emitting diode systems
US20180013259A1 (en) * 2016-07-08 2018-01-11 Fanuc Corporation Laser apparatus enabling calculation of effective driving time and remaining lifetime taking account of drive conditions including temperature
US20190197203A1 (en) * 2017-12-27 2019-06-27 Imec Vzw Simulation of Photovoltaic Systems
CN112487651A (en) * 2020-12-07 2021-03-12 广东电网有限责任公司江门供电局 Method for detecting service life of power device of photovoltaic converter

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
MOHSEN AKBARI等: ""An Extended Multilayer Thermal Model for Multichip IGBT Modules Considering Thermal Aging"", 《IEEE ACCESS》 *
SHENG LIN等: ""Research on the Regeneration Braking Energy Feedback System of Urban Rail Transit"", 《IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY》 *
丁杰等: "地铁车辆牵引逆变器IGBT模块的结温与疲劳寿命计算", 《电气工程学报》 *
陈民铀等: "考虑老化进程对热参数影响的IGBT模块寿命评估", 《中国电机工程学报》 *

Also Published As

Publication number Publication date
CN113343463B (en) 2022-04-29

Similar Documents

Publication Publication Date Title
Lai et al. Low $\Delta T_ {j} $ Stress Cycle Effect in IGBT Power Module Die-Attach Lifetime Modeling
Ma et al. New approaches to reliability assessment: Using physics-of-failure for prediction and design in power electronics systems
Hu et al. Online calculation of the increase in thermal resistance caused by solder fatigue for IGBT modules
CN109738773A (en) IGBT module life-span prediction method under a kind of non-stationary operating condition
CN104155587B (en) System and method for on-line detection of operating junction temperature of IGBT module
CN110147578B (en) IGBT device service life prediction method based on semi-physical simulation platform
CN109188232A (en) A kind of construction method of IGBT module status assessment and predicting residual useful life model
CN105242189B (en) IGBT health status monitoring methods based on collection emitter-base bandgap grading saturation voltage drop and solder layer voidage
CN106443400A (en) Electric-heat-aging junction temperature calculation model establishing method of IGBT module
Ma et al. Lifetime estimation for the power semiconductors considering mission profiles in wind power converter
CN106643765A (en) Method for calculating collection abnormality maintenance time
CN103399241A (en) Distribution transformer fault diagnosis system and method based on relation between temperature rise and load
CN105224819B (en) Power device radiator dynamic response performance optimization method based on iterative numerical
CN113591336B (en) Method and system for predicting service life of power supply IGBT module under passenger car
CN111060797A (en) IGBT module health state monitoring method based on natural frequency of heat network
CN108595376A (en) A kind of non-intruding load discrimination method for distinguishing fixed frequency air conditioner and impact drill
CN113343463B (en) Method for predicting residual life of diode of subway traction rectifier by considering aging process
CN107515366B (en) LED lead service life prediction method and test device based on coffee-Mason
CN113341293B (en) Subway traction rectifier diode junction temperature extraction method based on parameter identification
CN204925001U (en) Metal radiator heat dispersion testing arrangement
CN110197012B (en) Support capacitor life evaluation method considering fault influence of traction transmission system
Zhou et al. Online noninvasive technique for condition monitoring of cooling system in urban rail vehicles
Sang et al. Analysis on multiple factors influencing the lifetime of IGBTs of electric vehicles converters
CN114184927A (en) Thyristor life evaluation method
CN102081125A (en) Integrated test system for PTC (Positive Temperature Coefficient) resettable fuse

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant