A life prediction method and system considering IGBT module wire bonding failure
By monitoring the number of broken bond wires and transient impedance curves of IGBT modules online, an RC thermal network model is determined, which solves the problem of inaccurate lifetime prediction caused by bond wire breakage in the prior art and achieves more accurate lifetime assessment.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2022-07-20
- Publication Date
- 2026-04-07
AI Technical Summary
Existing IGBT module lifetime assessment methods do not consider bond wire breakage, leading to inaccurate junction temperature calculations and consequently affecting the accuracy of lifetime prediction results.
By monitoring the number of broken bond wires in IGBT modules online, their health status can be determined. Based on the transient impedance curve, an RC thermal network model can be determined, and power cycling experiments can be conducted to predict their lifetime.
The accuracy of IGBT module life prediction has been improved by taking into account the impact of bond wire breakage on electrothermal characteristics, avoiding structural damage, and improving evaluation accuracy.
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Figure CN115203953B_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the field of IGBT module life prediction, and particularly relates to a life prediction method and system considering IGBT module bonding wire failure. BACKGROUND
[0002] With the vigorous development of emerging industries such as new energy power generation, rail transit, smart grid, electric vehicles, the long-time safe operation of power electronic equipment is related to the stability of the whole system, so the reliability evaluation of power electronic equipment has become the focus of current researchers. Insulated Gate Bipolar Transistor (IGBT) module is widely used in converters as a power switching device. The existing IGBT module life evaluation method generally calculates the junction temperature curve by establishing a perfect device thermal network model, and predicts the life based on this, without considering the need to update the thermal network model due to bonding wire breakage, resulting in inaccurate junction temperature calculation and further leading to high life prediction results.
[0003] Therefore, it is urgent to provide a new life prediction method or system to improve the accuracy of the life prediction results of the IGBT module. SUMMARY
[0004] The purpose of the present application is to provide a life prediction method and system considering IGBT module bonding wire failure, which can improve the accuracy of the life prediction results of the IGBT module.
[0005] To achieve the above-mentioned purpose, the present application provides the following solutions:
[0006] A life prediction method considering IGBT module bonding wire failure, comprising:
[0007] judging the health state of the IGBT module according to online monitoring data of the IGBT module; the online monitoring data includes the number of broken bonding wires; the health state includes a health module with 0 broken bonding wires and an aging module with non-0 broken bonding wires;
[0008] when the IGBT module is a health module, directly obtaining a transient impedance curve, determining an RC thermal network model according to the transient impedance curve, and then performing a power cycle experiment to realize life prediction;
[0009] when the IGBT module is an aging module, measuring the current transient thermal impedance curve of the IGBT module according to the transient thermal impedance measurement test, and determining the current RC thermal network model by using the current transient thermal impedance curve, and then performing a power cycle experiment to realize life prediction.
[0010] Optionally, when the IGBT module is an aging module, the current transient thermal impedance curve of the IGBT module is obtained based on the transient thermal impedance measurement test, and the current RC thermal network model is determined using the current transient thermal impedance curve, thereby conducting a power cycle test to achieve lifetime prediction, specifically including:
[0011] Fit the current transient thermal impedance curve to determine the current RC thermal network model;
[0012] Power cycling experiments were conducted under the current RC thermal network model to determine the junction temperature variation curve of the IGBT module.
[0013] The junction temperature data for one period is determined based on the junction temperature change curve; the junction temperature data includes: average junction temperature and junction temperature wave action.
[0014] Based on junction temperature data, a life prediction model and a fatigue accumulation algorithm are used to predict life.
[0015] Optionally, fitting the current transient thermal impedance curve to determine the current RC thermal network model specifically includes:
[0016] use Perform fitting;
[0017] Among them, R i and C i Here, Z represents the fitted resistance and capacitance, t is time, n is the number of remaining bond lines, and Z is the resistance and capacitance. th denoted as the transient thermal resistance curve, e as the natural logarithm, and i as the order of the fitted RC thermal network model.
[0018] Optionally, the step of predicting the lifespan using a lifespan prediction model and a fatigue accumulation algorithm based on junction temperature data specifically includes:
[0019] Using formula Determine the lifetime prediction model;
[0020] Where, N f T represents the number of failure cycles under a certain load. j For the junction temperature, T javg For the average junction temperature, ΔT j For junction temperature fluctuations, E B To activate energy, E B = 9.89 × 10⁻²⁰ J, K B K is the Boltzmann constant. B = 1.38 × 10⁻²³ J·K -1 α and n are aging test parameters, where α = 97.2231 and n = 3.1292.
[0021] A life prediction system considering IGBT module bonding wire failure, comprising:
[0022] A health state judgment module for judging the health state of the IGBT module according to online monitoring data of the IGBT module; the online monitoring data includes the number of broken bonding wires; the health state includes a healthy module with the number of broken bonding wires being 0 and an aging module with the number of broken bonding wires not being 0;
[0023] A life prediction first module for directly obtaining a transient impedance curve when the IGBT module is a healthy module, determining an RC thermal network model according to the transient impedance curve, and then performing a power cycle experiment to realize life prediction;
[0024] A life prediction second module for measuring the current transient thermal impedance curve of the IGBT module according to the transient thermal impedance measurement test when the IGBT module is an aging module, determining the current RC thermal network model using the current transient thermal impedance curve, and then performing a power cycle experiment to realize life prediction.
[0025] Optionally, the life prediction second module specifically includes:
[0026] An RC thermal network model determination unit for fitting the current transient thermal impedance curve to determine the current RC thermal network model;
[0027] A junction temperature change curve determination unit for performing a power cycle experiment under the current RC thermal network model to determine the junction temperature change curve of the IGBT module;
[0028] A junction temperature data determination unit for determining the junction temperature data in a period according to the junction temperature change curve; the junction temperature data includes the average junction temperature and the junction temperature fluctuation;
[0029] A life prediction unit for performing life prediction using a life prediction model and a fatigue accumulation algorithm according to the junction temperature data.
[0030] Optionally, the RC thermal network model determination unit specifically includes:
[0031] An RC thermal network model determination subunit for fitting using to determine the RC thermal network model;
[0032] Wherein, R i and C i are the fitted resistance and capacitance, t is time, n is the number of remaining bonding wires, Z th is the transient thermal impedance curve, e is the natural logarithm, and i is the order of the fitted RC thermal network model.
[0033] Optionally, the life prediction unit specifically includes:
[0034] The lifetime prediction model determines the sub-units, which are used to utilize the formula Determine the lifetime prediction model;
[0035] Where, N f T represents the number of failure cycles under a certain load. j For the junction temperature, T javg For the average junction temperature, ΔT j For junction temperature fluctuations, E B To activate energy, E B = 9.89 × 10⁻²⁰ J, K B K is the Boltzmann constant. B = 1.38 × 10⁻²³ J·K -1 α and n are aging test parameters, where α = 97.2231 and n = 3.1292.
[0036] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:
[0037] This invention provides a lifetime prediction method and system considering bond wire failure in IGBT modules. The method determines the health status of the IGBT module based on the number of broken bond wires, thus considering the impact of bond wire breakage on electrothermal characteristics and consequently on the transient thermal impedance curve. This invention analyzes the transient thermal impedance changes of IGBT modules with broken bond wires, using online monitoring results of the number of bond wires. The combination of these two methods can be used in subsequent lifetime calculations for modules with broken bond wires, without damaging the device structure. This approach incorporates the health status of the bond wires during operation into lifetime assessment, improving the accuracy of lifetime assessment. Attached Figure Description
[0038] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0039] Figure 1 A schematic flowchart of a lifetime prediction method considering IGBT module bond wire failure provided by the present invention;
[0040] Figure 2 A comparison of transient thermal impedance curves for healthy modules and bond wire failures (n is the number of remaining bond wires);
[0041] Figure 3 This is a circuit diagram of an RC thermal network model;
[0042] Figure 4This is a schematic diagram of a heat network model;
[0043] Figure 5 This is a schematic diagram of a lifetime prediction system that takes into account the failure of bond wires in IGBT modules, provided by the present invention. Detailed Implementation
[0044] 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, and 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.
[0045] The purpose of this invention is to provide a life prediction method and system that takes into account the failure of bond wires in IGBT modules, which can improve the accuracy of IGBT module life prediction results.
[0046] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.
[0047] Figure 1 This is a schematic flowchart of a lifetime prediction method considering IGBT module bond wire failure provided by the present invention, as shown below. Figure 1 As shown, the present invention provides a lifetime prediction method considering IGBT module bond wire failure, comprising:
[0048] S101, determine the health status of the IGBT module based on the online monitoring data of the IGBT module; the online monitoring data includes: the number of broken bond wires; the health status includes: a healthy module with 0 broken bond wires and an aged module with a non-zero number of broken bond wires.
[0049] S102, when the IGBT module is a healthy module, directly obtain the transient impedance curve, determine the RC thermal network model based on the transient impedance curve, and then conduct a power cycle experiment to achieve lifetime prediction.
[0050] When the IGBT module is a healthy module, the transient impedance curve is determined based on the transient thermal impedance measurement experiment and recorded in the datasheet; that is, it can be obtained directly from the datasheet.
[0051] The steps of a transient thermal impedance measurement experiment include:
[0052] S1. Before the experiment, place the IGBT module on a temperature-controlled platform. Disconnect switch K and apply a small current I. c1 Control the temperature T of the constant temperature platform jThe collector-emitter voltage V was measured using an oscilloscope at different temperatures, ranging from 30 to 150°C. CE .
[0053] S2, utilizing the collector-emitter voltage V at different temperatures CE and corresponding temperature T j Fit the linear equation T of both. j =a*V CE +b (where a and b are the fitted parameters).
[0054] S3, move the IGBT module onto the air-cooled heatsink, close switch K, and apply a large current I. c2 and small current I c1 Until the device reaches thermal equilibrium (the junction temperature remains constant, as reflected in the collector-emitter voltage V), CE (Tend to stabilize).
[0055] S4, disconnect switch K, leaving only a small current I. c1 At this time, the IGBT module is in the cooling phase. An oscilloscope is used to collect the collector-emitter voltage V during the junction temperature phase. CE .
[0056] S5, utilizing the junction temperature T in S2 j and collector-emitter voltage V CE The linear formula T j =a*V CE +b, calculate the cooling stage V CE The corresponding junction temperature at each moment yields the junction temperature change curve over time during the cooling phase.
[0057] S6, Transient thermal impedance calculation formula Among them, T j (0) represents the initial junction temperature, T j (t) represents the junction temperature at time t during the cooling process, and P represents the power loss of the IGBT module.
[0058] S103, when the IGBT module is in the aging stage, the current transient thermal impedance curve of the IGBT module is obtained based on the transient thermal impedance measurement test. This transient thermal impedance curve is then used to determine the current RC thermal network model, followed by power cycle testing to achieve lifetime prediction. The current transient thermal impedance curve is as follows: Figure 2 As shown.
[0059] When the IGBT module is an aging module, manually cut the bonding wires and repeat S1-S6 above to measure the transient thermal resistance curves under different numbers of bonding wires.
[0060] Bonded wires electrically connect the collector and emitter; multiple bonded wires are placed in parallel to carry current I. cDuring each measurement test, the bond line is gradually shortened until only one bond line remains.
[0061] S103 specifically includes:
[0062] Fit the current transient thermal impedance curve to determine the current RC thermal network model, such as... Figure 4 As shown.
[0063] like Figure 3 As shown, the fitted R i C i For a fourth-order circuit, the capacitor and resistor are used... Perform fitting; where R i and C i Here, Z represents the fitted resistance and capacitance, t is time, n is the number of remaining bond lines, and Z is the resistance and capacitance. th denoted as the transient thermal resistance curve, e as the natural logarithm, and i as the order of the fitted RC thermal network model.
[0064] Power cycling experiments were conducted under the current RC thermal network model to determine the junction temperature variation curve of the IGBT module.
[0065] The junction temperature data within a cycle is determined based on the junction temperature change curve; the junction temperature data includes: average junction temperature and junction temperature wave action.
[0066] Based on junction temperature data, a life prediction model and fatigue accumulation algorithm are used to predict the life of a component. The formula is then used. Determine the lifetime prediction model.
[0067] Where, N f T represents the number of failure cycles under a certain load. j For the junction temperature, T javg For the average junction temperature, ΔT j For junction temperature fluctuations, E B To activate energy, E B = 9.89 × 10⁻²⁰ J, K B K is the Boltzmann constant. B = 1.38 × 10⁻²³ J·K -1 α and n are aging test parameters, where α = 97.2231 and n = 3.1292.
[0068] Figure 5 A schematic diagram of a lifetime prediction system considering IGBT module bond wire failure provided by the present invention is shown below. Figure 5 As shown, the present invention provides a lifetime prediction system considering IGBT module bond wire failure, comprising:
[0069] The health status judgment module 501 is used to judge the health status of the IGBT module based on the online monitoring data of the IGBT module; the online monitoring data includes: the number of broken bond wires; the health status includes: a healthy module with 0 broken bond wires and an aging module with a non-zero number of broken bond wires.
[0070] The first lifetime prediction module 502 is used to directly obtain the transient impedance curve when the IGBT module is a healthy module, and determine the RC thermal network model based on the transient impedance curve, and then conduct power cycling experiments to achieve lifetime prediction.
[0071] The second lifetime prediction module 503 is used to determine the current transient thermal impedance curve of the IGBT module based on the transient thermal impedance measurement test when the IGBT module is an aging module, and then to determine the current RC thermal network model using the current transient thermal impedance curve, and then to conduct a power cycle test to achieve lifetime prediction.
[0072] The second lifetime prediction module 503 specifically includes:
[0073] The RC thermal network model determination unit is used to fit the current transient thermal impedance curve and determine the current RC thermal network model.
[0074] The junction temperature change curve determination unit is used to conduct power cycling experiments under the current RC thermal network model to determine the junction temperature change curve of the IGBT module.
[0075] The junction temperature data determination unit is used to determine the junction temperature data within a period based on the junction temperature change curve; the junction temperature data includes: average junction temperature and junction temperature wave action.
[0076] The life prediction unit is used to predict the life based on junction temperature data, using a life prediction model and fatigue accumulation algorithm.
[0077] The RC thermal network model determination unit specifically includes:
[0078] The RC thermal network model determines the sub-units for use in... Perform fitting.
[0079] Among them, R i and C i Here, Z represents the fitted resistance and capacitance, t is time, n is the number of remaining bond lines, and Z is the resistance and capacitance. th denoted as the transient thermal resistance curve, e as the natural logarithm, and i as the order of the fitted RC thermal network model.
[0080] The lifetime prediction unit specifically includes:
[0081] The lifetime prediction model determines the sub-units, which are used to utilize the formula Determine the lifetime prediction model.
[0082] Where, N f T represents the number of failure cycles under a certain load. j For the junction temperature, T javg For the average junction temperature, ΔT j For junction temperature fluctuations, E B To activate energy, E B = 9.89 × 10⁻²⁰ J, K B K is the Boltzmann constant. B = 1.38 × 10⁻²³ J·K -1 α and n are aging test parameters, where α = 97.2231 and n = 3.1292.
[0083] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to the method section.
[0084] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.
Claims
1. A lifetime prediction method considering IGBT module bond wire failure, characterized in that, include: Determine the health status of the IGBT module based on its online monitoring data; The online monitoring data includes: the number of broken bond wires; the health status includes: a healthy module with 0 broken bond wires and an aging module with a non-zero number of broken bond wires; When the IGBT module is in good condition, the transient impedance curve is directly obtained, and the RC thermal network model is determined based on the transient impedance curve. Then, a power cycling experiment is conducted to achieve lifetime prediction. When the IGBT module is an aging module, the current transient thermal impedance curve of the IGBT module is obtained according to the transient thermal impedance measurement test, and the current RC thermal network model is determined by the current transient thermal impedance curve. Then, a power cycle test is carried out to achieve life prediction. When the IGBT module is an aging module, the current transient thermal impedance curve of the IGBT module is obtained based on the transient thermal impedance measurement test. The current RC thermal network model is then determined using this transient thermal impedance curve, and a power cycle test is conducted to predict the lifespan. Specifically, this includes: Fit the current transient thermal impedance curve to determine the current RC thermal network model; Power cycling experiments were conducted under the current RC thermal network model to determine the junction temperature variation curve of the IGBT module. The junction temperature data for one period is determined based on the junction temperature change curve; the junction temperature data includes: average junction temperature and junction temperature wave action. Based on the junction temperature data, a life prediction model and a fatigue accumulation algorithm are used to predict the life. The process of fitting the current transient thermal impedance curve to determine the current RC thermal network model specifically includes: use Perform fitting; Among them, R i and C i Here, Z represents the fitted resistance and capacitance, t is time, n is the number of remaining bond lines, and Z is the resistance and capacitance. th Here, represents the transient thermal resistance curve, e is the natural logarithm, and i is the order of the fitted RC thermal network model. The life prediction based on junction temperature data, using a life prediction model and fatigue accumulation algorithm, specifically includes: Using formula Determine the lifetime prediction model; Where, N f T represents the number of failure cycles under a certain load. j For the junction temperature, T javg For the average junction temperature, ΔT j For junction temperature fluctuations, E B To activate energy, E B = 9.89 × 10⁻²⁰ J, K B K is the Boltzmann constant. B = 1.38 × 10⁻²³ J·K -1 α and n are aging test parameters, where α = 97.2231 and n = 3.1292.
2. A lifetime prediction system considering IGBT module bond wire failure, used to implement the lifetime prediction method considering IGBT module bond wire failure as described in claim 1, characterized in that, include: The health status assessment module is used to determine the health status of the IGBT module based on the online monitoring data of the IGBT module. The online monitoring data includes: the number of broken bond wires; the health status includes: a healthy module with 0 broken bond wires and an aging module with a non-zero number of broken bond wires; The first lifetime prediction module is used to directly obtain the transient impedance curve when the IGBT module is a healthy module, and determine the RC thermal network model based on the transient impedance curve, and then conduct power cycling experiments to achieve lifetime prediction. The second lifetime prediction module is used to determine the current transient thermal impedance curve of the IGBT module when the IGBT module is an aging module, based on the transient thermal impedance measurement test, and then to determine the current RC thermal network model using the current transient thermal impedance curve, and then to conduct a power cycle test to achieve lifetime prediction.
3. The lifetime prediction system considering IGBT module bond wire failure according to claim 2, characterized in that, The second module for lifetime prediction specifically includes: The RC thermal network model determination unit is used to fit the current transient thermal impedance curve and determine the current RC thermal network model. The junction temperature change curve determination unit is used to conduct power cycling experiments under the current RC thermal network model to determine the junction temperature change curve of the IGBT module. A junction temperature data determination unit is used to determine the junction temperature data within a cycle based on the junction temperature change curve; the junction temperature data includes: average junction temperature and junction temperature wave action. The life prediction unit is used to predict the life based on junction temperature data, using a life prediction model and fatigue accumulation algorithm.
4. The lifetime prediction system considering IGBT module bond wire failure according to claim 3, characterized in that, The RC thermal network model determination unit specifically includes: The RC thermal network model determines the sub-units for use in... Perform fitting; Among them, R i and C i Here, Z represents the fitted resistance and capacitance, t is time, n is the number of remaining bond lines, and Z is the resistance and capacitance. th denoted as the transient thermal resistance curve, e as the natural logarithm, and i as the order of the fitted RC thermal network model.
5. A lifetime prediction system considering IGBT module bond wire failure according to claim 3, characterized in that, The lifetime prediction unit specifically includes: The lifetime prediction model determines the sub-units, which are used to utilize the formula Determine the lifetime prediction model; Where, N f T represents the number of failure cycles under a certain load. j For the junction temperature, T javg For the average junction temperature, ΔT j For junction temperature fluctuations, E B To activate energy, E B = 9.89 × 10⁻²⁰ J, K B K is the Boltzmann constant. B = 1.38 × 10⁻²³ J·K -1 α and n are aging test parameters, where α = 97.2231 and n = 3.1292.
Citation Information
Patent Citations
IGBT module bonding wire state monitoring and evaluating method based on multiple electrical parameters
CN114217202A