CN115526080B - Switch power supply reliability prediction method based on multi-physical-field digital prototype model - Google Patents
Switch power supply reliability prediction method based on multi-physical-field digital prototype model Download PDFInfo
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Abstract
The invention discloses a switching power supply reliability prediction method based on a multi-physical-field digital prototype model, which comprises the following steps: s1, establishing a digital prototype model of a switching power supply electric, thermal and vibration multiple physical fields suitable for reliability prediction; s2, based on a digital prototype model, analyzing and determining a key failure mode and a failure mechanism of the switching power supply, and determining an electronic component with weak reliability; s3, based on a digital prototype model and the reliability weak electronic components, establishing a switching power supply reliability prediction model integrating performance degradation and functional failure; and S4, solving and obtaining a reliability curve under a given expected working environment based on a switching power supply reliability expected model. According to the invention, by utilizing a digital prototype model, the influence factors of the functional failure and the performance degradation of key components of the switching power supply on the reliability under the conditions of electric, thermal and vibration stress are considered, the accuracy of the reliability prediction of the switching power supply can be improved, and a powerful support is provided for improving the reliability of the switching power supply.
Description
Technical Field
The invention relates to a switching power supply reliability prediction method, in particular to a switching power supply reliability prediction method based on a multi-physical-field digital prototype model.
Background
In order to improve the reliability of the switching power supply, it is particularly important to predict the accurate reliability of the switching power supply. Most of the existing reliability prediction methods of the switching power supply are also based on mathematical statistics, and the method calculates the failure rate of the electronic components by using an empirical formula containing factors such as quality grade, use condition and the like according to failure data in a reliability prediction manual or standard, so as to predict the reliability of the electronic components and the switching power supply. This approach is disjoint from the failure mechanism and does not take into account the impact of the degradation process on reliability, resulting in poor accuracy of its predictions.
Disclosure of Invention
Aiming at the problems existing in the prior art, the invention provides a switching power supply reliability prediction method based on a multi-physical-field digital prototype model. The method can improve the accuracy of reliability prediction of the switching power supply, and further provides a powerful support for improving the reliability of the switching power supply.
The invention aims at realizing the following technical scheme:
a switching power supply reliability prediction method based on a multi-physical-field digital prototype model comprises the following steps:
step S1, establishing a digital prototype model of a switching power supply electric, thermal and vibration multiple physical fields suitable for reliability prediction;
step S2, analyzing and determining a key failure mode and a failure mechanism of the switching power supply based on the digital prototype model established in the step S1, and determining an electronic component with weak reliability;
step S3, based on the digital prototype model established in the step S1 and the reliability weak electronic components determined in the step S2, establishing a switching power supply reliability prediction model with fusion performance degradation and functional failure;
and S4, solving and obtaining a reliability curve under a given expected working environment based on the switching power supply reliability expected model established in the step S3.
Compared with the prior art, the invention has the following advantages:
according to the invention, by utilizing a digital prototype model, the influence factors of the functional failure and the performance degradation of key components of the switching power supply on the reliability under the conditions of electric, thermal and vibration stress are considered, the accuracy of the reliability prediction of the switching power supply can be improved, and a powerful support is provided for improving the reliability of the switching power supply.
Drawings
FIG. 1 is a flow chart of a switching power supply reliability prediction method based on a multi-physical field digital prototype model;
FIG. 2 is a topology of a switching power supply circuit in an embodiment;
FIG. 3 is a switching power supply structural model in an embodiment;
fig. 4 is a data interaction flow of implementing electrothermal coupling simulation of a switching power supply by the iSIGHT platform in an embodiment;
FIG. 5 is a sample of the sensitivity analysis of the switching power supply in the example;
FIG. 6 is a switching power supply fault tree analysis result in an embodiment;
FIG. 7 is a switching power supply reliability prediction modeling flow considering electronic component performance degradation and functional failure in an embodiment;
fig. 8 is a switching power supply reliability curve and a functional reliability curve and a performance reliability curve according to an embodiment.
Detailed Description
The following description of the present invention is provided with reference to the accompanying drawings, but is not limited to the following description, and any modifications or equivalent substitutions of the present invention should be included in the scope of the present invention without departing from the spirit and scope of the present invention.
The invention provides a switching power supply reliability prediction method based on a multi-physical-field digital prototype model, which is shown in fig. 1 and comprises the following steps:
step S1, a digital prototype model of a switching power supply electric, thermal and vibration multiple physical fields suitable for reliability prediction is built, and the specific steps are as follows:
s11, establishing a switching power supply circuit model through EDA software, and performing circuit simulation analysis;
step S12, a switching power supply structure model is established through three-dimensional modeling software and finite element analysis software, and thermal simulation analysis and vibration simulation analysis are carried out;
and S13, realizing data interaction and process control of electric heating coupling simulation of the switching power supply through a simulation coupling platform, further completing electric heating coupling variable transmission and realizing indirect coupling of multiple physical fields.
Step S2, based on the digital prototype model established in the step S1, the key failure mode and failure mechanism of the switching power supply are analyzed and determined, and the electronic components with weak reliability are determined, wherein the specific steps are as follows:
step S21, carding typical failure modes of the electronic components forming the switching power supply according to the types of the electronic components;
step S22, referring to the failure mode of the performance degradation type of the electronic components in the step S21, and determining the electronic components and the sensitive parameters thereof which have great influence on the output performance of the switching power supply by using a sensitivity analysis method;
step S23, referring to the failure mode of the electronic component function failure type in the step S21, and determining the electronic component with the function failure affecting the function of the switching power supply by using a fault tree analysis method;
and step S24, integrating the electronic components determined by analysis in the step S22 and the step S23, namely the electronic components with weak reliability.
Step S3, based on the digital prototype model established in the step S1 and the reliability weak electronic components determined in the step S2, establishing a switching power supply reliability prediction model with fusion performance degradation and functional failure, wherein the specific steps are as follows:
step S31, according to the digital prototype model of the switching power supply established in the step S1, combining multiple data acquisition modes such as simulation, actual measurement and the like, establishing a working stress mapping model [ I ] capable of describing the relation between the working condition of the switching power supply and the electric, thermal and vibration stress of the electronic components 1 ,V 1 ,T 1 ,a 1 ,f 1 ,…,I i ,V i ,T i ,a i ,f i ,…]＝S(V s ,I S ,T S ,A S ,f S ) Wherein I i 、V i 、T i 、a i 、f i Respectively representing the effective value of current, effective value of voltage, average surface temperature, sinusoidal vibration acceleration, sinusoidal vibration frequency, V S 、I S 、T S 、A S 、f S Respectively representing an input voltage effective value, an output current effective value, an environment average temperature, an equivalent sinusoidal vibration acceleration and an equivalent sinusoidal vibration frequency of the switching power supply, wherein S (·) is a working stress mapping model;
step S32, according to performance parameter degradation data obtained by the electronic component electric, thermal and vibration acceleration stress test, a time-varying performance degradation model P of the electronic component i is established i (t)＝D i (s, t), wherein s= [ I ] i ,V i ,T i ,a i ,f i ]，D i (. Cndot.) is a model of performance degradation, and D i (s, t) has a distribution characteristic, P i (t) is a time-varying performance parameter vector of the performance-degrading electronic component i having a distribution characteristic;
step S33, establishing a functional failure model F of the electronic component i according to the functional failure time data (service life data) obtained by the electronic component electric, thermal and vibration acceleration stress test i (t)＝K i (s,t)，K i (. Cndot.) is a model of failure of function, and K i (s, t) has a distribution characteristic, F i (t) is the failure time of the functional failure type electronic component i;
step S34, determining the limiting state of the output characteristic parameter according to the use requirement of the switching power supply, and constructing a performance mapping model P capable of describing the relation between the degradation of the electronic components and the output characteristic of the switching power supply by utilizing a digital prototype model S (t)＝X(P 1 (t),…,P i (t), …), wherein P S (t) is a switching power supply output characteristic parameter vector, and X (·) is a performance mapping model;
step S35, constructing a switching power supply reliability block diagram by using a fault tree analysis result, and establishing a function mapping model F capable of describing the corresponding relation between electronic components and the functional failure of the switching power supply S (t)＝G(F 1 (t),…,F i (t), …), wherein F S (t) is the functional failure time of the switching power supply, and G (·) is a functional mapping model；
Step S36, the working stress mapping model S (-) inputs stress to the electronic component performance degradation model D i (. Cndot.) and functional failure model K i (·)，D i (. Cndot.) and K i Respectively transmitting respective outputs to a performance mapping model X (-) and a functional mapping model G (-) according to the X (-) and the G (-) and an output characteristic parameter threshold vector P th R is obtained respectively p (t) and R f (t), describing the reliability R of the switching power supply at any time t by the formula (1) S And (t) obtaining a switching power supply reliability prediction model:
wherein α=k/N s ，N s The total specification number of the electronic components in the switching power supply is represented, and k represents the specification number of the electronic components which are both performance degradation type electronic components and functional failure type electronic components.
Step S4, solving to obtain a reliability curve under a given expected working environment based on the switch power supply reliability expected model established in the step S3, wherein the specific steps are as follows:
s41, performing equivalent decomposition on the stress of the task section to obtain the predicted value { V ] of the temperature, vibration and electric stress used by the switching power supply S ,I S ,T S ,A S ,f S }；
Step S42, based on the switching power supply working stress mapping model established in step S31, the { V } S ,I S ,T S ,A S ,f S Substituted into the temperature, vibration and electric stress response value [ I ] of each electronic component composing the switch power supply 1 ,V 1 ,P 1 ,T 1 ,a 1 ,f 1 ,…,I i ,V i ,P i ,T i ,a i ,f i ,…]；
Step S43, sequentially combining [ I ] of the electronic component I calculated in step S42 i ,V i ,P i ,T i ,a i ,f i ]D substituted into electronic component i i (. Cndot.) and K i In the (-) model, a time-varying performance parameter vector P with distribution characteristics of the electronic component i is obtained i (t) and time to failure F i (t) sampling based on Monte Carlo mode to obtain N performance parameters P of electronic component i i ' and N functional failure times F i ′(t)；
Step S44, the time-varying performance parameter [ P ] of each electronic component batch obtained in step S43 1 ′(t),…,P i ′(t),…]Substituting the time-varying output characteristic parameter vectors into a switching power supply performance mapping model X (-), so as to obtain N time-varying output characteristic parameter vectors P of the corresponding switching power supply S (t), counting P at any t time S (t) satisfy P th Probability R of (2) P (t)＝Pr{P S (t)∈P th And obtaining a switching power supply performance degradation reliability curve R p (t)；
Step S45, the electronic component batch function failure time [ F ] obtained in the step S43 1 ′(t),…,F i ′(t),…]Substituting the N functional failure times F of the corresponding switching power supply into the switching power supply functional mapping model G (& gt) S (t), counting F at any t time S (t) probability of non-occurrence R f (t)＝Pr{F S (t) > t }, the functional failure reliability curve R of the switching power supply can be obtained f (t)；
Step S46, calculating a switching power supply reliability curve R for fusing performance degradation and functional failure according to the homology of the performance degradation model and the functional failure model by the formula (1) S (t)。
Examples:
the engineering object in this embodiment is a switching power supply, and its main function is energy conversion, which is a basic guarantee for normal operation of electric equipment, and the switching power supply used in this embodiment contains 50 specifications and 87 electronic components. The method is characterized in that a digital prototype model of the switching power supply is utilized, and the functional failure and performance degradation of electronic components in the switching power supply are considered under three stress environments of electricity, heat and vibration, so that the process of reliability prediction of the switching power supply mainly comprises the following aspects:
first, a digital prototype model of the switching power supply is built. According to the switching power supply operating principle, a circuit topology diagram thereof can be established, as shown in fig. 2, in which Q1 to Q6 represent MOSFETs. And then, based on a circuit topological diagram, using Saber software to build a switching power supply circuit model, and performing circuit simulation analysis to obtain the power loss of each electronic component in the switching power supply. Meanwhile, the structural composition of the switching power supply is analyzed, and a structural model of the switching power supply is built by utilizing SolidWorks, and the result is shown in figure 3. And then, the structural model is imported into ANSYS, and vibration simulation and thermal simulation are carried out through model simplification, material property setting, net separation and boundary condition setting. The thermal simulation needs to substitute the power consumption conversion of the electronic components into the internal heat generation power in the thermal simulation model based on the iSIGHT platform, so that the thermal field distribution of the switching power supply is obtained, and the specific flow is shown in fig. 4. And then, obtaining parameters of the electronic components through a functional relation between the temperature and the parameters of the devices, and transmitting the parameters to an electric simulation model. And (3) carrying out loop iteration until the iteration difference is smaller than 0.1 ℃, and considering that the electrothermal coupling simulation result is converged at the moment, so that the steady-state response of the switching power supply circuit and the thermal field can be obtained.
And secondly, determining the electronic components with weak reliability of the switching power supply. Based on the digital prototype model, the types of electronic components and typical failure modes thereof are combed, and the results are shown in table 1.
TABLE 1
And determining the electronic component with larger influence on the output performance of the switching power supply by using a sensitivity analysis method by referring to the failure mode of the performance degradation type of the electronic component. The relative sensitivity is obtained by the ratio of the relative change rate of the technical index P (mainly comprising voltage, ripple and efficiency) of the circuit to the relative change rate of the component parameter x, and the corresponding mathematical expression is as follows:
if relative sensitivity L i The higher the relative variation of the parameters representing component i, the more the voltage, ripple and efficiency of the circuit can be affected. For the switching power supply studied in this embodiment, sensitivity analysis was performed, and it was determined that 57 performance-degrading electronic components were present in the switching power supply, and a part of the results are shown in fig. 5.
And determining the electronic components with the function failure affecting the function of the switching power supply by referring to the failure modes of the function failure types of the electronic components and utilizing a fault tree analysis method. And taking the output fault of the switching power supply as the top event of the fault tree, finding out all possible factors and reasons for the occurrence of the event, and connecting the factors and reasons by using a specified logic symbol to analyze the fault tree. From the top event, the analysis proceeds down to the middle event, and proceeds deep layer by layer until the basic cause of the event, i.e., the bottom event of the fault tree, is found. And then solving the minimum cut set of the fault tree, thereby determining the electronic components affecting the functional failure of the switching power supply. Finally, 56 electronic components with failure type are contained in the switching power supply, and partial results of fault tree analysis are shown in fig. 6.
The results of the sensitivity analysis and the fault tree analysis are integrated, and the integrated result is an electronic component with weak reliability of the switching power supply, and the specification number of the electronic component with performance degradation and functional failure is 13.
Then, a switching power supply reliability prediction model considering component performance degradation and functional failure is established, and a specific flow is shown in fig. 7. Firstly, according to a digital prototype model of the switching power supply, the working stress of the switching power supply is input into the digital prototype model in a simulation and actual measurement mode, so that the working stress of an electronic component is obtained, and a working stress mapping model S (-) is built.
Simultaneously, the performance parameter degradation data and the functional failure time data obtained in the electric, thermal and vibration acceleration degradation test of the electronic component are utilized to respectively establish the performance degradation model D of the electronic component i (s, t) and functional failure model K i (s, t) wherein the form of the performance degradation modelThe method comprises the following steps:
D i (s,t)＝e i (s)Λ i (t)+σ i C i (Λ i (t)) (3)；
wherein s= [ I ] i ,V i ,T i ,a i ,f i ]，I i 、V i 、T i 、a i 、f i Respectively representing the effective value of the current, the effective value of the voltage, the average surface temperature, the sinusoidal vibration acceleration and the sinusoidal vibration frequency of the component i, e i (s) is a function of the stress vector s, Λ i (t) is a time-scale transformation function, σ i As drift coefficient, C i (Λ i (t)) is an uncertainty procedure, subject to a normal uncertainty distribution N (0, Λ) i (t)). The form of the functional failure model is as follows:
K i (s,t)＝e iK (s)θ i (t)+ε i (4)
wherein s= [ I ] i ,V i ,T i ,a i ,f i ]，I i 、V i 、T i 、a i 、f i Respectively representing the effective value of the current, the effective value of the voltage, the average surface temperature, the sinusoidal vibration acceleration and the sinusoidal vibration frequency of the component i,
is a function of the stress vector s, θ i (t) is a function of time ε i Is disturbance factor, obeys the mean value to be 0 and variance to be +.>
Is a normal distribution of (c).
And then determining the limit state of the output characteristic parameter according to the use requirement of the switching power supply, describing the multi-input multi-output quantitative mapping relation between the easily-degraded performance parameter of the electronic component and the output characteristic parameter of the switching power supply by using a digital prototype model, and constructing a performance mapping model X (.). Then, a switching power supply reliability block diagram is constructed by using the result of fault tree analysis, and a logical mapping relation between the function of the electronic component easy to fail and the function of the switching power supply is described, so that a function mapping model G (-) is constructed, and the method has the following form:
wherein F is i And (t) is the failure time of the functional failure type electronic components i, wherein the first m electronic components are in a series structure, and the last n-m electronic components are in a parallel structure. Then, as shown in fig. 7, the above model is connected.
And finally, carrying out state iteration by utilizing a reliability prediction model to obtain a reliability curve of the switching power supply. The method comprises the steps of firstly carrying out equivalent decomposition on stress under a task section of a switching power supply to obtain the predicted value { V ] of temperature, vibration and electric stress used by the switching power supply S ,I S ,T S ,A S ,f S }. Inputting the predicted value into a working stress mapping model, and calculating to obtain temperature, vibration and electric stress response values [ I ] of 87 electronic components in the switching power supply 1 ,V 1 ,T 1 ,a 1 ,f 1 ,…,I 87 ,V 87 ,T 87 ,a 87 ,f 87 ]＝S(V S ,I S ,T S ,A S ,f S ). Then, substituting the response value into the performance degradation model D of the corresponding electronic component i (s, t) and a functional failure model K i In (s, t) [ P ] can be obtained 1 (t),...,P 57 (t)]And [ F 1 (t),...,F 56 (t)]And sampling by Monte Carlo mode to obtain 5000 batch performance parameters [ P ] 1 ′(t),…,P 5 ′ 7 (t)]And time to failure of function F 1 ′(t),…,F 5 ′ 6 (t)]. Then, the electronic component batch performance parameters are input into a switching power supply performance mapping model, and 5000 time-varying output characteristic parameter vectors P can be obtained S (t)＝X(P 1 ′(t),...,P 5 ′ 7 (t)), where P S (t) is a time-varying vector with distribution characteristics including voltage, ripple and efficiency, and according to the set output characteristic parameter threshold value P th Counting P at any t time S (t) satisfy P th Is of (1)Rate R P (t)＝Pr{P S (t)∈P th And obtaining a switching power supply performance degradation reliability curve R p (t), the result is shown in FIG. 8 as curve (3). Meanwhile, the functional failure time of the electronic component batch is input into a switching power supply functional mapping model, so that 5000 functional failure times F of the corresponding switching power supply can be obtained S (t)＝G(F 1 ′(t),…,F 5 ′ 6 (t)), F at any t time is counted S (t) probability of non-occurrence R f (t)＝Pr{F S (t) > t }, the functional failure reliability curve R of the switching power supply can be obtained f (t), the result is shown in FIG. 8 as curve (2). Finally, according to the homology of the performance degradation model and the functional failure model, the performance degradation reliability curve and the functional failure reliability curve of the switching power supply are utilized, the performance degradation and functional failure reliability curve of the switching power supply is fused through the calculation of a formula (6), and the result is shown as a (1) curve in fig. 8.
Wherein α=k/N s Total number of specifications N s The specification number k of 50, which is both performance degradation and functional failure, is 13.
Claims (4)
1. A switching power supply reliability prediction method based on a multi-physical-field digital prototype model is characterized by comprising the following steps:
step S1, establishing a digital prototype model of a switching power supply electric, thermal and vibration multiple physical fields suitable for reliability prediction;
step S2, analyzing and determining a key failure mode and a failure mechanism of the switching power supply based on the digital prototype model established in the step S1, and determining an electronic component with weak reliability;
step S3, based on the digital prototype model established in the step S1 and the reliability weak electronic components determined in the step S2, establishing a switching power supply reliability prediction model with fusion performance degradation and functional failure, wherein the specific steps are as follows:
step S31, according to the digital prototype model of the switching power supply established in the step S1, a working stress mapping model [ I ] capable of describing the relation between the working condition of the switching power supply and the electric, thermal and vibration stress of the electronic components is established 1 ,V 1 ,T 1 ,a 1 ,f 1 ,…,I i ,V i ,T i ,a i ,f i ,…]＝S(V s ,I S ,T S ,A S ,f S ) Wherein I i 、V i 、T i 、a i 、f i Respectively representing the effective value of current, effective value of voltage, average surface temperature, sinusoidal vibration acceleration, sinusoidal vibration frequency, V S 、I S 、T S 、A S 、f S Respectively representing an input voltage effective value, an output current effective value, an environment average temperature, an equivalent sinusoidal vibration acceleration and an equivalent sinusoidal vibration frequency of the switching power supply, wherein S (·) is a working stress mapping model;
step S32, according to performance parameter degradation data obtained by the electronic component electric, thermal and vibration acceleration stress test, a time-varying performance degradation model P of the electronic component i is established i (t)＝D i (s, t), wherein s= [ I ] i ,V i ,T i ,a i ,f i ]，D i (. Cndot.) is a model of performance degradation, and D i (s, t) has a distribution characteristic, P i (t) is a time-varying performance parameter vector of the performance-degrading electronic component i having a distribution characteristic;
step S33, establishing a functional failure model F of the electronic component i according to the functional failure time data obtained by the electronic component electric, thermal and vibration acceleration stress test i (t)＝K i (s,t)，K i (. Cndot.) is a model of failure of function, and K i (s, t) has a distribution characteristic, F i (t) is the failure time of the functional failure type electronic component i;
step S34, determining the limiting state of the output characteristic parameter according to the use requirement of the switching power supply, and constructing a performance mapping model P capable of describing the relation between the degradation of the electronic components and the output characteristic of the switching power supply by utilizing a digital prototype model S (t)＝X(P 1 (t),…,P i (t), …), wherein P S (t) is a switching power supply output characteristic parameter vector, and X (·) is a performance mapping model;
step S35, constructing a switching power supply reliability block diagram by using a fault tree analysis result, and establishing a function mapping model F capable of describing the corresponding relation between electronic components and the functional failure of the switching power supply S (t)＝G(F 1 (t),…,F i (t), …), wherein F S (t) is the functional failure time of the switching power supply, and G (·) is a functional mapping model;
step S36, the working stress mapping model S (-) inputs stress to the electronic component performance degradation model D i (. Cndot.) and functional failure model K i (·)，D i (. Cndot.) and K i Respectively transmitting respective outputs to a performance mapping model X (-) and a functional mapping model G (-) according to the X (-) and the G (-) and an output characteristic parameter threshold vector P th R is obtained respectively p (t) and R f (t), describing the reliability R of the switching power supply at any time t by the formula (1) S And (t) obtaining a switching power supply reliability prediction model:
wherein α=k/N s ，N s The total specification number of the electronic components in the switching power supply is represented, and k represents the specification number of the electronic components which are not only performance degradation type electronic components but also functional failure type electronic components;
and S4, solving and obtaining a reliability curve under a given expected working environment based on the switching power supply reliability expected model established in the step S3.
2. The method for predicting the reliability of a switching power supply based on a digital prototype model of multiple physical fields according to claim 1, wherein the specific steps of step S1 are as follows:
s11, establishing a switching power supply circuit model through EDA software, and performing circuit simulation analysis;
step S12, a switching power supply structure model is established through three-dimensional modeling software and finite element analysis software, and thermal simulation analysis and vibration simulation analysis are carried out;
and S13, realizing data interaction and process control of electric heating coupling simulation of the switching power supply through a simulation coupling platform, further completing electric heating coupling variable transmission and realizing indirect coupling of multiple physical fields.
3. The method for predicting the reliability of a switching power supply based on a digital prototype model of multiple physical fields according to claim 1, wherein the specific steps of step S2 are as follows:
step S21, carding typical failure modes of the electronic components forming the switching power supply according to the types of the electronic components;
step S22, referring to the failure mode of the performance degradation type of the electronic components in the step S21, and determining the electronic components and the sensitive parameters thereof which have great influence on the output performance of the switching power supply by using a sensitivity analysis method;
step S23, referring to the failure mode of the electronic component function failure type in the step S21, and determining the electronic component with the function failure affecting the function of the switching power supply by using a fault tree analysis method;
and step S24, integrating the electronic components determined by analysis in the step S22 and the step S23, namely the electronic components with weak reliability.
4. The method for predicting the reliability of a switching power supply based on a digital prototype model of multiple physical fields according to claim 1, wherein the specific steps of step S4 are as follows:
s41, performing equivalent decomposition on the stress of the task section to obtain the predicted value { V ] of the temperature, vibration and electric stress used by the switching power supply S ,I S ,T S ,A S ,f S }；
Step S42, based on the switching power supply working stress mapping model established in step S31, the { V } S ,I S ,T S ,A S ,f S Substituted into the temperature of each electronic component in which the switching power supply is calculatedDegree, vibration, electrical stress response value [ I ] 1 ,V 1 ,P 1 ,T 1 ,a 1 ,f 1 ,…,I i ,V i ,P i ,T i ,a i ,f i ,…]；
Step S43, sequentially combining [ I ] of the electronic component I calculated in step S42 i ,V i ,P i ,T i ,a i ,f i ]D substituted into electronic component i i (. Cndot.) and K i In the (-) model, a time-varying performance parameter vector P with distribution characteristics of the electronic component i is obtained i (t) and time to failure F i (t) sampling based on Monte Carlo mode to obtain N performance parameters P of electronic component i i ' and N functional failure times F i ′(t)；
Step S44, the time-varying performance parameter [ P 'of each electronic component batch obtained in step S43 is set' 1 (t),…,P′ i (t),…]Substituting the time-varying output characteristic parameter vectors into a switching power supply performance mapping model X (-), so as to obtain N time-varying output characteristic parameter vectors P of the corresponding switching power supply S (t), counting P at any t time S (t) satisfy P th Probability R of (2) P (t)＝Pr{P S (t)∈P th And obtaining a switching power supply performance degradation reliability curve R p (t)；
Step S45, the electronic component batch function failure time [ F ] obtained in the step S43 1 ′(t),…,F i ′(t),…]Substituting the N functional failure times F of the corresponding switching power supply into the switching power supply functional mapping model G (& gt) S (t), counting F at any t time S (t) probability of non-occurrence R f (t)＝Pr{F S (t) > t }, the functional failure reliability curve R of the switching power supply can be obtained f (t)；
Step S46, calculating a switching power supply reliability curve R for fusing performance degradation and functional failure according to the homology of the performance degradation model and the functional failure model by the formula (1) S (t)。
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