Electronic component reliability digital design method based on multi-physics field coupling simulation

Abstract

The invention discloses an electronic component reliability digital design method based on multi-physics field coupling simulation, and belongs to the technical field of reliability analysis, and the method comprises the following steps: S1, obtaining a working environment index and a reliability design index of an electronic component; s2, constructing a component reliability digital evaluation model; s3, obtaining an electrical parameter and a temperature parameter of the electronic component; s4, constructing an overall reliability evaluation model for the electronic component; and S5, constructing an optimization model for the overall reliability evaluation model of the electronic component, and completing the reliability digital design of the electronic component. According to the method, the reliability of the electronic component can be accurately evaluated through multi-physical field coupling simulation and a digital evaluation technology under the condition of insufficient data, and reliability design optimization is realized under constraint conditions of other design factors; therefore, the stability and the long-term reliability of the electronic component in a complex environment are improved under a limited design condition.

Description

Technical Field

[0001] The present invention belongs to the technical field of reliability analysis, and in particular relates to a reliability digital design method for electronic components based on multi-physical field coupling simulation. Background Art

[0002] Electronic components play a vital role in modern electronic systems and are widely used in fields such as communications, computing, energy, and automobiles. As the complexity and functional requirements of the system increase, the reliability of electronic components directly affects the stability and safety of the entire system. The reliability design of electronic components needs to fully consider their performance under various working conditions, such as environmental factors such as temperature, current, and vibration. This requires a comprehensive reliability assessment of electronic components under certain constraints such as cost, quality, and volume, and improves their performance through optimized design to ensure their long life and efficient and stable operation in practical applications.

[0003] At present, traditional electronic component reliability assessment methods usually rely on empirical formulas or a large amount of test data. However, in the case of insufficient data, the accuracy and reliability of the assessment results are difficult to guarantee. Especially in some electronic devices with high precision and high reliability requirements, the application of traditional methods is greatly limited. In addition, existing reliability design methods often only consider a single physical field (such as temperature) and ignore the interaction between multiple physical fields (such as electric field, temperature field and stress field, etc.), resulting in the inability to comprehensively evaluate and optimize the reliability of electronic components.

[0004] Therefore, there is an urgent need for a new electronic component reliability design method based on multi-physics field coupling simulation and digital technology, which can comprehensively evaluate the reliability of electronic components and optimize the design scheme through multi-physics field coupling simulation models in the absence of a large amount of failure data. This method can not only improve the evaluation accuracy, but also provide a more effective reliability optimization scheme, thereby improving the stability and long-term reliability of electronic components under complex working conditions. Summary of the invention

[0005] In order to solve the above problems, the present invention proposes a digital design method for electronic component reliability based on multi-physical field coupling simulation.

[0006] The technical solution of the present invention is: a digital design method for electronic component reliability based on multi-physical field coupling simulation comprises the following steps:

[0007] S1. Obtain the working environment index and reliability design index of electronic components;

[0008] S2. Construct a digital evaluation model for component reliability based on the working environment indicators and reliability design indicators of electronic components;

[0009] S3. Processing the reliability digital evaluation model using a multi-physics field coupling simulation method to obtain electrical parameters and temperature parameters of the electronic components;

[0010] S4. construct an overall reliability assessment model for the electronic component based on the electrical parameters and temperature parameters of the electronic component;

[0011] S5. Build an optimization model for the overall reliability evaluation model of electronic components and complete the digital design of electronic component reliability.

[0012] Further, in S1, the working environment indicators of the electronic components include working temperature, voltage and power of the electronic components;

[0013] In S1, reliability design indicators include reliability, failure probability, failure rate and average life of electronic components.

[0014] Further, in S2, the component reliability digital evaluation model includes a reliability digital model of a resistor, a reliability digital model of a capacitor, a reliability digital model of an inductor, a reliability digital model of a switch tube, a reliability digital model of an integrated circuit, and a reliability digital model of a PCB;

[0015] The expression of the reliability digital model of resistor is:

[0016]

[0017] Wherein, R is the first nominal value of the resistance value, ΔR is the second nominal value of the resistance value, T is the ambient temperature, t is the working time, B is the first model parameter, C is the second model parameter, D is the third model parameter, F is the fourth model parameter, and ln(·) is a logarithmic function;

[0018] The expression of the reliability digital model of capacitor is:

[0019]

[0020] Where, L C (T) is the capacitor life at ambient temperature, L C,0 is the inductor life at reference temperature, T0 is the reference temperature;

[0021] The expression of the reliability digital model of inductor is:

[0022]

[0023] Where, L I (T) is the inductor life at ambient temperature, L I,0 is the life of the inductor at the reference temperature, E a1is the activation energy of the inductor material, k is the Boltzmann constant, and e is a natural constant;

[0024] The reliability digital model of the switch tube is expressed as:

[0025]

[0026] Where, L S (T) is the life of the switch tube at ambient temperature, L S,0 is the life of the switch tube at the reference temperature, E a2 is the activation energy of the switch tube material;

[0027] The expression of the reliability digital model of integrated circuit is:

[0028]

[0029] Where, L IC (T) is the life of the integrated circuit at ambient temperature, L IC,0 is the lifetime of the integrated circuit at the reference temperature, E a3 is the activation energy of the integrated circuit material;

[0030] The expression of the reliability digital model of PCB is:

[0031]

[0032] Where D is the corrosion depth of the solder joint, V is the volume of the sealed cavity, e is a natural constant, P0 is the standard atmospheric pressure, Vp is the initial water vapor partial pressure difference, p is the water vapor partial pressure in the sealed cavity, and M 水汽 is the molecular weight of water vapor, M 空气 is the molecular weight of air, P 饱和 is the saturated water vapor pressure, RH is the relative humidity, T c is the water vapor temperature, t is the working time, and ln(·) is the logarithmic function.

[0033] Further, S4 includes the following sub-steps:

[0034] S41, obtaining a circuit topology structure of the electronic component;

[0035] S42. Construct an overall reliability assessment model for the electronic component based on the circuit topology, electrical parameters, and temperature parameters of the electronic component.

[0036] Furthermore, S5 includes the following sub-steps:

[0037] S51, generating a relationship curve between mean time before failure and temperature for the electronic component according to electrical parameters, temperature parameters and an overall reliability evaluation model of the electronic component;

[0038] S52. Based on the relationship curve between the mean time before failure and the temperature, an optimization model is constructed.

[0039] Furthermore, the optimization model includes a reliability design model with minimizing the cost of the system as the optimization goal and a reliability design model with maximizing the reliability of the electronic components as the optimization goal.

[0040] Furthermore, the expression of the reliability design model with the optimization goal of minimizing the system cost is:

[0041]

[0042] Where θ* is the optimized reliability design solution, λ is the feasible solution of the failure rate of the selected components, Cost is the feasible solution of the cost of the selected components, Cost is the total cost, and Cost j is the cost of the jth type of components, λ j is the failure rate of the jth type of components, λ j,min is the lower limit constraint of the failure rate of the optional models of the j-th type of components, λ j,max is the upper limit constraint on the failure rate of the optional models of the j-th type of components, λ s is the failure rate of electronic components under feasible solutions, λ s,min is the lower limit constraint of the failure rate of electronic components, Cost j,min is the lower bound constraint on the cost of the j-th type of components, Cost j,max is the upper limit constraint on the cost of the j-th type of components, α j is the cost function fitting coefficient, w j are the coefficients of the cost function fitting exponential.

[0043] Furthermore, the expression of the reliability design model with the goal of maximizing the reliability of electronic components is:

[0044]

[0045] Where θ* is the optimized reliability design solution, λ is the feasible solution of the failure rate of the selected components, Cost is the feasible solution of the cost of the selected components, λ is the failure rate of the electronic component, f(λ) is the functional relationship between the failure rate of the electronic component and the failure rate of the component, and λ j is the failure rate of the jth type of components, λ j,min is the lower limit constraint of the failure rate of the optional models of the j-th type of components, λ j,max is the upper limit constraint on the failure rate of the optional models of the j-th type of components, λ s,min is the lower limit constraint of the failure rate of electronic components, Cost j is the cost of the jth type of components, Cost j,min is the lower bound constraint on the cost of the j-th type of components, Cost j,maxis the upper limit constraint on the cost of the j-th type of components, α j is the cost function fitting coefficient, w j are the coefficients of the cost function fitting exponential.

[0046] The beneficial effects of the present invention are as follows: when data is insufficient, the present invention can accurately evaluate the reliability of electronic components through multi-physical field coupling simulation and digital evaluation technology, and realize reliability design optimization under the constraints of other design factors, thereby improving the stability and long-term reliability of electronic components in complex environments under limited design conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 A flowchart of the digital design method for electronic component reliability based on multi-physics coupling simulation;

[0048] Figure 2 The Buck-Boost power conversion circuit schematic diagram of an embodiment of the present invention;

[0049] Figure 3 The finite element model diagram of the Buck-Boost power conversion circuit according to the embodiment of the present invention;

[0050] Figure 4 A cross-sectional diagram of temperature distribution of a multi-physics field simulation of a Buck-Boost power conversion circuit according to an embodiment of the present invention;

[0051] Figure 5 This is a graph showing the relationship between MTTF0 and unit price of components in an embodiment of the present invention;

[0052] Figure 6 MTTF of components in the embodiment of the present invention t Temperature relationship diagram. DETAILED DESCRIPTION

[0053] The embodiments of the present invention will be further described below in conjunction with the accompanying drawings.

[0054] like Figure 1 As shown, the present invention provides a digital design method for electronic component reliability based on multi-physical field coupling simulation, comprising the following steps:

[0055] S1. Obtain the working environment index and reliability design index of electronic components;

[0056] S2. Construct a digital evaluation model for component reliability based on the working environment indicators and reliability design indicators of electronic components;

[0057] S3. Processing the reliability digital evaluation model using a multi-physics field coupling simulation method to obtain electrical parameters and temperature parameters of the electronic components;

[0058] S4. construct an overall reliability assessment model for the electronic component based on the electrical parameters and temperature parameters of the electronic component;

[0059] S5. Build an optimization model for the overall reliability evaluation model of electronic components and complete the digital design of electronic component reliability.

[0060] In the embodiment of the present invention, in S1, the working environment index of the electronic component includes the working temperature, voltage and power of the electronic component;

[0061] In S1, reliability design indicators include reliability, failure probability, failure rate and average life of electronic components.

[0062] In the embodiment of the present invention, in S2, the component reliability digital evaluation model includes a reliability digital model of a resistor, a reliability digital model of a capacitor, a reliability digital model of an inductor, a reliability digital model of a switch tube, a reliability digital model of an integrated circuit, and a reliability digital model of a PCB;

[0063] Based on the physics of component failure, a digital reliability model is established. By modeling the failure mode and degradation mechanism of core components, theoretical support is provided for subsequent reliability evaluation.

[0064] The expression of the reliability digital model of resistor is:

[0065]

[0066] Wherein, R is the first nominal value of the resistance value, ΔR is the second nominal value of the resistance value, T is the ambient temperature, t is the working time, B is the first model parameter, C is the second model parameter, D is the third model parameter, F is the fourth model parameter, and ln(·) is a logarithmic function;

[0067] The expression of the reliability digital model of capacitor is:

[0068]

[0069] Where, L C (T) is the capacitor life at ambient temperature, L C,0 is the inductor life at reference temperature, T0 is the reference temperature;

[0070] The expression of the reliability digital model of inductor is:

[0071]

[0072] Where, L I (T) is the inductor life at ambient temperature, L I,0is the life of the inductor at the reference temperature, E a1 is the activation energy of the inductor material, k is the Boltzmann constant, and e is a natural constant;

[0073] The reliability digital model of the switch tube is expressed as:

[0074]

[0075] Where, L S (T) is the life of the switch tube at ambient temperature, L S,0 is the life of the switch tube at the reference temperature, E a2 is the activation energy of the switch tube material;

[0076] The expression of the reliability digital model of integrated circuit is:

[0077]

[0078] Where, L IC (T) is the life of the integrated circuit at ambient temperature, L IC,0 is the lifetime of the integrated circuit at the reference temperature, E a3 is the activation energy of the integrated circuit material;

[0079] The expression of the reliability digital model of PCB is:

[0080]

[0081] Where D is the corrosion depth of the solder joint, V is the volume of the sealed cavity, e is a natural constant, P0 is the standard atmospheric pressure, Vp is the initial water vapor partial pressure difference, p is the water vapor partial pressure in the sealed cavity, and M 水汽 is the molecular weight of water vapor, M 空气 is the molecular weight of air, P 饱和 is the saturated water vapor pressure, RH is the relative humidity, T c is the water vapor temperature, t is the working time, and ln(·) is the logarithmic function.

[0082] In this embodiment of the present invention, S4 includes the following sub-steps:

[0083] S41, obtaining a circuit topology structure of the electronic component;

[0084] S42. Construct an overall reliability assessment model for the electronic component based on the circuit topology, electrical parameters, and temperature parameters of the electronic component.

[0085] In this embodiment of the present invention, S5 includes the following sub-steps:

[0086] S51, generating a relationship curve between mean time before failure and temperature for the electronic component according to electrical parameters, temperature parameters and an overall reliability evaluation model of the electronic component;

[0087] S52. Based on the relationship curve between the mean time before failure and the temperature, an optimization model is constructed.

[0088] S5 is a digital-oriented electronic component reliability design and optimization. It uses digital technology to optimize the reliability of electronic components and proposes optimization solutions based on failure models and cost models. By optimizing the life, performance and cost-effectiveness of the system, it ensures the efficient and stable operation of the product under various working conditions and reduces potential risks in the design and production process.

[0089] In the embodiment of the present invention, the constraint conditions and objective functions of the reliability design of electronic components are constructed to obtain the best model combination scheme of components. Generally, the reliability design factors (failure rate and reliability, etc.) of the electronic components and other design factors (cost, quality and volume, etc.) are used as constraint conditions and objective functions, and the reliability design scheme is obtained by optimization. The optimization model includes a reliability design model with the optimization goal of minimizing the cost of the system and a reliability design model with the goal of maximizing the reliability of the electronic components.

[0090] In the embodiment of the present invention, the expression of the reliability design model with minimizing the cost of the system as the optimization goal is:

[0091]

[0092] Where θ* is the optimized reliability design solution, λ is the feasible solution of the failure rate of the selected components, Cost is the feasible solution of the cost of the selected components, Cost is the total cost, and Cost j is the cost of the jth type of components, λ j is the failure rate of the jth type of components, λ j,min is the lower limit constraint of the failure rate of the optional models of the j-th type of components, λ j,max is the upper limit constraint on the failure rate of the optional models of the j-th type of components, λ s is the failure rate of electronic components under feasible solutions, λ s,min is the lower limit constraint of the failure rate of electronic components, Cost j,min is the lower bound constraint on the cost of the j-th type of components, Cost j,max is the upper limit constraint on the cost of the j-th type of components, α j is the cost function fitting coefficient, w j are the coefficients of the cost function fitting exponential.

[0093] In the embodiment of the present invention, the expression of the reliability design model with the goal of maximizing the reliability of electronic components is:

[0094]

[0095] Where θ* is the optimized reliability design solution, λ is the feasible solution of the failure rate of the selected components, Cost is the feasible solution of the cost of the selected components, λ is the failure rate of the electronic component, f(λ) is the functional relationship between the failure rate of the electronic component and the failure rate of the component, and λ j is the failure rate of the jth type of components, λ j,min is the lower limit constraint of the failure rate of the optional models of the j-th type of components, λ j,max is the upper limit constraint on the failure rate of the optional models of the j-th type of components, λ s,min is the lower limit constraint of the failure rate of electronic components, Cost j is the cost of the jth type of components, Cost j,min is the lower bound constraint on the cost of the j-th type of components, Cost j,max is the upper limit constraint on the cost of the j-th type of components, α j is the cost function fitting coefficient, w j are the coefficients of the cost function fitting exponential.

[0096] The present invention is described below in conjunction with specific embodiments.

[0097] S1. Clarify product functions and reliability design indicators.

[0098] First, the functional requirements and reliability design indicators of the electronic components in the power supply system are clarified. Taking a power supply system as an example, the Buck-Boost circuit is its key component circuit (the circuit schematic diagram is shown in Figure 2 As shown in the figure, the working environment temperature is determined to be 25℃, and the circuit mean time to failure (MTTF)

[0099] ≥200000h, the total cost of key components such as resistors, capacitors, inductors, integrated circuits, switches and PCBs is less than 120 yuan, and the reliability of the product is required to be maximized within the cost range.

[0100] S2. Construct a digital reliability assessment model for components.

[0101] Construct a reliability digital model of electronic component parts. Buck-Boost circuits contain components such as resistors, capacitors, solder joints, diodes, switches, fuses, integrated circuits, and PCBs. This section describes the reliability digitalization method of the core components in the Buck-Boost circuit. To simplify the description, in this example, only the reliability digital processing of key core components (resistors, capacitors, inductors, integrated circuits, and switches) is analyzed at the reliability digitalization level of components, and only the reliability digital processing of printed circuit boards is analyzed at the reliability digitalization level of other components.

[0102] S21. Build a digital model of the reliability of resistors. The failure modes are mainly open circuit and resistance drift. The main manifestation is that the resistance value gradually increases or even opens, causing the circuit to fail to work properly. The failure mechanism of resistors is usually closely related to the operating temperature and working time. Especially in a long-term high temperature environment, the molecular structure of the resistor material may change, resulting in resistance drift. The degradation process is analyzed through the Arrhenius model.

[0103] S22. Build a digital model of capacitor reliability. The failure mode of electrolytic capacitors is mainly manifested in the decrease of capacitance and the increase of equivalent series resistance. Especially under high temperature and long-term working conditions, the evaporation of electrolyte and internal chemical reactions will lead to failure. The decrease in capacitance will affect the filtering and energy storage performance of the circuit, resulting in circuit instability. The degradation process of electrolytic capacitors is described by the Arrhenius model, and the formula is:

[0104] S23. Construct a digital reliability model for inductors. The failure mechanism of inductors is mainly related to their temperature rise under high-frequency working conditions. High temperature will cause the insulation material of the coil to age, which will in turn cause the inductance value to decrease, ultimately affecting its filtering and energy storage functions. When the inductance value drops below 20% of the initial design value, the inductor is considered to have failed. Generally, the digital reliability model of the inductor is

[0105] S24. Construct a digital reliability model for the switch tube. Taking the metal oxide semiconductor field effect tube as an example, the failure mode of the switch tube is mainly reflected in the increase of on-resistance. Especially under high temperature and high voltage working environment, the performance of semiconductor materials gradually degrades, the on-resistance increases, causing the device to heat up, power consumption increases, and even thermal runaway. Its degradation physical model is described as

[0106] S25. Build a digital reliability model for integrated circuits. The main failure modes of integrated circuits include electromigration of metal interconnects and breakdown of oxide layers, which are particularly significant at high temperatures. The Arrhenius model is used to predict the life of integrated circuits. Specifically,

[0107] S26. Build a digital reliability model for PCB. The failure of PCB is mainly manifested in thermal fatigue of plated through holes, corrosion of conductive paths and material aging. Especially in a humid environment, moisture penetration may cause tin whiskers and silver migration, resulting in short circuits or poor contact. The degradation model is

[0108] S3. Digital acquisition of component parameters based on multi-physics field coupling simulation.

[0109] Based on the digital model of the components obtained in step S2, the digital input of the model parameters is completed through the coupling simulation of multiple physical fields, and the reliability evaluation can be completed by combining the reliability prediction method of the electronic components. Specifically, through the analysis of the reliability digital model in step S2, it is found that the reliability of most components is related to electrical parameters and temperature parameters. Therefore, it is determined that the multi-physical field coupling simulation model constructed in the example is mainly a simulation model that couples the electric field and the temperature field. By studying the interaction of different physical fields, revealing the degradation mechanism of components, and evaluating their reliability under extreme conditions, the digital reliability evaluation results of electronic components are finally completed.

[0110] S31, build a circuit simulation model and obtain electrical parameters. First, Figure 2 As shown in FIG. 1 , a simulation model of the Buck-Boost main circuit is constructed. The circuit is simulated and analyzed using circuit simulation software to extract the electrical parameters of key components, such as current, voltage, and power dissipation, and obtain the electrical parameter levels of the components under actual working conditions as the attribute parameters of the next step S32.

[0111] S32, establish a finite element model and perform electrothermal coupling simulation. Next, construct a finite element model of the electronic component, such as Figure 3 As shown, the electrical parameters are imported into the finite element analysis software. According to the geometric and material properties of the components, a thermal-electric coupling model is established, and the electrical parameters in S31 are imported into the finite element model to determine the power consumption and other properties of the components. Furthermore, the temperature distribution of the electronic components under different working conditions is obtained through electrothermal coupling simulation, such as Figure 4 shown.

[0112] S33. Store simulation data and analyze multi-physics coupling effects. Store the electrical and thermodynamic parameters obtained from the simulation into the database, and analyze the effect of multi-physics coupling on components by combining the simulation results of electrothermal coupling. Evaluate the effect of temperature and stress interaction on component failure modes.

[0113] S4. Construct a digital evaluation model for the reliability of electronic components.

[0114] According to the circuit topology of electronic components, a reliability assessment model is constructed, such as a calculation model for the basic failure rate of electronic components. The reliability characteristics of components are generally related to factors such as price, cost, and volume, so the key information of the selected components is sorted out. Referring to GJBZ299C-2006 "Electronic Equipment Reliability Prediction Manual", the basic failure rate λ of components is calculated. i,0 The reliability evaluation model of the components and electronic assemblies obtained above is used as the input information of step S5, so as to carry out the digital reliability evaluation and design of the electronic assemblies in combination with the component parameters of step S3.

[0115] according to Figure 2 The Buck-Boost circuit topology structure can be obtained as R S =R C1 (1-(1-R R1 )(1-R R2 ))R L R D1 R D2 R Q1 R Q2 R PCB Where R S is the reliability of electronic components, R j is the reliability of each component. Since the life of electronic components follows an exponential distribution, the reliability of component j is R j =exp(-λ j t)=exp(-t / MTTF j ), where λ j is the failure rate of component j, MTTF j is the mean time before failure of component j, and t is the working time.

[0116] Conduct market research on optional models of components. To simplify the description, three optional samples are selected for each type of component. The relationship between the reliability index and price of each sample is shown in Table 1, where MTTF0 refers to the average time before failure of the sample under standard working conditions.

[0117] Table 1

[0118]

[0119] The price of a sample and its reliability index (reliability, mean time before failure, etc.) generally have an exponential function relationship. The cost of a certain type of component and its reliability index can be fitted and analyzed using the following formula: In the formula, α j and ω j is the parameter that characterizes the inherent characteristics of the j-th type of component; j It is the failure rate of components in normal working state. The relationship between component cost and reliability index is as follows Figure 5 shown.

[0120] S5: Reliability design of electronic components for digitalization.

[0121] Based on digital technology, the reliability design of electronic components is optimized to improve their reliability and performance. By establishing failure models and cost models of components, the system life and cost-effectiveness are optimized to ensure efficient and stable operation of products under complex working conditions. The specific implementation steps are as follows.

[0122] S51: Combined with steps S2 and S3, the relationship between component reliability index and component parameters is analyzed, with the goal of evaluating the actual reliability index of components under multi-physical field conditions. In this example, the reliability index of components is significantly related to temperature. Based on the information provided by the manufacturer and the reliability digital evaluation model in S2, the mean time to failure (MTTF) of components under multi-physical field conditions is established. t The relationship curve between ) and temperature is as follows Figure 6 As shown, the operating temperature of the components is extracted through S3 multi-physics field simulation.

[0123] S52: Construct a reliability design optimization model for digitalization.

[0124] The purpose of constructing the constraints and objective functions of the reliability design of electronic components is to obtain the best model combination scheme of components. Usually, the reliability design factors (failure rate and reliability, etc.) of electronic components and other design factors (cost, quality and volume, etc.) are used as constraints and objective functions, and the reliability design scheme is obtained through optimization.

[0125] In this example, the vector λ = {λ j} n The feasible solution for the failure rate of system components is represented by the vector Cost = {Cost j} nrepresents the feasible solution of reliability design (where j refers to the jth component and n is the total number of components). The digital reliability design problem of electronic components can be expressed as a combination of the feasible solution λ of the system structure and the feasible solution Cost of the failure rate of electronic components, denoted as: θ = {λ, Cost}. The total cost of electronic components Cost can be expressed as: Cost = ∑Cost j Based on the constructed digital-oriented reliability design optimization model, the optimized reliability design scheme θ* is solved.

[0126] According to the design goal determined by S1, taking maximizing reliability as the objective function, the reliability design model is: Finally, the comparison of the digital design schemes before and after optimization is shown in Table 2. Comparing the total price Cost before and after, the price of the optimized scheme reaches the design requirement of less than 120 yuan; comparing the reliability index 1 / λ before and after, that is, MTTF is improved from 2.29E+05 hours to 3.74E+05 hours. It can be seen that the optimized scheme not only reduces the total cost, but also improves the reliability index of the electronic components, thereby verifying the effectiveness of the present invention.

[0127] Table 2

[0128]

[0129] The above steps can obtain the reliability digital evaluation results and optimized design scheme of electronic components. The present invention realizes the evaluation and optimization of the reliability design of electronic components in the absence of a large amount of failure data through multi-physical field coupling simulation and digital modeling technology. The present invention first analyzes the degradation mechanism of each component under different physical field coupling conditions by constructing a digital reliability model of the components; then, based on the multi-physical field simulation model, key data such as temperature and electrical parameters of the components are obtained to evaluate their reliability performance under actual working conditions. Finally, the reliability evaluation results and optimization algorithms are combined to form an optimized electronic component design scheme, which significantly improves the overall reliability and economy of the system. Through the coupled simulation analysis of multi-physical fields, the present invention effectively reveals the key influencing factors in the degradation process of electronic components, and significantly improves the accuracy and applicability of reliability evaluation.

[0130] Those skilled in the art will appreciate that the embodiments described herein are intended to help readers understand the principles of the present invention, and should be understood that the protection scope of the present invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific variations and combinations that do not deviate from the essence of the present invention based on the technical revelations disclosed by the present invention, and these variations and combinations are still within the protection scope of the present invention.

Claims

1. A digital design method for electronic component reliability based on multi-physics field coupling simulation, characterized in that: The following steps are involved: S1. Obtain the working environment index and reliability design index of electronic components; S2. Construct a digital evaluation model for component reliability based on the working environment indicators and reliability design indicators of electronic components; S3. Processing the reliability digital evaluation model using a multi-physics field coupling simulation method to obtain electrical parameters and temperature parameters of the electronic components; S4. construct an overall reliability assessment model for the electronic component based on the electrical parameters and temperature parameters of the electronic component; S5. Build an optimization model for the overall reliability evaluation model of electronic components and complete the digital design of electronic component reliability.

2. The electronic component reliability digital design method based on multi-physics field coupling simulation according to claim 1 is characterized in that: In said S1, the working environment index of the electronic component includes the working temperature, voltage and power of the electronic component; In S1, the reliability design indicators include reliability, failure probability, failure rate and average life of the electronic components.

3. The electronic component reliability digital design method based on multi-physics field coupling simulation according to claim 1 is characterized in that: In said S2, the component reliability digital evaluation model includes a reliability digital model of a resistor, a reliability digital model of a capacitor, a reliability digital model of an inductor, a reliability digital model of a switch tube, a reliability digital model of an integrated circuit, and a reliability digital model of a PCB; The expression of the reliability digital model of the resistor is: Wherein, R is the first nominal value of the resistance value, ΔR is the second nominal value of the resistance value, T is the ambient temperature, t is the working time, B is the first model parameter, C is the second model parameter, D is the third model parameter, F is the fourth model parameter, and ln(·) is a logarithmic function; The expression of the reliability digital model of the capacitor is: Where, L C (T) is the capacitor life at ambient temperature, L C,0 is the inductor life at reference temperature, T0 is the reference temperature; The expression of the reliability digital model of the inductor is: Where, L I (T) is the inductor life at ambient temperature, L I,0 is the life of the inductor at the reference temperature, E a1 is the activation energy of the inductor material, k is the Boltzmann constant, and e is a natural constant; The reliability digital model of the switch tube is expressed as: Where, L S (T) is the life of the switch tube at ambient temperature, L S,0 is the life of the switch tube at the reference temperature, E a2 is the activation energy of the switch tube material; The expression of the reliability digital model of the integrated circuit is: Where, L IC (T) is the life of the integrated circuit at ambient temperature, L IC,0 is the lifetime of the integrated circuit at the reference temperature, E a3 is the activation energy of the integrated circuit material; The expression of the reliability digital model of the PCB is: Where D is the corrosion depth of the solder joint, V is the volume of the sealed cavity, e is a natural constant, P0 is the standard atmospheric pressure, Vp is the initial water vapor partial pressure difference, p is the water vapor partial pressure in the sealed cavity, and M 水汽 is the molecular weight of water vapor, M 空气 is the molecular weight of air, P 饱和 is the saturated water vapor pressure, RH is the relative humidity, T c is the water vapor temperature, t is the working time, and ln(·) is the logarithmic function.

4. The electronic component reliability digital design method based on multi-physics field coupling simulation according to claim 1 is characterized in that: The S4 comprises the following sub-steps: S41, obtaining a circuit topology structure of the electronic component; S42. Construct an overall reliability assessment model for the electronic component based on the circuit topology, electrical parameters, and temperature parameters of the electronic component.

5. The electronic component reliability digital design method based on multi-physics field coupling simulation according to claim 1 is characterized in that: The S5 comprises the following sub-steps: S51, generating a relationship curve between mean time before failure and temperature for the electronic component according to electrical parameters, temperature parameters and an overall reliability evaluation model of the electronic component; S52. Based on the relationship curve between the mean time before failure and the temperature, an optimization model is constructed.

6. The electronic component reliability digital design method based on multi-physics field coupling simulation according to claim 5 is characterized in that: The optimization model includes a reliability design model with minimizing the cost of the system as the optimization target and a reliability design model with maximizing the reliability of electronic components as the optimization target.

7. The electronic component reliability digital design method based on multi-physics field coupling simulation according to claim 6 is characterized in that: The expression of the reliability design model with the optimization goal of minimizing the system cost is: Where θ* is the optimized reliability design solution, λ is the feasible solution of the failure rate of the selected components, Cost is the feasible solution of the cost of the selected components, Cost is the total cost, and Cost j is the cost of the jth type of components, λ j is the failure rate of the jth type of components, λ j,min is the lower limit constraint of the failure rate of the optional models of the j-th type of components, λ j,max is the upper limit constraint on the failure rate of the optional models of the j-th type of components, λ s is the failure rate of electronic components under feasible solutions, λ s,min is the lower limit constraint of the failure rate of electronic components, Cost j,min is the lower bound constraint on the cost of the j-th type of components, Cost j,max is the upper limit constraint on the cost of the j-th type of components, α j is the cost function fitting coefficient, w j are the coefficients of the cost function fitting exponential.

8. The electronic component reliability digital design method based on multi-physics field coupling simulation according to claim 6 is characterized in that: The expression of the reliability design model aimed at maximizing the reliability of electronic components is: Where θ* is the optimized reliability design solution, λ is the feasible solution of the failure rate of the selected components, Cost is the feasible solution of the cost of the selected components, λ is the failure rate of the electronic component, f(λ) is the functional relationship between the failure rate of the electronic component and the failure rate of the component, and λ j is the failure rate of the jth type of components, λ j,min is the lower limit constraint of the failure rate of the optional models of the j-th type of components, λ j,max is the upper limit constraint on the failure rate of the optional models of the j-th type of components, λ s,min is the lower limit constraint of the failure rate of electronic components, Cost j is the cost of the jth type of components, Cost j,min is the lower bound constraint on the cost of the j-th type of components, Cost j,max is the upper limit constraint on the cost of the j-th type of components, α j is the cost function fitting coefficient, w j are the coefficients of the cost function fitting exponential.

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