Endurance test method for electronic controller

Abstract

The invention discloses a durability test method for an electronic controller, and particularly relates to the technical field of electronic equipment, and the method comprises the following steps: firstly, obtaining and installing an electronic controller sample on test equipment connected with a sensor and data recording equipment; then carrying out an accelerated aging experiment under an extreme condition, carrying out a normal operation experiment under a standard working condition, and respectively generating an accelerated aging data set and a normal operation data set; analyzing the data to generate an accelerated aging index and an operation fluctuation index; inputting the two indexes into a machine learning model to generate a durability coefficient; and finally, comparing the coefficient with a preset standard to judge whether the durability of the sample reaches the standard or not. According to the method, a mode of combining the accelerated aging index and the operation fluctuation index is adopted, the durability of the electronic controller is comprehensively evaluated, the overall performance of the controller in actual use can be more comprehensively reflected through combination of double indexes, and deviation possibly caused by single-index evaluation is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of electronic equipment, and more particularly to a durability testing method for an electronic controller. Background Art

[0002] In the design and manufacture of modern electronic equipment, electronic controllers are core components that undertake multiple key functions such as control, monitoring and communication. Therefore, the performance and durability of electronic controllers directly affect the stability and service life of the entire system. However, since electronic controllers often work in complex and changing environments, how to ensure their stability and reliability in long-term use has become an important research topic.

[0003] Existing durability test methods usually evaluate the performance of electronic controllers through single or limited environmental factors, which is difficult to fully reflect the durability performance of electronic controllers in actual use environments, because in real applications, electronic controllers are usually faced with the combined effects of multiple environmental factors. In addition, traditional test methods mostly rely on human judgment and lack systematic and automated evaluation methods, resulting in low accuracy and consistency of test results. Therefore, a durability test method for electronic controllers is proposed here. Summary of the invention

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] A durability testing method for an electronic controller comprises the following steps:

[0006] Step 1: Obtain an electronic controller sample and install it on a test device, which is connected to multiple types of preset sensors and data recording devices to monitor the performance of the electronic controller during the test;

[0007] Step 2: simulate the long-term use environment by setting extreme conditions and conduct accelerated aging experiments on the electronic controller samples, and summarize the data recorded by the data recording device into an accelerated aging data set;

[0008] Step 3: Simulate a long-term use environment under set standard working conditions and conduct a normal operation experiment on the electronic controller sample, and summarize the data recorded by the data recording device into a normal operation data set;

[0009] Step 4: Perform accelerated aging analysis based on the accelerated aging data set to generate an accelerated aging index, and perform normal operation analysis based on the normal operation data set to generate an operation fluctuation index;

[0010] Step 5: Substitute the accelerated aging index and the operation fluctuation index into the pre-trained machine learning model to generate a durability performance coefficient;

[0011] Step 6: Determine whether the durability performance of the electronic controller sample meets the preset standard based on the durability performance coefficient.

[0012] In a preferred embodiment, in the accelerated aging experiment and the normal operation experiment test, the electronic controller sample performs its designed function and goes through multiple operation cycles.

[0013] In a preferred embodiment, an operation cycle refers to the process in which the electronic controller sample repeatedly performs its normal working tasks during the experiment.

[0014] In a preferred embodiment, the logic for obtaining the accelerated aging index is:

[0015] The total time of the accelerated aging test, the functions of multiple preset environmental factors changing with time, and the decay rates of multiple preset performance indicators changing with time are obtained from the accelerated aging data set, and then substituted into the following calculation formula:

[0016] i is an index used to traverse all environmental factors, from the 1st environmental factor to the nth environmental factor, n is the total number of environmental factors, wi represents the preset influence coefficient of environmental factor i, γi represents the inherent characteristics of the material corresponding to the electronic controller under the influence of environmental factor i, ∈i represents the sensitivity of the material corresponding to the electronic controller to the environmental factor i under the influence of environmental factor i, T is the total time of the accelerated aging test, Ei(t) represents the function of environmental factor i changing with time, Di(t) represents the attenuation rate change function of the preset target performance indicator under the influence of environmental factor i with time t, and AAI represents the accelerated aging index.

[0017] In a preferred embodiment, the integration in the accelerated aging index calculation process is achieved by the trapezoidal method or the Simpson method.

[0018] In a preferred embodiment, the expression of the attenuation rate change function is:

[0019] Pi0 represents the initial value of the preset target performance indicator under the influence of environmental factor i at time t=0, and Pi(t) represents the current value of the preset target performance indicator under the influence of environmental factor i at time t.

[0020] In a preferred embodiment, the logic for obtaining the running volatility index is:

[0021] Obtain the maximum and minimum values ​​of each preset performance indicator from the normal operation data set, then calculate the difference between the maximum and minimum values ​​during the entire test period, and retain the performance indicators corresponding to the difference being greater than or equal to the preset screening threshold;

[0022] The retained performance indicators are marked as Pj, where j represents the number of the retained performance indicators. For each retained performance indicator Pj, its standard deviation σj during the test period is calculated, and the volatility of each performance indicator is measured using the ratio of the standard deviation to the fluctuation range:

[0023] Fj represents the volatility of performance indicator j, ΔPj represents the difference between the maximum and minimum values ​​of performance indicator j during the entire test period;

[0024] The volatility Fj corresponding to all retained performance indicators is weighted averaged to obtain the operating volatility index NFI.

[0025] In a preferred embodiment, the logic for obtaining the durability performance coefficient is:

[0026] The accelerated aging index and the operation fluctuation index are substituted into the pre-trained machine learning model. The machine learning model uses the linear regression model as a fitting tool, and the output result of the linear regression model is the durability performance coefficient.

[0027] In a preferred embodiment, judging whether the durability performance of the electronic controller sample reaches a preset standard based on the durability performance coefficient means:

[0028] The durability performance coefficient of the electronic controller sample is obtained, and then compared with the preset durability test range. If the durability performance coefficient of the electronic controller sample and the preset durability test range have an intersection, a normal signal is generated, indicating that the durability performance of the electronic controller sample meets the preset standard. If the durability performance coefficient of the electronic controller sample and the preset durability test range do not have an intersection, an abnormal signal is generated, indicating that the durability performance of the electronic controller sample does not meet the preset standard.

[0029] Technical effects and advantages of the present invention:

[0030] The present invention uses a combination of accelerated aging index and operation fluctuation index to comprehensively evaluate the durability of electronic controllers. The accelerated aging index reflects the performance degradation of the controller under extreme conditions, while the operation fluctuation index evaluates the stability of the controller under normal use conditions. This combination of dual indicators can more comprehensively reflect the overall performance of the controller in actual use, avoiding the deviation that may be caused by single indicator evaluation.

[0031] The present invention automatically generates a durability performance coefficient by inputting the accelerated aging index and the operating fluctuation index into a pre-trained machine learning model. The durability performance coefficient can be automatically compared with the preset durability standard to determine whether the sample meets the quality requirements. This process reduces human intervention, reduces judgment errors, greatly improves the efficiency and consistency of the evaluation, and is particularly suitable for quality control in large-scale production.

[0032] The present invention ensures the consistency evaluation of different batches and different samples through standardized testing and evaluation methods. The standardized judgment mechanism of durability performance not only improves the consistency of product quality, but also enhances the reliability of the entire production process. This method is particularly suitable for the production of electronic controllers that require high reliability, such as aerospace, automotive electronics and other key fields. By automatically comparing the durability performance coefficient of each electronic controller sample, the present invention can screen out products that do not meet the durability standards and prevent unqualified products from entering the market. This is of great significance for maintaining the brand reputation of the company and reducing after-sales risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0034] Figure 1 The schematic diagram of a durability testing method for an electronic controller in the present invention. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] Reference Figure 1 The following examples are obtained:

[0037] Embodiment 1: A durability test method for an electronic controller, comprising the following steps:

[0038] Step 1: Obtain an electronic controller sample and install it on a test device, which is connected to multiple types of preset sensors and data recording devices to monitor the performance of the electronic controller during the test;

[0039] Test plan development: First, develop a detailed test plan to identify the key functions of the electronic controller, the expected use environment, and the life goals. Select appropriate test conditions, including parameters such as temperature range, humidity, vibration frequency, voltage fluctuation, and operation cycle. Develop a test schedule and decide the type of data that needs to be collected during the test, such as voltage, current, temperature, response time, functional stability, etc.

[0040] Sample preparation and installation: Select representative samples of electronic controllers from the production line or batch and perform preliminary checks to ensure that they are working properly. Install these samples on the test equipment and connect the necessary sensors and data logging equipment to monitor the performance of the controllers during the test.

[0041] Step 2: simulate the long-term use environment by setting extreme conditions and conduct accelerated aging experiments on the electronic controller samples, and summarize the data recorded by the data recording device into an accelerated aging data set;

[0042] Accelerated aging testing: Start accelerated aging testing to simulate long-term use environments through set extreme conditions. Testing can include temperature cycling (such as repeated changes from extreme cold to extreme heat), vibration testing (simulating mechanical stress in operation), voltage fluctuations (testing controller performance when the power supply is unstable), and humidity testing (performance in high humidity environments). These conditions should be run at a planned time and frequency, and the performance of the controller should be continuously monitored throughout the process.

[0043] Intermediate checks and data recording: At different stages of the test, intermediate checks are performed to evaluate whether the controller functions properly. Relevant data such as voltage, current, response time and other parameters are collected and recorded.

[0044] During the accelerated aging experiment and normal operation experiment test, the electronic controller sample performs its designed functions and undergoes multiple operation cycles. The operation cycle refers to the process in which the electronic controller sample repeatedly performs its normal working tasks during the experiment, including but not limited to the following examples for easy understanding:

[0045] Function execution: Instruction processing: The controller is the abbreviation of the electronic controller sample, which receives and processes input signals or instructions. For example, it receives data from sensors and processes them, or controls mechanical or electrical equipment according to input instructions. Signal output: According to the processed data or instructions, the controller sends a control signal to drive the relevant equipment to perform corresponding operations. For example, it controls the start or stop of the motor, adjusts the operating status of the equipment, etc.

[0046] State switching: The controller switches between different working modes. For example, switching from standby mode to working mode and then switching back to standby mode. Each state switching may have an impact on the controller, and its stability in multiple switching needs to be tested.

[0047] Load changes: During an operation cycle, the controller may face different load conditions, such as different current, voltage or power requirements. These changes may cause different reactions in the internal circuits, and operation cycles are needed to evaluate the performance of the controller under various load conditions.

[0048] Temperature Cycling: The controller is run at different temperatures to test its performance at high and low temperatures and in rapid switching conditions.

[0049] Humidity Cycling: The controller operates under different humidity conditions to evaluate its tolerance in a humid environment.

[0050] Voltage stress cycling: The controller is operated under different voltage conditions, including rapid switching of voltage increases and decreases, to test its ability to withstand voltage fluctuations.

[0051] The "multiple" in the "multiple operation cycles" refers to repeated operations. In the experiment, the controller will repeatedly perform the same or similar operations to test its performance after long-term repeated operations. Each cycle represents a complete function execution, from receiving instructions, processing data to outputting results.

[0052] Step 3: Simulate a long-term use environment under set standard working conditions and conduct a normal operation experiment on the electronic controller sample, and summarize the data recorded by the data recording device into a normal operation data set;

[0053] Test condition setting: Unlike accelerated aging tests, normal operation tests are conducted under standard operating conditions. These conditions should be as close as possible to the typical operating state of the controller in the actual application environment. Factors including temperature, humidity, voltage, current, vibration, etc. should be set within the normal operating range rather than extreme values.

[0054] Sample selection and installation: Select representative electronic controller samples and install them in the test platform or actual application equipment to ensure that the environmental conditions are consistent with the actual use environment. As with the accelerated aging test, these samples should be equipped with sensors and data logging equipment to monitor their performance during the test.

[0055] Long-term operation test: Continuously operate the controller under standard conditions and record its performance. This is usually a long process that can last for weeks, months, or even longer. During the test, the controller should perform its designed functions and go through repeated operation cycles, such as switching, load changes, data processing, etc.

[0056] Regular inspection and data recording: During the test, check the controller's functionality regularly to ensure that it remains operational throughout the test. Record key parameters such as response time, voltage, current, temperature, etc. Compared with accelerated aging tests, these parameters should remain in a more stable range because the test conditions are closer to the actual use environment.

[0057] The logic for obtaining the accelerated aging index is:

[0058] The total time of the accelerated aging test, the functions of multiple preset environmental factors changing with time, and the decay rates of multiple preset performance indicators changing with time are obtained from the accelerated aging data set, and then substituted into the following calculation formula:

[0059] i is an index used to traverse all environmental factors, from the first environmental factor to the nth environmental factor. In the formula, the preset environmental factors that may affect the aging of the electronic controller are taken into consideration, such as temperature, humidity, voltage, vibration, etc. n is the total number of these different environmental factors, wi represents the preset influence coefficient of environmental factor i, γi represents the inherent characteristics of the material corresponding to the electronic controller under the influence of environmental factor i, ∈i represents the sensitivity of the material corresponding to the electronic controller to the environmental factor i under the influence of environmental factor i, T is the total time of the accelerated aging test, Ei(t) represents the function of the change of environmental factor i over time, and the value is the sampling value at time t, Ei(t) represents the change function of the preset target performance index under the influence of environmental factor i over time t, and the value is the decay rate value at time t, AAI represents the accelerated aging index. The larger the accelerated aging index, the faster the performance of the electronic controller decays in the accelerated aging test. This means that under extreme conditions (such as high temperature, humidity fluctuations, mechanical vibration, etc.), the key performance indicators of the controller (such as voltage stability, signal integrity, etc.) will decline more significantly. A higher AAI indicates that the controller may be more susceptible to failure or performance degradation under long-term use or extreme conditions.

[0060] The performance indicator attenuation rate Di(t) corresponding to Ei(t) corresponding to each environmental factor i is based on the specific environmental factor. For example, the attenuation rate D1(t) corresponding to temperature E1(t) reflects the attenuation of the performance of the electronic controller under different temperature conditions; the attenuation rate D2(t) corresponding to humidity E2(t) reflects the impact of humidity on the controller. Di(t) is a function of the attenuation rate change of a specific performance indicator (such as signal integrity, voltage stability, response time, etc.) of the electronic controller under a specific environmental factor i over time t. It indicates the degree of degradation of the performance indicator under the influence of the environmental factor over time. It describes how a certain performance indicator of the electronic controller changes over time under the influence of the specific environmental factor i. In the formula, a specific environmental factor corresponds to a specific performance indicator.

[0061] Suppose that the temperature tolerance of an electronic controller is being tested, and E1(t) is the time curve of the temperature change. In this case, D1(t) may represent the voltage stability decay rate of the controller under temperature conditions. As time t passes, the temperature increase may cause the voltage output to become gradually unstable, which is how D1(t) changes over time. If the effect of humidity is tested, E2(t) represents the time curve of humidity, and D2(t) may represent the signal integrity decay rate of the controller under humidity conditions.

[0062] In the accelerated aging experiment, a specific performance indicator of the controller can be measured regularly and its changes over time can be recorded. Then, these measured values ​​are compared with the initial values ​​to calculate the decay rate. The expression of the decay rate change function is:

[0063] Pi0 represents the initial value of the preset target performance indicator under the influence of environmental factor i at time t=0, and Pi(t) represents the current value of the preset target performance indicator under the influence of environmental factor i at time t.

[0064] γi represents the inherent characteristics of the material corresponding to the electronic controller under the influence of environmental factor i. It is a parameter related to the material characteristics in the electronic controller, reflecting the inherent characteristics of the material under the influence of specific environmental factors. It is usually a fixed value used to adjust the nonlinear response in the formula. In the accelerated aging index formula, γi is named as the material constant. The material constant γi is mainly used to adjust the attenuation rate of the controller when facing different environmental factors. For example, under high temperature conditions, the characteristics of a certain material may cause it to age faster or slower, which is reflected in the material constant γi. The material constant γi is usually obtained through experimental data or by consulting relevant literature. For example, a series of temperature tests can be performed on the material to determine the aging characteristics of the material at different temperatures. The environmental sensitivity coefficient ∈i represents the sensitivity of the material corresponding to the electronic controller to the environmental factor i under the influence of environmental factor i. The environmental sensitivity coefficient ∈i represents the sensitivity of the material of the electronic controller to a specific environmental factor (such as temperature, humidity, etc.), reflecting the response degree of the material when the environmental factor changes. The environmental sensitivity coefficient ∈i affects the attenuation rate in the formula, which is the performance intensity of the controller under a certain environmental factor i. It is used to adjust the degree of influence of environmental factors on material aging in the formula. If the environmental sensitivity coefficient ∈i is large, it means that the material is very sensitive to changes in environmental factor i, and its performance will change significantly with environmental fluctuations.

[0065] Integration is used to calculate the cumulative amount of a function within a certain interval. If the function Ei(t) is continuous, mathematical integration can be used directly. However, in actual testing, discrete test data points are usually obtained instead of a continuous function. Numerical methods are needed to approximate the integral. Numerical integration is a method used to approximate the integral, especially when there is only a set of discrete experimental data points. In this case, standard integral calculations cannot be performed directly, but numerical methods are needed to approximate. The integral in the accelerated aging index calculation process is implemented by the trapezoidal method or the Simpson method. The trapezoidal method divides the area under the function curve into multiple trapezoids and then calculates the sum of the areas of these trapezoids to approximate the integral value. The Simpson method divides the area under the function curve into multiple parabolic areas instead of simple trapezoids. Select the corresponding trapezoidal method or Simpson method according to the user's requirements for data accuracy. The Simpson method is more accurate than the trapezoidal method but occupies more computing resources.

[0066] Step 4: Perform accelerated aging analysis based on the accelerated aging data set to generate an accelerated aging index, and perform normal operation analysis based on the normal operation data set to generate an operation fluctuation index.

[0067] Acquire data from normal operating data sets: Under normal operating conditions, electronic controllers will continue to perform their designed functions and generate a series of operating data. This data usually includes key performance indicators of the controller, such as voltage, current, temperature, response time, etc. The data should be collected continuously over a period of time to capture the normal fluctuations of the system.

[0068] Select performance indicators to analyze: Select several key performance indicators from the normal operation data set for analysis. The selected indicators should reflect the core performance characteristics of the electronic controller, such as signal integrity, response time, voltage stability, etc. These indicators are the basis for the operation fluctuation index calculation.

[0069] The logic for obtaining the running volatility index is:

[0070] Logic for selecting performance indicators: Get the maximum and minimum values ​​of each preset performance indicator from the normal operation data set, then calculate the difference between the maximum and minimum values ​​during the entire test period, and retain the performance indicators whose difference is greater than or equal to the preset screening threshold;

[0071] The retained performance indicators are marked as Pj, where j represents the number of the retained performance indicators. For each retained performance indicator Pj, its standard deviation σj during the test period is calculated, and the volatility of each performance indicator is measured using the ratio of the standard deviation to the fluctuation range:

[0072] Fj represents the volatility of performance indicator j. This ratio represents the relative volatility of the performance indicator, that is, how much the performance indicator changes within the entire fluctuation range. ΔPj represents the difference between the maximum and minimum values ​​of performance indicator j during the entire test period.

[0073] The volatility Fj corresponding to all retained performance indicators is weighted averaged to obtain the operating volatility index NFI. The calculation formula is as follows:

[0074] vi represents the preset weight coefficient corresponding to the retained performance index j, which is used to balance the influence of different performance indexes j on the results, and N represents the total number of retained performance indexes. The higher the calculated NFI value, the greater the volatility and poorer the stability of the electronic controller under normal operating conditions. Conversely, a lower NFI value indicates that the controller is stable and has less volatility under normal operating conditions.

[0075] Step 5: Substitute the accelerated aging index and the operation fluctuation index into the pre-trained machine learning model to generate a durability performance coefficient. The logic for obtaining the durability performance coefficient is:

[0076] The accelerated aging index and the operation fluctuation index are substituted into the pre-trained machine learning model. The machine learning model uses the linear regression model as a fitting tool. The output result of the linear regression model is the durability performance coefficient. The linear regression model is expressed as:

[0077] DPC = β0-β1*NFI-β2*AAI; β1 and β2 are both positive values, which are used to adjust the influence of the corresponding parameters on the calculation results. β0 is the intercept term, which represents the durability performance coefficient when AAI = 0 and NFI = 0. It is the basic durability under certain ideal conditions. When AAI increases, it means that aging is accelerated and durability deteriorates, so DPC should be reduced, which is represented by the -β2*AAI term. When NFI increases, it means that stability and reliability deteriorate, and DPC should also be reduced, which is represented by the -β1*NFI term. The larger the durability performance coefficient DPC, the stronger the overall durability of the electronic controller. This coefficient combines the effects of the accelerated aging index and the operation fluctuation index, and reflects the overall performance of the controller under long-term use and various environmental conditions. A higher DPC means that the controller can maintain more stable performance and a lower failure rate under long-term operation and extreme conditions. Therefore, a larger DPC usually means that the controller has better durability and reliability.

[0078] Step 6: Determine whether the durability of the electronic controller sample meets the preset standard based on the durability performance coefficient. Obtain the durability performance coefficient of the electronic controller sample, and then compare it with the preset durability test range. If the durability performance coefficient of the electronic controller sample and the preset durability test range have an intersection, a normal signal is generated, indicating that the durability of the electronic controller sample meets the preset standard. If the durability performance coefficient of the electronic controller sample and the preset durability test range do not have an intersection, an abnormal signal is generated, indicating that the durability of the electronic controller sample does not meet the preset standard. The preset durability test range refers to a reasonable durability range defined in the experimental design or quality standard. This is usually based on industry standards, experimental data or product design requirements, indicating that the durability of a qualified product should be within this range. Through this judgment method based on the durability performance coefficient, the durability of the electronic controller can be automatically evaluated, reducing the error of human judgment. This is very important for improving efficiency and consistency in large-scale production or quality control processes. This method can help manufacturers quickly screen out products with insufficient durability on the production line, thereby avoiding putting unqualified products on the market. This is critical to maintaining product quality and brand reputation. By standardizing the judgment of durability performance, it is possible to ensure consistent evaluation of different batches and samples, and enhance the consistency and reliability of product quality.

[0079] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0080] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0081] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0082] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0083] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A durability test method for an electronic controller, characterized in that: The following steps are involved: Step 1: Obtain an electronic controller sample and install it on a test device, which is connected to multiple types of preset sensors and data recording devices to monitor the performance of the electronic controller during the test; Step 2: simulate the long-term use environment by setting extreme conditions and conduct accelerated aging experiments on the electronic controller samples, and summarize the data recorded by the data recording device into an accelerated aging data set; Step 3: Simulate a long-term use environment under set standard working conditions and conduct a normal operation experiment on the electronic controller sample, and summarize the data recorded by the data recording device into a normal operation data set; Step 4: Perform accelerated aging analysis based on the accelerated aging data set to generate an accelerated aging index, and perform normal operation analysis based on the normal operation data set to generate an operation fluctuation index; Step 5: Substitute the accelerated aging index and the operation fluctuation index into the pre-trained machine learning model to generate a durability performance coefficient; Step 6: Determine whether the durability performance of the electronic controller sample meets the preset standard based on the durability performance coefficient.

2. A durability testing method for an electronic controller according to claim 1, characterized in that: In the accelerated aging and normal operation tests, the electronic controller samples perform their designed functions and go through multiple operation cycles.

3. A durability testing method for an electronic controller according to claim 2, characterized in that: An operating cycle is the process by which an electronic controller sample repeatedly performs its normal operating tasks during an experiment.

4. A durability testing method for an electronic controller according to claim 3, characterized in that: The logic for obtaining the accelerated aging index is: The total time of the accelerated aging test, the functions of multiple preset environmental factors changing with time, and the decay rates of multiple preset performance indicators changing with time are obtained from the accelerated aging data set, and then substituted into the following calculation formula: i is an index used to traverse all environmental factors, from the 1st environmental factor to the nth environmental factor, n is the total number of environmental factors, wi represents the preset influence coefficient of environmental factor i, γi represents the inherent characteristics of the material corresponding to the electronic controller under the influence of environmental factor i, ∈i represents the sensitivity of the material corresponding to the electronic controller to the environmental factor i under the influence of environmental factor i, T is the total time of the accelerated aging test, Ei(t) represents the function of environmental factor i changing with time, Di(t) represents the attenuation rate change function of the preset target performance indicator under the influence of environmental factor i with time t, and AAI represents the accelerated aging index.

5. A durability testing method for an electronic controller according to claim 4, characterized in that: Integration during the calculation of the accelerated aging index is achieved using the trapezoidal method or the Simpson method.

6. A durability testing method for an electronic controller according to claim 5, characterized in that: The expression of the decay rate change function is: Pi0 represents the initial value of the preset target performance indicator under the influence of environmental factor i at time t=0, and Pi(t) represents the current value of the preset target performance indicator under the influence of environmental factor i at time t.

7. A durability testing method for an electronic controller according to claim 6, characterized in that: The logic for obtaining the running volatility index is: Obtain the maximum and minimum values ​​of each preset performance indicator from the normal operation data set, then calculate the difference between the maximum and minimum values ​​during the entire test period, and retain the performance indicators corresponding to the difference being greater than or equal to the preset screening threshold; The retained performance indicators are marked as Pj, where j represents the number of the retained performance indicators. For each retained performance indicator Pj, its standard deviation σj during the test period is calculated, and the volatility of each performance indicator is measured using the ratio of the standard deviation to the fluctuation range: Fj represents the volatility of performance indicator j, ΔPj represents the difference between the maximum and minimum values ​​of performance indicator k during the entire test period; The volatility Fj corresponding to all retained performance indicators is weighted averaged to obtain the operating volatility index NFI.

8. A durability testing method for an electronic controller according to claim 7, characterized in that: The logic for obtaining the durability performance coefficient is: The accelerated aging index and the operation fluctuation index are substituted into the pre-trained machine learning model. The machine learning model uses the linear regression model as a fitting tool, and the output result of the linear regression model is the durability performance coefficient.

9. A durability testing method for an electronic controller according to claim 8, characterized in that: Judging whether the durability performance of the electronic controller sample meets the preset standard based on the durability performance coefficient means: The durability performance coefficient of the electronic controller sample is obtained, and then compared with the preset durability test range. If the durability performance coefficient of the electronic controller sample and the preset durability test range have an intersection, a normal signal is generated, indicating that the durability performance of the electronic controller sample meets the preset standard. If the durability performance coefficient of the electronic controller sample and the preset durability test range do not have an intersection, an abnormal signal is generated, indicating that the durability performance of the electronic controller sample does not meet the preset standard.

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