Power supply monitoring method and system for vehicle lamp production

Abstract

The invention relates to the field of data processing, in particular to a power supply monitoring method and system for vehicle lamp production, and the method comprises the steps: presetting a power supply parameter model and setting an initial monitoring parameter threshold; secondly, data acquisition and preprocessing are carried out during testing; a dynamic stress factor is obtained based on the power supply pressure load borne by the tested vehicle lamp at each sampling moment, an adaptive tolerance coefficient is obtained based on a piecewise linear function of dynamic stress factor value domain distribution, a basic current tolerance percentage is obtained, and an adaptive dynamic current reference tolerance percentage is determined by combining the adaptive tolerance coefficient; further determining a reference current and obtaining a final self-adaptive dynamic current threshold based on the reference current; and finally, judging a result and outputting a report. According to the method, the dynamic stress factor is constructed to evaluate the power supply scene pressure, and the current monitoring threshold is adaptively adjusted in combination with the characteristics of the DUT and the scene pressure, so that intelligent fault diagnosis is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of data processing, in particular to a power supply monitoring method and system for vehicle lamp production. BACKGROUND

[0002] Vehicle lamp is a vital component of vehicle. With the development of automobile industry, LED vehicle lamp has become the mainstream choice of modern automobile lighting and signaling system due to its high efficiency, long service life, fast response speed, flexible design and other advantages. However, it must go through strict quality control during its production process, especially the reliability monitoring of the power supply system, to ensure its continuous, stable and safe operation in the complex and changeable actual vehicle operating environment.

[0003] During the actual operation of the vehicle, its electrical system is not a constant ideal power supply environment. For example, when the engine starts, the huge current consumed by the starter will cause the voltage of the vehicle power supply to drop sharply; when the high-power electrical appliances of the vehicle (such as air conditioning compressor, electric power steering, etc.) start or stop, it will cause voltage transient change on the power supply line, etc. These severe voltage fluctuations, high-frequency ripple, transient overvoltage / undervoltage and high-energy pulse will pose a severe test to the power supply system of the vehicle lamp.

[0004] At present, in the power supply monitoring link of vehicle lamp production, the traditional method usually includes functional test of vehicle lamp under power and certain time of aging test (or called lighting test), and when judging whether the parameters are qualified, the traditional method usually adopts fixed threshold range based on the rated working condition. However, in the dynamic process of severe voltage change, the instantaneous current, power and other parameters of the vehicle lamp will produce certain fluctuations which are acceptable within a certain range. If the fixed narrow threshold under static condition is still used, these normal transient responses will be easily misjudged as faults. On the contrary, if the fixed threshold is set too loose in order to avoid false positives, the small but continuous parameter abnormalities which appear under stable working condition and indicate early performance degradation or potential faults may not be effectively detected. SUMMARY

[0005] To solve the problem that the fixed threshold range is easy to cause misjudgment, the application provides a power supply monitoring method for vehicle lamp production in the first aspect, which comprises the following steps: applying a preset power supply parameter model to a measured vehicle lamp, and synchronously collecting operating parameters of the measured vehicle lamp, including input voltage and input current; calculating a dynamic stress factor based on the input voltage, which represents the load degree of the power supply scene of the measured vehicle lamp at each sampling time; obtaining an adaptive tolerance coefficient through a preset segmented function based on the value range distribution characteristics of the dynamic stress factor; obtaining the arithmetic mean and standard deviation of the working current of the measured vehicle lamp under a nominal working condition through pre-testing, multiplying the ratio of the arithmetic mean and the standard deviation by a set statistical coverage factor to obtain a basic current tolerance percentage; the product of the basic current tolerance percentage and the adaptive tolerance coefficient constitutes an adaptive dynamic current reference tolerance percentage; determining a reference current value of the measured vehicle lamp and combining the adaptive dynamic current reference tolerance percentage to obtain a reference current threshold interval; in response to the input current not being in the reference current threshold interval, it is determined that the measured vehicle lamp is abnormal.

[0006] The application dynamically quantifies the severity of the power supply scene, and combines the stability characteristics of the measured vehicle lamp, to realize real-time adaptive adjustment of the monitoring threshold. Compared with the traditional method of using a fixed threshold or limited static point testing, the application can more accurately and intelligently identify the real power supply performance and potential abnormalities of the vehicle lamp under complex dynamic electrical environments, significantly improve the accuracy, robustness and automation level of monitoring, and effectively reduce false positives and false negatives.

[0007] Further, the calculation method of the dynamic stress factor is as follows: ; Wherein represents the dynamic stress factor calculated at the sampling point ; represents the input voltage value at the sampling point ; represents the size of the set sliding window; represents the set sampling frequency; represents the average voltage value of the current test stage; represents the voltage standard deviation of the current test stage; represents the set reference fluctuation value; represents the set time constant.

[0008] The application can more comprehensively and objectively represent the dynamic stress of the power supply scene by quantifying the relative size of the voltage change rate and the deviation degree respectively, normalizing the inherent voltage statistical characteristics of the current test stage, and integrating through L2 norm, avoiding the dependence on experience weight, and the calculation result provides a more reliable basis for subsequent adaptive adjustment. Compared with the method of simply using the voltage absolute value or the fixed change rate threshold, the evaluation is more accurate.

[0009] Further, the calculation method of the adaptive tolerance coefficient is specifically: ; Among them represents the adaptive tolerance coefficient calculated at the sampling point ; represents the dynamic stress factor calculated at the sampling point ; and respectively represent the low stress threshold and the high stress threshold set by statistical analysis of the data of the reference qualified sample under various working conditions, and the reference qualified sample refers to the same model vehicle lamp that meets the power supply test requirements. represents the maximum value of the adaptive tolerance coefficient set.

[0010] The application links the key parameters (segmented threshold) of the adaptive tolerance coefficient with the statistical distribution characteristics of the dynamic stress factor of the reference qualified sample in the actual test scene, so that the tolerance adjustment mechanism can better adapt to the stress range of the specific test scheme and the typical response characteristics of the DUT. Compared with the method of using fixed gain or relying on complex nonlinear functions with uncertain physical meaning for tolerance adjustment, the parameter determination of the method has more objective basis, stronger scene adaptability, and is easy to understand and implement.

[0011] Further, the reference current value is determined according to at least one of the following ways: based on the V-I characteristic mathematical model of the measured vehicle lamp; or based on the fitting function constructed based on the measured current data of the reference qualified sample under the same test sequence and corresponding input voltage as the measured vehicle lamp; or based on the simplified constant power model of the measured vehicle lamp under the current main working mode; or using the nominal working current of the current test stage.

[0012] Further, the calculation method of the basic current tolerance percentage is specifically: ; Among them represents the average value of the working current of the measured vehicle lamp under the nominal working condition; represents the standard deviation (A) of the working current of the measured vehicle lamp under the nominal working condition.​​​ represents a set statistical coverage factor.

[0013] The application takes the current fluctuation characteristics of the measured object itself under ideal stable working conditions as the basis for setting the tolerance, so that the initial accuracy reference of the monitoring directly comes from the inherent electrical characteristics of the DUT. Compared with the method of using industry general fixed tolerance value or purely relying on the experience of engineers, the basic tolerance determined by the method is more targeted and objective, and can better distinguish the normal background noise of the DUT itself from the real abnormal signal.

[0014] Further, the calculation method of the reference current threshold interval is specifically: ; ; wherein and represent the threshold upper limit and the threshold lower limit of the reference current threshold interval calculated at the sampling point ; represents the reference current value at the sampling point ; represents the adaptive dynamic current reference tolerance percentage at the sampling point ; represents the set absolute minimum current lower limit.

[0015] Further, the pre-set power supply parameter model includes at least one basic power supply curve selected from an engine cold start curve, a normal operation curve with alternating current ripple, a load sudden unloading overvoltage pulse curve, or a continuous overvoltage / undervoltage curve, or a composite test sequence formed by combination of these basic power supply curves.

[0016] The application tests the vehicle lamp by using a standardized or specific voltage waveform that can reflect the real harsh working conditions of the vehicle, which can more comprehensively expose the potential defects and design margin problems of the vehicle lamp under various expected electrical stresses compared with the traditional method of testing only at the rated voltage or a limited number of static voltage points, thereby more effectively evaluating the reliability of the vehicle lamp in the actual use environment.

[0017] Further, it further includes a pre-processing operation on the operating parameters, specifically, digital filtering of the originally collected voltage and current signals to remove noise, unit conversion of the temperature sensor signal, and calculation of instantaneous power according to the pre-processed voltage and current.

[0018] Further, the method further comprises optionally performing pattern matching between the identified characteristics of the persistent abnormal event and a pre-constructed fault feature database to preliminarily classify or diagnose the possible cause of the abnormal event; the persistent abnormal event refers to an abnormality of the DUT (Device Under Test) lamp lasting for more than a certain set time.

[0019] In a second aspect, the present application provides a power supply monitoring system for vehicle lamp production, comprising a processor and a memory, wherein the memory stores computer program instructions which, when executed by the processor, implement a power supply monitoring method for vehicle lamp production of the present application.

[0020] The technical effects of the present application are: Firstly, the present application innovatively evaluates the dynamic change rate and deviation degree of the power supply voltage currently borne by the DUT in real time and quantitatively by constructing a dynamic stress factor, thereby accurately characterizing the severity of the test scene; secondly, based on this scene dynamic stress factor and in combination with the threshold obtained from the actual scene data statistics, the present application introduces an adaptive tolerance coefficient to realize dynamic adjustment of the monitoring parameter tolerance with the change of the scene stress, thereby overcoming the limitations of fixed tolerance; thirdly, the present application also considers the inherent characteristics of the DUT, and by pre-determining the basic current tolerance percentage of the DUT under ideal stable working conditions, the adaptive dynamic monitoring threshold is not only adapted to the change of the external power supply scene, but also takes into account the internal stability difference of the DUT individual or model; finally, the present application can form a completely adaptive dynamic current threshold, thereby significantly improving the detection accuracy and robustness of the vehicle lamp power supply abnormality under complex dynamic electrical environment, and effectively reducing false positives and false negatives. BRIEF DESCRIPTION OF DRAWINGS

[0021] Figure 1 FIG. 1 is a flow chart of a power supply monitoring method for vehicle lamp production according to an embodiment of the present application; Figure 2 FIG. 2 is a preset power supply model according to an embodiment of the present application; Figure 3 FIG. 3 is a preset power supply model according to an embodiment of the present application; Figure 4 FIG. 4 is a preset power supply model according to an embodiment of the present application; Figure 5 FIG. 5 is a preset power supply model according to an embodiment of the present application; Figure 6 FIG. 6 is a structural block diagram of a power supply monitoring system for vehicle lamp production according to an embodiment of the present application. DETAILED DESCRIPTION​​​​

[0022] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative effort belong to the scope of the present application.

[0023] The specific implementation of the present application will be described in detail below with reference to the drawings.

[0024] A power supply monitoring method for vehicle lamp production embodiment: As Figure 1 shown, a power supply monitoring method for vehicle lamp production of the present application includes: S1, presetting a power supply parameter model and setting an initial monitoring parameter threshold.

[0025] Before actual power supply monitoring of the measured vehicle lamp DUT, a power supply parameter model capable of scientifically and comprehensively simulating the electrical system characteristics of the vehicle under various actual operating conditions needs to be constructed in the embodiment. This model not only defines the voltage excitation form applied to the DUT, but also specifies the reference and threshold for evaluating the DUT response, and is the basis of the entire monitoring method.

[0026] S1.1, define a set of basic power supply curves.

[0027] In order to comprehensively simulate the electrical environment of the vehicle, a series of standard or typical vehicle power supply operating conditions are first collected and defined in the embodiment to form a set of basic power supply curves . Each basic power supply curve represents a specific power environment operating condition of the vehicle, and its waveform characteristics are defined by a set of accurate parameters.

[0028] In the embodiment, several representative basic power supply curves can be set, specifically including: : an engine cold start curve as Figure 2 shown. This curve simulates the dramatic change of the vehicle's on-board power supply voltage when starting the engine in a low temperature environment (for example, -20℃). Its characteristic parameters can include: the initial voltage before starting (for example, 12.5V); the voltage drops to the lowest (for example, 6.0V) when the starting motor is involved; the duration of the lowest voltage (for example, 100ms); the time required for the voltage to recover to the idle charge stable state (for example, 200ms); and the target stable voltage after recovery (e.g. 13.8V). The expected average voltage for this steady stage is , and the expected voltage standard deviation is

[0029] : The normal operation with AC ripple curve as shown in Figure 3 . This curve models the AC ripple commonly found in DC power supply networks due to rectification and load variations, etc. when the vehicle generator is operating normally. Its characteristic parameters can include: the nominal DC operating voltage (e.g. 13.8V); the superimposed sinusoidal ripple peak-to-peak value (e.g. 0.5V, corresponding to an amplitude = 0.25V); and the ripple frequency (e.g. 100Hz). The expected average voltage for this stage is , and the expected voltage standard deviation can be calculated from the ripple amplitude, e.g. for a sinusoidal ripple, .

[0030] : The Load Dump overvoltage pulse curve as shown in Figure 4 . This curve refers to Pulse 5a (or 5b, depending on the vehicle electrical system design, e.g. whether a centralized suppression strategy is employed) in ISO 7637-2 standard, modeling the destructive high-energy overvoltage pulse generated when the battery connection is suddenly broken (e.g. due to corrosion or accidental disconnection) while the generator is still charging the battery. Its characteristic parameters can include: the pulse peak voltage (e.g. up to 87V for a 12V system); the pulse exponential rise time (usually defined as the time from 10% to 90% of the peak value) (e.g. 0.5ms); the pulse exponential decay duration (usually defined as the time from peak to 10% or 50% of the peak value) (e.g. 400ms to 10% of the peak value); and the source internal resistance (e.g. 0.5Ω to 4Ω) modeling the vehicle wiring harness and generator internal resistance. The voltage transient of this model is extremely severe, with both and being large and can be obtained by mathematical analysis or simulation of the standard pulse waveform, e.g. assuming an equivalent average voltage of about 35V and a voltage standard deviation of up to 30V within the analysis window.

[0031] :like Figure 5 The diagram shows a sustained overvoltage / undervoltage curve. This curve simulates a prolonged deviation of the supply voltage from the normal range due to a generator voltage regulator malfunction or other electrical system anomalies. Its characteristic parameters may include: abnormal voltage values. (Can be an overvoltage value) For example, 18V; or undervoltage value (e.g., 9V); and the duration of the abnormal voltage. (For example, 60 seconds). The expected average voltage during this phase. That is Its expected voltage standard deviation Theoretically close to 0 (also usable) ).

[0032] S1.2 Construct a composite test sequence.

[0033] To more realistically reflect the continuity and multi-condition combination characteristics of vehicle operation, it is possible to... Select one or more basic power supply curves and combine them into one or more composite test sequences according to a certain logical order (e.g., simulating a vehicle from startup, normal driving, encountering a specific electrical event to possible system failure) or a specific test focus. .

[0034] In this embodiment, the aforementioned basic curves can be combined into a representative test sequence. Its composition order is as follows: → (lasts 5 minutes) → (Apply 3 independent pulses, 1 second apart) → (Continue for another 5 minutes) → (Select overvoltage here) (lasts 60 seconds) → (The last 5 minutes). The total duration of this sequence is approximately 16 minutes.

[0035] S1.3 Set the initial monitoring parameter threshold.

[0036] For the electrical specifications of the tested vehicle headlight DUT (such as rated operating voltage) Rated current consumption or rated power And the maximum permissible operating temperature of its internal key components such as the LED driver IC. (etc.), requiring the entire testing process or composite test sequence. Preset corresponding monitoring parameter initial threshold sets for different stages These initial thresholds are primarily used to detect catastrophic, obvious failures.

[0037] Example illustration: A 12V, 30W LED headlight DUT exists, with a rated current of approximately Assuming the driver IC's datasheet specifies the maximum allowable case temperature. Considering design and testing margins, this embodiment sets an absolute temperature limit for the driver IC during monitoring. In addition, certain absolute electrical parameter limits should be set, such as an absolute current limit. (Twice the rated current), absolute power limit (twice the rated power). These initial, relatively lenient thresholds are primarily intended to prevent immediate damage to the DUT during testing and to record very serious deviations.

[0038] All these preset power supply parameter models (including) Detailed characteristic parameters of each curve are as follows: (etc.), selected composite test sequences The structure and the initial monitoring parameter threshold set (like All parameters (such as those for testing and data processing) will be digitized and stored in the central control computer system. This complete set of preset parameters constitutes the precise instruction set for subsequent test execution and the data reference system for preliminary evaluation.

[0039] S2. Data acquisition and preprocessing during testing.

[0040] After constructing the power supply parameter model and initial evaluation benchmark characterizing the complex electrical environment of the vehicle in step S1, the next step is to place the vehicle headlight DUT under these simulated environments and use high-precision sensors and data acquisition systems to accurately and synchronously capture its key electrical and thermal response parameters during the testing process. This step is the foundation for subsequent advanced data analysis, and the accuracy, completeness, and effectiveness of its data acquisition and preprocessing directly affect the reliability and accuracy of the final diagnostic results.

[0041] First, the vehicle headlight DUT under test is connected to an automated test platform consisting of a programmable precision DC power supply (e.g., Chroma 62050P-100-100), a multi-channel data acquisition system (DAQ) (e.g., NI USB-6212), and corresponding voltage, current, and temperature sensors; then, the computer instructs the programmable power supply to perform the test according to the steps defined in step S1. Output voltage, and simultaneously instruct DAQ to use a preset sampling frequency. (e.g., 10kHz) Synchronously acquire the input voltage of the DUT. Input current and driving IC temperature sensor signal; then in order to eliminate noise, convert engineering units and calculate necessary derived parameters, a series of preprocessing operations are needed, including sliding average filtering of the original voltage, current signals to get smoothed voltage and current , converting the voltage signal output by the temperature sensor into Celsius and performing cold junction compensation (CJC) to eliminate the influence of ambient temperature on measurement accuracy to get temperature ; finally, based on the smoothed voltage and current data, the instantaneous input power of the DUT is calculated point by point . After the above series of preprocessing operations, a set of time-aligned, low-noise data sets are obtained The above preprocessing operations are known techniques and will not be described here.

[0042] S3, based on the power supply stress load borne by the measured car lamp at each sampling time, obtain a dynamic stress factor; based on the piecewise linear function of the value range distribution of the dynamic stress factor, obtain an adaptive tolerance coefficient; obtain a basic current tolerance percentage and determine an adaptive dynamic current reference tolerance percentage according to the adaptive tolerance coefficient, determine a reference current and obtain a final threshold value based on the adaptive dynamic current reference tolerance percentage.

[0043] In step S2, the high-quality response data stream of the measured car lamp DUT under the simulated dynamic electrical environment is obtained and preprocessed. For a general test process, the quality of the car lamp DUT is determined by comparing the parameters in the data stream with the threshold values set in step S1, but in this embodiment, instead of simple threshold comparison, any potential power supply abnormality or early failure sign of the DUT under various complex working conditions is dynamically and intelligently identified, thereby overcoming the inherent defects of false positives (too sensitive) or false negatives (not sensitive enough) that often occur when traditional fixed threshold methods face dynamic scenes.

[0044] S3.1, based on the power supply stress load borne by the measured car lamp at each sampling time, obtain a dynamic stress factor.

[0045] In order to dynamically evaluate how much stress load the measured car lamp DUT bears at each sampling time from the power supply scene, a dynamic stress factor (Scenario Dynamic-stressFactor) is introduced in this embodiment. It aims to objectively and quantitatively evaluate the relative change rate of the power supply voltage currently applied to the DUT and the degree of deviation of the voltage value from its state at this test stage through mathematical methods.

[0046] is composed of two orthogonal stress components: voltage rate of change stress component and voltage deviation stress component . Before calculating these two components, the reference voltage statistical characteristics of the current test phase (corresponding to a certain basic power supply curve or its specific segment in S1) need to be determined first. These characteristics include: the expected average voltage of this phase, and the expected voltage standard deviation of this phase. These values can be directly extracted or calculated from the definition of each in S1 (for example, 0 for ideal DC, and the standard deviation can be calculated for the one with ripple). To prevent the denominator from being too small and causing instability in the calculation in the case of extreme stability tending to 0, a global minimum reference fluctuation (for example, 0.1% to 0.5% of the rated voltage , such as 0.05V) is introduced.

[0047] Voltage rate of change stress component is defined as: ; Voltage deviation stress component is defined as: ; The final comprehensive scenario dynamic stress factor is calculated by the Euclidean norm (i.e. L2 norm) of these two components to comprehensively reflect the overall stress size, which is: ; where represents the dynamic stress factor (dimensionless) calculated at sampling point ; represents the actual input voltage value (V) after preprocessing at sampling point ; represents the size of the sliding window used to calculate the voltage instantaneous rate of change (unit: number of sampling points), which can be set according to the system response characteristics and the expected transient speed to be captured, and in this embodiment it can be set to an empirical value of 5 sampling points; represents the sampling frequency of the data acquisition system (Hz), which in this embodiment can be set to an empirical value of 10000 Hz, then represents the actual time length corresponding to this sliding window; represents the expected average voltage value (V) of the test phase in which the current DUT is located; Vref represents the expected voltage standard deviation (V) at this stage, reflecting the degree of fluctuation the voltage should have at this stage; represents a globally set minimum reference fluctuation value (V) to ensure that at stages where the voltage should be completely constant in theory, the denominator is not zero, and provides a basic fluctuation measurement scale; represents a time constant, which in this embodiment can be set to the empirical value 1S, for maintaining dimensional consistency with the voltage rate of change stress component without changing the voltage deviation stress component.

[0048] represents the rate of change of the current input voltage and compares it with the stability the current test stage itself should have (embodied by ) and the selected observation time window . If the voltage changes dramatically in a short time ( ), or the current stage should be very stable (the in the denominator is small), the value of this component will significantly increase.

[0049] represents the degree to which the current input voltage value deviates from its central position in this stage (embodied by ), and also compares it with the stability the current stage itself should have. If the voltage instantaneous value is much higher or much lower than its stage average (the numerator is large), or the current stage should be very stable (the denominator is small), the value of this component will significantly increase.

[0050] combines the stress information of the above two orthogonal dimensions by squaring and square rooting (L2 norm). This means that whether the voltage changes extremely fast or the voltage deviates extremely, or both, its value will increase accordingly. It provides a comprehensive, quantitative indicator reflecting the dynamic electrical stress level of the DUT at any moment from the power supply scenario.

[0051] Example explanation: assume that the current test is at a certain moment of the sequence in the (load dump pulse) stage . According to the setting of in S1, it is a severe scenario of high voltage and fast transient. By analyzing the standard waveform of , it is known that its expected average voltage , expected voltage standard deviation , global minimum reference fluctuation Set to 0.05V, sliding window. Each sampling point, sampling frequency .exist The rapid rising edge of the pulse, assuming the control computer is at the sampling point Collected and preprocessed , and in front of it sampling points Therefore, we have: ; ; ; Calculated Value (approximately) The value is quite large, which objectively reflects the extremely high dynamic stress that the DUT is currently experiencing from the load unloading pulse.

[0052] S3.2 Obtain the adaptive tolerance coefficient based on the piecewise linear function of the dynamic stress factor value range distribution.

[0053] The magnitude of the tolerance coefficient indicates the severity or instability of the current power supply scenario. When the scenario stress is high, fluctuations in certain electrical parameters of the DUT (such as operating current) within certain limits may be considered normal responses rather than faults. Therefore, it is necessary to appropriately widen the normal fluctuation range of the parameters as the scenario stress increases, and further determine the adaptive tolerance coefficient. (Scene-Adaptive Tolerance Coefficient).

[0054] In this embodiment, based on The range distribution is generated by a piecewise linear function (or by looking up a table). Specifically, it is necessary to pre-analyze typical test sequences that include multiple operating conditions (such as those in this embodiment). When, the reference qualified sample produces The statistical distribution characteristics of the values, where the aforementioned benchmark qualified samples refer to the same model of vehicle lights that meet the power supply test requirements. Based on this distribution, several key parameters can be set. Threshold point. For example: Let... For low-stress scenarios Threshold, when Below this value, the scenario is considered very stable, and the tolerance does not need to be increased. This value can be taken as the baseline for qualified samples under stable operating conditions (such as...). )Down The higher quantiles of the distribution (e.g., the 80th or 90th percentile). Let... For high-stress scenarios Threshold, when When the value exceeds this, the scenario is considered to have reached or is close to its most demanding state, and the tolerance amplification should reach the preset upper limit. This value can be taken as the benchmark qualified sample under the most demanding operating conditions (e.g., )Down The higher quantiles of the distribution (e.g., the 95th or 98th percentile). The calculation formula (piecewise linear) is as follows: ; in Indicates at the sampling point The calculated adaptive tolerance coefficient (dimensionless). Indicates at the sampling point The calculated dynamic stress factor; and They represent low stress, respectively. Threshold and High Stress Threshold, determined by testing benchmark qualified samples under various operating conditions. The data was obtained through statistical analysis; This represents the maximum value that the tolerance factor can reach. In this embodiment, the upper limit empirical value can be set according to the design specifications of the DUT. This indicates that the tolerance can be expanded to a maximum of 2.5 times the basic tolerance.

[0055] when Very small, that is, when the scene is very stable ( ), This means that the basic tolerance is not amplified in any way, maintaining the most stringent monitoring; when When the stress threshold is between the low stress threshold and the high stress threshold ( ), Follow It increases linearly from 1 to [the value of ]. This means that as the scene stress increases, the allowable parameter fluctuation range gradually and proportionally widens; when Extremely high, meaning the scenario is extremely demanding ( ), Reach and maintain the preset upper limit This sets a maximum value for the tolerance amplification, preventing damage caused by extremely rare occurrences. This value leads to the tolerance being expanded indefinitely or unreasonably.

[0056] Exemplary illustration: Assuming that the benchmark qualified sample is used throughout... The results obtained by running under the test sequence Statistical analysis of the values ​​was performed, and the following settings were made: (for example in) Under stable operating conditions, most all far less than 100); (e.g. in Under the most severe working conditions such as load dump, most of all fall within 3500 or so) and set For the calculated value in the example of the previous step S3.1 Since , according to the formula, If at another sampling point , the calculated value is . Then: The value of can be calculated.

[0057] S3.3, Obtain the basic current tolerance percentage and determine the adaptive dynamic current reference tolerance percentage according to the adaptive tolerance coefficient, determine the reference current and obtain the final threshold value based on the adaptive dynamic current reference tolerance percentage.

[0058] Adjusting the tolerance only according to the scene stress is not comprehensive enough, because different models or even different batches of DUTs may have different parameter (such as current) fluctuation levels under ideal stable working conditions. Therefore, first, a basic current tolerance percentage that objectively reflects the stability level of the DUT needs to be determined; then, the dynamic addition is made to this basic tolerance to adapt to the current scene dynamic stress.

[0059] Place the measured vehicle lamp DUT under its rated input voltage (e.g. 12.0V, provided by a high-precision, high-stability programmable DC power supply, ensuring that the power supply itself has minimal output voltage fluctuation, such as <0.05%) and continuously work under standard ambient temperature (such as 25℃±2℃) for a period of time (e.g. 1 to 5 minutes, sufficient for the DUT to reach an electrothermal steady state).

[0060] During this stable working period, continuously collect the working current of the DUT at a high sampling frequency (such as in step S2). Perform statistical analysis on the collected stable current sequence , calculate its arithmetic mean and standard deviation . Then the characteristic-related basic current tolerance percentage of the DUT (or the model DUT) can be defined as: ; where represents the basic current tolerance percentage; This represents the average value (A) of the operating current of the DUT under the above ideal stable nominal operating conditions; It represents the standard deviation (A) of the operating current of the DUT under the above ideal stable nominal operating conditions, which directly reflects the degree of uncertainty of the current output of the DUT itself; This represents the statistical coverage factor, which is a constant typically chosen based on the desired statistical confidence interval. In this embodiment, it is taken as... When, for normally distributed data, It covers approximately 99.7% of the data points. This means... This defines the relative fluctuation range of the current that a DUT should experience for most of the time in its most stable state. The resulting adaptive dynamic current reference tolerance percentage is: ; in Indicates at the sampling point Adaptive dynamic current reference tolerance percentage (dimensionless). Indicates at the sampling point The calculated adaptive tolerance coefficient; The baseline current tolerance percentage reflects the stability characteristics of the DUT itself. Finally, the calculated adaptive dynamic current reference tolerance percentage will be used. Applied to a suitable reference current From this, the absolute upper and lower current thresholds can be obtained. For the reference current... There are many ways to determine it.

[0061] In one embodiment, if the precise mathematical model of the VI characteristics of the lamp under test (DUT) as a function of the input voltage is known... ,but In the second embodiment, if the DUT primarily exhibits constant power characteristics in most of its operating area ( Then, it can be approximately estimated. In the third embodiment, in step S1, one (or more) benchmark qualified samples that have been confirmed as fully qualified undergo the exact same test sequence as the DUT being tested. Record it in each (and possible) Current response under ) This data can be used to construct a lookup table (LUT) or fit an empirical function. Thus, for the tested DUT at any At any time, a corresponding value can be queried or calculated. .

[0062] The final threshold is: ; ; At the same time, in order to prevent the lower threshold from becoming negative or an impractical small value (e.g. for LEDs, current cannot be negative) in some cases (e.g. when the current is very small or very large), an absolute minimum current lower limit (e.g. 0.01A or DUT standby current) based on the DUT minimum operating current specification needs to be set. The actual lower limit is then: ; Where and represent the adaptive dynamic current upper and lower absolute thresholds (A) calculated at sampling point and finally used for comparison with the measured current ; represent the expected reference current value (A) at sampling point ; represent the adaptive dynamic current reference tolerance percentage at sampling point ; represent the set absolute minimum current lower limit (A).

[0063] The above formula converts the adaptive tolerance in percentage form into an absolute fluctuation range around the reference current . This range is considered as the normal current interval at the current time. When the scenario is stable, small, this interval is narrow and the monitoring is strict; when the scenario is severe, large, this interval is correspondingly widened and allows larger instantaneous current fluctuations without being judged as abnormal.

[0064] Exemplary illustration: for the LED headlamp DUT sample in this embodiment, after being powered on for 5 minutes under a 12.0V high-precision stable power supply and in a 25℃ environment, the working current data of the subsequent 1 minute is collected. Assuming that the analysis obtains: current mean , current standard deviation . Selecting a statistical coverage factor , then . Further obtaining calculated in step S3.2 (corresponding to a high-stress scenario of ), then , which indicates that at this particular high-stress moment, the allowed current relative fluctuation range is expanded from the basic about to about . ​​

[0065] That is, the current is still in the sampling point of the (load dump pulse) phase , Here, the Now need to determine For such an extreme high voltage transient of load dump, the current behavior of the DUT is usually dominated by its internal overvoltage protection (OVP) or current limiting circuit. It is assumed that by consulting the datasheet of the LED driver chip used by the DUT, it is known that when the input voltage is as high as 75V, its precise internal protection circuit will strictly limit the output current to a lower level to protect the LED lamp beads and itself from being damaged. For example, in this case, its input current should be controlled at or so. Therefore, the at this moment is set. At the same time, the global absolute minimum current lower limit is set. Then: ; .

[0066] Therefore, at this particular, extremely high stress sampling point of the input voltage up to 75.0V, the adaptive dynamic current monitoring window (i.e. "normal" range) calculated by the embodiment of the present application is .

[0067] S4, result determination and output report.

[0068] Compare the real-time current with the calculated and , if is out of this range, mark the transient abnormality. After marking the transient abnormality, track the continuity of the transient abnormality, if the continuous time exceeds the empirical value of 5ms, it can be confirmed as a persistent abnormal event. Optionally, it can be combined with power, temperature and other multi-parameter correlation analysis, or compared with the fault feature library to preliminarily diagnose the fault type. Automatically generate a structured report containing test configuration, DUT characteristic parameters, adaptive parameter setting, key data chart (or link), abnormal event details, final determination and basis.

[0069] An embodiment of a power supply monitoring system for vehicle lamp production: In another aspect, the present application also provides a power supply monitoring system for vehicle lamp production. As Figure 6As shown, a power supply monitoring system for vehicle lamp production comprises a processor and a memory, the memory storing computer program instructions which, when executed by the processor, implement a power supply monitoring method for vehicle lamp production according to the first aspect of the present application.

[0070] A power supply monitoring system for vehicle lamp production can further comprise other components such as a communication interface, which are well known to those skilled in the art, and thus will not be described in detail herein.

[0071] In the present application, the aforementioned memory can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device. For example, the computer-readable storage medium can be any suitable magnetic storage medium or magneto-optical storage medium, such as Resistive Random Access Memory (RRAM), Dynamic Random Access Memory (DRAM), Static Random-Access Memory (SRAM), Enhanced Dynamic Random Access Memory (EDRAM), High-Bandwidth Memory (HBM), Hybrid Memory Cube (HMC), etc., or any other medium that can be used to store the desired information and that can be accessed by an application, module, or both. Any such computer storage media can be part of the device or accessible or connectable thereto. Any applications or modules described in the present application can be implemented using computer-readable / executable instructions stored or otherwise held by such computer-readable media.

Claims

1. A power supply monitoring method for automotive lamp production, characterized in that, The method includes: A preset power supply parameter model is applied to the vehicle lamp under test, and the operating parameters of the vehicle lamp under test, including at least the input voltage and input current, are collected simultaneously. Based on the input voltage, a dynamic stress factor is calculated to characterize the power supply load of the tested vehicle lamp at each sampling time; based on the value range distribution characteristics of the dynamic stress factor, an adaptive tolerance coefficient is obtained through a preset piecewise function. The test lamp is pre-tested under nominal operating conditions to obtain the arithmetic mean and standard deviation of its operating current. The ratio of the arithmetic mean to the standard deviation is multiplied by a set statistical coverage factor to obtain the basic current tolerance percentage. The product of the basic current tolerance percentage and the adaptive tolerance coefficient constitutes the adaptive dynamic current reference tolerance percentage. The reference current value of the vehicle lamp under test is determined and combined with the adaptive dynamic current reference tolerance percentage to obtain the reference current threshold range; in response to the input current not being within the reference current threshold range, it is determined that the vehicle lamp under test is abnormal.

2. The power supply monitoring method for automotive lighting production according to claim 1, characterized in that, The specific method for calculating the dynamic stress factor is as follows: ； in Indicates at the sampling point The calculated dynamic stress factor; Indicates at the sampling point The input voltage value; This indicates the set size of the sliding window; This indicates the set sampling frequency; This indicates the average voltage value at the current testing phase; This indicates the standard deviation of voltage during the current testing phase; This indicates the set reference fluctuation value; This represents the set time constant.

3. A power supply monitoring method for automotive lighting production according to claim 1 or 2, characterized in that, The specific method for calculating the adaptive tolerance coefficient is as follows: ； in Indicates at the sampling point The calculated adaptive tolerance coefficient; Indicates at the sampling point The calculated dynamic stress factor; and These represent the results of testing the reference qualified samples under various operating conditions. Low stress was set based on statistical analysis of the data. Threshold and High Stress The threshold, the benchmark qualified sample refers to the same model of vehicle lamp that meets the power supply test requirements; This indicates the maximum value of the set adaptive tolerance coefficient.

4. A power supply monitoring method for automotive lighting production according to claim 1 or 3, characterized in that, The reference current value is determined according to at least one of the following methods: Mathematical model based on the VI characteristics of the tested vehicle lights; Alternatively, a fitting function can be constructed based on measured current data of a qualified benchmark sample under the same test sequence and corresponding input voltage as the vehicle lamp under test; Or based on a simplified constant power model of the tested vehicle headlights under the current main operating mode; Alternatively, the nominal operating current of the current testing phase can be used.

5. The power supply monitoring method for automotive lighting production according to claim 1, characterized in that, The specific method for calculating the basic current tolerance percentage is as follows: ； in This represents the average operating current of the tested vehicle lamp under nominal operating conditions; This represents the standard deviation (A) of the operating current of the tested vehicle lamp under nominal operating conditions; This indicates the set statistical coverage factor.

6. A power supply monitoring method for automotive lighting production according to claim 1 or 5, characterized in that, The specific method for calculating the reference current threshold range is as follows: ； ； in and Indicates at the sampling point The calculated upper and lower thresholds of the reference current threshold range; Indicates at the sampling point The reference current value; Indicates at the sampling point The percentage of the adaptive dynamic current reference tolerance; This indicates the set absolute minimum current lower limit.

7. The power supply monitoring method for automotive lamp production according to claim 1, characterized in that, The preset power supply parameter model includes: At least one basic power supply curve selected from engine cold start curve, normal operation with AC ripple curve, load unloading overvoltage pulse curve, or continuous overvoltage / undervoltage curve, or a composite test sequence formed by combining these basic power supply curves.

8. The power supply monitoring method for automotive lamp production according to claim 1, characterized in that, It also includes preprocessing the operating parameters, specifically: The system performs digital filtering on the raw voltage and current signals to remove noise, converts the temperature sensor signals to units, and calculates the instantaneous power based on the preprocessed voltage and current.

9. A power supply monitoring method for automotive lighting production according to claim 1, characterized in that, It also includes, optionally, pattern matching of the characteristics of confirmed persistent anomalies with a pre-built fault characteristic database to preliminarily classify or diagnose the possible causes of the anomalies. The term "persistent abnormal event" refers to an abnormality in the tested vehicle light that exceeds a certain set time.

10. A power supply monitoring system for automotive lighting production, characterized in that, It includes a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, it implements the power supply monitoring method for vehicle lamp production as described in any one of claims 1 to 9.

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