Intelligent monitoring method and system for LED vehicle lamp integrated circuit module

Abstract

This application relates to the field of LED automotive lighting technology, and discloses an intelligent monitoring method and system for LED automotive lighting integrated circuit modules. First, by evaluating the difference between the current temperature and historical temperatures, a predictive temperature change rate is quantified, and a forward-looking effective temperature is extracted to proactively predict thermal risks. Simultaneously, the cumulative operating time is quantified into an aging level and introduced into the device's full lifecycle health coordinates. Finally, a target current arbitration engine jointly adjudicates the effective temperature and aging level, dynamically generating a target drive current, thereby achieving precise and adaptive intelligent monitoring of the LED module under different operating conditions and aging stages.

Description

Technical Field

[0001] This application relates to the field of LED vehicle lighting technology, and more specifically, to an intelligent monitoring method and system for LED vehicle lighting integrated circuit modules. Background Technology

[0002] The performance of LED automotive lights, including their luminous flux, color temperature stability, and lifespan, is closely related to the operating status of their core integrated circuit modules, especially their operating temperature and the degree of aging caused by long-term use. On the one hand, excessively high junction temperatures can directly lead to a decrease in the luminous efficacy of LED chips, color shift, and even permanent damage in extreme cases, thus seriously affecting driving safety at night or in inclement weather. On the other hand, with the increase in cumulative operating time, LEDs inevitably experience light decay, i.e., aging, which causes their luminous intensity to gradually decrease. Therefore, in order to ensure that LED automotive lights provide stable, reliable, and safety-compliant lighting throughout their entire lifespan, building a solution that can accurately monitor and intelligently regulate the operating status of their integrated circuit modules has become a key technical problem that urgently needs to be solved in the automotive electronics field.

[0003] To address these needs, existing technologies mostly employ basic thermal protection strategies, such as placing a temperature sensor on the heat sink substrate. When the temperature exceeds a preset threshold, thermal foldback is triggered, reducing the drive current to control the temperature. However, this method has significant shortcomings: First, it is a passive response, intervening only after the temperature exceeds the limit. In dynamic conditions such as sudden temperature rises, it is prone to instantaneous overshoot due to response lag, making it difficult to effectively protect the LED. Second, it ignores the impact of LED aging factors and does not consider the differences in the device's response to temperature and current at different aging stages. Severely aged LEDs may require a more conservative drive strategy even at lower temperatures. Current solutions separate temperature management from aging status, lacking multi-dimensional coordinated control. This results in management strategies that are either too conservative, limiting performance, or too aggressive, accelerating aging, making it difficult to achieve the optimal balance between performance, lifespan, and reliability. Summary of the Invention

[0004] To address the aforementioned technical problems, this application is proposed. Embodiments of this application propose an intelligent monitoring method and system for LED vehicle lighting integrated circuit modules, overcoming the shortcomings of existing LED vehicle lighting monitoring schemes that rely solely on static temperature thresholds, exhibit response lag, and ignore device aging conditions.

[0005] According to one aspect of this application, an intelligent monitoring method for an LED automotive lighting integrated circuit module is provided, comprising: acquiring the current temperature, the temperature of the previous cycle, and the quantized aging level collected by a sensor; dynamically evaluating the operating condition trend based on the current temperature and the temperature of the previous cycle to obtain the temperature change rate; extracting the effective temperature from the current temperature and the temperature change rate; inputting the effective temperature and the quantized aging level into a target current arbitration engine to obtain a target drive current; and generating a PWM control signal based on the target drive current.

[0006] In one possible implementation, acquiring the current temperature, the temperature of the previous cycle, and the quantized aging level collected by the sensor includes: acquiring the aging count value collected by the aging counter; and mapping the aging count value to discrete aging levels based on a preset threshold to obtain the quantized aging level.

[0007] In one possible implementation, the operating condition trend is dynamically evaluated based on the current temperature and the temperature of the previous period to obtain the temperature change rate. This includes: dynamically evaluating the operating condition trend based on the current temperature and the temperature of the previous period using the following formula to obtain the temperature change rate, wherein the formula is: ;in, The current temperature. The temperature of the previous cycle, For time intervals, This represents the rate of temperature change.

[0008] In one possible implementation, extracting the effective temperature from the current temperature and the rate of temperature change includes: inputting the rate of temperature change into a forward adjustment function to obtain a temperature margin; and adding the current temperature to the temperature margin to obtain the effective temperature.

[0009] In one possible implementation, the temperature change rate is input into a forward adjustment function to obtain a temperature margin, including: determining a trend interval marker for the temperature change rate based on the temperature change rate and positive and negative change rate thresholds; and performing a predictive temperature margin calculation on the temperature change rate based on the trend interval marker to obtain the temperature margin.

[0010] In one possible implementation, the trend interval marker of the temperature change rate is determined based on the temperature change rate and positive and negative change rate thresholds, including: determining the trend interval marker as a warming zone in response to the temperature change rate being greater than the positive change rate threshold; determining the trend interval marker as a stable zone in response to the temperature change rate being between the negative and positive change rate thresholds; and determining the trend interval marker as a cooling zone in response to the temperature change rate being less than the negative change rate threshold.

[0011] In one possible implementation, calculating a predictive temperature margin based on the trend interval marker to obtain the temperature margin includes: in response to the trend interval marker being a heating zone, calculating the predictive temperature margin on the temperature change rate using the following formula: ;in, Basic warming margin, This is the heating gain coefficient. The threshold for the positive rate of change. This indicates a temperature margin.

[0012] In one possible implementation, calculating a predictive temperature margin based on the trend interval marker to obtain the temperature margin includes: in response to the trend interval marker being a cooling zone, calculating the predictive temperature margin of the temperature change rate using the following formula: ;in, The cooling gain coefficient; and In response to the trend interval being marked as a stable region, the temperature margin is zero.

[0013] In one possible implementation, the effective temperature and quantized aging level are input into the target current arbitration engine to obtain the target drive current, including: using the effective temperature and quantized aging level as coordinates, performing a lookup in a two-dimensional target current lookup table to obtain the target drive current.

[0014] According to another aspect of this application, an intelligent monitoring system for LED vehicle lighting integrated circuit modules is provided. The intelligent monitoring system for LED vehicle lighting integrated circuit modules includes a memory, a processor, and a computer program stored in the memory and executable on the processor. The system is characterized in that the processor executes the computer program to implement the steps of the above-described intelligent monitoring method for LED vehicle lighting integrated circuit modules.

[0015] Compared with existing technologies, the intelligent monitoring method and system for LED automotive lighting integrated circuit modules provided in this application firstly achieves predictive temperature management by introducing a temperature change rate and constructing an effective temperature. When a rapid temperature rise is detected, even if the current temperature has not yet reached the traditionally considered danger threshold, this method can calculate a higher effective temperature in advance, thereby intervening in advance and smoothly adjusting the drive current. This effectively avoids the impact and damage to the LED chip caused by temperature overshoot, greatly improving the reliability and safety of the system. Secondly, by incorporating quantified aging levels into the current decision process, adaptive management of the entire life cycle of the LED module is achieved. For brand-new LEDs in the early stages of their life cycle, they can be allowed to operate at a higher drive current to achieve optimal luminous efficiency, provided that safety is ensured. For aging LEDs that have already experienced some light decay, a more conservative drive current is intelligently matched to slow down their aging process and ensure the long-term stability of light output. In this way, the shortcomings of the one-size-fits-all, coarse control of existing technologies are solved, achieving a good dynamic balance between the immediate performance and long-term lifespan of LED automotive lighting. Attached Figure Description

[0016] The above and other objects, features, and advantages of this application will become more apparent from the more detailed description of the embodiments of this application in conjunction with the accompanying drawings. The drawings are provided to further illustrate the embodiments of this application and form part of the specification. They are used together with the embodiments of this application to explain this application and do not constitute a limitation thereof. In the drawings, the same reference numerals generally represent the same components or steps.

[0017] Figure 1 The illustration shows a schematic flowchart of an intelligent monitoring method for an LED vehicle light integrated circuit module according to an embodiment of this application.

[0018] Figure 2 The illustration shows a schematic flowchart of step S1 in the intelligent monitoring method for LED vehicle light integrated circuit modules according to an embodiment of this application.

[0019] Figure 3 The figure shows a schematic flowchart of step S3 in the intelligent monitoring method for LED vehicle light integrated circuit modules according to an embodiment of this application.

[0020] Figure 4 The figure shows a schematic flowchart of step S31 in the intelligent monitoring method for LED vehicle light integrated circuit modules according to an embodiment of this application.

[0021] Figure 5 The figure shows a schematic flowchart of step S311 in the intelligent monitoring method for LED vehicle light integrated circuit modules according to an embodiment of this application.

[0022] Figure 6The figure shows a schematic block diagram of an intelligent monitoring system for an LED vehicle light integrated circuit module according to an embodiment of this application. Detailed Implementation

[0023] Hereinafter, exemplary embodiments according to this application will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments of this application. It should be understood that this application is not limited to the exemplary embodiments described herein.

[0024] Figure 1 The illustration shows a schematic flowchart of an intelligent monitoring method and system for LED vehicle light integrated circuit modules according to an embodiment of this application. Figure 1 As shown, this application provides an intelligent monitoring method for LED automotive lighting integrated circuit modules, including: S1, acquiring the current temperature, the temperature of the previous cycle, and the quantized aging level collected by sensors; S2, dynamically evaluating the operating condition trend based on the current temperature and the temperature of the previous cycle to obtain the temperature change rate; S3, extracting the effective temperature from the current temperature and the temperature change rate; S4, inputting the effective temperature and the quantized aging level into a target current arbitration engine to obtain a target drive current; S5, generating a PWM control signal based on the target drive current.

[0025] For example, in step S1, the current temperature, the temperature of the previous cycle, and the quantified aging level are acquired by the sensor. It should be understood that the current temperature directly reflects the real-time thermal load of the module at the current moment and is the baseline fact for any thermal management decision. However, the current temperature alone is insufficient to form a forward-looking judgment; therefore, this application further acquires the temperature of the previous cycle. The temperature of the previous cycle provides a temporal reference point. Furthermore, considering that LEDs, as semiconductor devices, experience irreversible degradation in their photoelectric performance with increasing cumulative operating time, i.e., aging, LEDs with different aging levels exhibit different thermal characteristics and luminous efficacy, and their tolerance to driving current also changes accordingly. Therefore, quantifying the aging state and incorporating it into the decision-making system allows the control strategy to dynamically adapt to the state evolution of the LED throughout its entire life cycle, thereby enabling optimized and differentiated management of devices with different health conditions while ensuring safety.

[0026] In one embodiment, acquiring the current temperature, the temperature of the previous cycle, and the quantized aging level collected by the sensor includes: First, the controller's microprocessor unit periodically acquires the analog voltage signal output by the sensor through its built-in analog-to-digital converter, and accurately calculates the voltage signal into a physical value of the current temperature in degrees Celsius according to a conversion formula or lookup table preset in the firmware. Simultaneously, to acquire the temperature of the previous cycle, after the controller completes the calculation task of each monitoring cycle, it stores the acquired current temperature value into a specific RAM (random access memory) variable. At the beginning of the next monitoring cycle, the controller first reads the value from this RAM variable, which is the temperature of the previous cycle, and then overwrites it with the newly acquired current temperature value. This process is repeated to achieve continuous acquisition of temperature values ​​between consecutive cycles. Next, the quantized aging level is acquired, such as... Figure 2 As shown, acquiring the current temperature, the temperature of the previous cycle, and the quantized aging level collected by the sensor includes: S11, acquiring the aging count value collected by the aging counter; S12, mapping the aging count value to discrete aging levels based on a preset threshold to obtain the quantized aging level. Specifically, firstly, the effective operating time of the LED is accumulated using an aging counter built into non-volatile memory (such as EEPROM or Flash). This counter starts timing each time the system is powered on and updates its accumulated time (e.g., in hours) to the non-volatile memory before power failure or periodically to prevent data loss, thereby obtaining an original aging count value. Next, the controller performs quantization processing, reading this accumulated aging count value and comparing it with a set of preset thresholds in the firmware. For example, 0 to 5000 hours can be preset as aging level 0, 5001 to 10000 hours as aging level 1, and so on. The controller determines the range to which the aging count value belongs and maps it to a discrete, non-continuous integer value, which is the quantified aging level.

[0027] For example, in step S2, the operating condition trend is dynamically evaluated based on the current temperature and the temperature of the previous cycle to obtain the temperature change rate. It should be understood that traditional LED thermal management schemes typically rely on a static, preset absolute temperature threshold, triggering a protection mechanism only when the detected temperature exceeds this threshold. This approach is essentially a lagging, passive response mode that cannot predict the temperature change process. In the complex environment of vehicle operation, the operating conditions of LED modules change drastically and dynamically. For example, a vehicle suddenly entering a congested road after high-speed driving, or rapidly moving from a low-temperature underground parking garage into a hot ground environment, can cause the LED junction temperature to rise sharply in a short period. Under traditional control strategies, by the time the system finally detects a temperature exceedance, a significant temperature overshoot may have already occurred, causing instantaneous or cumulative damage to the luminous efficacy, color temperature stability, and even the lifespan of the LED chip. Therefore, this application recognizes that a truly effective monitoring system must have predictive capabilities, and the basis of prediction is the accurate grasp of the system's state change trend. By introducing the temperature of the previous period as a time reference and comparing it with the current temperature, isolated temperature data points can be transformed into dynamic vectors with a time dimension, thereby calculating the rate of temperature change. This rate of change not only includes the direction of temperature change (heating or cooling) but also quantifies the severity of the change.

[0028] In one embodiment, dynamically evaluating the operating condition trend based on the current temperature and the temperature of the previous period to obtain the temperature change rate includes: dynamically evaluating the operating condition trend based on the current temperature and the temperature of the previous period using the following formula to obtain the temperature change rate, wherein the formula is: ;in, The current temperature. The temperature of the previous cycle, For time intervals, This represents the rate of temperature change. Specifically, the molecular part ( ) calculated in a monitoring cycle The absolute temperature change that occurs within a given time period. Then, this temperature change is divided by the time interval. It is then normalized to a standard physical rate, namely the rate of temperature change (denoted as ). The unit is degrees Celsius per second (°C / s). This calculated rate of temperature change is a signed floating-point or fixed-point number, whose positive or negative sign directly indicates the trend of temperature rise or fall, and whose absolute value precisely represents how fast the temperature changes.

[0029] For example, in step S3, the effective temperature is extracted from the current temperature and the rate of temperature change. It should be understood that in actual vehicle operation, drastic changes in operating conditions, such as switching from prolonged low-speed driving to high-speed hill climbing, or sudden changes in ambient temperature, can cause the LED junction temperature to rise non-linearly and at a high rate within a very short time. If the traditional thermal foldback strategy is used, the control system must wait until the current temperature actually and physically reaches a preset critical point before it can begin to reduce the drive current. The inherent delay in this response mode makes a significant temperature overshoot almost unavoidable under conditions of rapid temperature rise. That is, before the control command takes effect, the actual junction temperature of the LED may have already far exceeded its safe operating limit; even a brief exceedance is enough to cause irreversible and permanent damage to its luminous flux, color coordinate stability, and long-term reliability.

[0030] Therefore, this application further extracts the effective temperature from the current temperature and the rate of temperature change. Specifically, when the calculated rate of temperature change is a large positive value, it means that the temperature is rapidly deteriorating. This step can proactively calculate an effective temperature much higher than the current physical temperature, thereby forcing the subsequent decision engine to intervene early and smoothly, implementing control before the physical temperature reaches a dangerous critical point. This offsets the inherent delay in system response and effectively suppresses or even eliminates temperature overshoot. Conversely, when the rate of temperature change is stable or negative, it indicates that the thermal state is under control or is improving. The effective temperature will approach or even fall below the current temperature in some advanced implementations, thus avoiding unnecessary overprotection and ensuring that the LED can maximize its performance under safe operating conditions.

[0031] In one embodiment, such as Figure 3 As shown, the effective temperature is extracted from the current temperature and the rate of temperature change, including: S31, inputting the rate of temperature change into a forward adjustment function to obtain a temperature margin; S32, adding the current temperature and the temperature margin to obtain the effective temperature.

[0032] Specifically, such as Figure 4 As shown, in step S31, the temperature change rate is input into a forward adjustment function to obtain a temperature margin, including: S311, determining a trend interval marker for the temperature change rate based on the temperature change rate and a positive and negative change rate threshold; S312, performing a predictive temperature margin calculation on the temperature change rate based on the trend interval marker to obtain the temperature margin.

[0033] In one specific embodiment, firstly, the trend interval marker is determined: the system presets a positive rate of change threshold. and negative rate of change threshold For example, it can be set Of course, this is just an example, and it can be adjusted according to the actual situation. Next, as... Figure 5 As shown, based on the rate of temperature change and the thresholds for positive and negative rates of change, the trend interval markers for the rate of temperature change are determined, including: S3111, in response to the rate of temperature change being greater than the threshold for positive rates of change, the trend interval marker is determined to be a warming zone; S3112, in response to the rate of temperature change being between the thresholds for negative and positive rates of change, the trend interval marker is determined to be a stable zone; S3113, in response to the rate of temperature change being less than the threshold for negative rates of change, the trend interval marker is determined to be a cooling zone.

[0034] Here, when the positive and negative rate of change thresholds are set to fixed values, the rate of temperature change is not taken into account. The danger is related to absolute temperature and Relatedly, according to semiconductor physics, the aging and failure process of devices is a highly nonlinear thermal activation process. For example, in the low-temperature region (40°C), the LED junction temperature has a huge safety margin. Even if there is a temperature rise of +1°C / s, the increase in the instantaneous damage accumulation rate is very small. Conversely, in the high-temperature region (110°C), the LED is close to the boundary of its safe operating area. At this time, the same temperature rise of +1°C / s will lead to an exponential and catastrophic increase in its damage accumulation rate.

[0035] Therefore, the improved judgment mechanism aims to make the threshold itself a function of absolute temperature. This would make the threshold more sensitive (i.e., smaller) in high-temperature regions to respond quickly to minute temperature increases, while relaxing the threshold in low-temperature regions to avoid unnecessary overreaction. Based on this, a physical model can be used to describe the relationship between the chemical reaction rate (i.e., the light decay and aging rate of the LED) and temperature, focusing on the damage acceleration rate, i.e., how quickly the aging rate changes. Only when the damage acceleration rate exceeds a set critical value is the system considered to have entered a temperature rise zone requiring alert.

[0036] That is, in a preferred embodiment, inputting the temperature change rate into a forward adjustment function to obtain a temperature margin further includes: based on the current temperature and using an aging rate model characterizing the nonlinear physical relationship between LED aging rate and temperature, determining a dynamic positive change rate threshold and a dynamic negative change rate threshold corresponding to the current temperature, wherein the dynamic threshold is set to be more sensitive to temperature changes in high-temperature environments than in low-temperature environments; and determining a trend range marker for the temperature change rate based on the temperature change rate and the dynamic positive change rate threshold and the dynamic negative change rate threshold.

[0037] Specifically, firstly, regarding the aging rate model: ;in, At absolute temperature Instantaneous aging rate (in units of Kelvin) (which can be understood as the amount of damage per unit time); These are constants related to material properties; The activation energy (in electron volts) represents the energy barrier that the aging reaction needs to overcome. For LED light decay, this is a constant related to semiconductor materials and packaging. This refers to the Boltzmann constant, which is known to those skilled in the art. The aforementioned parameter can be determined through accelerated life testing. In other words, based on the aging rate model, the aging rate increases exponentially with increasing temperature.

[0038] Therefore, the aging rate is determined based on the aging rate model. Over time The rate of change, i.e.: .

[0039] The dynamic threshold is determined when the damage acceleration rate exceeds a certain preset critical value. (For example, 0.01s) -2 When the aging rate increment per second does not exceed 0.01 (this is just one example and can be adjusted according to actual conditions), it is considered to have entered the heating zone. Then, for the above aging rate model, calculate... The derivative: .

[0040] That is, This represents the sensitivity of the aging rate to temperature changes at a specific temperature point, and it is related to... Inversely proportional to, and with It is directly proportional, therefore it increases sharply with increasing temperature. Substituting this derivative into the inequality, we get... dynamic positive rate of change threshold The threshold for negative rate of change can be set in relation to the threshold for dynamic positive rate of change, such as... .

[0041] In this way, the settings of the positive and negative rate of change thresholds possess adaptive sensitivity. That is, the thresholds automatically adjust according to the current temperature; the system is less sensitive at low temperatures, tolerating larger temperature fluctuations, while at high temperatures, the system is more alert, reacting quickly to even small temperature increases. Simultaneously, since the aging rate model is directly linked to the physical failure mechanism of LEDs, intervention can be initiated before damage truly begins to accumulate rapidly, achieving proactive physical protection.

[0042] In one embodiment, calculating a predictive temperature margin based on the trend interval marker to obtain the temperature margin includes: in response to the trend interval marker being a warming zone, calculating the predictive temperature margin on the temperature change rate using the following formula: ;in, This is the base temperature rise margin, a positive constant, ensuring a basic protection level even when the rate of temperature change just exceeds a threshold, such as 3°C. It can be adjusted according to actual conditions. This is the temperature rise gain coefficient, which amplifies the portion of the temperature change rate that exceeds a threshold. This means the faster the temperature rises, the larger the added predictive temperature margin, demonstrating a non-linear, strongly adaptive property that is positively correlated with the level of risk. For example, 2.0s can be adjusted according to actual conditions. The threshold for the positive rate of change. This indicates a temperature margin.

[0043] In one embodiment, calculating a predictive temperature margin based on the trend interval marker to obtain the temperature margin includes: in response to the trend interval marker being a cooling zone, calculating the predictive temperature margin on the temperature change rate using the following formula: ;in, The cooling gain coefficient is used to moderately relax the protection when a clear cooling trend is detected, allowing the drive current to recover more quickly, thereby improving the dynamic response of the system performance. For example, 0.5s, which can be adjusted according to the actual situation. In response to the trend interval being designated as a stable region, the temperature margin is zero. After obtaining a unique temperature margin through the above-described detailed, case-by-case calculation process, the current temperature is added to the temperature margin to obtain the effective temperature.

[0044] For example, in step S4, the effective temperature and the quantified aging level are input into the target current arbitration engine to obtain the target drive current. It should be understood that while making decisions solely based on the effective temperature can effectively address short-term dynamic thermal risks, it completely ignores the device's inherent health condition. A brand-new LED module and an aged module that has undergone thousands of hours of operation and experienced severe light decay have vastly different upper limits for electrical and thermal stress when facing the same effective temperature. Aging not only leads to a decrease in the luminous efficacy of the LED chip but may also be accompanied by an increase in its internal thermal resistance and a deterioration in the performance of the packaging materials. This means that under the same drive current, an aged device will generate a higher junction temperature and have poorer heat dissipation. Therefore, a control strategy that ignores the aging state will inevitably fail to achieve optimal performance in the early stages of the LED's life cycle due to excessive conservatism, or accelerate its failure process in the later stages due to excessively aggressive strategies, failing to achieve optimal management throughout the entire life cycle.

[0045] On the other hand, if control is based solely on the quantified aging level, the ability to respond to instantaneous changes in operating conditions will be completely lost, degenerating into a coarser, static derating strategy based on usage time, which cannot cope with the complex and ever-changing thermal environment challenges encountered by vehicles in actual driving. Therefore, this application further considers the result of simultaneous trade-offs and dynamic arbitration between the two dimensions of short-term risk and long-term health. Specifically, the effective temperature and the quantified aging level are input into the target current arbitration engine to obtain the target drive current. The target current arbitration engine can receive and understand the two heterogeneous input information, the effective temperature representing instantaneous thermal risk and the aging level representing long-term cumulative damage. Based on a preset internal logic that incorporates expert knowledge and a large amount of experimental data, it comprehensively adjudicates the two interrelated and sometimes conflicting objectives (maximizing immediate performance and maximizing long-term lifespan), and finally outputs an optimized target drive current under the current specific state combination.

[0046] In one embodiment, inputting the effective temperature and quantized aging level into the target current arbitration engine to obtain the target drive current includes: using the effective temperature and quantized aging level as coordinates, searching a two-dimensional target current lookup table to obtain the target drive current. It should be understood that the two-dimensional target current lookup table is essentially a two-dimensional array or matrix stored in the controller's non-volatile memory (such as Flash or ROM). The design and filling of this data structure are completed offline during the product development phase, embodying expert knowledge gained from extensive theoretical analysis, simulation calculations (such as thermodynamic finite element analysis), and long-term empirical testing (such as accelerated aging experiments) of the LED modules used. The two dimensions (rows and columns) of this two-dimensional table correspond to two input parameters. One dimension, such as the row index, directly corresponds to the discrete quantized aging level (e.g., level 0, level 1, level 2, etc.). Since the aging level itself is an integer, it can be directly used as the row index of the array. The other dimension, the column index, corresponds to the effective temperature. Since the effective temperature is a continuous variable, it needs to be discretized or range-mapped before it can be used as the column index. A common approach is to divide the entire possible range of effective temperatures into several consecutive, non-overlapping sub-intervals (e.g., 80-85°C, 85-90°C, 90-95°C, etc.), with each sub-interval corresponding to a unique column index.

[0047] Crucially, this lookup table design proactively addresses the light decay issues caused by LED aging, ensuring that the vehicle lights consistently meet the minimum illuminance requirements stipulated by relevant regulations throughout their entire lifespan. Specifically, when filling the lookup table with data, the light decay models of LEDs at different aging levels can be comprehensively considered. Accordingly, for levels that have entered the aging stage (e.g., Level 1 and Level 2), a target drive current higher than its initial rated value can be preset within the range of lower effective temperatures and good heat dissipation. This proactive current compensation strategy effectively counteracts the impact of light decay on brightness while ensuring thermal safety. Conversely, in the range of higher effective temperatures, a conservative derating current is still used to prioritize device reliability. Through this two-dimensional refined management, this solution safely combines static brightness compensation requirements with dynamic thermal management, achieving an optimal balance between performance, lifespan, and regulatory requirements.

[0048] When the controller performs a lookup, it first uses the quantized aging level as the row coordinate and converts the effective temperature into the corresponding column coordinate through interval judgment or simple mathematical operations (such as subtracting a baseline value, dividing by the interval width, and then rounding). After determining the unique row and column coordinates (i.e., the index), the controller performs a direct memory read operation to access the specific cell located by these coordinates in the two-dimensional lookup table. The value pre-stored in this cell is the target drive current value that the system should use under this specific state combination. For example, if the effective temperature is 92°C (corresponding to column index m) and the aging level is 1 (corresponding to row index n), the controller will read the value at the lookup table address [n][m] as the target current. To achieve a smoother control output and avoid a step change in the target current due to the effective temperature crossing the interval boundary, in another embodiment, a linear interpolation algorithm can be introduced based on the lookup table. In this way, the controller will perform linear interpolation calculations proportionally between the target current values ​​corresponding to two adjacent column indices found, based on the specific position of the effective temperature within its interval, thereby obtaining a smoother and more continuous target drive current. Whether using direct lookup or interpolation lookup, this implementation based on a two-dimensional lookup table transforms the complex, nonlinear, multidimensional decision-making process into one or more simple memory accesses and basic arithmetic operations with extremely low computational overhead. This greatly ensures the real-time performance and determinism of the decision-making process, fully meeting the stringent requirements of automotive-grade embedded systems for high reliability and high efficiency.

[0049] For example, in step S5, a PWM control signal is generated based on the target drive current. It should be understood that the target drive current is an abstract, digital calculation result, such as a value in milliamperes (mA), which exists in the microcontroller's registers or memory. However, the power stage hardware responsible for directly driving LED light emission, i.e., the LED driver chip and its peripheral circuitry, cannot directly execute such a digital quantity. Modern high-efficiency LED driver circuits, especially the switching-mode constant current sources (such as Buck, Boost, or Buck-Boost topologies) commonly found in automotive applications, do not regulate their output current by changing an analog voltage reference, but rather by frequently controlling the on and off states of a power switching element (usually a MOSFET). The core of this control method lies in precisely adjusting the on-time ratio of the switch in each cycle.

[0050] Therefore, to translate the results of high-level decisions into effective control of the underlying hardware, a language that can be understood by both parties is essential. Pulse Width Modulation (PWM) signals are precisely the standard interface developed for this purpose, and are the most widely used and mature technology in modern digital control. A PWM signal is a digital square wave signal, whose key information is carried in the pulse's duty cycle—the proportion of high-level duration within a fixed signal period. By changing the duty cycle, the average power or average current delivered to the load can be precisely controlled. This control method is extremely efficient because the power switching elements always operate in a low-loss state of being fully on or fully off; simultaneously, it also has extremely high precision and linearity, and is easily generated by digital microcontrollers.

[0051] Specifically, the core of generating a PWM control signal based on the target drive current lies in accurately mapping a current value to a PWM duty cycle value. This mapping relationship is not generated out of thin air, but is predetermined during the system design and calibration phase through precise analysis and experimental testing of the characteristics of the entire LED driver circuit (including the driver chip, inductor, sampling resistor, etc.). This relationship can be solidified into two main forms: one is a mathematical formula, such as a linear or piecewise linear function, whose input is the target current and output is the duty cycle; the other is a more precise and flexible one-dimensional lookup table, which directly stores a series of target current values ​​and their corresponding PWM duty cycle register settings that can achieve that current.

[0052] In actual operation, after the microprocessor unit (MCU) within the controller obtains the target drive current value from the target current arbitration engine, it initiates the firmware algorithm for this step. The algorithm first converts the current value into a specific PWM duty cycle value, or more directly, into an integer value that will be written to a specific register in the PWM hardware peripheral, based on the aforementioned preset mapping relationship (whether by calling a formula or looking up a table). Modern microcontrollers typically integrate a dedicated, high-performance PWM generator hardware module. This module contains several programmable registers, the most critical of which are the period register and the compare / duty cycle register. The period register determines the frequency of the PWM signal, which is usually set to a fixed value to optimize system electromagnetic compatibility (EMC) and efficiency. The compare / duty cycle register determines the pulse width. After calculating the register value corresponding to the required duty cycle, the firmware algorithm loads this value into the PWM generator's compare / duty cycle register through a single write operation. Once the write operation is complete, the PWM hardware module automatically and continuously generates a square wave signal with the newly set duty cycle on a designated general-purpose input / output (GPIO) pin of the MCU with extremely high precision and stability. This process does not consume valuable CPU computing resources. Finally, this GPIO pin carrying the control command is physically connected to a dedicated control input pin (usually labeled DIM, PWM, or EN) of the LED driver chip via traces on the printed circuit board (PCB). After receiving this PWM signal, the LED driver chip's internal control logic precisely modulates the switching timing of its internal power MOSFETs according to the duty cycle of the signal, thereby accurately adjusting the average current flowing through the LED beads to stabilize it at the target drive current value desired by the arbitration engine.

[0053] In summary, the intelligent monitoring method for LED automotive lighting integrated circuit modules provided in this application has been clarified. First, by introducing a temperature change rate and constructing an effective temperature, predictive temperature management is achieved. When a rapid temperature rise is detected, even if the current temperature has not yet reached the traditionally considered danger threshold, this method can calculate a higher effective temperature in advance, thereby intervening and smoothly adjusting the drive current. This effectively avoids the impact and damage to the LED chip caused by temperature overshoot, greatly improving the reliability and safety of the system. Second, by incorporating quantified aging levels into the current decision process, adaptive management of the entire lifecycle of the LED module is achieved. For brand-new LEDs in the early stages of their lifecycle, they can be allowed to operate at a higher drive current to achieve optimal luminous efficacy, provided safety is ensured. For aged LEDs that have already experienced some light decay, a more conservative drive current is intelligently matched to slow down their aging process and ensure long-term stability of light output. In this way, the shortcomings of the existing one-size-fits-all, coarse control are solved, achieving a good dynamic balance between the immediate performance and long-term lifespan of LED automotive lighting.

[0054] This application also provides an intelligent monitoring system for LED vehicle light integrated circuit modules, such as... Figure 6 As shown, the LED vehicle light integrated circuit module intelligent monitoring system 600 includes a memory 610, a processor 620, and a computer program 630 stored in the memory and executable on the processor. The processor 620 executes the computer program 630 to implement the steps of the LED vehicle light integrated circuit module intelligent monitoring method as described above.

[0055] This application also provides a computer-readable storage medium storing computer program code. When the computer program code is run on a computer, the computer executes the above-described related method steps to implement the intelligent monitoring method for LED vehicle light integrated circuit modules provided in the above embodiments.

[0056] This application also provides a computer program product that, when run on a computer, causes the computer to perform the aforementioned related steps to realize the intelligent monitoring method for LED vehicle light integrated circuit modules provided in the above embodiments.

[0057] In this application, the system, computer-readable storage medium, or computer program product provided in the embodiments are all used to execute the corresponding methods provided above. Therefore, the beneficial effects that can be achieved can be referred to the beneficial effects in the corresponding methods provided above, and will not be repeated here.

[0058] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments.

[0059] The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some embodiments, multitasking and parallel processing are possible or may be advantageous. The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A method for intelligent monitoring of LED vehicle light integrated circuit modules, characterized in that, include: Acquire the current temperature, the temperature of the previous cycle, and the quantified aging level collected by the sensor; Based on the current temperature and the temperature of the previous cycle, the operating condition trend is dynamically evaluated to obtain the temperature change rate. Extract the effective temperature from the current temperature and the rate of temperature change; The effective temperature and quantified aging level are input into the target current arbitration engine to obtain the target drive current; Based on the target drive current, a PWM control signal is generated; The effective temperature is extracted from the current temperature and the rate of temperature change, including: The temperature change rate is input into a forward-looking adjustment function to obtain a temperature margin, including: Based on the temperature change rate and thresholds for both positive and negative rates of change, a trend range for the temperature change rate is determined. The dynamic positive rate of change threshold is defined as follows: The threshold for negative rate of change is When the aging rate varies with time The rate of change exceeds the preset critical value. At that time, it enters the heating zone, where the aging rate model is calculated. The formula for the derivative is as follows: ； in, This represents the sensitivity of the aging rate to temperature changes at a given temperature point. These are constants related to material properties; To activate energy; It is the Boltzmann constant; It is absolute temperature; Based on the trend interval indicator, a predictive temperature margin is calculated for the temperature change rate to obtain the temperature margin, including: In response to the trend interval being designated as a warming zone, a predictive temperature margin for the rate of temperature change is calculated using the following formula: ； in, Basic warming margin, This is the heating gain coefficient. The threshold for the positive rate of change. Indicates temperature margin; In response to the trend interval being designated as a cooling zone, a predictive temperature margin is calculated for the rate of temperature change using the following formula: ； in, This is the cooling gain coefficient; In response to the trend interval being marked as a stable region, the temperature margin is zero; The effective temperature is obtained by adding the current temperature to the temperature margin.

2. The intelligent monitoring method for LED vehicle light integrated circuit modules according to claim 1, characterized in that, Acquire the current temperature, the temperature of the previous cycle, and the quantified aging level collected by the sensor, including: Obtain the aging count value collected by the aging counter; Based on a preset threshold, the aging count value is mapped to a discrete aging level to obtain the quantified aging level.

3. The intelligent monitoring method for LED vehicle light integrated circuit modules according to claim 1, characterized in that, Based on the current temperature and the temperature of the previous period, a dynamic assessment of the operating condition trend is performed to obtain the temperature change rate, including: based on the current temperature and the temperature of the previous period, the operating condition trend is dynamically assessed using the following formula to obtain the temperature change rate, wherein the formula is: ； in, The current temperature. The temperature of the previous cycle, For time intervals, This represents the rate of temperature change.

4. The intelligent monitoring method for LED vehicle light integrated circuit modules according to claim 3, characterized in that, Based on the temperature change rate and thresholds for both positive and negative changes, the trend interval markers for the temperature change rate are determined, including: When the rate of temperature change exceeds the positive rate of change threshold, the trend interval is identified as the warming zone. The trend interval is defined as the stable region in response to the temperature change rate falling between the negative and positive change rate thresholds. When the rate of temperature change is less than the negative rate of change threshold, the trend interval is identified as the cooling zone.

5. The intelligent monitoring method for LED vehicle light integrated circuit modules according to claim 1, characterized in that, The effective temperature and quantified aging level are input into the target current arbitration engine to obtain the target drive current, including: Using the effective temperature and quantified aging level as coordinates, the target driving current is obtained by searching in a two-dimensional target current lookup table.

6. An intelligent monitoring system for LED vehicle light integrated circuit modules, the intelligent monitoring system for LED vehicle light integrated circuit modules comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the intelligent monitoring method for LED vehicle light integrated circuit modules as described in any one of claims 1-5.

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