Thermal detection system and method of PFC power supply module

Abstract

The invention provides a thermal detection system and method for a PFC power supply module, and relates to the technical field of thermal detection alarm, and the method comprises the steps: obtaining the temperature distribution information and dynamic heat flow data of the PFC power supply module during operation; determining a heat accumulation track in the key heat source area according to the temperature distribution information, and determining a heat flow trend of the operation temperature of the PFC power supply module during temperature diffusion according to the heat accumulation track and the adjusted qualitative heat early warning strategy; performing multi-path thermal conductance matching on the calibrated temperature deviation to obtain an alarm response index of the PFC power supply module during cooperative heat dissipation operation, and determining a thermal out-of-limit boundary on a temperature detection point in the PFC power supply module according to the alarm response index and the dynamic heat flow data; and according to the heat flow trend and the heat out-of-limit boundary, performing graded alarm on the PFC power supply module during dynamic heat balance synchronous detection. According to the invention, the thermal state can be accurately monitored and early warned when the PFC power supply module is dynamically operated, so that the accuracy of thermal detection alarm is improved.

Description

Technical Field

[0001] This application relates to the field of thermal detection and alarm technology, and more specifically, to a thermal detection system and method for a PFC power module. Background Technology

[0002] Thermal detection alarms for PFC power modules refer to protective technologies that address thermal risks during PFC power module operation by collecting thermal parameters, analyzing thermal trends, determining thermal boundaries, and triggering corresponding responses. Since PFC power modules are widely used in scenarios such as new energy charging piles and server power supplies, characterized by high power density and long-term full-load operation, the reliability of thermal detection alarms directly affects the lifespan of module components, operational stability, and even system safety. Inaccurate alarms may lead to false alarms interfering with operation or missed alarms causing component failure or module burnout. Therefore, developing thermal detection alarm methods that closely match the module's thermal characteristics is a key technological support for ensuring the safe and stable operation of PFC power modules.

[0003] However, existing thermal detection methods for PFC power modules largely rely on fixed temperature thresholds to trigger alarms, collecting only localized, single-point temperature data without integrating dynamic heat flow information and heat diffusion patterns. This means that thermal detection can only reflect static temperature states, failing to capture heat accumulation trajectories and heat flow trends. Consequently, it cannot accurately identify the impact of active cooling channel calibration temperature deviations on thermal safety, and the thermal limit boundary settings lack dynamic adaptability, leading to frequent false alarms and missed alarms. Therefore, thermal risks under dynamic thermal equilibrium conditions cannot be predicted in a timely manner. Thus, how to accurately monitor and warn of the thermal state of PFC power modules during dynamic operation to improve the accuracy of thermal detection alarms is a current technical challenge. Summary of the Invention

[0004] This application provides a thermal detection system and method for PFC power modules, which can accurately monitor and warn of the thermal status of PFC power modules during dynamic operation, thereby improving the accuracy of thermal detection alarms.

[0005] In a first aspect, this application provides a thermal detection method for a PFC power module, the thermal detection method comprising the following steps: Acquire temperature distribution information and dynamic heat flow data of the PFC power module during operation; The temperature change of the PFC power module is detected in real time and the qualitative thermal warning strategy is adjusted. The heat accumulation trajectory in the key heat source area is determined based on the temperature distribution information. The heat flow trend of the operating temperature of the PFC power module during temperature diffusion is determined based on the heat accumulation trajectory and the adjusted qualitative thermal warning strategy. The calibration temperature deviation of the PFC power module in the active heat dissipation channel is determined, and multi-path thermal conductivity matching is performed on the calibration temperature deviation to obtain the alarm response index of the PFC power module during collaborative heat dissipation operation. Then, the thermal over-limit boundary at the temperature detection point in the PFC power module is determined by the alarm response index and the dynamic heat flow data. Based on the heat flow trend and the heat exceedance boundary, the PFC power module is given a graded alarm during dynamic thermal balance synchronous detection.

[0006] In this embodiment, the temperature distribution information refers to the quantitative information on the temperature levels and spatial distribution in different areas within the PFC power module.

[0007] In this embodiment, the dynamic heat flow data refers to the parameters of the real-time heat transfer rate, path, and heat flux density within the PFC power module.

[0008] In this embodiment, determining the thermal flow trend of the PFC power module's operating temperature during temperature diffusion based on the heat accumulation trajectory and the adjusted qualitative thermal early warning strategy specifically includes: Based on the heat accumulation trajectory and the adjusted qualitative thermal early warning strategy, temperature flow descriptions under different operating modes are determined; The temperature flow description is reconstructed by feedback to obtain the heat flow path of the operating temperature during temperature diffusion; The thermal flow trend of the PFC power module's operating temperature during temperature diffusion is determined based on the described thermal flow path.

[0009] In this embodiment, determining the calibration temperature deviation of the PFC power module in the active cooling channel specifically includes: Obtain the real-time temperature sequence of the PFC power module in the active cooling channel; The real-time temperature sequence is decomposed to obtain the temperature deviation attributes of each node in the active heat dissipation channel. The calibration temperature deviation of the PFC power module in the active cooling channel is determined based on all temperature deviation attributes.

[0010] In this embodiment, determining the thermal exceedance boundary at the temperature detection point in the PFC power module based on the alarm response index and the dynamic heat flow data specifically includes: The thermal inertia gradient at the temperature detection point is determined based on the alarm response index and the dynamic heat flow data. The cumulative thermal characteristics at each temperature detection point under heat flow fluctuations are evaluated based on the thermal inertia gradient. The thermal overshoot boundary at the temperature detection point in the PFC power module is determined by all the cumulative thermal characteristics.

[0011] In this embodiment, multi-path thermal conductivity matching is performed on the calibrated temperature deviation to obtain the alarm response indicators of the PFC power module during collaborative heat dissipation operation, specifically including: The thermal conductivity properties of each heat dissipation path of the PFC power module are determined based on the calibrated temperature deviation. The thermal conductivity contribution of each path during collaborative heat dissipation is matched to obtain the thermal conductivity contribution rule during collaborative heat dissipation. The transient thermoelastic coefficient during synergistic heat dissipation operation is determined based on all thermal conductivity contribution rules and real-time temperature change rate. The alarm response index of the PFC power module during cooperative heat dissipation operation is determined based on the transient thermoelastic coefficient and all thermal conductivity properties.

[0012] In this embodiment, the multi-path thermal conductivity matching refers to matching the thermal conductivity properties of each heat dissipation path in the PFC power module so that heat is distributed and transferred according to its capacity, avoiding local overload.

[0013] In this embodiment, the dynamic thermal balance synchronous detection refers to the process of real-time synchronous monitoring of the heat generation power and heat dissipation power of the PFC module, and comparing the difference between the heat generation power and heat dissipation power to determine the thermal imbalance state.

[0014] Secondly, this application provides a thermal detection system for a PFC power module, used to perform a thermal detection method for a PFC power module, the thermal detection system comprising: The data acquisition module is used to acquire temperature distribution information and dynamic heat flow data of the PFC power module during operation; The early warning adjustment module is used to detect the temperature change of the PFC power module in real time and adjust the qualitative thermal early warning strategy. Based on the temperature distribution information, it determines the heat accumulation trajectory in the key heat source area and determines the heat flow trend of the PFC power module's operating temperature during temperature diffusion based on the heat accumulation trajectory and the adjusted qualitative thermal early warning strategy. The thermal conductivity matching module is used to determine the calibration temperature deviation of the PFC power module in the active heat dissipation channel, perform multi-path thermal conductivity matching on the calibration temperature deviation, obtain the alarm response index of the PFC power module during collaborative heat dissipation operation, and then determine the thermal over-limit boundary at the temperature detection point in the PFC power module by the alarm response index and the dynamic heat flow data. The graded detection and alarm module is used to issue graded alarms to the PFC power module during dynamic thermal balance synchronous detection based on the thermal flow trend and the thermal over-limit boundary.

[0015] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects: The system acquires temperature distribution information and dynamic heat flow data of the PFC power module during operation; it monitors the temperature change of the PFC power module in real time and adjusts the qualitative thermal warning strategy; it determines the heat accumulation trajectory in key heat source areas based on the temperature distribution information; it determines the heat flow trend of the PFC power module's operating temperature during temperature diffusion based on the heat accumulation trajectory and the adjusted qualitative thermal warning strategy; it determines the calibration temperature deviation of the PFC power module in the active heat dissipation channel; it performs multi-path thermal conduction matching on the calibration temperature deviation to obtain the alarm response index of the PFC power module during collaborative heat dissipation operation; and it determines the thermal exceedance boundary at the temperature detection point in the PFC power module based on the alarm response index and the dynamic heat flow data; it performs graded alarms on the PFC power module during dynamic thermal balance synchronous detection based on the heat flow trend and the thermal exceedance boundary.

[0016] Therefore, this application demonstrates that, addressing the shortcomings of existing PFC power module thermal detection methods that rely on single-point static temperature acquisition and lack dynamic heat flow information, it enhances the comprehensiveness and dynamism of thermal status data. By acquiring temperature distribution information and dynamic heat flow data, it covers the spatial temperature distribution and dynamic heat transfer process in key areas of the module, avoiding the problem that traditional single-point temperature detection cannot reflect the overall heat distribution and heat flow path. Determining the heat accumulation trajectory and heat flow trend through temperature distribution information solves the shortcomings of existing fixed early warning strategies that cannot adapt to dynamic temperature changes and are difficult to capture heat accumulation and diffusion patterns, enabling dynamic optimization of early warning strategies and accurate identification of thermal trends, avoiding delayed or excessive early warnings due to misjudgments of thermal trends. Using multi-path thermal conductivity matching to obtain alarm response indicators and determine thermal limit boundaries compensates for the shortcomings of existing thermal detection methods that ignore heat dissipation channel temperature deviations, unbalanced thermal conductivity distribution, and statically set thermal limit boundaries. By implementing graded alarms during dynamic thermal balance synchronous detection, it addresses the shortcomings of existing single alarm methods that cannot handle different thermal risk levels and are difficult to adapt to dynamic thermal balance states, improving the effectiveness of thermal risk management.

[0017] In summary, the technical solution adopted in this application can accurately monitor and warn of the thermal status of the PFC power module during dynamic operation, thereby improving the accuracy of thermal detection alarms. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only for this embodiment of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1This is an exemplary flowchart of a thermal detection method for a PFC power module provided in this application; Figure 2 This is a flowchart illustrating the process of determining the heat accumulation trajectory provided in this application; Figure 3 This is a flowchart illustrating the process for determining alarm response indicators provided in this application; Figure 4 This is a module structure diagram of a thermal detection system for a PFC power module provided in this application. Detailed Implementation

[0020] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0021] This application provides a thermal detection system and method for a PFC power module. The core of the system is to acquire temperature distribution information and dynamic heat flow data of the PFC power module during operation; to detect temperature changes in the PFC power module in real time and adjust a qualitative thermal warning strategy; to determine the heat accumulation trajectory in key heat source areas based on the temperature distribution information; to determine the heat flow trend of the PFC power module's operating temperature during temperature diffusion based on the heat accumulation trajectory and the adjusted qualitative thermal warning strategy; to determine the calibration temperature deviation of the PFC power module in the active heat dissipation channel; to perform multi-path thermal conductivity matching on the calibration temperature deviation to obtain an alarm response index for the PFC power module during collaborative heat dissipation operation; and to determine the thermal exceedance boundary at the temperature detection point in the PFC power module based on the alarm response index and the dynamic heat flow data; and to perform graded alarms on the PFC power module during dynamic thermal balance synchronous detection based on the heat flow trend and the thermal exceedance boundary.

[0022] Example 1: To better understand the above technical solution, the following will provide a detailed description of the technical solution in conjunction with the accompanying drawings and specific implementation methods. (Refer to...) Figure 1 As shown in the figure, this is an exemplary flowchart of a thermal detection method for a PFC power module according to this embodiment of the present application. The thermal detection method includes the following steps: In step S1, the temperature distribution information and dynamic heat flow data of the PFC power module during operation are obtained.

[0023] In practical implementation, surface-mount NTC thermistors can be selected to form an array, configured according to module size, and embedded in the module by drilling holes (applying thermally conductive silicone) next to key components (IGBTs, rectifier bridges, etc.) on the PCB board, with signal lines soldered to the pins. Simultaneously, a miniature thin-film heat flow meter is attached to the heat transfer path, such as the IGBT-heatsink. Both are connected to an NI9219 data acquisition card, which is then connected to an industrial host computer via USB. A 100ms sampling interval is set in LabVIEW, and the module is gradually loaded from no load to full load. That is, the temperature values ​​of the NTC thermistors are used as temperature distribution information, and the information collected by the miniature thin-film heat flow meter is used as dynamic heat flow data. In other embodiments, other methods can be used to determine the temperature distribution information and dynamic heat flow data of the PFC power module during operation; this is not limited here.

[0024] It should be noted that, in this application, temperature distribution information refers to the quantitative information on the temperature levels and spatial distribution in different areas within the PFC power module; dynamic heat flow data refers to parameters such as the real-time heat transfer rate, path, and heat flux density within the PFC power module.

[0025] In step S2, the temperature change of the PFC power module is detected in real time and the qualitative thermal warning strategy is adjusted. The heat accumulation trajectory in the key heat source area is determined based on the temperature distribution information. The heat flow trend of the PFC power module's operating temperature during temperature diffusion is determined based on the heat accumulation trajectory and the adjusted qualitative thermal warning strategy.

[0026] In practice, real-time detection of temperature changes in the PFC power module and adjustment of the qualitative thermal warning strategy can be achieved as follows: First, the deployed NTC thermistor array is used to read temperature data from each detection point at a fixed sampling period of 100ms using LabVIEW software on a host computer. The temperature difference between two adjacent sampling periods is calculated in real time and then divided by the sampling interval (0.1s) to obtain the temperature change (ΔT / Δt). After calculation, a Kalman filter algorithm is used to filter out interference data caused by power grid fluctuations and load changes to ensure the accuracy of the change. Subsequently, the software compares the real-time change with a preset threshold: when ΔT / Δt < 0.5℃ / s, the sampling frequency of 1Hz and the basic warning threshold are maintained; when 0.5℃ / s ≤ ΔT / Δt < 2℃ / s, the sampling frequency is increased to 10Hz and a warning is triggered; when ΔT / Δt ≥ 2℃ / s, the heat dissipation system is immediately accelerated, and the warning judgment criteria are tightened, thus completing the dynamic adjustment of the qualitative thermal warning strategy. Further details are omitted here.

[0027] It should be noted that, in this application, the temperature change refers to the rate of temperature change per unit time at the detection point of the PFC power module; the qualitative thermal early warning strategy refers to the strategy of adjusting the early warning rules and response measures according to the temperature change characteristics to adapt to different thermal risks.

[0028] Preferably, in this embodiment, the heat accumulation trajectory in the key heat source region is determined based on the temperature distribution information, with reference to... Figure 2 As shown in the figure, this is a flowchart illustrating the process of determining the heat accumulation trajectory in some embodiments of this application. In this embodiment, the determination of the heat accumulation trajectory can be achieved using the following steps: In step S21, the heat change sequence of the key heat source region is extracted from the temperature distribution information; In step S22, the diffusion disturbance information of heat accumulation is determined based on the heat change sequence; In step S23, the diffusion compensation characteristics of temperature in the key heat source region are determined by the diffusion disturbance information; In step S24, the heat accumulation trajectory in the key heat source region is determined by the diffusion compensation feature.

[0029] In practice, firstly, data collected by NTC thermistors corresponding to key heat source areas (such as the core area of ​​the IGBT chip) are selected from the temperature distribution information and sorted according to the acquisition time (the time interval is consistent with the sampling period, which is 100ms). Using the heat calculation formula Q=cmΔT, where c is the specific heat capacity of the core component material (e.g., the specific heat capacity of silicon in the IGBT is 712J / (kg·K); m is the mass of the heat-generating core of the device, obtained from the device datasheet; and ΔT is the difference between the temperature of this area and the ambient temperature), the heat value at each time point is calculated sequentially, and all heat values ​​are arranged in chronological order to form a heat change sequence for the key heat source area. Next, the sliding window method in time series analysis is used to process the heat change sequence, setting the window size to 5 sampling periods (total duration 500ms), with a sliding window step of 1 sampling period. Calculate the standard deviation of the heat value within each window. If the standard deviation is greater than a preset threshold (set according to the heat fluctuation range under the module's rated operating conditions, such as ±5W), mark the time interval corresponding to that window as a "disturbance interval," and record the maximum heat fluctuation value and the duration of the fluctuation within the interval. Organize the location and fluctuation parameters of all disturbance intervals into structured data to form diffusion disturbance information for heat accumulation. Then, for each "disturbance interval" marked in the diffusion disturbance information, extract the maximum heat fluctuation value within the interval. Based on the conversion relationship between heat and temperature ΔT=Q / (cm)), calculate the temperature fluctuation corresponding to this fluctuation value, and use it as the "compensation amplitude." Simultaneously, using the duration of the disturbance interval as the "compensation period," fit a compensation curve using the least squares method (the curve type can be linear or polynomial, selected according to the fluctuation trend) so that the compensation curve can cover the temperature fluctuation within the disturbance interval. Summarize the compensation amplitude, compensation period, and compensation curve parameters for each disturbance interval to form the diffusion compensation characteristics of the temperature in the key heat source area. Finally, the temperature data corresponding to the heat change sequence are substituted into the diffusion compensation feature one by one along the time axis: in the non-disturbance range, the original temperature data is used directly; in the disturbance range, the original temperature data is corrected according to the compensation amplitude and compensation curve. After correction, a continuous curve is plotted in LabVIEW software with time as the horizontal axis (unit: s) and the compensated temperature value as the vertical axis (unit: ℃), and the temperature peak points and abrupt changes in temperature rise rate (points with slope changes greater than 0.5℃ / s²) on the curve are marked to form the heat accumulation trajectory in the key heat source region.

[0030] It should be noted that, in this application, the critical heat source area refers to the area in the PFC power module where heat generation is concentrated and heat flux density is high, significantly affecting the thermal safety and operational reliability of the PFC power module; the heat change sequence refers to the ordered data set of heat value changes in the critical heat source area at different time points; the diffusion disturbance information refers to the heat fluctuation characteristic data generated by the influence of external load fluctuations and changes in heat dissipation airflow during the heat diffusion process in the critical heat source area; the diffusion compensation characteristics refer to the set of characteristic features that correct the influence of diffusion disturbance information on the temperature diffusion analysis of the critical heat source area; and the heat accumulation trajectory refers to the curve data of the heat accumulation and temperature diffusion change trends in the critical heat source area at different time points.

[0031] In this embodiment, determining the thermal flow trend of the PFC power module's operating temperature during temperature diffusion based on the heat accumulation trajectory and the adjusted qualitative thermal early warning strategy can be achieved through the following steps: Based on the heat accumulation trajectory and the adjusted qualitative thermal early warning strategy, temperature flow descriptions under different operating modes are determined; The temperature flow description is reconstructed by feedback to obtain the heat flow path of the operating temperature during temperature diffusion; The thermal flow trend of the PFC power module's operating temperature during temperature diffusion is determined based on the described thermal flow path.

[0032] In practice, firstly, key parameters are extracted from the heat accumulation trajectory, including the temperature value at each time point, the rate of temperature rise (calculated from the slope of the trajectory curve), and the location corresponding to the temperature peak point. Then, the adjusted qualitative heat warning strategy is retrieved to clarify the operating mode corresponding to different warning levels (e.g., ΔT / Δt < 0.5℃ / s is the "slow operation mode," 0.5℃ / s ≤ ΔT / Δt < 2℃ / s is the "rapid heating mode," and ΔT / Δt ≥ 2℃ / s is the "rapid heating mode"). For each operating mode, combined with the heat accumulation trajectory parameters, the direction of temperature diffusion (e.g., diffusion towards the heat sink, accumulation in a local area), diffusion rate (e.g., 0.3℃ / s, 1.8℃ / s), and the area of ​​concentrated temperature distribution are described, forming a temperature flow description under different operating modes. Then, key nodes for temperature diffusion are extracted from the temperature flow description, including key heat source areas, intermediate heat transfer components, and heat dissipation terminals. Using the adjacency matrix method in graph theory, each key node is treated as a matrix vertex. Based on the description of "transfer from node A to node B" in the temperature flow description, the transfer relationship is marked at the corresponding position in the matrix, and the temperature transfer rate is assigned as a weight (e.g., the transfer rate from the IGBT chip to the thermal paste layer has a weight of 0.9). Valid transfer relationships with a weight ≥ 0.6 are selected through matrix operations, and the key nodes are connected in series according to the temperature diffusion direction to reconstruct the heat flow path during temperature diffusion at the operating temperature. Finally, the temperature transfer rate of each segment on the heat flow path (derived from the adjacency matrix weights) is analyzed. A linear fitting algorithm is used to fit the rate data of each path segment to obtain a rate change curve. If the slope of the curve is positive, it indicates that the transfer rate of that segment is increasing; if the slope is negative, it indicates that the rate is decreasing. Combining the adjusted qualitative thermal warning strategy, the thermal risk level under the current operating mode is determined: for example, in the "smooth operation mode," the slope of the path rate fitting curve for each segment is close to 0, indicating that the heat flow trend is "stable diffusion"; in the "rapid heating mode," the slope of the path rate from the heat source area to the intermediate heat transfer component is positive and exceeds the warning threshold, indicating that the heat flow trend is "increased risk of local accumulation." Finally, the path analysis results of each segment are summarized as the thermal flow trend of the PFC power module's operating temperature during temperature diffusion.

[0033] It should be noted that, in this application, temperature diffusion refers to the process of heat transfer from high-temperature areas to low-temperature areas during the operation of the PFC power module, which directly affects the module's thermal distribution and thermal safety; temperature flow description refers to the set of directions, rates, and distribution states of temperature diffusion during different operating modes of the PFC power module; heat flow path refers to the specific route along which the operating temperature of the PFC power module is transferred from the heat source area to the heat dissipation terminal during the diffusion process; and heat flow trend refers to the predictive judgment of the future trend of changes in the direction of heat transfer, the increase or decrease in the rate of heat transfer, and whether heat accumulation will occur during the diffusion process of the PFC power module's operating temperature.

[0034] In step S3, the calibration temperature deviation of the PFC power module in the active heat dissipation channel is determined, and multi-path thermal conductivity matching is performed on the calibration temperature deviation to obtain the alarm response index of the PFC power module during collaborative heat dissipation operation. Then, the thermal over-limit boundary at the temperature detection point in the PFC power module is determined by the alarm response index and the dynamic heat flow data.

[0035] In this embodiment, the calibration temperature deviation of the PFC power module in the active cooling channel can be determined by the following steps: Obtain the real-time temperature sequence of the PFC power module in the active cooling channel; The real-time temperature sequence is decomposed to obtain the temperature deviation attributes of each node in the active heat dissipation channel. The calibration temperature deviation of the PFC power module in the active cooling channel is determined based on all temperature deviation attributes.

[0036] In practical implementation, firstly, the core nodes of the active cooling channel are identified, including the channel inlet, heatsink surface, channel outlet, and the area near the fan. A surface-mount PT100 platinum resistance sensor is installed at each node, and the sensor is connected to a data acquisition card via a shielded cable. The acquisition card is connected to a host computer via a USB interface. In the LabVIEW software on the host computer, the sampling interval is set to 500ms. The PFC power module is started and maintained at rated load, continuously collecting temperature data for 2 hours. The temperature data of each node is organized in chronological order of collection time, forming an independent real-time temperature sequence for each node. Then, the calibration temperatures of each node are retrieved from the PFC power module design document (e.g., inlet calibration temperature 25℃, heatsink surface calibration temperature 55℃, outlet calibration temperature 35℃, fan area calibration temperature 40℃). For each node's real-time temperature sequence, the difference between the real-time temperature and the corresponding calibration temperature is calculated sequentially to obtain the instantaneous deviation value for that node (positive values ​​indicate over-temperature deviation, negative values ​​indicate under-temperature deviation). A sliding window method (window size set to 10 sampling periods, i.e., 5 seconds) is used to analyze deviation values. If more than 80% of the instantaneous deviation values ​​within the window have an absolute value exceeding 2℃, the duration of that window is recorded as the deviation duration. The maximum and minimum deviation values ​​within the window are calculated, and the difference between the two is the deviation fluctuation amplitude. The deviation range, deviation duration, and deviation fluctuation amplitude of each node are organized into structured data to obtain the temperature deviation attribute of each node. Finally, weights are assigned to each node according to its influence on active cooling efficiency (0.4 for heat sink surface, 0.3 for air outlet, 0.2 for air inlet, and 0.1 for near the fan). For each node, the average deviation value in its temperature deviation attribute (obtained by the arithmetic mean of instantaneous deviation values) is multiplied by the corresponding weight to calculate the weighted deviation value of each node. The weighted deviation values ​​of all nodes are summed to obtain the overall deviation value of the active cooling channel. Simultaneously, the number of nodes exhibiting persistent deviations (deviation duration exceeding 10 minutes) was counted. If such nodes accounted for more than 30%, "persistent deviation" was marked after the overall deviation value; if the proportion was less than 30%, "intermittent deviation" was marked. Combining the overall deviation value and the deviation type, the calibration temperature deviation of the PFC power module in the active cooling channel was finally determined.

[0037] It should be noted that, in this application, the active cooling channel refers to a channel in the PFC power module consisting of an air inlet, air duct, heat sink, fan, and air outlet, used to guide heat from the heat-generating components to the heat dissipation terminal and exhaust it under external power drive; the real-time temperature sequence refers to an ordered set of data that continuously records the temperature changes of each node in the active cooling channel over time; the temperature deviation attribute refers to a set of parameters that describe the difference between the real-time temperature and the calibration temperature of each node in the active cooling channel; and the calibration temperature deviation refers to the difference between the overall temperature of the active cooling channel and the design calibration temperature.

[0038] Preferably, in this embodiment, multi-path thermal conductivity matching is performed on the calibrated temperature deviation to obtain the alarm response index of the PFC power module during collaborative heat dissipation operation, with reference to... Figure 3 As shown in the figure, this is a flowchart illustrating the process of determining alarm response indicators in some embodiments of this application. In this embodiment, the determination of alarm response indicators can be achieved through the following steps: In step S31, the thermal conductivity properties of each heat dissipation path of the PFC power module are determined based on the calibrated temperature deviation. In step S32, the thermal conductivity contribution of each path during collaborative heat dissipation is matched to obtain the thermal conductivity contribution rule during collaborative heat dissipation. In step S33, the transient thermoelastic coefficient during synergistic heat dissipation is determined based on all thermal conductivity contribution rules and the real-time temperature change rate. In step S34, the alarm response index of the PFC power module during cooperative heat dissipation operation is determined based on the transient thermoelastic coefficient and all thermal conductivity properties.

[0039] In practical implementation, firstly, all heat dissipation paths of the module are identified, including the IGBT-heatsink path, the PCB-air convection path, and the inductor-thermal pad path. The thermal resistance parameters of the core components for each path are retrieved from the module's datasheet (e.g., the thermal resistance R1 between the IGBT and the heatsink thermal paste = 0.2℃ / W). The baseline thermal conductivity value for each path is calculated using the thermal conductivity formula G = 1 / R (G is thermal conductivity, unit W / ℃). Combined with the calibration temperature deviation (e.g., overall deviation +3℃), the impact of temperature deviation on the calibration thermal conductivity is analyzed: if the temperature deviation at a certain path node exceeds 2℃, the fluctuation range of the thermal conductivity for that path is recorded. Finally, the baseline thermal conductivity value, fluctuation range, and temperature sensitivity of each path are integrated to form the thermal conductivity attribute. Next, the total thermal conductivity requirement of the module is calculated: based on the total heat generation power P (e.g., 100W) under the module's rated load and the calibration temperature deviation ΔT (e.g., +3℃), the total thermal conductivity requirement is calculated as approximately 33.3W / ℃ using Gtotal = P / ΔT. Based on the baseline thermal conductivity values ​​in the thermal conductivity attributes of each path, a weighted allocation method is used to determine the contribution: if the IGBT-heatsink path G1 = 15W / ℃, the PCB path G2 = 10W / ℃, and the inductor path G3 = 8W / ℃, then the contribution rates are approximately 15 / 33.3×100%≈45%, 30%, and 25%, respectively. Finally, adjustment conditions are established: when the temperature deviation of a path exceeds 3℃, its contribution rate can fluctuate by 5%. The contribution rates and adjustment conditions are then combined to form a thermal conductivity contribution rule. Then, the real-time temperature change rate ΔT / Δt (e.g., 1.2℃ / s) is extracted from the NTC thermistor array data. For each path, based on the contribution rate in the thermal conductivity contribution rule (e.g., 45% for the IGBT path) and the temperature sensitivity of the path's thermal conductivity properties (e.g., G1 decreases by 0.05 W / ℃ for every 1℃ increase in temperature), the rate of change of thermal conductivity ΔG / G0 (G0 is the baseline thermal conductivity) is calculated: if ΔT = 2℃, then ΔG1 = -0.05 × 2 = -0.1 W / ℃, ΔG1 / G1 = -0.1 / 15 ≈ -0.67%. Then, the transient thermoelastic coefficient of each path is calculated using the formula α = (ΔG / G0) / (ΔT / Δt), and the weighted average of the coefficients and contribution rates of each path is taken to obtain the overall transient thermoelastic coefficient. Finally, an alarm threshold is set based on the absolute value of the transient thermoelastic coefficient α: if the absolute value of α > 0.008 (sensitive to thermal conductivity response), an alarm is triggered when the thermal conductivity value is lower than 80% of the baseline thermal conductivity; if the absolute value of α < 0.003 (sluggish response), the threshold is set to 70% of the baseline thermal conductivity. Based on the fluctuation range of thermal conductivity properties for each path: if the thermal conductivity fluctuation of a certain path exceeds ±0.2W / ℃, the response delay time is set to 50ms (shortening the delay); if the fluctuation is <±0.1W / ℃, the delay is set to 100ms. Finally, the threshold, delay time, and linkage measures are integrated to form the alarm response index of the PFC power module during collaborative heat dissipation operation.

[0040] It should be noted that, in this application, multi-path thermal conductivity matching refers to matching the thermal conductivity properties of each heat dissipation path in the PFC power module to distribute and transfer heat according to its capacity, avoiding local overload; coordinated heat dissipation operation refers to the process of multiple heat dissipation systems in the PFC power module working simultaneously or in shifts according to set rules to achieve dynamic allocation of heat dissipation capacity; thermal conductivity properties refer to the set of core parameters of the heat transfer capacity of each heat dissipation path in the PFC power module; thermal conductivity contribution matching refers to the process of allocating the proportion of heat transfer undertaken by each path in coordinated heat dissipation based on the thermal conductivity properties of each path; thermal conductivity contribution rules refer to the criteria for clarifying the heat transfer ratio and adjustment conditions of each path; real-time temperature change rate refers to the amount of temperature change of the PFC power module per unit time; transient thermoelastic coefficient refers to the parameter of the dynamic response capability of the thermal conductivity of each path with real-time temperature changes during coordinated heat dissipation; and alarm response index refers to the judgment criteria for determining whether the coordinated heat dissipation system needs to trigger an alarm.

[0041] In this embodiment, determining the thermal exceedance boundary at the temperature detection point in the PFC power module based on the alarm response index and the dynamic heat flow data can be achieved through the following steps: The thermal inertia gradient at the temperature detection point is determined based on the alarm response index and the dynamic heat flow data. The cumulative thermal characteristics at each temperature detection point under heat flow fluctuations are evaluated based on the thermal inertia gradient. The thermal overshoot boundary at the temperature detection point in the PFC power module is determined by all the cumulative thermal characteristics.

[0042] In practice, firstly, the response delay time is extracted from the alarm response indicators, and the change in heat flux density over 10 consecutive sampling periods is extracted from the dynamic heat flux data. For each temperature detection point, the delay time of temperature change at the detection point is calculated when the heat flux density changes by 10 W / m². The gradient is calculated using the formula "thermal inertia gradient = delay time / change in heat flux density". If the delay is 30 ms and the heat flux change is 50 W / m², the gradient is 0.6 ms / (W / m²). This calculation is repeated for all detection points to obtain the thermal inertia gradient at each point. Then, a heat flux fluctuation segment within one minute is selected from the dynamic heat flux data and combined with the thermal inertia gradient at each detection point. A sliding window method (window size of 5 sampling periods) is used to calculate the cumulative heat at each detection point within the window: first, the instantaneous heat generation is calculated using the heat flux density, and then the heat release is corrected according to the thermal inertia gradient. The cumulative heat value, accumulation rate, and maximum cumulative value for each window are recorded and integrated into the cumulative thermal characteristics of each temperature detection point under heat flux fluctuations. Finally, the maximum cumulative heat value is extracted from the cumulative thermal characteristics of each detection point and combined with the alarm threshold in the alarm response index (e.g., alarm when thermal conductivity is below 80% of the baseline value). The maximum cumulative heat value is multiplied by a safety factor of 0.8 (leaving a safety margin) to obtain the maximum allowable cumulative heat at that detection point (e.g., 16J). Then, it is converted to the corresponding temperature value (e.g., from 60℃ to 75℃) using the formula "heat = cmΔT" (where c is the specific heat capacity of the device at the detection point and m is the mass). This temperature value is the thermal limit boundary. This calculation is repeated for all detection points to obtain the thermal limit boundary at the temperature detection points in the PFC power module.

[0043] It should be noted that, in this application, the temperature detection point refers to a specific location within the critical heat-generating area of ​​the PFC power module where a temperature sensor is installed to collect data; the thermal inertia gradient refers to the parameters of the lag and rate of temperature change at the temperature detection point in response to dynamic heat flow changes; the cumulative thermal characteristics refer to the set of parameters of the degree, rate, and peak value of heat accumulation at the temperature detection point due to thermal inertia during heat flow fluctuations; and the thermal limit boundary refers to the threshold that defines the maximum allowable cumulative heat at the temperature detection point under heat flow fluctuations.

[0044] In step S4, the PFC power module is given a graded alarm during dynamic thermal balance synchronous detection based on the thermal flow trend and the thermal over-limit boundary.

[0045] In practice, the dynamic thermal balance synchronous detection of the PFC power module is initiated. The heat generation power is calculated by collecting the module's input and output power, and the heat dissipation power is calculated by combining this with the heat flow data from the active cooling channel. The difference between the two is compared in real time. Simultaneously, the heat flow trend (e.g., stable diffusion, increased risk of localized accumulation) and the thermal exceedance boundaries of each temperature detection point are retrieved: If the heat flow trend is stable diffusion and all detection point temperatures are below 90% of the thermal exceedance boundary, it is considered risk-free, and routine monitoring is maintained; if the heat flow trend shows localized accumulation and the temperature of 1-2 detection points reaches 80%-90% of the thermal exceedance boundary, a level one alarm is triggered, the sensor sampling frequency is increased to 10Hz, and maintenance checks are prompted; if the heat flow trend is dangerous accumulation and the temperature of any detection point exceeds the thermal exceedance boundary, a level two alarm is triggered, the backup cooling system is activated, and the system operates at 10% derated; if the heat generation power exceeds the heat dissipation power by 20% and the detection point temperature exceeds the boundary by 5°C, a level three alarm is triggered, the system is immediately shut down, and an audible and visual alarm is triggered. Further details are omitted here.

[0046] It should be noted that in this application, dynamic thermal balance synchronous detection refers to the detection process of real-time synchronous monitoring of the heat generation power and heat dissipation power of the PFC module, and comparing the difference between the heat generation power and heat dissipation power to determine the thermal imbalance state; graded alarm refers to the alarm method that classifies the PFC module into different levels according to the degree of thermal risk, and corresponding to different response measures.

[0047] Therefore, this application demonstrates that, addressing the shortcomings of existing PFC power module thermal detection methods that rely on single-point static temperature acquisition and lack dynamic heat flow information, it enhances the comprehensiveness and dynamism of thermal status data. By acquiring temperature distribution information and dynamic heat flow data, it covers the spatial temperature distribution and dynamic heat transfer process in key areas of the module, avoiding the problem that traditional single-point temperature detection cannot reflect the overall heat distribution and heat flow path. Determining the heat accumulation trajectory and heat flow trend through temperature distribution information solves the shortcomings of existing fixed early warning strategies that cannot adapt to dynamic temperature changes and are difficult to capture heat accumulation and diffusion patterns, enabling dynamic optimization of early warning strategies and accurate identification of thermal trends, avoiding delayed or excessive early warnings due to misjudgments of thermal trends. Using multi-path thermal conductivity matching to obtain alarm response indicators and determine thermal limit boundaries compensates for the shortcomings of existing thermal detection methods that ignore heat dissipation channel temperature deviations, unbalanced thermal conductivity distribution, and statically set thermal limit boundaries. By implementing graded alarms during dynamic thermal balance synchronous detection, it addresses the shortcomings of existing single alarm methods that cannot handle different thermal risk levels and are difficult to adapt to dynamic thermal balance states, improving the effectiveness of thermal risk management.

[0048] In summary, the technical solution adopted in this application can accurately monitor and warn of the thermal status of the PFC power module during dynamic operation, thereby improving the accuracy of thermal detection alarms.

[0049] Example 2: This application provides a thermal detection system for a PFC power module, referring to... Figure 4 As shown in the figure, this is a module structure diagram of a thermal detection system for a PFC power module according to this embodiment of the present application. The thermal detection system includes: Data acquisition module 100 is used to acquire temperature distribution information and dynamic heat flow data of PFC power module during operation; The early warning adjustment module 200 is used to detect the temperature change of the PFC power module in real time and adjust the qualitative thermal early warning strategy. Based on the temperature distribution information, it determines the heat accumulation trajectory in the key heat source area and determines the heat flow trend of the PFC power module's operating temperature during temperature diffusion based on the heat accumulation trajectory and the adjusted qualitative thermal early warning strategy. The thermal conductivity matching module 300 is used to determine the calibration temperature deviation of the PFC power module in the active heat dissipation channel, perform multi-path thermal conductivity matching on the calibration temperature deviation, obtain the alarm response index of the PFC power module during collaborative heat dissipation operation, and then determine the thermal over-limit boundary at the temperature detection point in the PFC power module by the alarm response index and the dynamic heat flow data. The graded detection and alarm module 400 is used to perform graded alarms on the PFC power module during dynamic thermal balance synchronous detection based on the heat flow trend and the heat over-limit boundary.

[0050] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0051] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, including read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-Erasable Programmable Read-Only Memory (EEPROM), compactdisc read-only memory (CD-ROM) or other optical disc storage, disk storage, magnetic tape storage, or any other computer-readable medium capable of carrying or storing data.

[0052] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

Claims

1. A thermal detection method for a PFC power module, characterized in that, The thermal detection method includes the following steps: Acquire temperature distribution information and dynamic heat flow data of the PFC power module during operation; The temperature change of the PFC power module is detected in real time and the qualitative thermal warning strategy is adjusted. The heat accumulation trajectory in the key heat source area is determined based on the temperature distribution information. The heat flow trend of the operating temperature of the PFC power module during temperature diffusion is determined based on the heat accumulation trajectory and the adjusted qualitative thermal warning strategy. The calibration temperature deviation of the PFC power module in the active heat dissipation channel is determined, and multi-path thermal conductivity matching is performed on the calibration temperature deviation to obtain the alarm response index of the PFC power module during collaborative heat dissipation operation. Then, the thermal over-limit boundary at the temperature detection point in the PFC power module is determined by the alarm response index and the dynamic heat flow data. Based on the heat flow trend and the heat exceedance boundary, the PFC power module is given a graded alarm during dynamic thermal balance synchronous detection.

2. The thermal detection method for a PFC power module as described in claim 1, characterized in that, The temperature distribution information refers to the quantitative information on the temperature levels and spatial distribution in different areas within the PFC power module.

3. The thermal detection method for a PFC power module as described in claim 1, characterized in that, The dynamic heat flow data refers to parameters such as the real-time transfer rate, path, and heat flux density of heat within the PFC power module.

4. The thermal detection method for a PFC power module as described in claim 1, characterized in that, The determination of the thermal flow trend of the PFC power module's operating temperature during temperature diffusion based on the aforementioned thermal accumulation trajectory and the adjusted qualitative thermal early warning strategy specifically includes: Based on the heat accumulation trajectory and the adjusted qualitative thermal early warning strategy, temperature flow descriptions under different operating modes are determined; The temperature flow description is reconstructed by feedback to obtain the heat flow path of the operating temperature during temperature diffusion; The thermal flow trend of the PFC power module's operating temperature during temperature diffusion is determined based on the described thermal flow path.

5. The thermal detection method for a PFC power module as described in claim 1, characterized in that, Determining the calibration temperature deviation of the PFC power module in the active cooling channel specifically includes: Obtain the real-time temperature sequence of the PFC power module in the active cooling channel; The real-time temperature sequence is decomposed to obtain the temperature deviation attributes of each node in the active heat dissipation channel. The calibration temperature deviation of the PFC power module in the active cooling channel is determined based on all temperature deviation attributes.

6. The thermal detection method for a PFC power module as described in claim 1, characterized in that, Determining the thermal exceedance boundary at the temperature detection point in the PFC power module based on the alarm response index and the dynamic heat flow data specifically includes: The thermal inertia gradient at the temperature detection point is determined based on the alarm response index and the dynamic heat flow data. The cumulative thermal characteristics at each temperature detection point under heat flow fluctuations are evaluated based on the thermal inertia gradient. The thermal overshoot boundary at the temperature detection point in the PFC power module is determined by all the cumulative thermal characteristics.

7. The thermal detection method for a PFC power module as described in claim 1, characterized in that, Multi-path thermal conductivity matching is performed on the calibrated temperature deviation to obtain the alarm response indicators of the PFC power module during collaborative heat dissipation operation, specifically including: The thermal conductivity properties of each heat dissipation path of the PFC power module are determined based on the calibrated temperature deviation. The thermal conductivity contribution of each path during collaborative heat dissipation is matched to obtain the thermal conductivity contribution rule during collaborative heat dissipation. The transient thermoelastic coefficient during synergistic heat dissipation operation is determined based on all thermal conductivity contribution rules and real-time temperature change rate. The alarm response index of the PFC power module during cooperative heat dissipation operation is determined based on the transient thermoelastic coefficient and all thermal conductivity properties.

8. The thermal detection method for a PFC power module as described in claim 1, characterized in that, The aforementioned multi-path thermal conductivity matching refers to matching the thermal conductivity properties of each heat dissipation path in the PFC power module, so that heat is distributed and transferred according to its capacity, avoiding local overload.

9. The thermal detection method for a PFC power module as described in claim 1, characterized in that, The aforementioned dynamic thermal balance synchronous detection refers to the process of real-time synchronous monitoring of the heat generation power and heat dissipation power of the PFC module, and comparing the difference between the heat generation power and heat dissipation power to determine the thermal imbalance state.

10. A thermal detection system for a PFC power module, used to execute a thermal detection method for a PFC power module as described in any one of claims 1 to 9, characterized in that, The thermal detection system includes: The data acquisition module is used to acquire temperature distribution information and dynamic heat flow data of the PFC power module during operation; The early warning adjustment module is used to detect the temperature change of the PFC power module in real time and adjust the qualitative thermal early warning strategy. Based on the temperature distribution information, it determines the heat accumulation trajectory in the key heat source area and determines the heat flow trend of the PFC power module's operating temperature during temperature diffusion based on the heat accumulation trajectory and the adjusted qualitative thermal early warning strategy. The thermal conductivity matching module is used to determine the calibration temperature deviation of the PFC power module in the active heat dissipation channel, perform multi-path thermal conductivity matching on the calibration temperature deviation, obtain the alarm response index of the PFC power module during collaborative heat dissipation operation, and then determine the thermal over-limit boundary at the temperature detection point in the PFC power module by the alarm response index and the dynamic heat flow data. The graded detection and alarm module is used to issue graded alarms to the PFC power module during dynamic thermal balance synchronous detection based on the thermal flow trend and the thermal over-limit boundary.

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