Self-adaptive intelligent temperature control method and refrigeration wireless charger

Abstract

The invention relates to the technical field of wireless charging temperature control, in particular to a self-adaptive intelligent temperature control method and a refrigeration wireless charger. According to the method, the inherent heating tendency of the mobile equipment is quantified through the charging initial data, the heating index is obtained, the basic temperature threshold interval is obtained according to the heating index, and the charging environment data is introduced to intervene in the obtaining of the personalized temperature threshold in real time; the method solves the problem of unreasonable threshold setting caused by the difference of batteries of new and old equipment and the difference of heating characteristics of different models, then, by capturing charging process data of mobile equipment and combining threshold judgment, early warning and refrigeration triggering can be carried out in the early stage of abnormity, and the charging efficiency of the mobile equipment is improved. The emergency degree of the current refrigeration demand can be accurately described by analyzing the temperature control demand intensity value calculated by the charging process data, and the accurate temperature control adjustment parameters are dynamically generated in combination with the preset control parameter group of the refrigeration wireless charger, so that the charging and refrigeration assembly is directly controlled, and the temperature control response speed is favorably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless charging temperature control, and in particular to an adaptive intelligent temperature control method and a refrigeration wireless charger. Background Art

[0002] A refrigerated wireless charger is a wireless charging device that integrates cooling and heat dissipation functions. Its core function is to solve the heating problem caused by energy conversion and electromagnetic induction during wireless charging, so as to ensure the safety, stability and efficiency of the charging process. The device realizes wireless charging based on the principles of electromagnetic induction or magnetic resonance, and monitors the charging device and ambient temperature in real time through temperature sensors. When the temperature exceeds the preset threshold, the built-in cooling module (such as semiconductor cooling plate, fan, heat pipe, etc.) will automatically start and reduce the temperature through active heat dissipation mechanism. When the temperature drops to a safe range, the cooling module automatically reduces power or shuts down to achieve energy-saving operation, thus effectively avoiding device performance degradation, battery loss or safety hazards caused by excessive temperature. It is particularly suitable for scenarios such as high-power wireless charging, long-term charging or high-temperature environments.

[0003] Existing temperature control strategies for cooling wireless chargers are rigid. The root cause lies in the use of a fixed threshold control mode. The preset unified temperature threshold fails to take into account the heating characteristics of different devices and the differences in batteries between new and old devices. As a result, the threshold setting deviates from actual needs and is either too high or too low, ultimately leading to poor temperature control effects. Summary of the Invention

[0004] The main purpose of the present invention is to provide an adaptive intelligent temperature control method and a refrigeration wireless charger, aiming to solve the technical problems in the prior art.

[0005] The present invention proposes an adaptive intelligent temperature control method, which is applicable to a refrigerated wireless charger connected to a mobile device to power the mobile device, comprising: Acquiring charging status data and basic device data of the mobile device, wherein the charging status data includes charging initial data, charging process data, and charging environment data; Obtaining a heating index of the mobile device according to the initial charging data and the basic device data, and obtaining a basic temperature threshold interval according to the heating index; Acquire a personalized temperature threshold corresponding to the mobile device according to the charging environment data and the basic temperature threshold range; determining whether cooling is required based on the charging process data and the personalized temperature threshold; If cooling is required, obtaining a temperature control demand intensity value based on the charging process data; Obtain a control parameter group for the refrigerated wireless charger, and obtain temperature control adjustment parameters based on the control parameter group and the temperature control requirement intensity value, wherein the temperature control adjustment parameters include a charging power adjustment parameter, a cooling plate current adjustment parameter, and a fan speed adjustment parameter; Refrigeration adjustment is performed according to the temperature control adjustment parameters.

[0006] Preferably, the step of obtaining a heating index of the mobile device according to the initial charging data and the basic device data, and obtaining a basic temperature threshold range according to the heating index includes: Obtaining the battery health, aging impact coefficient, and ideal operating temperature based on the basic device data, and obtaining the real-time surface temperature value and initial charging power of the mobile device based on the initial charging data; Obtain the ambient temperature value based on the charging environment data; Obtaining an initial output power of the refrigeration wireless charger, and obtaining a real-time thermal resistance of the mobile device based on the real-time surface temperature value, the ambient temperature value, the initial output power, and the initial charging power; Obtaining an aging compensation value of the mobile device according to the battery health and the aging impact coefficient, and obtaining a heating index according to the aging compensation value, the initial output power, the initial charging power, and the real-time thermal resistance; A thermal threshold mapping table is obtained, and a basic temperature threshold interval is obtained according to the thermal threshold mapping table and a fever index.

[0007] Preferably, the step of obtaining the personalized temperature threshold corresponding to the mobile device according to the charging environment data and the basic temperature threshold range includes: Acquiring environmental characteristic impact data based on the charging environment data, wherein the environmental characteristic impact data includes a temperature comprehensive impact value, a humidity comprehensive impact value, an air flow impact value, and a space restriction impact value; Obtaining an environmental heat dissipation efficiency index based on the temperature comprehensive impact value, the air flow impact value, and the space restriction impact value, and obtaining an environmental severity index based on the temperature comprehensive impact value, the humidity comprehensive impact value, and the air flow impact value; Obtaining an environmental adaptive threshold association table, and obtaining environmental stress action data according to the environmental adaptive threshold association table; Obtaining a heat dissipation-temperature response curve and a severity-temperature response curve according to the environmental stress action data, and obtaining an efficiency compensation value according to the environmental heat dissipation efficiency index and the heat dissipation-temperature response curve; Obtaining a safety compensation value according to the environmental severity index and the severity-temperature response curve; A personalized temperature threshold is obtained according to the safety compensation value, the efficiency compensation value and the basic temperature threshold range.

[0008] Preferably, the step of determining whether cooling is required based on the charging process data and the personalized temperature threshold comprises: Acquire charging power fluctuation data, equivalent impedance change data, and surface thermal field distribution data based on the charging process data; Acquire a three-dimensional temperature field according to the surface thermal field distribution data, and acquire a plurality of core heating areas and core area temperature values ​​according to the three-dimensional temperature field; Obtaining weight parameters of the core heating area through principal component analysis, and obtaining a comprehensive temperature value based on the core area temperature value and the corresponding weight parameters; Obtaining instantaneous thermal shock intensity based on the charging power fluctuation data, and obtaining an impedance temperature rise coefficient based on the equivalent impedance change data; Obtaining a temperature compensation value according to the instantaneous thermal shock intensity and the instantaneous thermal shock intensity, and obtaining a final temperature value according to the temperature compensation value and the comprehensive temperature value; Determine whether the final temperature value is greater than the personalized temperature threshold: If the final temperature value is not greater than the personalized temperature threshold, it is determined that the refrigerated wireless charger does not need to be refrigerated; If the final temperature value is greater than the personalized temperature threshold, it is determined that the refrigerated wireless charger needs to be refrigerated.

[0009] Preferably, the step of obtaining the temperature control requirement intensity value according to the charging process data includes: Performing a fast Fourier transform on the charging power fluctuation data to obtain a high-frequency disturbance characteristic frequency band, and obtaining a disturbance energy ratio based on the high-frequency disturbance characteristic frequency band; Acquire dynamic correlation data according to the equivalent impedance change data and the surface thermal field distribution data, and acquire a temperature rise response coefficient according to the dynamic correlation data; Obtaining a coupling influence value according to the temperature rise response coefficient and the disturbance energy ratio, and obtaining an aging state correction coefficient according to the weight parameter of the core heating area and the battery health; A temperature control requirement intensity value is obtained according to the coupling influence value and the aging state correction coefficient.

[0010] Preferably, the step of obtaining the temperature control adjustment parameter according to the control parameter group and the temperature control requirement intensity value includes: Obtaining a temperature deviation value according to the final temperature value and the personalized temperature threshold, and obtaining a power adjustment amount according to the control parameter group, the temperature deviation value, and the temperature control requirement intensity value; Obtaining power reduction limit data, and obtaining a maximum charging power and a maximum reduction ratio based on the power reduction limit data; Obtaining a charging power adjustment parameter based on the maximum charging power, the maximum reduction ratio, and the power adjustment amount, and obtaining a cooling fin current adjustment parameter based on the charging power adjustment parameter and the temperature control requirement intensity value; Obtaining a temperature control requirement level according to the temperature control requirement intensity value and the ambient temperature value; Obtain a speed parameter comparison table, and obtain fan speed adjustment parameters based on the speed parameter comparison table and the temperature control requirement level.

[0011] Preferably, the step of performing refrigeration adjustment according to the temperature control adjustment parameter includes: Obtaining a cooling efficiency index according to the charging power adjustment parameter, the cooling plate current adjustment parameter, and the fan speed adjustment parameter; Obtaining a multi-parameter collaborative optimization table, and obtaining refrigeration adjustment data according to the multi-parameter collaborative optimization table and the refrigeration efficiency index; Execute charging power adjustment, cooling plate current control and fan speed adjustment according to the cooling adjustment data to obtain real-time operating parameters; Obtaining a cooling efficiency evaluation value according to the real-time operating parameters, and determining whether the cooling efficiency evaluation value exceeds a preset threshold; If not, obtaining an adjustment correction coefficient based on the cooling efficiency evaluation value and the preset threshold, and correcting the charging power adjustment parameter, the cooling fin current adjustment parameter, and the fan speed adjustment parameter based on the adjustment correction coefficient to obtain a dynamic adjustment parameter; The dynamic adjustment parameter is used as the temperature control adjustment parameter and returned to the step of obtaining the refrigeration performance index until the refrigeration performance evaluation value exceeds a preset threshold.

[0012] The present application also provides a refrigeration wireless charger, comprising: A first acquisition module is used to acquire charging status data and device basic data of the mobile device, wherein the charging status data includes charging initial data, charging process data and charging environment data; a second acquisition module, configured to acquire a fever index of the mobile device according to the initial charging data and the basic device data, and acquire a basic temperature threshold interval according to the fever index; A third acquisition module is configured to acquire a personalized temperature threshold corresponding to the mobile device according to the charging environment data and the basic temperature threshold range; a judgment module, configured to judge whether cooling is required based on the charging process data and the personalized temperature threshold; a fourth acquisition module, configured to acquire a temperature control demand intensity value based on the charging process data if cooling is required; a fifth acquisition module, configured to acquire a control parameter group of the refrigeration wireless charger, and acquire temperature control adjustment parameters based on the control parameter group and the temperature control requirement intensity value, wherein the temperature control adjustment parameters include a charging power adjustment parameter, a cooling plate current adjustment parameter, and a fan speed adjustment parameter; The regulating module is used to perform refrigeration regulation according to the temperature control regulation parameters.

[0013] Preferably, the judgment module includes: a first acquiring unit, configured to acquire charging power fluctuation data, equivalent impedance change data, and surface thermal field distribution data according to the charging process data; a second acquiring unit, configured to acquire a three-dimensional temperature field according to the surface thermal field distribution data, and acquire a plurality of core heating areas and core area temperature values ​​according to the three-dimensional temperature field; a third acquiring unit, configured to acquire a weight parameter of a core heating area through principal component analysis, and acquire a comprehensive temperature value according to the core area temperature value and the corresponding weight parameter; a fourth acquiring unit, configured to acquire an instantaneous thermal shock intensity according to the charging power fluctuation data, and acquire an impedance temperature rise coefficient according to the equivalent impedance change data; a fifth acquiring unit, configured to acquire a temperature compensation value according to the instantaneous thermal shock intensity and the instantaneous thermal shock intensity, and acquire a final temperature value according to the temperature compensation value and the comprehensive temperature value; A judging unit, configured to judge whether the final temperature value is greater than the personalized temperature threshold: If the final temperature value is not greater than the personalized temperature threshold, it is determined that the refrigerated wireless charger does not need to be refrigerated; If the final temperature value is greater than the personalized temperature threshold, it is determined that the refrigerated wireless charger needs to be refrigerated.

[0014] The present invention also provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned adaptive intelligent temperature control method when executing the computer program.

[0015] The beneficial effects of the present invention are as follows: by acquiring charging status data and basic device data, the present invention can establish a three-dimensional data model of "basic data + dynamic status + environmental perception", and quantify the inherent heating tendency of the mobile device through the initial charging data to obtain the heating index, and obtain the basic temperature threshold range according to the heating index. This method solves the problem of unreasonable threshold setting caused by "battery differences between new and old devices and different heating characteristics of different models", and this solution introduces charging environment data to intervene in the acquisition of personalized temperature thresholds in real time, thereby effectively solving the problem of "unified threshold failure in extreme environments". Then, by capturing the charging process data of the mobile device and combining it with threshold judgment, it can be used in abnormal situations. Early warning is given and cooling is triggered to prevent the problem from worsening. The dual judgment mechanism of "real-time data + dynamic threshold" is used to solve the problem of poor temperature control effect caused by the "delayed reaction" of the fixed threshold. When it is judged that cooling needs to be started, the charging process data is quantitatively analyzed to calculate the temperature control demand intensity value to accurately describe the urgency and intensity level of the current cooling demand. Finally, by integrating the preset control parameter group of the cooling wireless charger and combining the real-time calculated temperature control demand intensity value, accurate temperature control adjustment parameters are dynamically generated to directly control the charging and cooling components. Through this multi-component collaborative adjustment method, a dual mechanism of "heat production control + active heat dissipation" is formed, which is conducive to improving the temperature control response speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 Schematic diagram of a method flow according to an embodiment of the present invention.

[0017] Figure 2 A schematic diagram of the device structure of an embodiment of the present invention Figure 3 This is a schematic diagram of the internal structure of a computer device according to an embodiment of the present application.

[0018] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0019] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0020] like Figure 1 As shown, the present application provides an adaptive intelligent temperature control method, which is applicable to a refrigerated wireless charger, wherein the refrigerated wireless charger is connected to a mobile device to power the mobile device, comprising: S1. Acquire charging status data and basic device data of a mobile device, wherein the charging status data includes charging initial data, charging process data, and charging environment data; S2. Obtaining a heating index of the mobile device according to the initial charging data and the basic device data, and obtaining a basic temperature threshold interval according to the heating index; S3. Obtaining a personalized temperature threshold corresponding to the mobile device according to the charging environment data and the basic temperature threshold range; S4. Determining whether cooling is required based on the charging process data and the personalized temperature threshold; S5. If cooling is required, obtaining a temperature control demand intensity value based on the charging process data; S6. Obtain a control parameter group for the refrigeration wireless charger, and obtain temperature control adjustment parameters based on the control parameter group and the temperature control requirement intensity value to perform refrigeration adjustment, wherein the temperature control adjustment parameters include a charging power adjustment parameter, a refrigeration plate current adjustment parameter, and a fan speed adjustment parameter.

[0021] S7. Perform cooling adjustment according to the temperature control adjustment parameters.

[0022] As described in the above steps S1-S7, the present invention can establish a three-dimensional data model of "basic data + dynamic state + environmental perception" by acquiring charging status data and device basic data, wherein the charging status data refers to various status data of mobile devices (such as mobile phones, smart watches) during the charging process collected through sensors, protocol interactions and device bottom-layer interfaces, including charging initial data, charging process data and charging environment data, wherein the charging initial data refers to the device status data collected in the initial stage of charging (such as within the first 30 seconds after connecting to the charger), such as the initial charging power, etc. The charging process data refers to the dynamic data continuously collected during the charging process, which reflects the energy status and temperature change trend of the device in real time, such as the real-time power. etc. Charging environment data refers to external environmental parameters collected by environmental sensors (such as temperature sensors, humidity sensors, and light sensors). The environmental sensors are installed in the refrigeration wireless refrigerator. Equipment basic data refers to the inherent attribute data of mobile devices, such as battery health, etc. Since traditional temperature control solutions do not take into account the heating characteristics of different devices and only rely on a unified threshold (such as 42°C alarm), the unified threshold may cause the actual temperature of the device to far exceed the safe range without triggering an alarm, and the device may frequently start cooling in a low temperature environment due to overly conservative thresholds, wasting energy. Therefore, this solution quantifies the inherent heating tendency of mobile devices through the initial charging data to obtain a heating index, where the heating index is used to evaluate the device in a standard environment. The value of the inherent heating tendency under the condition of heating index is obtained, and the basic temperature threshold range is obtained according to the heating index. The basic temperature threshold range refers to the temperature safety range dynamically set for a single device based on the heating index. This method solves the problem of unreasonable threshold setting caused by "battery differences between new and old devices and different heating characteristics of different models". The traditional solution does not consider the influence of environmental factors, but in actual scenarios, environmental variables (such as indoor and outdoor temperature differences, direct sunlight during vehicle charging) have a significant impact on device heat dissipation. Therefore, this solution introduces charging environment data to intervene in the acquisition of personalized temperature thresholds in real time. The personalized temperature threshold refers to the real-time threshold that is further corrected based on the basic temperature threshold range and combined with the charging environment data, thereby effectively solving the "unified temperature threshold" problem. This solution captures the charging process data of mobile devices and combines it with threshold judgment to provide early warning and trigger cooling at the early stage of abnormalities (such as when the temperature rises rapidly but does not reach the traditional threshold) to prevent the problem from worsening. The dual judgment mechanism of "real-time data + dynamic threshold" solves the problem of poor temperature control effect caused by the "delayed response" of fixed thresholds. When cooling is determined to be necessary, the temperature control demand intensity value is calculated through quantitative analysis of the charging process data. The temperature control demand intensity value refers to the value that reflects the degree to which the current device temperature deviates from the personalized threshold and the urgency of heat dissipation.The system accurately describes the urgency and intensity of the current cooling demand. Finally, by integrating the preset control parameter group of the cooling wireless charger, which refers to the set of control parameters supported by the cooling wireless charger hardware, such as the hardware-supported charging power range, cooling plate current range, fan speed gear, etc., and combining it with the real-time calculated temperature control demand intensity value, it dynamically generates precise temperature control adjustment parameters. The temperature control adjustment parameters refer to specific execution parameters dynamically generated based on the temperature control demand intensity value and the control parameter group, directly controlling the charging and cooling components (such as reducing the charging power to 15W, adjusting the cooling plate current to 1.2A, and increasing the fan speed to 2500 rpm). This multi-component coordinated adjustment method solves the problem of "low regulation efficiency of a single actuator" and forms a dual mechanism of "heat generation control + active heat dissipation", which is conducive to improving the temperature control response speed.

[0023] In one embodiment, the step S2 of obtaining a heating index of the mobile device according to the initial charging data and the basic device data, and obtaining a basic temperature threshold interval according to the heating index includes: S21. Obtaining a battery health, an aging impact coefficient, and an ideal operating temperature based on the basic device data, and obtaining a real-time surface temperature value and an initial charging power of the mobile device based on the initial charging data; S22. Obtaining an ambient temperature value based on the charging environment data; S23. Obtaining the initial output power of the cooling wireless charger, and obtaining the real-time thermal resistance of the mobile device based on the real-time surface temperature value, the ambient temperature value, the initial output power, and the initial charging power; S24. Obtaining an aging compensation value of the mobile device according to the battery health and the aging impact coefficient, and obtaining a heating index according to the aging compensation value, the initial output power, the initial charging power, and the real-time thermal resistance; S25 . Obtain a thermal threshold mapping table, and obtain a basic temperature threshold interval according to the thermal threshold mapping table and the fever index.

[0024] As described in the above steps S21-S25, the present invention obtains the battery health, aging influence coefficient and ideal operating temperature of the mobile device, thereby identifying the aging status and inherent characteristics of the mobile device. By introducing the battery health and aging influence coefficient, the battery status of new and old devices can be distinguished, which enables the temperature control strategy to be adjusted according to the age of the device battery, so as to solve the problem that the traditional temperature control method ignores the aging differences of mobile devices. Then, the real-time surface temperature and initial charging power of the mobile device, as well as the ambient temperature of the mobile device, are obtained, and the real-time thermal resistance is calculated by the formula "real-time thermal resistance = (real-time surface temperature - ambient temperature) / (initial output power - initial charging power)". Thermal resistance, among which real-time thermal resistance refers to the resistance of the mobile device's internal heat to the external environment when it is currently charging. It reflects the relationship between the heat generated by the device and the temperature change in the current state. Since the traditional temperature control method assumes that the thermal resistance is fixed by default, and in actual applications, the thermal resistance changes with the device state, the heat dissipation characteristics of different devices can be represented by dynamically calculating the thermal resistance. Then, the aging compensation value is calculated by the formula "aging compensation value = 1 + (1-battery health) * aging impact coefficient". Among them, the aging compensation value refers to the compensation coefficient for correcting the heating risk according to the device's battery health status and aging degree. By introducing the aging compensation mechanism, the problem of old devices can be solved. The problem of changes in heating patterns due to battery attenuation is solved. The heating index is calculated using the formula "thermal index = (initial output power - initial charging power) * aging compensation value / [(1 / real-time thermal resistance) * ideal operating temperature]". Its essence is the ratio of "actual heating value" to "theoretical heat dissipation demand". If the heating index is high, it means that the heat generation is high or the heat dissipation is poor. In this case, a stricter temperature threshold should be set to cool down in advance. If the heating index is low, it means that the heat generation is low or the heat dissipation is good. In this case, the temperature threshold should be relaxed to avoid unnecessary cooling. The heating index can be used to intuitively compare the heating levels of different devices and under different conditions, providing an accurate basis for subsequent temperature control decisions, and finally obtaining the thermal threshold. Mapping table, where the thermal threshold mapping table refers to a pre-established mapping relationship table between the fever index and the basic temperature threshold interval. It is essentially a "threshold database" based on the fever characteristics of the device, and matches the corresponding basic temperature threshold interval from the thermal threshold mapping table according to the fever index. Through the above method, it can be better applied to different new and old devices, and no longer "one size fits all" to control all devices with a fixed temperature threshold. Instead, it dynamically obtains a reasonable temperature threshold interval based on the real-time heat generation and heat dissipation capabilities of the mobile device. Different devices have different fever indexes, and the corresponding fever levels and basic temperature threshold intervals are also different, avoiding the problem of traditional fixed thresholds being high or low, and laying the foundation for achieving precise temperature control.

[0025] In one embodiment, the step S3 of acquiring the personalized temperature threshold corresponding to the mobile device according to the charging environment data and the basic temperature threshold interval includes: S31. Acquire environmental characteristic impact data based on the charging environment data, wherein the environmental characteristic impact data includes a temperature comprehensive impact value, a humidity comprehensive impact value, an air flow impact value, and a space restriction impact value; S32. Obtaining an environmental heat dissipation efficiency index based on the temperature comprehensive impact value, the air flow impact value, and the space restriction impact value, and obtaining an environmental severity index based on the temperature comprehensive impact value, the humidity comprehensive impact value, and the air flow impact value; S33, obtaining an environment adaptation threshold association table, and obtaining environmental stress action data according to the environment adaptation threshold association table; S34, obtaining a heat dissipation-temperature response curve and a severity-temperature response curve according to the environmental stress data, and obtaining an efficiency compensation value according to the environmental heat dissipation efficiency index and the heat dissipation-temperature response curve; S35, obtaining a safety compensation value according to the environmental severity index and the severity-temperature response curve; S36. Obtain a personalized temperature threshold according to the safety compensation value, the efficiency compensation value, and the basic temperature threshold range.

[0026] As described in the above steps S31-S36, the present invention obtains environmental characteristic impact data by normalizing the charging environment data, wherein the environmental characteristic impact data refers to the core physical characteristic parameters that quantify the impact of device heat dissipation and temperature safety in the charging environment, including the comprehensive temperature impact value, the comprehensive humidity impact value, the air flow impact value and the space restriction impact value, thereby converting complex environmental information into quantifiable and analyzable key indicators, providing basic data for the subsequent evaluation of the impact of the environment on the temperature of the charging device, breaking through the limitation of traditional unified threshold temperature control that does not consider environmental factors, and enabling the temperature control strategy to perceive environmental changes by quantifying environmental characteristics. For example, different usage scenarios (indoor, outdoor, closed space, open space) have a huge impact on device heat dissipation. This step allows the temperature control system to have environmental adaptability, thereby more accurately setting the temperature threshold. Since the wind speed and convective heat dissipation efficiency are not linearly related, combined with the boundary layer theory in fluid mechanics, and the inhibitory effect of space restrictions on heat dissipation is inversely proportional, through the formula The environmental heat dissipation efficiency index is calculated, where: Indicates the environmental heat dissipation efficiency index, Indicates a nonlinear transformation of the air flow impact value to the power of 0.8. Indicates the space restriction impact value, It represents the comprehensive impact value of temperature. The environmental heat dissipation efficiency index is a comprehensive indicator value that measures the degree to which the charging environment promotes or inhibits the heat dissipation capacity of the device. The higher the value, the more conducive the environment is to the heat dissipation of the device. In order to highlight the severity of the high temperature environment and make the temperature control strategy more sensitive to high temperature, super linear growth is used to simulate the accelerated aging effect of high temperature on the device, and a logarithmic function is used to control the penalty degree of the high humidity range. This can avoid the overreaction to high humidity in traditional methods and is more in line with reality: humidity mainly indirectly affects heat dissipation through condensation and corrosion, and the mitigating effect of air flow is inversely proportional to the square root of wind speed. Through the formula The environmental severity index is calculated, where represents the environmental severity index, Indicates a superlinear transformation of the temperature comprehensive influence value to the power of 1.2, Indicates the comprehensive impact value of humidity, The environmental severity index is a comprehensive indicator used to assess the threat posed by the charging environment to device safety. A higher index indicates harsher environmental conditions and higher requirements for device temperature control. The environmental heat dissipation efficiency index and environmental severity index, calculated using specific formulas, further integrate multiple environmental feature impact data into a comprehensive indicator that can intuitively reflect the environmental heat dissipation capacity and severity, providing a quantitative basis for subsequent adjustment of temperature thresholds. Traditional temperature control does not systematically quantify environmental conditions, but this step directly links environmental factors with device temperature control requirements by constructing an index. For example, a low environmental heat dissipation efficiency index indicates heat dissipation difficulties, requiring a corresponding lowering of the temperature threshold to ensure device safety. A high environmental severity index indicates a greater threat to the device, requiring adjustment of the threshold to strengthen protection. This effectively addresses the problem of a unified threshold failing to adapt to environmental changes. Based on extensive experiments and empirical summaries, an environmental adaptive threshold association table is obtained. The environmental adaptive threshold association table refers to the pre-generated "environmental feature combination and threshold adjustment rules." The mapping relationship table is obtained, and the environmental stress effect data is obtained according to the environmental adaptive threshold association table, wherein the environmental stress effect data refers to a parameter set that describes the physical effect intensity of environmental factors on the temperature safety of the device and the threshold adjustment logic. Then, the heat dissipation-temperature response curve and the severity-temperature response curve are obtained according to the environmental stress effect data, wherein the heat dissipation-temperature response curve refers to a function curve that reflects the relationship between the environmental heat dissipation efficiency index and the temperature threshold adjustment amount, and the severity-temperature response curve refers to a function curve that reflects the relationship between the environmental severity index and the temperature threshold adjustment amount. Then, the efficiency compensation value is obtained according to the environmental heat dissipation efficiency index and the heat dissipation-temperature response curve, wherein the efficiency compensation value refers to the impact of the environmental heat dissipation efficiency on the charging efficiency of the device. , the compensation adjustment amount for the temperature threshold is obtained according to the environmental severity index and the severity-temperature response curve to obtain the safety compensation coefficient, where the safety compensation coefficient refers to the mandatory safety margin adjustment amount for the temperature threshold based on the impact of environmental severity on the safety risk of the equipment. Through these two coefficients, the environmental factors are converted into adjustment parameters of the temperature threshold. The basic temperature threshold range includes the basic temperature upper value and the basic temperature middle value. Therefore, the personalized temperature threshold = [(basic temperature upper value + efficiency compensation value) + (basic temperature middle value + safety compensation coefficient)] / 2. The above method converts equipment characteristics and environmental stresses into calculable compensation parameters through a mathematical model that integrates multiple factors, forming a "benchmark + correction" hierarchical control framework, breaking through the limitations of the traditional single threshold.

[0027] In one embodiment, the step S4 of determining whether cooling is required based on the charging process data and the personalized temperature threshold includes: S41. Acquire charging power fluctuation data, equivalent impedance change data, and surface thermal field distribution data based on the charging process data; S42, obtaining a three-dimensional temperature field according to the surface thermal field distribution data, and obtaining a plurality of core heating areas and core area temperature values ​​according to the three-dimensional temperature field; S43, obtaining weight parameters of the core heating area through principal component analysis, and obtaining a comprehensive temperature value according to the core area temperature value and the corresponding weight parameters; S44. Obtaining instantaneous thermal shock intensity based on the charging power fluctuation data, and obtaining an impedance temperature rise coefficient based on the equivalent impedance change data; S45, obtaining a temperature compensation value according to the instantaneous thermal shock intensity and the instantaneous thermal shock intensity, and obtaining a final temperature value according to the temperature compensation value and the comprehensive temperature value; S46. Determine whether the final temperature value is greater than the personalized temperature threshold: If the final temperature value is not greater than the personalized temperature threshold, it is determined that the refrigerated wireless charger does not need to be refrigerated; If the final temperature value is greater than the personalized temperature threshold, it is determined that the refrigerated wireless charger needs to be refrigerated.

[0028] As described in the above steps S41-S46, the present invention comprehensively characterizes the heating state of the device by acquiring multi-dimensional data (electrical parameters, thermal parameters) to solve the problem that "fixed thresholds cannot perceive dynamic thermal shocks". For example, when the power fluctuation is large but the instantaneous temperature does not exceed the threshold, an early warning of potential overheating risks is issued, and then the two-dimensional surface temperature distribution is reconstructed into a three-dimensional temperature field based on the surface thermal field distribution data, wherein the three-dimensional temperature field refers to a three-dimensional spatial model of the temperature distribution of each point inside and on the surface of the mobile device during the charging process, which is usually presented in the form of a temperature gradient cloud map or a grid. Then, the core heating area inside the device is identified based on the three-dimensional temperature field, and the temperature value of the core area is obtained by the core heating area, wherein the core heating area refers to the area in the three-dimensional temperature field where the temperature is significantly higher than the average temperature of the device. The core area temperature value refers to the real-time temperature measurement value in the core heating area to avoid misjudgment based on surface temperature alone (such as low shell temperature but overheated inside). This method uses three-dimensional modeling to achieve reverse calculation of "surface-to-internal" heat conduction, solving the problem of "missed detection of overheating inside the device", which is especially suitable for wireless charging devices with closed structures. Principal component analysis (PCA) is then introduced to quantify the thermal importance of different areas to solve the problem of "ignoring the difference in contribution of multiple heat sources". For example, when the temperature of the battery core area is close to the threshold and the shell temperature is low, the traditional strategy may not trigger cooling, while this method prioritizes response through weight distribution. For high-risk areas, calculate the contribution weight of each area to the overall thermal safety (such as the battery area has a higher weight than the shell) to avoid neglecting the risks of key areas due to averaging. Then calculate the comprehensive temperature value based on the temperature of the core heating area and the weight parameters. The comprehensive temperature value refers to the overall temperature index obtained by weighted calculation of the temperature values ​​of each core heating area through principal component analysis (PCA). Then, obtain the power change and change time interval based on the charging power fluctuation data, and obtain the instantaneous thermal shock intensity based on the ratio of the power change and the change time interval. The instantaneous thermal shock intensity refers to the thermal power generated by the equipment in a short period of time due to sudden fluctuations in charging power (such as fast charging protocol switching, load mutation) during charging. The impedance change rate is then obtained based on the equivalent impedance change data, and the impedance change and temperature change are obtained, and the impedance temperature rise coefficient is obtained based on the ratio of the impedance change and the temperature change, where the impedance temperature rise coefficient refers to the sensitivity of the equivalent impedance inside the mobile device (such as battery internal resistance, line impedance) to changes in temperature. The power impact and impedance feedback are combined to obtain an additional temperature compensation value, where the temperature compensation value refers to the calculated additional temperature increment, which is used to correct the real-time temperature measurement value. The final temperature value is then obtained based on the sum of the comprehensive temperature value and the temperature compensation value, where the final temperature value refers to the temperature index after the comprehensive temperature value and the temperature compensation value are superimposed. The final temperature value is compared with the personalized temperature threshold to determine whether cooling is triggered.This method uses a comprehensive temperature criterion, replacing the traditional "black-or-white" judgment of a single threshold. For example, if the comprehensive temperature approaches the threshold but the compensation value indicates a potential warming trend, low-intensity cooling can be initiated in advance even if the threshold has not been exceeded, which is conducive to "preventive temperature control."

[0029] In one embodiment, the step S5 of obtaining the temperature control requirement intensity value according to the charging process data includes: S51. Performing a fast Fourier transform on the charging power fluctuation data to obtain a high-frequency disturbance characteristic frequency band, and obtaining a disturbance energy ratio based on the high-frequency disturbance characteristic frequency band; S52, obtaining dynamic correlation data according to the equivalent impedance change data and the surface thermal field distribution data, and obtaining a temperature rise response coefficient according to the dynamic correlation data; S53: Obtaining a coupling influence value according to the temperature rise response coefficient and the disturbance energy ratio, and obtaining an aging state correction coefficient according to the weight parameter of the core heating area and the battery health; S54: Obtain a temperature control requirement intensity value according to the coupling influence value and the aging state correction coefficient.

[0030] As described in the above steps S51-S54, the present invention converts the time domain signal into the frequency domain signal by performing Fourier transform on the charging power fluctuation data, identifies the high-frequency frequency band where the energy is concentrated as the high-frequency disturbance characteristic frequency band, wherein the high-frequency disturbance characteristic frequency band refers to the frequency interval with significant high-frequency fluctuation characteristics, and calculates the proportion of the energy in the frequency band in the total energy according to the high-frequency disturbance characteristic frequency band to obtain the disturbance energy proportion, wherein the disturbance energy proportion refers to the proportion of the energy in the high-frequency disturbance characteristic frequency band to the total energy of the charging power, and then obtains the dynamic correlation data according to the equivalent impedance change data and the surface thermal field distribution data, wherein the dynamic correlation data refers to the dynamic mapping relationship data established by analyzing the spatiotemporal correlation between the equivalent impedance change data and the surface thermal field distribution data, and establishes a dynamic correlation model based on the dynamic correlation data fitting, finds the point where the impedance suddenly changes in the dynamic correlation model, and calculates the point where the impedance suddenly changes. The temperature rise corresponding to the unit impedance change at the point is used to obtain the temperature rise response coefficient, where the temperature rise response coefficient refers to the temperature rise amplitude caused by the unit impedance change in the dynamic correlation data, which is used to reflect the sensitivity of the internal temperature change of the battery to the impedance. Then, the correlation effect of high-frequency power disturbance and battery temperature change is comprehensively considered, and the temperature rise response coefficient is combined with the disturbance energy ratio to obtain the coupling influence value, where the coupling influence value refers to the value reflecting the synergistic effect of high-frequency disturbance and impedance change on temperature. Then, the influence of battery aging on temperature control demand is further considered, and the aging state correction coefficient is obtained by combining the weight parameter of the core heating area and the battery health. Finally, the coupling influence value and the aging state correction coefficient are integrated to obtain the temperature control demand intensity value, so as to intuitively quantify the intensity of temperature control demand in the current state, and provide a clear basis for the determination of subsequent temperature control adjustment parameters.

[0031] In one embodiment, the step S6 of acquiring the temperature control adjustment parameter according to the control parameter group and the temperature control requirement intensity value includes: S61. Obtaining a temperature deviation value according to the final temperature value and the personalized temperature threshold, and obtaining a power adjustment amount according to the control parameter group, the temperature deviation value, and the temperature control requirement intensity value; S62: Obtain power reduction limit data, and obtain a maximum charging power and a maximum reduction ratio based on the power reduction limit data; S63: Obtain a charging power adjustment parameter based on the maximum charging power, the maximum reduction ratio, and the power adjustment amount, and obtain a cooling fin current adjustment parameter based on the charging power adjustment parameter and the temperature control requirement intensity value; S64: Obtaining a temperature control requirement level according to the temperature control requirement intensity value and the ambient temperature value; S65: Obtain a speed parameter comparison table, and obtain a fan speed adjustment parameter according to the speed parameter comparison table and the temperature control requirement level.

[0032] As described in the above steps S61-S65, the present invention adopts a PID control algorithm to obtain a power adjustment amount according to the control parameter group, the temperature deviation value and the temperature control demand intensity value, wherein the power adjustment amount refers to the charging power adjustment amount calculated by the algorithm, and then obtains the power reduction limit data, wherein the power reduction limit data refers to the pre-set charging power reduction constraint conditions, including the maximum charging power and the maximum reduction ratio. The adjustable range and the safe reduction limit of the charging power are clarified through the power reduction limit data, which can avoid the power adjustment exceeding the tolerance range of the equipment hardware, and obtain the charging power adjustment parameter according to the maximum charging power, the maximum reduction ratio and the power adjustment amount, wherein the charging power adjustment parameter refers to the actual charging power adjustment value finally determined. This method can solve the risk of equipment damage caused by the "unbounded parameter adjustment" in the traditional strategy, and since the refrigeration and power adjustment in the traditional temperature control operate independently, this method is achieved by combining The charging power adjustment parameter and the temperature control demand intensity value are combined to dynamically adjust the cooling plate current adjustment parameter. The cooling plate current adjustment parameter refers to the cooling plate working current adjustment amount calculated based on the charging power adjustment parameter and the temperature control demand intensity value, thereby realizing the coordinated control of "power derating + active cooling", thereby avoiding the limitations of a single adjustment method. For example, in a high temperature environment, the power is reduced and the cooling is enhanced at the same time to improve the temperature control efficiency. Finally, the temperature control demand intensity value and the ambient temperature are discretized into temperature control demand levels. The temperature control demand level refers to the temperature control urgency level (such as low, medium, high, and emergency) divided by the temperature control demand intensity value (reflecting the thermal stress level) and the ambient temperature value. The obtained speed parameter comparison table refers to the pre-established mapping table between the temperature control demand level and the fan speed. The preset speed parameter comparison table is used to convert the temperature control demand level into the actual fan speed value, thereby realizing a step-by-step adjustment of the heat dissipation capacity.

[0033] In one embodiment, the step S7 of performing refrigeration adjustment according to the temperature control adjustment parameter includes: S71. Obtaining a cooling efficiency index according to the charging power adjustment parameter, the cooling plate current adjustment parameter, and the fan speed adjustment parameter; S72: Obtain a multi-parameter collaborative optimization table, and obtain refrigeration adjustment data based on the multi-parameter collaborative optimization table and the refrigeration efficiency index; S73, performing charging power adjustment, cooling plate current control, and fan speed adjustment according to the cooling adjustment data to obtain real-time operating parameters; S74. Obtaining a cooling efficiency evaluation value according to the real-time operating parameter, and determining whether the cooling efficiency evaluation value exceeds a preset threshold; S75. If not, obtaining an adjustment correction coefficient based on the cooling efficiency evaluation value and the preset threshold, and correcting the charging power adjustment parameter, the cooling fin current adjustment parameter, and the fan speed adjustment parameter based on the adjustment correction coefficient to obtain a dynamic adjustment parameter. S76: Return the dynamic adjustment parameter as the temperature control adjustment parameter to the step of obtaining a refrigeration performance index until the refrigeration performance evaluation value exceeds a preset threshold.

[0034] As described in steps S71-S76 above, the present invention converts the charging power adjustment parameter, the cooling plate current adjustment parameter, and the fan speed adjustment parameter into a comprehensive index through a neural network model to reflect the nonlinear characteristics of the actual cooling efficiency, thereby obtaining a cooling efficiency index. The cooling efficiency index refers to a quantitative value of the overall cooling capacity that comprehensively reflects multi-dimensional input parameters such as the charging power adjustment parameter, the cooling plate current adjustment parameter, and the fan speed adjustment parameter, and obtains a multi-parameter collaborative optimization table. The multi-parameter collaborative optimization table refers to preset optimized combination data between parameters such as charging power, cooling plate current, and fan speed and cooling effect and energy efficiency. The cooling efficiency index is converted into specific adjustment instructions according to the multi-parameter collaborative optimization table. The cooling adjustment data is obtained, wherein the cooling adjustment data refers to specific adjustment instructions, including a charging power step-down sequence, a cooling plate pulse current waveform, and a fan speed change cycle. The cooling adjustment data is then converted into an actual control signal to drive the charging module, cooling plate, fan and other actuators to operate. For example, the wireless charging output power is adjusted according to the charging power step-down sequence to obtain the real-time charging power, the intermittent working mode of the semiconductor cooling plate is controlled according to the cooling plate pulse current waveform to obtain the real-time current of the cooling plate, and the fan speed frequency is adjusted according to the fan speed change cycle to obtain the real-time fan speed. This method can synchronously adjust the charging power and the cooling equipment to avoid the temperature control lag caused by "only adjusting cooling without adjusting charging" or "only adjusting charging at the expense of efficiency" in the traditional solution, and achieve power- Temperature dynamic coupling control, then based on the real-time operating parameters after execution (such as real-time charging power, real-time current of the cooling plate and real-time speed of the fan), the refrigeration efficiency evaluation value is calculated through the comprehensive evaluation model, wherein the refrigeration efficiency evaluation value refers to the value used to measure the actual efficiency of the current refrigeration system, and the refrigeration efficiency evaluation value is compared with the preset threshold to determine whether further parameter correction is needed to achieve the termination condition judgment of the closed-loop control. If the refrigeration efficiency evaluation value does not exceed the preset threshold, the adjustment correction coefficient is obtained according to the refrigeration efficiency evaluation value and the preset threshold through the PID control algorithm, wherein the adjustment correction coefficient refers to the value used to quantify the actual efficiency of the refrigeration system. Adjust the amplitude values ​​of parameters such as charging power, cooling plate current, and fan speed, and correct the charging power adjustment parameter, cooling plate current adjustment parameter, and fan speed adjustment parameter according to the adjustment correction coefficient to obtain dynamic adjustment parameters. The dynamic adjustment parameter refers to a new parameter combination obtained by correcting the original temperature control adjustment parameter by adjusting the correction coefficient. Finally, the corrected parameters are returned to the initial evaluation step to form a closed-loop adjustment until the performance meets the standard. This adjustment method can achieve a balance between cooling performance and adjustment efficiency, and ensure that the system reaches the optimal state within a reasonable time by limiting the number of cycles or the error range.

[0035] The present application also provides a refrigeration wireless charger, comprising: A first acquisition module is used to acquire charging status data and device basic data of the mobile device, wherein the charging status data includes charging initial data, charging process data and charging environment data; a second acquisition module, configured to acquire a fever index of the mobile device according to the initial charging data and the basic device data, and acquire a basic temperature threshold interval according to the fever index; A third acquisition module is configured to acquire a personalized temperature threshold corresponding to the mobile device according to the charging environment data and the basic temperature threshold range; a judgment module, configured to judge whether cooling is required based on the charging process data and the personalized temperature threshold; a fourth acquisition module, configured to acquire a temperature control demand intensity value based on the charging process data if cooling is required; a fifth acquisition module, configured to acquire a control parameter group of the refrigeration wireless charger, and acquire temperature control adjustment parameters based on the control parameter group and the temperature control requirement intensity value, wherein the temperature control adjustment parameters include a charging power adjustment parameter, a cooling plate current adjustment parameter, and a fan speed adjustment parameter; The regulating module is used to perform refrigeration regulation according to the temperature control regulation parameters.

[0036] In one embodiment, the judgment module includes: a first acquiring unit, configured to acquire charging power fluctuation data, equivalent impedance change data, and surface thermal field distribution data according to the charging process data; a second acquiring unit, configured to acquire a three-dimensional temperature field according to the surface thermal field distribution data, and acquire a plurality of core heating areas and core area temperature values ​​according to the three-dimensional temperature field; a third acquiring unit, configured to acquire a weight parameter of a core heating area through principal component analysis, and acquire a comprehensive temperature value according to the core area temperature value and the corresponding weight parameter; a fourth acquiring unit, configured to acquire an instantaneous thermal shock intensity according to the charging power fluctuation data, and acquire an impedance temperature rise coefficient according to the equivalent impedance change data; a fifth acquiring unit, configured to acquire a temperature compensation value according to the instantaneous thermal shock intensity and the instantaneous thermal shock intensity, and acquire a final temperature value according to the temperature compensation value and the comprehensive temperature value; A judging unit, configured to judge whether the final temperature value is greater than the personalized temperature threshold: If the final temperature value is not greater than the personalized temperature threshold, it is determined that the refrigerated wireless charger does not need to be refrigerated; If the final temperature value is greater than the personalized temperature threshold, it is determined that the refrigerated wireless charger needs to be refrigerated.

[0037] The present invention also provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned adaptive intelligent temperature control method when executing the computer program.

[0038] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media provided in this application and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct RAM bus dynamic RAM (DRDRAM), and RAM bus dynamic RAM (RDRAM).

[0039] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, apparatus, article, or method comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, apparatus, article, or method. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, apparatus, article, or method comprising the element.

[0040] The above description is only a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. An adaptive intelligent temperature control method, applicable to a refrigeration wireless charger, wherein the refrigeration wireless charger is connected to a mobile device to power the mobile device, characterized in that: include: Acquiring charging status data and basic device data of the mobile device, wherein the charging status data includes charging initial data, charging process data, and charging environment data; Obtaining a heating index of the mobile device according to the initial charging data and the basic device data, and obtaining a basic temperature threshold interval according to the heating index; Acquire a personalized temperature threshold corresponding to the mobile device according to the charging environment data and the basic temperature threshold range; determining whether cooling is required based on the charging process data and the personalized temperature threshold; If cooling is required, obtaining a temperature control demand intensity value based on the charging process data; Obtain a control parameter group for the refrigerated wireless charger, and obtain temperature control adjustment parameters based on the control parameter group and the temperature control requirement intensity value, wherein the temperature control adjustment parameters include a charging power adjustment parameter, a cooling plate current adjustment parameter, and a fan speed adjustment parameter; Refrigeration adjustment is performed according to the temperature control adjustment parameters.

2. The adaptive intelligent temperature control method according to claim 1, characterized in that: The step of obtaining a heating index of the mobile device according to the initial charging data and the basic device data, and obtaining a basic temperature threshold range according to the heating index includes: Obtaining the battery health, aging impact coefficient, and ideal operating temperature based on the basic device data, and obtaining the real-time surface temperature value and initial charging power of the mobile device based on the initial charging data; Obtain the ambient temperature value based on the charging environment data; Obtaining an initial output power of the refrigeration wireless charger, and obtaining a real-time thermal resistance of the mobile device based on the real-time surface temperature value, the ambient temperature value, the initial output power, and the initial charging power; Obtaining an aging compensation value of the mobile device according to the battery health and the aging impact coefficient, and obtaining a heating index according to the aging compensation value, the initial output power, the initial charging power, and the real-time thermal resistance; A thermal threshold mapping table is obtained, and a basic temperature threshold interval is obtained according to the thermal threshold mapping table and a fever index.

3. The adaptive intelligent temperature control method according to claim 1, characterized in that: The step of obtaining the personalized temperature threshold corresponding to the mobile device according to the charging environment data and the basic temperature threshold range includes: Acquiring environmental characteristic impact data based on the charging environment data, wherein the environmental characteristic impact data includes a temperature comprehensive impact value, a humidity comprehensive impact value, an air flow impact value, and a space restriction impact value; Obtaining an environmental heat dissipation efficiency index based on the temperature comprehensive impact value, the air flow impact value, and the space restriction impact value, and obtaining an environmental severity index based on the temperature comprehensive impact value, the humidity comprehensive impact value, and the air flow impact value; Obtaining an environmental adaptive threshold association table, and obtaining environmental stress action data according to the environmental adaptive threshold association table; Obtaining a heat dissipation-temperature response curve and a severity-temperature response curve according to the environmental stress action data, and obtaining an efficiency compensation value according to the environmental heat dissipation efficiency index and the heat dissipation-temperature response curve; Obtaining a safety compensation value according to the environmental severity index and the severity-temperature response curve; A personalized temperature threshold is obtained according to the safety compensation value, the efficiency compensation value and the basic temperature threshold range.

4. The adaptive intelligent temperature control method according to claim 1, characterized in that: The step of determining whether cooling is required based on the charging process data and the personalized temperature threshold comprises: Acquire charging power fluctuation data, equivalent impedance change data, and surface thermal field distribution data based on the charging process data; Acquire a three-dimensional temperature field according to the surface thermal field distribution data, and acquire a plurality of core heating areas and core area temperature values ​​according to the three-dimensional temperature field; Obtaining weight parameters of the core heating area through principal component analysis, and obtaining a comprehensive temperature value based on the core area temperature value and the corresponding weight parameters; Obtaining instantaneous thermal shock intensity based on the charging power fluctuation data, and obtaining an impedance temperature rise coefficient based on the equivalent impedance change data; Obtaining a temperature compensation value according to the instantaneous thermal shock intensity and the instantaneous thermal shock intensity, and obtaining a final temperature value according to the temperature compensation value and the comprehensive temperature value; Determine whether the final temperature value is greater than the personalized temperature threshold: If the final temperature value is not greater than the personalized temperature threshold, it is determined that the refrigerated wireless charger does not need to be refrigerated; If the final temperature value is greater than the personalized temperature threshold, it is determined that the refrigerated wireless charger needs to be refrigerated.

5. The adaptive intelligent temperature control method according to claim 4, characterized in that: The step of obtaining the temperature control requirement intensity value according to the charging process data includes: Performing a fast Fourier transform on the charging power fluctuation data to obtain a high-frequency disturbance characteristic frequency band, and obtaining a disturbance energy ratio based on the high-frequency disturbance characteristic frequency band; Acquire dynamic correlation data according to the equivalent impedance change data and the surface thermal field distribution data, and acquire a temperature rise response coefficient according to the dynamic correlation data; Obtaining a coupling influence value according to the temperature rise response coefficient and the disturbance energy ratio, and obtaining an aging state correction coefficient according to the weight parameter of the core heating area and the battery health; A temperature control requirement intensity value is obtained according to the coupling influence value and the aging state correction coefficient.

6. The adaptive intelligent temperature control method according to claim 4, characterized in that: The step of obtaining the temperature control adjustment parameter according to the control parameter group and the temperature control requirement intensity value includes: Obtaining a temperature deviation value according to the final temperature value and the personalized temperature threshold, and obtaining a power adjustment amount according to the control parameter group, the temperature deviation value, and the temperature control requirement intensity value; Obtaining power reduction limit data, and obtaining a maximum charging power and a maximum reduction ratio based on the power reduction limit data; Obtaining a charging power adjustment parameter based on the maximum charging power, the maximum reduction ratio, and the power adjustment amount, and obtaining a cooling fin current adjustment parameter based on the charging power adjustment parameter and the temperature control requirement intensity value; Obtaining a temperature control requirement level according to the temperature control requirement intensity value and the ambient temperature value; Obtain a speed parameter comparison table, and obtain fan speed adjustment parameters based on the speed parameter comparison table and the temperature control requirement level.

7. The adaptive intelligent temperature control method according to claim 1, characterized in that: The step of performing refrigeration adjustment according to the temperature control adjustment parameter includes: Obtaining a cooling efficiency index according to the charging power adjustment parameter, the cooling plate current adjustment parameter, and the fan speed adjustment parameter; Obtaining a multi-parameter collaborative optimization table, and obtaining refrigeration adjustment data according to the multi-parameter collaborative optimization table and the refrigeration efficiency index; Execute charging power adjustment, cooling plate current control and fan speed adjustment according to the cooling adjustment data to obtain real-time operating parameters; Obtaining a cooling efficiency evaluation value according to the real-time operating parameters, and determining whether the cooling efficiency evaluation value exceeds a preset threshold; If not, obtaining an adjustment correction coefficient based on the cooling efficiency evaluation value and the preset threshold, and correcting the charging power adjustment parameter, the cooling fin current adjustment parameter, and the fan speed adjustment parameter based on the adjustment correction coefficient to obtain a dynamic adjustment parameter; The dynamic adjustment parameter is used as the temperature control adjustment parameter and returned to the step of obtaining the refrigeration performance index until the refrigeration performance evaluation value exceeds a preset threshold.

8. A refrigeration wireless charger, characterized in that: include: A first acquisition module is used to acquire charging status data and device basic data of the mobile device, wherein the charging status data includes charging initial data, charging process data and charging environment data; a second acquisition module, configured to acquire a fever index of the mobile device according to the initial charging data and the basic device data, and acquire a basic temperature threshold interval according to the fever index; A third acquisition module is configured to acquire a personalized temperature threshold corresponding to the mobile device according to the charging environment data and the basic temperature threshold range; a judgment module, configured to judge whether cooling is required based on the charging process data and the personalized temperature threshold; a fourth acquisition module, configured to acquire a temperature control demand intensity value based on the charging process data if cooling is required; a fifth acquisition module, configured to acquire a control parameter group of the refrigeration wireless charger, and acquire temperature control adjustment parameters based on the control parameter group and the temperature control requirement intensity value, wherein the temperature control adjustment parameters include a charging power adjustment parameter, a cooling plate current adjustment parameter, and a fan speed adjustment parameter; The regulating module is used to perform refrigeration regulation according to the temperature control regulation parameters.

9. The refrigeration wireless charger according to claim 8, characterized in that: The judgment module includes: a first acquiring unit, configured to acquire charging power fluctuation data, equivalent impedance change data, and surface thermal field distribution data according to the charging process data; a second acquiring unit, configured to acquire a three-dimensional temperature field according to the surface thermal field distribution data, and acquire a plurality of core heating areas and core area temperature values ​​according to the three-dimensional temperature field; a third acquiring unit, configured to acquire a weight parameter of a core heating area through principal component analysis, and acquire a comprehensive temperature value according to the core area temperature value and the corresponding weight parameter; a fourth acquiring unit, configured to acquire an instantaneous thermal shock intensity according to the charging power fluctuation data, and acquire an impedance temperature rise coefficient according to the equivalent impedance change data; a fifth acquiring unit, configured to acquire a temperature compensation value according to the instantaneous thermal shock intensity and the instantaneous thermal shock intensity, and acquire a final temperature value according to the temperature compensation value and the comprehensive temperature value; A judging unit, configured to judge whether the final temperature value is greater than the personalized temperature threshold: If the final temperature value is not greater than the personalized temperature threshold, it is determined that the refrigerated wireless charger does not need to be refrigerated; If the final temperature value is greater than the personalized temperature threshold, it is determined that the refrigerated wireless charger needs to be refrigerated.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

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