Temperature control method and device of mobile terminal, equipment and storage medium

Abstract

The invention provides a temperature control method and device of a mobile terminal, equipment and a storage medium. The method comprises the steps that element temperature data and shell temperature data of the mobile terminal are acquired; when the element temperature data is greater than the preset temperature data, calculating first environment temperature data according to the element temperature data and the shell temperature data; calling an infrared camera to obtain second environment temperature data, and detecting whether human body temperature data exists in the second environment temperature data or not; if the human body temperature data is not detected, selecting a target temperature control mode from first preset temperature control modes according to the first environment temperature data and the second environment temperature data; if the human body temperature data is detected, updating the second environment temperature data to third environment temperature data according to the human body temperature data, and selecting a target temperature control mode from second preset temperature control modes according to the first environment temperature data and the third environment temperature data; and performing temperature control on the mobile terminal according to the target temperature control mode.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of mobile terminals, and in particular to a temperature control method and device for a mobile terminal, an apparatus, and a storage medium. BACKGROUND

[0002] Currently, when the temperature of a mobile terminal is too high, an efficient cooling strategy is usually adopted, such as directly reducing the operating frequency of a processor main core, forcibly limiting the screen refresh rate, or shutting down part of the functional modules. However, such methods lack dynamic analysis of the environmental temperature, user usage scenarios, and device heat conduction characteristics, resulting in a disconnection between the cooling measures and the actual situation, and reducing the user experience. SUMMARY

[0003] The present application provides a temperature control method and device for a mobile terminal, an apparatus, and a storage medium, for gradient temperature control according to the usage environment and user usage scenarios, to improve the user experience of using the mobile terminal.

[0004] In a first aspect, an embodiment of the present application provides a temperature control method for a mobile terminal, applied to the mobile terminal, wherein the mobile terminal comprises an infrared camera, and the method comprises the following steps: obtaining element temperature data and shell temperature data of the mobile terminal; when the element temperature data is greater than preset temperature data, calculating first environmental temperature data according to the element temperature data and the shell temperature data; calling the infrared camera to obtain second environmental temperature data, and detecting whether human body temperature data exists in the second environmental temperature data; if the human body temperature data is not detected, selecting a target temperature control mode from a first preset temperature control mode according to the first environmental temperature data and the second environmental temperature data; if the human body temperature data is detected, updating the second environmental temperature data to third environmental temperature data according to the human body temperature data, and selecting a target temperature control mode from a second preset temperature control mode according to the first environmental temperature data and the third environmental temperature data; controlling the temperature of the mobile terminal according to the target temperature control mode.

[0005] In a second aspect, an embodiment of the present application provides a temperature control device for a mobile terminal, which is used to execute the temperature control method for the mobile terminal as described in any of the embodiments of the present application, applied to the mobile terminal, wherein the mobile terminal comprises an infrared camera, and the device comprises the following modules: a data acquisition module, configured to obtain element temperature data and shell temperature data of the mobile terminal; The first temperature measurement module is configured to calculate first ambient temperature data according to the element temperature data and the case temperature data when the element temperature data is greater than the preset temperature data; The second temperature measurement module is configured to call the infrared camera to obtain second ambient temperature data, and detect whether human body temperature data exists in the second ambient temperature data. The first selection module is configured to select a target temperature control mode from first preset temperature control modes according to the first ambient temperature data and the second ambient temperature data if the human body temperature data is not detected. The second selection module is configured to update the second ambient temperature data to third ambient temperature data according to the human body temperature data if the human body temperature data is detected, and select a target temperature control mode from second preset temperature control modes according to the first ambient temperature data and the third ambient temperature data. The mode execution module is configured to perform temperature control on the mobile terminal according to the target temperature control mode.

[0006] In a third aspect, an embodiment of the present application provides a mobile device, which comprises a memory and a processor. The memory is configured to store a computer program. The processor is configured to execute the computer program and implement the temperature control method of the mobile terminal as described in any of the embodiments of the present application when the computer program is executed.

[0007] In a fourth aspect, an embodiment of the present application provides a computer readable storage medium, which stores a computer program. The computer program is executed by a processor to make the processor implement the temperature control method of the mobile terminal as described in any of the embodiments of the present application.

[0008] The embodiment of the present application provides a temperature control method of a mobile terminal, which is applied to a mobile terminal, the mobile terminal comprising an infrared camera, and the method comprises the following steps: acquiring element temperature data and shell temperature data of the mobile terminal; when the element temperature data is greater than preset temperature data, calculating first ambient temperature data according to the element temperature data and the shell temperature data; calling the infrared camera to acquire second ambient temperature data, and detecting whether human body temperature data exists in the second ambient temperature data; if the human body temperature data is not detected, selecting a target temperature control mode from first preset temperature control modes according to the first ambient temperature data and the second ambient temperature data; if the human body temperature data is detected, updating the second ambient temperature data into third ambient temperature data according to the human body temperature data, and selecting the target temperature control mode from second preset temperature control modes according to the first ambient temperature data and the third ambient temperature data; and performing temperature control on the mobile terminal according to the target temperature control mode. In the above method, the first ambient temperature data is constructed based on the heat conduction relationship between the element temperature and the shell temperature, which can more accurately reflect the heat exchange characteristics of the environment where the device is located, the infrared camera actively captures the ambient temperature distribution, and the human body temperature recognition algorithm is combined to effectively distinguish the user operation scene and the natural high temperature scene of the environment, so that the reinforced heat dissipation mechanism in the first preset temperature control mode is preferentially started in the non-user use scene, and the moderate temperature control measure considering the performance and the body sensation is adopted in the user use scene, and the layered judgment mechanism can dynamically balance the heat dissipation intensity and the device performance according to the actual use scene. While ensuring the safe operation of the mobile device, the use experience of the user is maintained. BRIEF DESCRIPTION OF DRAWINGS

[0009] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0010] Figure 1 A schematic flow chart of a temperature control method of a mobile terminal provided by the embodiment of the present application is shown in the figure. Figure 2 A schematic block diagram of a temperature control device of a mobile terminal provided by the embodiment of the present application is shown in the figure. DETAILED DESCRIPTION

[0011] The technical solutions in the embodiments of the present application will be described clearly and completely in the following with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the present application.

[0012] The flowcharts shown in the drawings are merely illustrative and do not necessarily include all contents and operations / steps, nor are they necessarily executed in the order described. For example, some operations / steps can be further broken down, combined, or partially merged, so the actual execution order can be changed according to actual conditions.

[0013] It should also be understood that the terms used in this specification of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in this specification and the appended claims, the singular forms "a," "an" and "the" are intended to include plural forms unless the context clearly indicates otherwise.

[0014] It should be further understood that the term "and / or" used in this specification and the appended claims means one or more of the associated listed items as well as all possible combinations of these items.

[0015] Please refer to Figure 1 , Figure 1 is a schematic flowchart of a temperature control method of a mobile terminal provided by an embodiment of the present application. As shown in Figure 1 , the specific steps of the temperature control method of the mobile terminal include S101-S106.

[0016] S101, acquire element temperature data and housing temperature data of the mobile terminal.

[0017] For example, the junction temperature data of the SOC chip, the surface temperature data of the battery, and the housing temperature data of the screen and the back shell are collected in real time by the multi-point temperature sensor integrated inside the mobile terminal. The temperature data of the SOC chip is acquired by the built-in thermistor or digital temperature sensor, the battery temperature data is fed back by the real-time monitoring value provided by the battery management chip (BMS), and the housing temperature data of the screen and the back shell is measured by the patch temperature sensor distributed on the edge of the screen and the inside of the back shell. During data acquisition, the sensor needs to be dynamically calibrated, such as eliminating the sensor drift error by the environmental temperature reference value, to ensure that the sampling frequency of the SOC temperature data and the battery temperature data is synchronized to at least 10 times per second, and the sampling frequency of the housing temperature data is adjusted to 5 times per second to reduce power consumption. When the SOC temperature exceeds the preset threshold (such as 55°C), a high-precision temperature measurement mode is triggered, and the SOC temperature sampling frequency is increased to 20Hz to capture transient temperature rise. The collected element temperature data and housing temperature data are transmitted to the temperature control decision module through the bus to form a raw temperature data set containing a time stamp, providing input parameters for subsequent environmental temperature calculation.

[0018] S102, calculate first ambient temperature data according to the element temperature data and the shell temperature data when the element temperature data is greater than the preset temperature data.

[0019] For example, when the SOC temperature data or the battery temperature data exceeds a preset temperature threshold (e.g., SOC ≥ 60°C or battery ≥ 45°C), the ambient temperature estimation process is started. Based on the heat generation power model of the SOC and the battery, combined with the shell temperature data of the screen and the back shell, an equivalent thermal resistance network of the heat conduction path is constructed. For example, the SOC chip is in contact with the screen middle frame through the heat-conducting gel, and the thermal resistance coefficient of its heat diffusion path is mapped to a linear decay model through a pre-calibrated heat dissipation parameter table. By calculating the gradient difference between the shell temperature and the element temperature (e.g., the difference ΔT = 15°C between the SOC temperature and the screen temperature), combined with the thermal conductivity coefficient of the shell material (e.g., the thermal conductivity coefficient of the aluminum alloy back shell is 237 W / m·K), the compensation effect of the ambient temperature on the shell heat dissipation is derived. When the difference between the shell temperature and the element temperature is less than a critical threshold, it is determined that the ambient heat dissipation condition is limited, and a pre-stored temperature decay curve (e.g., for every 1°C rise in the back shell temperature, the ambient temperature estimation value is raised by 0.8°C) is called to generate first ambient temperature data. This data serves as a reference for subsequent infrared camera ambient temperature calibration, avoiding environmental misjudgment caused by local temperature distortion of the shell.

[0020] S103, call the infrared camera to obtain second ambient temperature data, and detect whether there is human body temperature data in the second ambient temperature data.

[0021] For example, the infrared camera built-in the mobile terminal collects the infrared thermal imaging data of the external environment to generate a temperature matrix with a resolution of 160x120 pixels. Each pixel point in the temperature matrix corresponds to a temperature value in the environment, covering an approximately fan-shaped area within 1 meter in front of the mobile terminal. An adaptive threshold segmentation algorithm is used to filter out a pixel set (e.g., 32°C to 42°C) that meets the human body temperature interval from the temperature matrix, and a spatial continuity detection algorithm is used to identify continuous regions. If a continuous high-temperature region with an area greater than a preset threshold (e.g., 50 pixels) is detected, its morphological characteristics are further analyzed: the region contour is extracted by an edge detection algorithm, and is matched with a pre-stored human head or hand thermal imaging template. For example, the human hand thermal zone usually presents an elliptical distribution, and the temperature gradient decreases from the center to the edge, while the heat zone distribution of the electronic device heat source (e.g., charger) presents an irregular diffusion form. If the matching degree exceeds a threshold (e.g., similarity ≥ 75%), it is determined that there is human body temperature data; otherwise, it is considered as environmental heat source interference. The detection result is used to dynamically correct the validity of the second ambient temperature data, for example, to exclude the influence of human body heat radiation on the ambient temperature rise.

[0022] S104, if the human body temperature data is not detected, selecting a target temperature control mode from the first preset temperature control mode according to the first environment temperature data and the second environment temperature data.

[0023] For example, when the infrared camera does not detect the human body temperature data, it is determined that the mobile terminal is in a non-use state (e.g., placed on a desktop), and at this time, the estimation of the ambient temperature needs to be integrated with the first environment temperature data (based on the thermal conduction function of the shell and the element) and the second environment temperature data (the direct measurement value of the infrared camera). Through a weighted fusion algorithm, the weight of the first environment temperature data is set to 70% (depending on the stability of the hardware thermal conduction), and the weight of the second environment temperature data is set to 30% (greatly affected by environmental obstructions), to generate a fused ambient temperature estimation value. For example, when the first environment temperature data is 30°C and the second environment temperature data is 28°C, the fusion result is 29.4°C. According to the fusion result, the first preset temperature control mode is matched: if the fusion temperature is ≥ 35°C, the active cooling mode is selected (e.g., forcibly reducing the SOC maximum frequency to 70%, limiting the screen brightness to 50%); if the fusion temperature is between 25°C and 35°C, the dynamic frequency adjustment mode is enabled (adjusting the frequency according to the SOC load); and if the fusion temperature is < 25°C, only the background process limiting measure is enabled. The selection logic of the temperature control mode is realized by a lookup table method, and the frequency reduction amplitude and power consumption limiting parameters corresponding to different temperature intervals are pre-stored.

[0024] S105, if the human body temperature data is detected, updating the second environment temperature data to third environment temperature data according to the human body temperature data, and selecting a target temperature control mode from the second preset temperature control mode according to the first environment temperature data and the third environment temperature data.

[0025] For example, when the human body temperature data is detected, it is determined that the user is using the mobile terminal (e.g., hand-held calling or watching video), and the interference of human body heat radiation on the measurement of the infrared camera needs to be excluded. The pixel region corresponding to the human body temperature data is excluded from the second environment temperature data (e.g., cropping the high temperature region in the thermal imaging image), and the average temperature value of the remaining pixels is taken as the third environment temperature data. For example, the original second environment temperature data is 32°C, and after excluding the human body heat region, it is updated to 28°C. The first environment temperature data (e.g., 29°C calculated based on the shell temperature) and the third environment temperature data are fused according to a 6:4 weight to generate an ambient temperature reference value in the user use scenario. According to the reference value, a strategy is selected from the second preset temperature control mode: if the reference temperature is ≥ 30°C, a gentle frequency reduction mode is adopted (the frequency is limited to 80%, and the screen brightness is reduced by 30%), to avoid overheating affecting the touch experience; and if the reference temperature is < 30°C, only the intelligent backlight adjustment is triggered (the brightness is dynamically adjusted according to the ambient light sensor). The second preset temperature control mode prioritizes user experience, avoids operation lag caused by aggressive cooling, and reduces the occupation rate of large cores through SOC scheduling algorithm, indirectly reducing the chip junction temperature.

[0026] S106, temperature control is performed on the mobile terminal according to the target temperature control mode.

[0027] For example, a set of parameters defined in the target temperature control mode (such as the main core frequency reduction amplitude, screen brightness threshold, and battery charging current limit value) is analyzed to generate multi-level temperature control instructions. For the SOC chip, the kernel scheduler dynamically closes part of the large core or limits its maximum frequency (such as from 2.8 GHz to 2.2 GHz), and adjusts the upper limit of the GPU rendering frame rate (such as from 60 FPS to 45 FPS). For the screen component, the display brightness is reduced in stages (such as from 600 nits to 400 nits), and the refresh rate is switched from 120 Hz to 90 Hz to reduce the power consumption of the driving chip. The battery management module intervenes synchronously, and if the battery temperature is greater than or equal to 40°C, the charging current is limited from 3A to 1.5A and the wireless charging function is suspended. During the temperature control execution process, the temperature change rate of the SOC and the battery is monitored in real time, and if the temperature drop amplitude does not reach the expected value (such as SOC temperature drop rate <0.5°C / s) within 10 seconds, additional measures are taken: further reduce the screen brightness to the lowest gear (200 nits), or forcibly close the background high-load application (such as the game process). All temperature control operations are coordinated through system-level API to ensure the coordinated response of hardware modules, and the original performance configuration is automatically restored after the temperature falls back to the safety threshold.

[0028] The embodiment of the application provides a temperature control method of a mobile terminal, which is applied to a mobile terminal including an infrared camera, and the method comprises the following steps: acquiring element temperature data and shell temperature data of the mobile terminal; when the element temperature data is greater than preset temperature data, calculating first environment temperature data according to the element temperature data and the shell temperature data; calling the infrared camera to acquire second environment temperature data, and detecting whether human body temperature data exists in the second environment temperature data; if no human body temperature data is detected, selecting a target temperature control mode from first preset temperature control modes according to the first environment temperature data and the second environment temperature data; if human body temperature data is detected, updating the second environment temperature data into third environment temperature data according to the human body temperature data, and selecting the target temperature control mode from second preset temperature control modes according to the first environment temperature data and the third environment temperature data; and performing temperature control on the mobile terminal according to the target temperature control mode. In the above method, the first environment temperature data is constructed based on the heat conduction relationship between the element temperature and the shell temperature, which can more accurately reflect the heat exchange characteristics of the environment where the device is located. The infrared camera actively captures the environment temperature distribution, and the human body temperature recognition algorithm is combined to effectively distinguish the user operation scene and the natural high temperature environment scene, so that the reinforced heat dissipation mechanism in the first preset temperature control mode is preferentially started in the non-user use scene, and the moderate temperature control measure considering the performance and the body sensation is adopted in the user use scene. The layered judgment mechanism can dynamically balance the heat dissipation intensity and the device performance according to the actual use scene. The safety operation of the mobile device is ensured, and the use experience of the user is maintained.

[0029] In order to more clearly introduce the technical scheme of the application, the technical scheme of the application will be introduced through specific embodiments below. It should be noted that the specific embodiments are used to expand the description of the technical scheme of the application, and are not intended to limit the application.

[0030] In some embodiments, calculating the first environment temperature data according to the element temperature data and the shell temperature data comprises: calculating a temperature diffusion gradient value according to the element temperature data and the shell temperature data; matching a heat dissipation diffusion coefficient according to the temperature diffusion gradient value based on a pre-stored temperature gradient-heat dissipation coefficient reference table; determining preliminary environment temperature data according to a preset temperature conduction formula, the shell temperature data, the temperature diffusion gradient value and the heat dissipation diffusion coefficient; and matching the preliminary environment temperature data value with a pre-stored environment temperature calibration table to output the first environment temperature data. The temperature gradient-heat dissipation coefficient reference table comprises heat conduction attenuation coefficients of heat dissipation measures under different environment temperatures.

[0031] The preliminary environment temperature data value is calculated through a preset temperature conduction formula, and the preset temperature conduction formula is as follows: wherein, T h0 ​T k T temperature diffusion gradient value, thermal diffusion coefficient.

[0032] In the process of calculating the first ambient temperature data, the temperature diffusion gradient value is determined by analyzing the dynamic relationship between the real-time temperature data of the SOC chip, the surface temperature data of the battery, and the shell temperature data of the screen and the back shell. The calculation of the temperature diffusion gradient value is based on the heat source characteristics of the SOC chip or the battery and the temperature attenuation law of its corresponding shell area, such as the temperature difference between the high heat generation area of the SOC chip (such as the CPU core) and the middle frame of the screen, and the temperature difference between the middle part of the battery and the edge of the back shell. Through the real-time data collected by the multi-point temperature sensor, the gradient change rate between the SOC temperature and the screen temperature (such as ΔT soc-screen = 8°C / cm) and the gradient change rate between the battery temperature and the back shell temperature (such as ΔT battery-rear = 5°C / cm) are calculated, and combined with the heat conduction path length of the shell material (such as the thickness of the screen middle frame 0.5mm, the thickness of the back shell aluminum alloy 1.2mm), the temperature diffusion gradient value representing the heat transfer efficiency from the element to the shell is comprehensively obtained. This gradient value reflects the dynamic characteristics of the internal heat conduction of the mobile terminal, for example, when the temperature of the SOC chip rises sharply, if the temperature of the screen does not rise synchronously, the gradient value will increase significantly, indicating that there is local thermal resistance in the heat dissipation path or the environmental heat dissipation condition is limited.

[0033] Based on the pre-stored temperature gradient-thermal diffusion coefficient table, the calculated temperature diffusion gradient value is mapped to the corresponding thermal diffusion coefficient. The temperature gradient-thermal diffusion coefficient table is generated by laboratory calibration and contains the heat conduction attenuation parameters of typical heat dissipation scenarios of the mobile terminal under different ambient temperatures (such as 20°C, 30°C, 40°C). For example, at an ambient temperature of 30°C, if the temperature diffusion gradient value is 15°C / cm, the matching thermal diffusion coefficient is 0.85W / (m·K); when the gradient value decreases to 10°C / cm, the thermal diffusion coefficient is adjusted to 1.2W / (m·K). The table takes into account the thermal radiation characteristics of the shell material (such as the emissivity of the screen glass 0.92, the emissivity of the back shell metal 0.25) and the environmental compensation effect of air convection intensity, to ensure that the thermal diffusion coefficient can dynamically reflect the actual heat dissipation condition. For example, in a closed environment, the air convection is weakened, which leads to the decrease of the shell heat dissipation efficiency, at this time, the thermal diffusion coefficient corresponding to the same temperature diffusion gradient value needs to be adjusted by 15%-20% to correct the influence of environmental factors on heat conduction.

[0034] The shell temperature data, temperature diffusion gradient value and heat dissipation diffusion coefficient are substituted into the preset temperature conduction formula to derive preliminary ambient temperature data. The physical meaning of the temperature conduction formula is to quantify the reverse influence of the ambient temperature on the heat dissipation capacity of the shell. For example, when the shell temperature data (such as screen temperature 38°C and back shell temperature 36°C) is combined with the heat dissipation diffusion coefficient (such as 0.9 W / (m·K)), the formula estimates the overall heat exchange effect of the external environment on the mobile terminal by linearly superimposing the shell temperature contribution value and the heat dissipation attenuation compensation value. This process needs to consider the spatial distribution characteristics of the shell temperature data, such as the temperature difference (such as ±1.5°C) between the screen edge and the center area, which may cause fluctuations in the preliminary ambient temperature data value. Therefore, a weighted average algorithm is used to fuse the multi-region shell temperature data to ensure the stability of the input parameters. For example, when the screen middle frame temperature data is 40°C and the back shell middle temperature is 37°C, according to the corresponding heat dissipation area weight (screen proportion 60%, back shell proportion 40%), the comprehensive shell temperature reference value 39.2°C is calculated, and then combined with the temperature diffusion gradient value (12°C / cm) and the heat dissipation diffusion coefficient (1.0 W / (m·K)), the preliminary ambient temperature data value 32°C is output.

[0035] The preliminary ambient temperature data value is matched with the pre-stored ambient temperature calibration table to output the calibrated first ambient temperature data. The ambient temperature calibration table is generated by comparing experimental data with external high-precision temperature sensors and covers temperature compensation parameters of the mobile terminal in different use postures (such as flat and vertical) and external shielding conditions (such as placed on a fabric surface). For example, when the preliminary ambient temperature data value is 32°C, the calibration table matches the corresponding compensation offset (+1.5°C) according to the current shell temperature data (screen 39°C, back shell 37°C) and the heat dissipation diffusion coefficient (1.0 W / (m·K)) to output the first ambient temperature data 33.5°C. The dynamic correction logic built-in the calibration table can identify abnormal scenarios: if the correlation between the preliminary ambient temperature data value and the shell temperature data deviates from the historical rules (such as the preliminary value suddenly drops by 5°C while the shell temperature does not change synchronously), the data reliability verification mechanism is triggered to cross-verify the second ambient temperature data obtained by the infrared camera, avoiding environmental misjudgment caused by sensor failure or transient thermal shock. This process ensures that the first ambient temperature data can accurately reflect the external thermal environment of the mobile terminal and provides reliable input for subsequent temperature control mode decision.

[0036] In some embodiments, the infrared camera is called to obtain second environmental temperature data, and it is detected whether human body temperature data exists in the second environmental temperature data, including: acquiring infrared thermal imaging data of an external environment through the infrared camera to generate temperature matrix data containing temperature distribution; identifying preselected temperature data conforming to a preset human body temperature interval from the temperature matrix data; based on the spatial distribution of the preselected temperature data in the temperature matrix, filtering out candidate region data with a continuous coverage area greater than a preset area threshold; calculating a pixel region area of the candidate region data in the infrared thermal imaging data, and comparing the pixel region area with a preset area range; if the pixel region area is within the preset area range, it is determined that the preselected temperature data is human body temperature data; if the pixel region area does not reach the preset area range, the similarity of the edge form of the candidate region data and a pre-stored human body contour template is compared, and when the similarity is greater than a preset threshold, it is determined that the preselected temperature data is human body temperature data.

[0037] For example, when infrared cameras collect infrared thermal imaging data of the external environment, the sensitivity of the microbolometer array to thermal radiation in the 8-14μm band is used to generate temperature matrix data with spatial temperature resolution capabilities. The row and column coordinates of this data matrix form a mapping relationship with the actual physical space, ensuring the geometric authenticity of subsequent analysis. When identifying pre-selected temperature data that meets the preset human body temperature range from the temperature matrix data, setting a core threshold range of 35-42°C has a physiological basis: this range covers the radiant temperature characteristics of the human epidermis under normal conditions, while excluding interference from common heat sources (such as lamps that usually generate heat >60°C and electronic equipment that dissipates heat at approximately 45-55°C), but retains tolerance for users with fever symptoms (the upper limit is extended to 42°C). When screening candidate regions with continuous coverage greater than a preset area threshold, a spatial continuity assessment mechanism is crucial. This requires avoiding misclassification of discrete hot spots (such as hot cups or radiator parts) as human bodies within a topologically connected area of ​​high-temperature pixels. The preset area threshold of 80 pixels (corresponding to the projection of an adult face at a distance of 30 cm) is based on extensive field-measured statistical data: the minimum effective imaging size of a face or hand in the infrared field of view when a user holds a mobile device in a natural position. When calculating the pixel area of ​​the candidate region data within the infrared thermal imaging data, a boundary tracing algorithm is used to precisely delineate the hot area. By comparing it with a preset area range (typical projection of an adult palm: 150-300 pixels, 200-400 pixels for a face), it effectively distinguishes human targets from similar heat sources such as pets and small heaters. When the pixel area falls within the preset area range, the preselected temperature data is directly identified as human body temperature data with sufficient reliability. This determination combines both temperature and size characteristics. For example, in an office scenario, a hot area on a keyboard that fits the temperature range is excluded due to its area being less than 15 pixels. For special cases where the pixel area does not meet the standard (such as when the user wears heat-insulating gloves, resulting in a 30% reduction in the thermal imaging area of ​​the hand), the similarity analysis between the edge morphology and the pre-stored human contour template is initiated as a supplementary verification method. The Hu invariant moment algorithm is used to quantify the contour similarity. The preset threshold of 85% balances the recognition accuracy and false rejection rate: when the user wears sunglasses, causing the facial contour to be deformed, the arc features of the forehead and cheeks can still maintain a matching degree of more than 75%. At this time, combined with the temperature range compliance, a supplementary judgment can be triggered.

[0038] In some embodiments, selecting the target temperature control mode from the first preset temperature control mode according to the first ambient temperature data and the second ambient temperature data comprises: determining an ambient light illumination level and ambient temperature estimation data according to the second ambient temperature data; performing weighted estimation on the first ambient temperature data and the ambient temperature estimation data to obtain target ambient temperature data; comparing the target ambient temperature data with a preset temperature gradient threshold to obtain a temperature influence level; generating a comprehensive intensity index based on a combination relationship between the ambient light illumination level and the temperature influence level; matching a corresponding target temperature control level according to the comprehensive intensity index and a preset temperature control intensity mapping table; selecting a main core frequency reduction amplitude, a screen refresh rate threshold and a display brightness reduction ratio parameter from a pre-stored temperature control measure combination library based on the target temperature control level; determining the target temperature control mode according to a synergistic relationship of the main core frequency reduction amplitude, the screen refresh rate threshold and the display brightness reduction ratio parameter; wherein the first preset temperature control mode comprises at least three temperature control levels, each level corresponding to a different intensity of heat dissipation measure combination, and a high-order level in the temperature control measure combination library comprises all measures of a low-order level and at least one enhanced heat dissipation means.

[0039] For example, when determining the ambient light level and the ambient temperature estimation data according to the second ambient temperature data, the spectral analysis capability of the infrared camera is used: by analyzing the correlation between the near-infrared band (850 nm) and the ambient visible light intensity, the light intensity is divided into five levels (such as <200 lux for dark light and >800 lux for strong light), and the real ambient temperature estimation data is extracted by excluding the interference of heat sources (such as eliminating the local high temperature caused by direct sunlight). When the first ambient temperature data (thermal conduction function output) and the ambient temperature estimation data are weighted and estimated, the weight distribution is based on confidence evaluation: when the infrared data fluctuates by less than 0.5℃ for three consecutive frames, 70% weight is given, otherwise the thermal model data is given priority, and this dynamic fusion mechanism eliminates the limitations of a single data source (such as infrared interference from glass reflection and thermal model inaccuracy in strong convection environment), and the error of the output target ambient temperature data can be controlled within ±1.5℃. When comparing the target ambient temperature data with the preset temperature gradient threshold, the threshold is set considering the human comfort zone and the hardware safety boundary: 25-32℃ is the mild temperature rise zone, 32-39℃ is the moderate temperature rise zone, and >39℃ is the high-risk zone, and the temperature influence level is directly related to the heat dissipation urgency. When generating the comprehensive intensity index based on the ambient light level and the temperature influence level, a two-dimensional decision matrix is constructed: for example, strong light environment (level 4) superimposed with high-risk temperature rise (level 3) generates an index of 9 / 10, while dark light (level 1) and mild temperature rise (level 1) only generate an index of 2 / 10, which reflects the combined effect of light on device temperature rise (strong light intensifies screen heating, and dark light reduces display power consumption). When matching the target temperature control level according to the comprehensive intensity index, the preset temperature control intensity mapping table adopts a non-linear segmented strategy: index 1-3 corresponds to Level 1, 4-6 corresponds to Level 2, and 7-10 corresponds to Level 3, ensuring that low-load scenarios do not trigger excessive frequency reduction. When selecting parameters from the temperature control measure combination library, the main core frequency reduction amplitude (Level 1: 20% reduction / Level 3: 50% reduction), screen refresh rate threshold (90Hz / 60Hz / 30Hz), and display brightness reduction ratio (10% / 30% / 50%) form a synergistic constraint, and high-level levels are forced to inherit low-level measures (such as Level 3 must include Level 1's 20% frequency reduction and Level 2's 60Hz refresh rate limit) and additional reinforcement measures (such as Level 3 additionally turns off the GPS module). The determination of the target temperature control mode depends on the parameter synergistic verification: the main core frequency reduction reduces the intensity of the SOC heat source, the refresh rate threshold suppresses the GPU load, and the brightness reduction alleviates screen heat accumulation, and the three are dynamically proportioned according to the thermal contribution ratio (such as when the SOC temperature rise contribution rate is >60%, the main core frequency reduction amplitude weight is increased to 70%), and the temperature feedback closed loop calibration is used: if the shell temperature data does not decrease at the expected rate (such as <0.8℃ / min) after the measures are enabled, the target temperature control level is automatically increased.The whole process forms a closed-loop control chain of environment perception-data fusion-grade mapping-measure linkage, and realizes precise thermal management and minimum performance loss under the condition of fanless heat dissipation.

[0040] In some embodiments, updating the second environment temperature data to the third environment temperature data according to the human body temperature data comprises: removing the human body temperature data from the second environment temperature data to obtain environment light sensing data; and determining the third environment temperature data according to the environment light sensing data.

[0041] For example, when the human body temperature data is detected, the human body temperature data will interfere with the determination of the environment temperature because the distance between the user and the mobile terminal is less than 1 meter during the use of the mobile terminal. Therefore, the human body data needs to be removed to obtain the environment light sensing data without human body interference, and then the third environment temperature data is calculated according to the environment light sensing data. In this way, the accuracy of the environment temperature identification can be improved.

[0042] In some embodiments, selecting the target temperature control mode from the second preset temperature control mode according to the first environment temperature data and the third environment temperature data comprises: performing weighted calculation on the first environment temperature data and the third environment temperature data to obtain fifth environment temperature data; comparing the fifth environment temperature data with a preset high temperature threshold and a preset low temperature threshold to determine a temperature gradient level, wherein the high temperature threshold is higher than the low temperature threshold, and both of them are higher than a regular trigger threshold of the first preset temperature control mode; and selecting the target temperature control mode from the second preset temperature control mode according to the temperature gradient level.

[0043] For example, when performing weighted calculation on the first environment temperature data (thermal conduction function output) and the third environment temperature data (infrared data without human body interference), the number of noise points can be determined according to the two, the more the number of noise points, the lower the weight coefficient allocated, and the fifth environment temperature data is obtained after weighting. In this way, the interference of single data source fluctuation on the final result can be avoided.

[0044] The fifth ambient temperature data is compared with the preset high temperature threshold (42°C) and the low temperature threshold (37°C), and the threshold setting strictly follows the ergonomic safety specification: the high temperature threshold is 7°C higher than the regular trigger threshold (35°C) of the first preset temperature control mode, which covers the maximum tolerable temperature rise when the human body contacts the mobile terminal (the ISO 13732-1 standard stipulates that the skin will not be burned when contacting an object of 44°C for 60 seconds); the low temperature threshold is set at the critical point of human basal metabolic heat compensation (below this value, it is easy to cause body discomfort). The temperature gradient level is divided into three levels: when the fifth ambient temperature data is ≤37°C, it is Level A (safe zone), 37-42°C is Level B (warning zone), and >42°C is Level C (danger zone), and the level upgrade trigger condition is more stringent than the first mode (2°C higher than the same ambient temperature to upgrade the response).

[0045] When the target temperature control mode is selected from the second preset temperature control mode, Level A only enables basic measures (such as a 10% main core frequency reduction range and a 5% brightness fine adjustment), Level B forcibly activates double constraints: on the basis of inheriting all measures of Level A, it additionally locks the screen refresh rate threshold (≤60Hz) and limits the charging current (≤1A); Level C introduces human body protection exclusive strategies - when the temperature of the contact area of the shell is >39°C, the SOC operation load is redistributed in real time based on thermal imaging data, and the high-temperature hot spot is migrated from the holding area to the top of the device (such as binding CPU-intensive processes to cores away from the holding area through a task scheduler), and the display brightness is reduced by 40% to suppress screen heat conduction. The core advantage of this mode is dynamic safety protection: for example, when the fifth ambient temperature data reaches 40°C (Level B), if it is detected that the user continuously holds the back shell for more than 30 seconds, a contact point temperature equalization algorithm is automatically injected (equalizing the temperature difference within 1 cm in the holding area to ±0.5°C), to avoid the burning sensation caused by local overheating. The execution intensity of all measures is directly controlled by the temperature gradient level, and the high-order level retains all the functions of the low-order level and adds human adaptability optimization, forming a more precise thermal safety control chain than the first mode.

[0046] In some embodiments, temperature control of the mobile terminal according to the target temperature control mode includes: analyzing the main core frequency reduction range, the screen refresh rate threshold, and the display brightness reduction ratio parameters in the target temperature control mode to generate a corresponding temperature control instruction set; synchronously executing processor main core frequency dynamic adjustment, cooling fan speed matching control, and screen backlight brightness step-down operation according to the temperature control instruction set, and monitoring the change rate of the element temperature data in real time during the execution process, and if the change rate does not reach the preset cooling rate threshold, the main core frequency reduction range and the screen refresh rate threshold are dynamically superimposed and compensated.

[0047] For example, when parsing the main core frequency reduction amplitude (e.g., 30%), screen refresh rate threshold (e.g., 60 Hz), and display brightness reduction ratio (e.g., 40%) parameters in the target temperature control mode, the system management service converts the abstract instructions into a set of operable temperature control instructions: the main core frequency reduction instruction is mapped to the frequency upper limit lock of the CPU scheduler (e.g., from 2.8 GHz to 1.9 GHz), the refresh rate threshold triggers the vertical synchronization signal reconfiguration of the display engine, and the brightness parameter drives the backlight PWM controller to adjust the duty cycle. The generation of this instruction set needs to verify the compatibility of the parameters - for example, when the main core frequency reduction amplitude exceeds 50%, the screen refresh rate threshold is automatically adjusted to the lowest level (30 Hz) to avoid visual lag.

[0048] For example, the grounding path of the graphene heat sink is dynamically adjusted according to the hot spot position of the SOC chip; the screen backlight brightness is gradually reduced, and the human eye adaptability algorithm is introduced to gradually change to the target value at a gradient of 5% per second, preventing visual fatigue caused by sudden brightness changes. The coordination sequence of the three needs to be accurately aligned: the backlight reduction is delayed by 200 ms from the start of the main core frequency reduction to avoid the superimposed perception of screen flicker and performance drop.

[0049] The monitoring link focuses on the change rate of the temperature data of the focusing element (e.g., the SOC temperature drop value AT per minute), and the preset cooling rate threshold is set based on the heat capacity model (e.g., ≥0.8℃ / min). When the actual change rate is not up to standard (e.g., only 0.3℃ / min), the dynamic superposition compensation mechanism responds in two stages: the primary compensation proportionally increases the main core frequency reduction amplitude (e.g., by 15 percentage points to 45%), and if it is still ineffective after 120 seconds, the screen refresh rate threshold is lowered (e.g., from 60 Hz to 45 Hz). The compensation amount is calculated in relation to the thermal inertia coefficient: for high-heat-capacity elements such as batteries, the compensation amplitude is expanded to 1.5 times the reference value; for thin screen elements, small-step compensation is used (≤5% each time). The entire execution process forms a closed loop of instruction issuance, effect monitoring, and parameter correction, ensuring that the shell temperature data returns to the threshold range within a safe time (usually <3 minutes), while the triggering conditions and performance coefficients of each compensation are recorded in the temperature control log, providing a data basis for mode self-optimization.

[0050] Please refer to Figure 2 , Figure 2 is a schematic block diagram of a temperature control device of a mobile terminal provided by an embodiment of the present application. The temperature control device 200 of the mobile terminal is used to execute the temperature control method of the mobile terminal described above. The temperature control device 200 of the mobile terminal can be configured in a server.

[0051] The server can be a standalone server, a server cluster, a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and basic cloud computing services such as big data and artificial intelligence platforms.

[0052] As shown in Figure 2 The temperature control device 200 of the mobile terminal includes a data acquisition module 201, a first temperature measurement module 202, a second temperature measurement module 203, a first selection module 204, a second selection module 205, and a mode execution module 206.

[0053] The data acquisition module 201 is configured to acquire element temperature data and shell temperature data of the mobile terminal.

[0054] The first temperature measurement module 202 is configured to calculate first ambient temperature data according to the element temperature data and the shell temperature data when the element temperature data is greater than preset temperature data.

[0055] The second temperature measurement module 203 is configured to call an infrared camera to acquire second ambient temperature data, and detect whether human body temperature data exists in the second ambient temperature data.

[0056] The first selection module 204 is configured to select a target temperature control mode from first preset temperature control modes according to the first ambient temperature data and the second ambient temperature data if no human body temperature data is detected.

[0057] The second selection module 205 is configured to update the second ambient temperature data to third ambient temperature data according to human body temperature data if human body temperature data is detected, and select a target temperature control mode from second preset temperature control modes according to the first ambient temperature data and the third ambient temperature data.

[0058] The mode execution module 206 is configured to perform temperature control on the mobile terminal according to the target temperature control mode.

[0059] The embodiment of the present application provides a mobile device, which includes a memory and a processor; the memory is used for storing a computer program; the processor is used for executing the computer program and realizing the temperature control method of the mobile terminal as any one of the embodiments of the present application.

[0060] The embodiment of the present application provides a computer readable storage medium, which stores a computer program; the computer program is executed by a processor to make the processor realize the temperature control method of the mobile terminal as any one of the embodiments of the present application.

[0061] The above merely provides the specific implementation of the present application, but the protection scope of the present application is not limited to this. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical range disclosed by the present application, and these modifications or replacements should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A temperature control method for a mobile terminal, characterized in that: Applied to a mobile terminal, the mobile terminal including an infrared camera, the method comprising: Obtaining component temperature data and housing temperature data of the mobile terminal; When the component temperature data is greater than the preset temperature data, calculating the first ambient temperature data according to the component temperature data and the housing temperature data; Calling the infrared camera to obtain second ambient temperature data, and detecting whether human body temperature data exists in the second ambient temperature data; If the human body temperature data is not detected, selecting a target temperature control mode from a first preset temperature control mode according to the first ambient temperature data and the second ambient temperature data; If the human body temperature data is detected, updating the second ambient temperature data to third ambient temperature data according to the human body temperature data, and selecting a target temperature control mode from a second preset temperature control mode according to the first ambient temperature data and the third ambient temperature data; The temperature of the mobile terminal is controlled according to the target temperature control mode.

2. The temperature control method of a mobile terminal according to claim 1, wherein: The calculating the first ambient temperature data according to the component temperature data and the housing temperature data includes: Calculate and determine a temperature diffusion gradient value based on the component temperature data and the shell temperature data; Based on a pre-stored temperature gradient-heat dissipation coefficient comparison table, the heat dissipation diffusion coefficient is obtained according to the temperature diffusion gradient value; Determining preliminary ambient temperature data based on a preset temperature conduction formula, the housing temperature data, the temperature diffusion gradient value, and the heat dissipation diffusion coefficient; The preliminary ambient temperature data value is matched with a pre-stored ambient temperature calibration table to output the first ambient temperature data. The temperature gradient-heat dissipation coefficient comparison table contains the heat conduction attenuation coefficients corresponding to the heat dissipation measures at different ambient temperatures.

3. The temperature control method of a mobile terminal according to claim 1, wherein: The step of calling the infrared camera to obtain the second ambient temperature data and detecting whether the second ambient temperature data contains human body temperature data includes: The infrared camera collects infrared thermal imaging data of the external environment to generate temperature matrix data; identifying preselected temperature data that conforms to a preset human body temperature range from the temperature matrix data; Based on the spatial distribution of the preselected temperature data in the temperature matrix, screening out candidate region data having a continuous coverage area greater than a preset area threshold; Calculating the pixel area of ​​the candidate region data in the infrared thermal imaging data and comparing it with a preset area range; If the area of ​​the pixel region is within the preset area range, determining that the preselected temperature data is the human body temperature data; If the area of ​​the pixel region does not reach the preset area range, the similarity between the edge shape of the candidate region data and the pre-stored human body contour template is determined. When the similarity is greater than a preset threshold, it is additionally determined that the pre-selected temperature data is the human body temperature data.

4. The temperature control method of a mobile terminal according to claim 1, wherein: The selecting a target temperature control mode from a first preset temperature control mode according to the first ambient temperature data and the second ambient temperature data includes: determining ambient light level and ambient temperature estimation data based on the second ambient temperature data; Performing weighted estimation on the first ambient temperature data and the ambient temperature estimation data to obtain target ambient temperature data; Comparing the target ambient temperature data with a preset temperature gradient threshold to obtain a temperature impact level; generating a comprehensive intensity index based on a combination of the ambient light level and the temperature impact level; Matching the corresponding target temperature control level according to the comprehensive intensity index and the preset temperature control intensity mapping table; Based on the target temperature control level, select the main core frequency reduction amplitude, screen refresh rate threshold and display brightness reduction ratio parameters from a pre-stored temperature control measure combination library; Determining the target temperature control mode according to a synergistic relationship between the main core frequency reduction amplitude, the screen refresh rate threshold, and the display brightness reduction ratio parameter; Among them, the first preset temperature control mode includes at least three temperature control levels, each level corresponds to a combination of heat dissipation measures of different strengths, and the high-level level in the temperature control measure combination library includes all measures of the low-level level and adds at least one enhanced heat dissipation measure.

5. The temperature control method of a mobile terminal according to claim 1, wherein: The updating of the second ambient temperature data to third ambient temperature data according to the human body temperature data includes: removing the human body temperature data from the second ambient temperature data to obtain ambient light sensing data; The third ambient temperature data is determined according to the ambient light sensing data.

6. The temperature control method of a mobile terminal according to claim 1, wherein: The selecting a target temperature control mode from a second preset temperature control mode according to the first ambient temperature data and the third ambient temperature data includes: Performing weighted calculation on the first ambient temperature data and the third ambient temperature data to obtain fifth ambient temperature data; comparing the fifth ambient temperature data with a preset high temperature threshold and a preset low temperature threshold to determine a temperature gradient level, wherein the high temperature threshold is greater than the low temperature threshold and both are higher than a conventional trigger threshold of the first preset temperature control mode; A target temperature control mode is selected from the second preset temperature control modes according to the temperature gradient level.

7. The temperature control method of a mobile terminal according to claim 1, wherein: The controlling the temperature of the mobile terminal according to the target temperature control mode includes: Analyze the main core frequency reduction range, screen refresh rate threshold, and display brightness reduction ratio parameters in the target temperature control mode to generate a corresponding temperature control instruction set; According to the temperature control instruction set, the processor main core frequency dynamic adjustment, cooling fan speed matching control and screen backlight brightness step-by-step reduction operations are synchronously executed, and the change rate of the component temperature data is monitored in real time during the execution process. If the change rate does not reach the preset cooling rate threshold, the main core frequency reduction amplitude and the screen refresh rate threshold are dynamically superimposed and compensated.

8. A temperature control device for a mobile terminal, characterized in that: The temperature control device of the mobile terminal is used to execute the temperature control method of the mobile terminal according to any one of claims 1 to 7, and is applied to the mobile terminal, wherein the mobile terminal includes an infrared camera, and the temperature control device of the mobile terminal includes: A data acquisition module, used to acquire component temperature data and housing temperature data of the mobile terminal; a first temperature measurement module, configured to calculate first ambient temperature data based on the component temperature data and the housing temperature data when the component temperature data is greater than a preset temperature data; a second temperature measurement module, configured to call the infrared camera to obtain second ambient temperature data, and detect whether human body temperature data exists in the second ambient temperature data; a first selection module, configured to select a target temperature control mode from a first preset temperature control mode according to the first ambient temperature data and the second ambient temperature data if the human body temperature data is not detected; a second selection module, configured to, if the human body temperature data is detected, update the second ambient temperature data to third ambient temperature data according to the human body temperature data, and select a target temperature control mode from a second preset temperature control mode according to the first ambient temperature data and the third ambient temperature data; A mode execution module is used to control the temperature of the mobile terminal according to the target temperature control mode.

9. A mobile device, characterized in that: The mobile device includes a memory and a processor; The memory is used to store computer programs; The processor is configured to execute the computer program and implement the temperature control method for the mobile terminal according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor enables the processor to implement the temperature control method of the mobile terminal according to any one of claims 1 to 7.

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