Thermal prediction method and device, electronic equipment and storage medium

Abstract

The invention discloses a thermal prediction method and device, electronic equipment and a storage medium, and belongs to the technical field of electronics. The method comprises the following steps: acquiring a first temperature rise value of the electronic equipment between a first time point and a second time point; predicting a first surface temperature of the electronic equipment at a second time point based on the first temperature rise value, the heat dissipation capability coefficient, the heat consumption curve and the environment temperature curve; wherein the heat dissipation capability coefficient is determined based on hardware resources of the electronic equipment, the heat consumption curve is used for representing the change amplitude of heat generated by the electronic equipment in the using process, and the environment temperature curve is used for representing the change amplitude of the environment temperature of the environment where the electronic equipment is located.

Description

Technical Field

[0001] The present application belongs to the field of electronic technology, and specifically relates to a thermal prediction method, device, electronic equipment and storage medium. Background Art

[0002] At present, with the continuous development of electronic devices, the performance of electronic devices is getting higher and higher, but high performance also brings high power consumption. The disadvantage of high power consumption is that electronic devices will generate heat, and heat will limit the performance of electronic devices. Therefore, if the thermal state of electronic devices can be known, the performance of electronic devices can be achieved through more reasonable scheduling of the thermal state, so predicting the thermal state of electronic devices is becoming more and more important.

[0003] In the related art, an electronic device can predict the temperature of the electronic device at the next time point based on a linear algorithm according to the power consumption of the electronic device. However, the accuracy of this thermal prediction is poor. Summary of the invention

[0004] The purpose of the embodiments of the present application is to provide a thermal prediction method, device, electronic device, storage medium and program product, which can improve the accuracy of thermal prediction of electronic equipment.

[0005] In a first aspect, an embodiment of the present application provides a thermal prediction method, which includes: obtaining a first temperature rise value of an electronic device between a first time point and a second time point; predicting a first surface temperature of the electronic device at the second time point based on the first temperature rise value, a heat dissipation capacity coefficient, a heat consumption curve, and an ambient temperature curve; wherein the heat dissipation capacity coefficient is determined based on the hardware resources of the electronic device, the heat consumption curve is used to characterize the amplitude of change in heat generated by the electronic device during use, and the ambient temperature curve is used to characterize the amplitude of change in the ambient temperature of the environment in which the electronic device is located.

[0006] In a second aspect, an embodiment of the present application provides a thermal prediction device, which includes: an acquisition module and a prediction module. The acquisition module is used to acquire a first temperature rise value of the electronic device between a first time point and a second time point. The prediction module is used to predict the first surface temperature of the electronic device at the second time point based on the first temperature rise value, the heat dissipation capacity coefficient, the heat consumption curve and the ambient temperature curve; wherein the heat dissipation capacity coefficient is determined based on the hardware resources of the electronic device, the heat consumption curve is used to characterize the change amplitude of the heat generated by the electronic device during use, and the ambient temperature curve is used to characterize the change amplitude of the ambient temperature of the environment in which the electronic device is located.

[0007] In a third aspect, an embodiment of the present application provides an electronic device, which includes a processor and a memory, wherein the memory stores programs or instructions that can be run on the processor, and when the program or instructions are executed by the processor, the steps of the method described in the first aspect are implemented.

[0008] In a fourth aspect, an embodiment of the present application provides a readable storage medium, on which a program or instruction is stored, and when the program or instruction is executed by a processor, the steps of the method described in the first aspect are implemented.

[0009] In a fifth aspect, an embodiment of the present application provides a chip, comprising a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run a program or instruction to implement the method described in the first aspect.

[0010] In a sixth aspect, an embodiment of the present application provides a computer program product, which is stored in a storage medium and is executed by at least one processor to implement the method described in the first aspect.

[0011] In an embodiment of the present application, a first temperature rise value of an electronic device between a first time point and a second time point is obtained; then, based on the first temperature rise value, the heat dissipation capacity coefficient, the heat consumption curve and the ambient temperature curve, the first surface temperature of the electronic device at the second time point is predicted, and the second time point is a time point after the first time point; wherein the heat dissipation capacity coefficient is determined based on the hardware resources of the electronic device, the heat consumption curve is used to characterize the amplitude of change of the heat generated by the electronic device during use, and the ambient temperature curve is used to characterize the amplitude of change of the ambient temperature of the environment in which the electronic device is located. In this solution, since the heat dissipation capacity coefficient is determined based on the hardware resources of the electronic device, when predicting the first surface temperature of the electronic device at the second time point, the heat dissipation capacity of the electronic device during use can be known through the heat dissipation capacity coefficient, so that when performing thermal prediction, the heat dissipation capacity coefficient, the heat consumption curve and the ambient temperature curve are combined, and the predicted first surface temperature will be more accurate, avoiding the problem of poor accuracy caused by thermal prediction through power consumption, thereby improving the accuracy of thermal prediction of electronic devices. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 This is one of the flow charts of a thermal prediction method provided in an embodiment of the present application;

[0013] Figure 2 This is the second flowchart of a heat prediction method provided in an embodiment of the present application;

[0014] Figure 3 This is one of the example diagrams of a temperature rise process provided in an embodiment of the present application;

[0015] Figure 4 This is the second example diagram of a temperature rise process provided in an embodiment of the present application;

[0016] Figure 5 This is the third flowchart of a heat prediction method provided in an embodiment of the present application;

[0017] Figure 6 This is the third example diagram of a temperature rise process provided by an embodiment of the present application;

[0018] Figure 7 This is the fourth flowchart of a heat prediction method provided in an embodiment of the present application;

[0019] Figure 8 is an example diagram of load distribution provided by an embodiment of the present application;

[0020] Fig. 9 is a schematic diagram of the structure of a thermal prediction device provided in an embodiment of the present application;

[0021] Fig.10 This is one of the hardware structure diagrams of an electronic device provided in an embodiment of the present application;

[0022] Fig.11 This is the second schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments in the present application belong to the scope of protection of this application.

[0024] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the terms used in this way are interchangeable where appropriate, so that the embodiments of the present application can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0025] The terms "at least one (item)", "at least one of" and the like in the specification and claims of the present application refer to any one, any two or a combination of more than two of the objects included therein. For example, at least one (item) of a, b, and c can be represented by: "a", "b", "c", "a and b", "a and c", "b and c" and "a, b and c", where a, b, and c can be single or multiple. Similarly, "at least two (items)" refers to two or more, and its meaning is similar to that of "at least one (item)".

[0026] The thermal prediction method, device, electronic device, storage medium and program product provided in the embodiments of the present application are described in detail below with reference to the accompanying drawings through specific embodiments and their application scenarios.

[0027] The heat prediction method, device, electronic device, and storage medium provided in the embodiments of the present application can be applied in heat prediction scenarios, such as heat prediction scenarios for playing games, watching videos, and reading e-books.

[0028] In the above-mentioned gaming heat prediction scenario, taking the electronic device as a mobile phone as an example, assuming that the mobile phone is in high-performance mode, the mobile phone can obtain the first temperature rise value of the mobile phone from the current time point to one minute later, and obtain the heat dissipation capacity coefficient of the mobile phone, the heat consumption curve of the mobile phone from power-on to the current time point, and the ambient temperature curve; then, the mobile phone can calculate the surface temperature of the mobile phone one minute later through the first temperature rise value, the heat dissipation capacity coefficient, the heat consumption curve and the ambient temperature curve, and then perform load scheduling based on the surface temperature of the mobile phone one minute later to reduce heating, thereby increasing the running time of the high-performance mode.

[0029] In the above-mentioned video watching heat prediction scenario, taking the mobile phone playing a video with a resolution of 1080P as an example, the mobile phone can obtain the first temperature rise value of the mobile phone from the current time point to one minute later, and obtain the heat dissipation capacity coefficient of the mobile phone, the heat consumption curve of the mobile phone from power-on to the current time point, and the ambient temperature curve; then, the mobile phone can calculate the surface temperature of the mobile phone one minute later through the first temperature rise value, the heat dissipation capacity coefficient, the heat consumption curve and the ambient temperature curve, and then perform load scheduling based on the surface temperature of the mobile phone one minute later to reduce heating, thereby delaying the time of thermal restriction. For example, the thermal restriction can be to reduce the resolution from 1080P to 720P.

[0030] In the above-mentioned e-book reading heat prediction scenario, taking the example of a mobile phone refreshing an e-book page at a frequency of 120HZ, the mobile phone can obtain the first temperature rise value of the mobile phone from the current time point to one minute later, and obtain the heat dissipation capacity coefficient of the mobile phone, the heat consumption curve of the mobile phone from power-on to the current time point, and the ambient temperature curve; then, the mobile phone can calculate the surface temperature of the mobile phone one minute later through the first temperature rise value, the heat dissipation capacity coefficient, the heat consumption curve and the ambient temperature curve, and then perform load scheduling based on the surface temperature of the mobile phone one minute later to reduce heating, thereby delaying the time of thermal restriction. For example, the thermal restriction can be to reduce the frequency from 120HZ to 60HZ.

[0031] It should be noted that the above-mentioned scenarios are merely illustrative examples of some scenarios in which the embodiments of the present application may be applied. In actual implementation, the embodiments of the present application can also be applied to any more possible scenarios such as watching live broadcasts, shopping, navigation, etc., and the embodiments of the present application are not limited here.

[0032] In the thermal prediction method, device, electronic device, storage medium and program product provided in the embodiments of the present application, since the heat dissipation capacity coefficient is determined based on the hardware resources of the electronic device, when predicting the first surface temperature of the electronic device at the second time point, the heat dissipation capacity of the electronic device during use can be known through the heat dissipation capacity coefficient. Therefore, when performing thermal prediction, the heat dissipation capacity coefficient, the heat consumption curve and the ambient temperature curve are combined, and the predicted first surface temperature will be more accurate, avoiding the problem of poor accuracy caused by thermal prediction based on power consumption. In this way, the accuracy of thermal prediction of electronic devices is improved.

[0033] The execution subject of the heat prediction method provided in the embodiment of the present application may be a heat prediction device, which may be an electronic device or a functional module in an electronic device. The technical solution provided in the embodiment of the present application is described below using an electronic device as an example.

[0034] The present application embodiment provides a thermal prediction method. Figure 1 FIG. 1 is a flow chart of a heat prediction method provided by an embodiment of the present application. Figure 1 As shown, the thermal prediction method provided in the embodiment of the present application may include the following steps 201 and 202.

[0035] Step 201: The electronic device obtains a first temperature rise value of the electronic device between a first time point and a second time point.

[0036] In the embodiment of the present application, the second time point is a time point after the first time point.

[0037] In the embodiment of the present application, the first time point mentioned above may be a system time point of the electronic device.

[0038] Exemplarily, if the system time point of the electronic device is 8 o'clock, then the first time point mentioned above is 8 o'clock; or, if the system time point of the electronic device is 9 o'clock, then the first time point mentioned above is 9 o'clock.

[0039] Optionally, in the embodiment of the present application, the second time point is any time point after the first time point. For example, the second time point may be a time point corresponding to one minute after the first time point; or, the second time point may be a time point corresponding to 30 seconds after the first time point; or, the second time point may be a time point corresponding to two minutes after the first time point, etc. The specific time point may be determined according to actual use requirements, and the embodiment of the present application does not limit the time point.

[0040] Exemplarily, taking the first time point as 8 o'clock as an example, the second time point may be 8:01.

[0041] It should be noted that the second time point is user-defined or preset by the electronic device.

[0042] It can be understood that the first temperature rise value refers to how much the surface temperature of the electronic device rises between the first time point and the second time point.

[0043] Optionally, in the embodiment of the present application, combined with Figure 1 ,like Figure 2 As shown, the above step 201 can be specifically implemented through the following steps 201a and 201b.

[0044] Step 201a: The electronic device obtains a second temperature rise value of the electronic device at a first time point.

[0045] Optionally, in an embodiment of the present application, when the electronic device is turned on, the third time point referred to below can directly execute the scheme of the embodiment of the present application, and the electronic device can calculate the second temperature rise value based on the temperature rise value at the third time point and the following embodiment.

[0046] It can be understood that when the electronic device is just turned on, the second temperature rise value of the electronic device is 0.

[0047] Optionally, in an embodiment of the present application, the electronic device can obtain the temperature of each hardware in the hardware resources at multiple time points through a negative temperature coefficient (NTC) resistor included in the hardware resources in the electronic device, and then, based on the temperature of each hardware and multiple time points, fit a third surface temperature curve through the least squares method, bring the first time point into the third surface temperature curve to obtain the temperature value at the first time point, and subtract the temperature value at the first time point from the temperature value at the third time point to obtain the above-mentioned second temperature rise value.

[0048] It should be noted that the above-mentioned NTC resistor is a special resistor whose resistance value decreases as the temperature increases. The main material of this resistor is metal oxide, which has semiconductor properties. When the temperature is low, the number of carriers in these oxide materials is small, so the resistance value is high; as the temperature increases, the number of carriers increases, resulting in a decrease in resistance value. In other words, the electronic device can obtain the temperature of each hardware in the above-mentioned hardware resources based on the resistance value of the NTC resistor.

[0049] Optionally, in the embodiment of the present application, the hardware resources include at least one of the following: a central processing unit (CPU), a battery, a hard disk, and a camera module, etc. The specific hardware resources can be determined according to actual use requirements, and the embodiment of the present application does not limit them.

[0050] Step 201b: The electronic device calculates the first temperature rise value based on the second temperature rise value, the time interval between the first time point and the second time point, the heat dissipation capacity coefficient and the heat consumption curve.

[0051] In an embodiment of the present application, the electronic device can bring the first time point into the heat consumption curve to obtain the heat consumption at the first time point, and then calculate the first temperature rise value based on the second temperature rise value, the time interval between the first time point and the second time point, the heat dissipation capacity coefficient, the heat consumption at the first time point and the time constant, which can be specifically achieved by the following formula 1.

[0052]

[0053] Where, ΔT n is the first temperature rise value, ΔT n-1 is the second temperature rise value, Δt is the time interval between the first time point and the second time point, B is the time constant, A is the heat dissipation capacity coefficient, and P is the heat consumption at the first time point.

[0054] For example, Figure 3 As shown, Figure 3 The process of obtaining the first temperature rise value of the electronic device is shown. Figure 3 The horizontal axis t is time, and the vertical axis ΔT is the temperature rise value. n-1 is the second temperature rise value, and ΔT n-1 e -BΔt For heat accumulation.

[0055] Exemplarily, the heat dissipation capacity coefficient can be obtained by the following formula 2.

[0056] A=h*S (2)

[0057] Among them, A is the heat dissipation capacity coefficient, h is the heat transfer coefficient of the electronic device, and S is the surface area of ​​the electronic device.

[0058] In the embodiment of the present application, the electronic device can predict the first surface temperature of the electronic device at the second time point by calculating the first temperature rise value and combining it with the heat dissipation capacity coefficient, thereby improving the accuracy of thermal prediction of the electronic device.

[0059] Step 202: The electronic device predicts a first surface temperature of the electronic device at a second time point based on the first temperature rise value, the heat dissipation capacity coefficient, the heat consumption curve, and the ambient temperature curve; the heat dissipation capacity coefficient is determined based on the hardware resources of the electronic device; the heat consumption curve is used to characterize the variation range of the heat generated by the electronic device during use, and the ambient temperature curve is used to characterize the variation range of the ambient temperature of the environment in which the electronic device is located.

[0060] It should be noted that the first surface temperature is the temperature of the housing of the electronic device.

[0061] Optionally, in the embodiment of the present application, the above-mentioned shell may be at least one of a screen of the electronic device and a back shell of the electronic device.

[0062] In the embodiment of the present application, the electronic device can obtain the ambient temperature of the environment in which the electronic device is located at multiple time points through a temperature sensor, and then fit the above-mentioned ambient temperature curve according to the multiple time points and the ambient temperatures corresponding to the multiple time points.

[0063] Exemplarily, the electronic device may obtain the above-mentioned ambient temperature curve by fitting based on multiple time points through the least square method.

[0064] It can be understood that when the user does not move, the ambient temperature will basically not change, so the above ambient temperature curve is usually a straight line.

[0065] Optionally, in the embodiment of the present application, the temperature sensor may be a thermal resistor temperature sensor or a thermocouple temperature sensor.

[0066] In the embodiment of the present application, the electronic device can determine the five parameters of the temperature rise process through the temperature rise principle: ambient temperature curve, initial temperature rise, heat dissipation capacity coefficient, heat consumption curve, and time constant. The electronic device can perform thermal prediction through these five parameters, that is, predict the first surface temperature of the electronic device at the second time point.

[0067] Exemplarily, the temperature rise principle is shown in the following formula 3.

[0068] m*C*T s '=Ph*S*(T s -T a ) (3)

[0069] Where m is the mass of the electronic device, C is the specific heat capacity, T s ' is the surface temperature curve of the electronic device after temperature change, T a is the ambient temperature curve, P is the self-heating power of the electronic equipment, S is the surface area of ​​the electronic equipment, and h is the heat transfer coefficient of the electronic equipment.

[0070] For example, Figure 4 As shown, the above temperature rise principle can be obtained by Figure 4 It indicates that, Figure 4 The horizontal axis t is time, and the vertical axis Ts is the surface temperature of the object. Figure 4 The dotted line 10 is the ambient temperature curve, and the parabola 11 is the temperature rise curve.

[0071] Optionally, in an embodiment of the present application, before the electronic device obtains the first surface temperature, it can be detected whether there is a thermal prediction interface in the electronic device. If there is a thermal prediction interface, a thermal prediction method in the thermal prediction interface is called to obtain the above-mentioned first surface temperature.

[0072] Optionally, in the embodiment of the present application, combined with Figure 1 ,like Figure 5 As shown, the above step 202 can be specifically implemented through the following steps 202a and 202b.

[0073] Step 202a: The electronic device obtains a first temperature curve by fitting based on the first temperature rise value, the heat dissipation capacity coefficient, the heat consumption curve and the ambient temperature curve.

[0074] In the embodiment of the present application, the electronic device obtains the first temperature curve by fitting based on the first temperature rise value, the heat dissipation capacity coefficient, the heat consumption curve, the ambient temperature curve and the time constant. Specifically, this can be achieved by the following formula 4.

[0075]

[0076] Among them, T ss is the first surface temperature curve, T a is the ambient temperature curve, ΔT0 is the first temperature rise value, B is the time constant, A is the heat dissipation capacity coefficient, and P is the heat consumption curve.

[0077] Optionally, in an embodiment of the present application, the above time constant can be obtained by the following formula 5.

[0078]

[0079] Among them, B is the time constant, m is the mass of the electronic device, C is the specific heat capacity, S is the surface area of ​​the electronic device, and h is the heat transfer coefficient of the electronic device.

[0080] For example, in combination Figure 4 ,like Figure 6 As shown, Figure 6 The process of obtaining the first surface temperature curve of the electronic device is shown, wherein: Figure 6 P1 and P2 are the temperature rise values ​​at historical moments, and Pn, Pn+1, and Pn+m are the temperature rise values ​​at future moments; Figure 6 The horizontal axis t is time, Figure 6 The vertical axis Ts is the temperature value.

[0081] Step 202b: The electronic device calculates a first surface temperature based on the second time point and the first temperature curve.

[0082] In the embodiment of the present application, after obtaining the first temperature curve, the electronic device may input the second time point into the first temperature curve to calculate the first surface temperature.

[0083] In the thermal prediction method provided in the embodiment of the present application, a first temperature rise value of an electronic device between a first time point and a second time point is obtained; then, based on the first temperature rise value, the heat dissipation capacity coefficient, the heat consumption curve and the ambient temperature curve, the first surface temperature of the electronic device at the second time point is predicted, and the second time point is a time point after the first time point; wherein the heat dissipation capacity coefficient is determined based on the hardware resources of the electronic device, the heat consumption curve is used to characterize the change amplitude of the heat generated by the electronic device during use, and the ambient temperature curve is used to characterize the change amplitude of the ambient temperature of the environment in which the electronic device is located. In this solution, since the heat dissipation capacity coefficient is determined based on the hardware resources of the electronic device, when predicting the first surface temperature of the electronic device at the second time point, the heat dissipation capacity of the electronic device during use can be known through the heat dissipation capacity coefficient, so that when performing thermal prediction, the heat dissipation capacity coefficient, the heat consumption curve and the ambient temperature curve are combined, and the predicted first surface temperature will be more accurate, avoiding the problem of poor accuracy caused by thermal prediction through power consumption, thereby improving the accuracy of thermal prediction of electronic devices.

[0084] Optionally, in the embodiment of the present application, combined with Figure 1 ,like Figure 7 As shown, after the above step 202, the thermal prediction method provided in the embodiment of the present application further includes the following steps 301 and 302.

[0085] Step 301: The electronic device obtains a second surface temperature of the electronic device at a first time point.

[0086] Optionally, in an embodiment of the present application, the electronic device can obtain the temperature of the hardware resources in the electronic device at multiple time points, and then fit a fourth surface temperature curve based on the multiple time points and the temperatures of the hardware resources corresponding to the multiple time points, and then obtain the above-mentioned second surface temperature based on the fourth surface temperature curve.

[0087] Exemplarily, the electronic device may obtain the fourth surface temperature curve by fitting through the least square method according to multiple time points and the temperatures of the hardware resources corresponding to the multiple time points.

[0088] Optionally, in the embodiment of the present application, the above step 301 can be specifically implemented by the following steps 301a and 301b.

[0089] Step 301a: The electronic device obtains a second temperature curve by fitting based on the heat dissipation capacity coefficient, the heat consumption curve and the ambient temperature curve.

[0090] In the embodiment of the present application, it can be seen from the above formula 3 that the electronic device can obtain the second temperature curve based on the ambient temperature curve, the heat dissipation capacity coefficient, the heat consumption curve, the time constant, the self-heating power, the mass and specific heat capacity of the electronic device, which can be specifically achieved by the following formula 6.

[0091]

[0092] Among them, T s is the second temperature curve, m is the mass of the electronic device, C is the specific heat capacity, T a is the ambient temperature curve, P is the self-heating power of the electronic equipment, and A is the heat dissipation capacity coefficient.

[0093] Step 301b: The electronic device calculates a second surface temperature based on the first time point and the second temperature curve.

[0094] In the embodiment of the present application, the electronic device may input the first time point into the second temperature curve to calculate the second surface temperature.

[0095] Optionally, in an embodiment of the present application, the electronic device may input N time points into the above-mentioned fourth surface temperature curve and the second surface temperature curve respectively to obtain 2N second surface temperatures, and then average the 2N second surface temperatures to obtain N third surface temperatures corresponding to the N time points; then, according to the N time points and the N third surface temperatures corresponding to the N time points, a fifth surface temperature curve is fitted by the least squares method, and finally, the first time point is input into the fifth surface temperature curve to obtain the above-mentioned second surface temperature; wherein N is a positive integer.

[0096] In this way, by fitting the fifth surface temperature curve using the multiple surface temperature curves, the electronic device can obtain the second surface temperature more accurately.

[0097] Step 302: The electronic device calculates a thermal margin corresponding to a second time point based on the second surface temperature and the first surface temperature.

[0098] It should be noted that the thermal margin is the remaining heat when it reaches a certain temperature. The higher the thermal margin, the larger the heat generation space and the more performance can be released. If the thermal margin is very low, it means that the set temperature is approaching and the performance needs to be controlled in time to lower the temperature.

[0099] In the embodiment of the present application, the electronic device may perform a subtraction operation on the first surface temperature and the second surface temperature to obtain a thermal margin corresponding to the second time point.

[0100] In the embodiment of the present application, the electronic device can determine whether load balancing scheduling is required through thermal margin, thereby reducing the heat generation of the electronic device.

[0101] Optionally, in an embodiment of the present application, after the above step 302, the thermal prediction method provided in the embodiment of the present application further includes the following steps 401 and 402.

[0102] Step 401: When the thermal headroom is less than or equal to a first threshold, the electronic device obtains at least one voltage level corresponding to at least one core of a CPU in the electronic device.

[0103] In the embodiment of the present application, each voltage level of the at least one voltage level is used to characterize the power consumption of a core.

[0104] In the embodiment of the present application, the at least one core corresponds to at least one voltage level.

[0105] Optionally, in the embodiment of the present application, the first threshold may be user-defined or preset by the electronic device.

[0106] Exemplarily, the electronic device may display a threshold setting interface, which includes a threshold input box, in which a user may input a first threshold value, so that the electronic device may obtain the first threshold value.

[0107] Optionally, in an embodiment of the present application, the first threshold may be determined by the electronic device according to a current usage scenario.

[0108] For example, when the usage scenario is a movie watching scenario, the first threshold may be 5 degrees; or, when the usage scenario is a game scenario, the first threshold may be 10 degrees. The specific value may be determined according to actual usage requirements, and the present application embodiment does not limit this.

[0109] It can be understood that when the thermal margin is less than or equal to the second threshold, it means that the second surface temperature predicted by the electronic device is close to the second threshold, so the electronic device can perform load balancing scheduling to slow down the heating time of the electronic device.

[0110] Optionally, in an embodiment of the present application, when the thermal headroom is greater than the first threshold, the electronic device may continue to perform thermal prediction operations until it is detected that the thermal headroom of the electronic device at a certain point in the future is less than or equal to the first threshold.

[0111] Optionally, in an embodiment of the present application, the electronic device may obtain the load size of each core in at least one core to obtain the voltage level corresponding to each core.

[0112] Optionally, in the embodiment of the present application, the above step 401 can be specifically implemented by the following steps 401a to 401d.

[0113] Step 401a: The electronic device obtains static power consumption, dynamic power consumption, and load factor of each core in at least one core.

[0114] In the embodiment of the present application, static power consumption represents the basic power consumption of the CPU in an idle or low-load state, which is usually fixed.

[0115] In the embodiment of the present application, dynamic power consumption refers to the additional power consumption generated by dynamic adjustments such as frequency increase of the CPU under high load conditions, which is usually related to the load.

[0116] In the embodiment of the present application, the load factor represents the load condition of the CPU, and is usually a proportional value between 0 and 1. A load factor of 1 indicates that the CPU has reached the maximum load.

[0117] Step 401b: The electronic device calculates the power consumption of each core in the at least one core based on the static power consumption, dynamic power consumption and load factor of each core in the at least one core.

[0118] In the embodiment of the present application, the electronic device can obtain the power consumption of a core through the following formula 7.

[0119] Power consumption = static power consumption + dynamic power consumption * load factor^2 (7)

[0120] It should be noted that the above formula 7 is used to calculate the power consumption of one core. The power consumption of each core in at least one core can be obtained by the above formula 7. To avoid repetition, it will not be repeated here.

[0121] Step 401c: The electronic device calculates the load size of each core in the at least one core based on the power consumption, static power consumption and dynamic power consumption of each core in the at least one core.

[0122] In the embodiment of the present application, the following formula 8 can be derived based on the above formula 7.

[0123] Load = sqrt((power consumption - static power consumption) / dynamic power consumption) (8)

[0124] It should be noted that the above formula 8 is used to calculate the load of one core, and the load of each core in at least one core can be obtained by the above formula 7, which will not be repeated here to avoid repetition.

[0125] Step 401d: The electronic device determines a voltage level corresponding to each core in the at least one core based on the load size of each core in the at least one core.

[0126] In the embodiment of the present application, the electronic device can determine the voltage level corresponding to each core in the at least one core according to the corresponding relationship between the load size of each core in the at least one core and the voltage level.

[0127] Step 402: When a first voltage level corresponding to a first core among the at least one core is greater than or equal to a second threshold, the electronic device distributes a first load of the first core to a second core among the at least one core.

[0128] In the embodiment of the present application, the second core is a core whose voltage level is less than a second threshold, and the first load is a load corresponding to a voltage level exceeding the second threshold.

[0129] Optionally, in an embodiment of the present application, the second core may be one or more.

[0130] Optionally, in the embodiment of the present application, the second threshold may be user-defined or preset by the electronic device.

[0131] For example, Figure 8 As shown, taking the CPU core as 3 cores as an example, assuming Figure 8 If the voltage level of CPU3 in the circuit exceeds the second threshold, the electronic device can load the load corresponding to the second threshold. Figure 8 It is represented by dotted lines and is allocated to CPU1 and CPU2.

[0132] In the embodiment of the present application, according to the actual heat dissipation of the electronic device and the actual power consumption, the future thermal state changes are detected through the thermal prediction function. When the device is close to the predicted thermal state, the application can avoid being restricted by reducing the workload with the help of these parameters. The present application proactively adjusts the workload of the application engine in advance by monitoring and predicting the heating state of the device, actively adjusts the load instead of passively limiting the frequency, and reduces the heating of the device while meeting the minimum restrictions on the maximum performance, so that the heating state does not exceed the expected temperature control line.

[0133] The above-mentioned method embodiments, or various possible implementation methods in each method embodiment, can be executed separately, or, under the premise that there is no contradiction, can also be executed in combination with each other. The specific implementation can be determined according to actual usage requirements, and the embodiments of the present application do not limit this.

[0134] It should be noted that the thermal prediction method provided in the embodiment of the present application can be executed by a thermal prediction device. In the embodiment of the present application, the thermal prediction device provided in the embodiment of the present application is described by taking the thermal prediction method executed by the thermal prediction device as an example.

[0135] Fig. 9 A possible structural schematic diagram of a thermal prediction device involved in an embodiment of the present application is shown. Fig. 9 As shown, the thermal prediction device 70 may include: an acquisition module 71 and a prediction module 72 .

[0136] The acquisition module 71 is used to acquire a first temperature rise value of the electronic device between a first time point and a second time point. The prediction module 72 is used to predict a first surface temperature of the electronic device at a second time point based on the first temperature rise value, the heat dissipation capacity coefficient, the heat consumption curve and the ambient temperature curve, wherein the second time point is a time point after the first time point; wherein the heat dissipation capacity coefficient is determined based on the hardware resources of the electronic device, the heat consumption curve is used to characterize the variation range of the heat generated by the electronic device during use, and the ambient temperature curve is used to characterize the variation range of the ambient temperature of the environment in which the electronic device is located.

[0137] In a possible implementation, the heat prediction device 70 further includes: a processing module. The acquisition module 71 is specifically used to acquire the second temperature rise value of the electronic device at the first time point. The processing module is used to calculate the first temperature rise value based on the second temperature rise value, the time interval between the first time point and the second time point, the heat dissipation capacity coefficient and the heat consumption curve.

[0138] In a possible implementation, the prediction module 72 is specifically used to fit the first temperature curve based on the first temperature rise value, the heat dissipation capacity coefficient, the heat consumption curve and the ambient temperature curve; and calculate the first surface temperature based on the second time point and the first temperature curve.

[0139] In a possible implementation, the acquisition module 71 is further configured to acquire the second surface temperature of the electronic device at the first time point after the prediction module predicts the first surface temperature of the electronic device at the second time point. The processing module is further configured to calculate the thermal headroom corresponding to the second time point based on the second surface temperature and the first surface temperature.

[0140] In a possible implementation, the processing module is specifically used to fit the second temperature curve based on the heat dissipation capacity coefficient, the heat consumption curve and the ambient temperature curve; and calculate the second surface temperature based on the first time point and the second temperature curve.

[0141] In a possible implementation, the thermal prediction device provided in the embodiment of the present application also includes: an allocation module. The above-mentioned acquisition module 71 is also used to calculate the thermal margin corresponding to the second time point, and when the thermal margin is less than or equal to the first threshold, obtain at least one voltage level corresponding to at least one core of the central processing unit CPU in the electronic device, and each voltage level is used to characterize the power consumption of a core. The above-mentioned allocation module is used to allocate the first load of the first core to the second core of at least one core when the first voltage level corresponding to the first core of at least one core is greater than or equal to the second threshold; wherein the second core is a core whose voltage level is less than the second threshold, and the first load is a load corresponding to the voltage level exceeding the second threshold.

[0142] In a possible implementation, the acquisition module 71 is specifically used to acquire the static power consumption, dynamic power consumption and load factor of each core. The processing module is also used to calculate the power consumption of each core based on the static power consumption, dynamic power consumption and load factor of each core; and calculate the load size of each core based on the power consumption, static power consumption and dynamic power consumption of each core; and determine the voltage level corresponding to each core based on the load size of each core.

[0143] An embodiment of the present application provides a thermal prediction device. Since the heat dissipation capacity coefficient is determined based on the hardware resources of the thermal prediction device, when predicting the first surface temperature of the thermal prediction device at the second time point, the heat dissipation capacity of the electronic device during use can be known through the heat dissipation capacity coefficient. Therefore, when performing thermal prediction, the heat dissipation capacity coefficient, the heat consumption curve and the ambient temperature curve are combined, and the predicted first surface temperature will be more accurate, avoiding the problem of poor accuracy caused by thermal prediction based on power consumption. In this way, the accuracy of thermal prediction of the thermal prediction device is improved.

[0144] The heat prediction device in the embodiment of the present application can be an electronic device, or a component in the electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal, or other devices other than a terminal. Exemplarily, the mobile electronic device can be a mobile phone, a tablet computer, a laptop computer, a PDA, a car electronic device, a mobile Internet device (Mobile Internet Device, MID), an augmented reality (augmented reality, AR) / virtual reality (virtual reality, VR) device, a robot, a wearable device, an ultra-mobile personal computer (ultra-mobile personal computer, UMPC), a netbook or a personal digital assistant (personal digital assistant, PDA), etc., and can also be a server, a network attached storage (Network Attached Storage, NAS), a personal computer (personal computer, PC), a television (television, TV), a teller machine or a self-service machine, etc., which is not specifically limited in the embodiment of the present application.

[0145] The heat prediction device in the embodiment of the present application may be a device having an operating system. The operating system may be an Android operating system, an iOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

[0146] The thermal prediction device provided in the embodiment of the present application can implement each process implemented in the above embodiment, and will not be described again here to avoid repetition.

[0147] Alternatively, if Fig.10 As shown, an embodiment of the present application further provides an electronic device 90, including a processor 91 and a memory 92, wherein the memory 92 stores programs or instructions that can be executed on the processor 91, and when the program or instructions are executed by the processor 91, the various steps of the above-mentioned thermal prediction method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, they are not described here.

[0148] It should be noted that the electronic devices in the embodiments of the present application include the mobile electronic devices and non-mobile electronic devices mentioned above.

[0149] Fig.11 A schematic diagram of the hardware structure of an electronic device to implement an embodiment of the present application.

[0150] The electronic device 100 includes but is not limited to components such as a radio frequency unit 101, a network module 102, an audio output unit 103, an input unit 104, a sensor 105, a display unit 106, a user input unit 107, an interface unit 108, a memory 109, and a processor 110.

[0151] Those skilled in the art will appreciate that the electronic device 100 may also include a power source (such as a battery) for supplying power to various components, and the power source may be logically connected to the processor 110 through a power management system, thereby implementing functions such as managing charging, discharging, and power consumption management through the power management system. Fig.11 The electronic device structure shown in the figure does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently, which will not be described in detail here.

[0152] The processor 110 is used to obtain a first temperature rise value of the electronic device between a first time point and a second time point; based on the first temperature rise value, the heat dissipation capacity coefficient, the heat consumption curve and the ambient temperature curve, predict the first surface temperature of the electronic device at the second time point, where the second time point is a time point after the first time point; wherein the heat dissipation capacity coefficient is determined based on the hardware resources of the electronic device, the heat consumption curve is used to characterize the variation range of the heat generated by the electronic device during use, and the ambient temperature curve is used to characterize the variation range of the ambient temperature of the environment in which the electronic device is located.

[0153] Optionally, in an embodiment of the present application, the above-mentioned processor 110 is specifically used to obtain a second temperature rise value of the electronic device at a first time point; based on the second temperature rise value, the time interval between the first time point and the second time point, the heat dissipation capacity coefficient and the heat consumption curve, the first temperature rise value is calculated.

[0154] Optionally, in an embodiment of the present application, the processor 110 is specifically used to fit a first temperature curve based on a first temperature rise value, a heat dissipation capacity coefficient, a heat consumption curve and an ambient temperature curve; and calculate a first surface temperature based on a second time point and the first temperature curve.

[0155] Optionally, in an embodiment of the present application, the processor 110 is further used to obtain the second surface temperature of the electronic device at the first time point after predicting the first surface temperature of the electronic device at the second time point; and calculate the thermal margin corresponding to the second time point based on the second surface temperature and the first surface temperature.

[0156] Optionally, in an embodiment of the present application, the processor 110 is specifically used to fit a second temperature curve based on the heat dissipation capacity coefficient, the heat consumption curve and the ambient temperature curve; and calculate the second surface temperature based on the first time point and the second temperature curve.

[0157] Optionally, in an embodiment of the present application, the above-mentioned processor 110 is also used to calculate the thermal margin corresponding to the second time point, and when the thermal margin is less than or equal to the first threshold, obtain at least one voltage level corresponding to at least one core of the central processing unit CPU in the electronic device, and each voltage level is used to characterize the power consumption of a core; when the first voltage level corresponding to the first core of at least one core is greater than or equal to the second threshold, distribute the first load of the first core to the second core of at least one core; wherein the second core is a core whose voltage level is less than the second threshold, and the first load is a load corresponding to the voltage level exceeding the second threshold.

[0158] Optionally, in an embodiment of the present application, the above-mentioned processor 110 is specifically used to obtain the static power consumption, dynamic power consumption and load factor of each core; based on the static power consumption, dynamic power consumption and load factor of each core, calculate the power consumption of each core; based on the power consumption, static power consumption and dynamic power consumption of each core, calculate the load size of each core; based on the load size of each core, determine the voltage level corresponding to each core.

[0159] An embodiment of the present application provides an electronic device. Since the heat dissipation capacity coefficient is determined based on the hardware resources of the electronic device, when predicting the surface temperature of the electronic device at a second time point, that is, the second surface temperature mentioned above, the heat dissipation capacity of the electronic device during use can be known through the heat dissipation capacity coefficient. Therefore, when performing thermal prediction, the heat dissipation capacity coefficient, the heat consumption curve and the ambient temperature curve are combined, and the predicted first surface temperature will be more accurate, avoiding the problem of poor accuracy caused by thermal prediction based on power consumption. In this way, the accuracy of thermal prediction of the electronic device is improved.

[0160] The electronic device provided in the embodiment of the present application can implement each process implemented in the above method embodiment and can achieve the same technical effect. To avoid repetition, it will not be described here.

[0161] The beneficial effects of various implementations in this embodiment can be specifically referred to the beneficial effects of the corresponding implementations in the above method embodiment. To avoid repetition, they will not be described again here.

[0162] It should be understood that in the embodiment of the present application, the input unit 104 may include a graphics processor (Graphics Processing Unit, GPU) 1041 and a microphone 1042, and the graphics processor 1041 processes the image data of a static picture or video obtained by an image capture device (such as a camera) in a video capture mode or an image capture mode. The display unit 106 may include a display panel 1061, and the display panel 1061 may be configured in the form of a liquid crystal display, an organic light emitting diode, etc. The user input unit 107 includes a touch panel 1071 and at least one of other input devices 1072. The touch panel 1071 is also called a touch screen. The touch panel 1071 may include two parts: a touch detection device and a touch controller. Other input devices 1072 may include, but are not limited to, a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a trackball, a mouse, and a joystick, which will not be repeated here.

[0163] The memory 109 can be used to store software programs and various data. The memory 109 may mainly include a first storage area for storing programs or instructions and a second storage area for storing data, wherein the first storage area may store an operating system, an application program or instructions required for at least one function (such as a sound playback function, an image playback function, etc.), etc. In addition, the memory 109 may include a volatile memory or a non-volatile memory, or the memory 109 may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), a static random access memory (SRAM), a dynamic random access memory (DRAM), a synchronous dynamic random access memory (SDRAM), a double data rate synchronous dynamic random access memory (DDRSDRAM), an enhanced synchronous dynamic random access memory (ESDRAM), a synchronous link dynamic random access memory (SLDRAM) and a direct memory bus random access memory (DRRAM). The memory 109 in the embodiment of the present application includes but is not limited to these and any other suitable types of memory.

[0164] The processor 110 may include one or more processing units; optionally, the processor 110 integrates an application processor and a modem processor, wherein the application processor mainly processes operations related to an operating system, a user interface, and application programs, and the modem processor mainly processes wireless communication signals, such as a baseband processor. It is understandable that the modem processor may not be integrated into the processor 110.

[0165] An embodiment of the present application also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the various processes of the above-mentioned method embodiment are implemented and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0166] The processor is the processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk.

[0167] An embodiment of the present application further provides a chip, which includes a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0168] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0169] An embodiment of the present application provides a computer program product, which is stored in a storage medium. The program product is executed by at least one processor to implement the various processes of the above-mentioned thermal prediction method embodiment and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0170] It should be noted that, in this article, the terms "comprise", "include" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise one..." do not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0171] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, a disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0172] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

Claims

1. A thermal prediction method, characterized in that: The method comprises: Obtaining a first temperature rise value of the electronic device between a first time point and a second time point; Predicting a first surface temperature of the electronic device at the second time point based on the first temperature rise value, the heat dissipation capacity coefficient, the heat consumption curve, and the ambient temperature curve; Among them, the heat dissipation capacity coefficient is determined based on the hardware resources of the electronic device, the heat consumption curve is used to characterize the change range of the heat generated by the electronic device during use, and the ambient temperature curve is used to characterize the change range of the ambient temperature of the environment in which the electronic device is located.

2. The method according to claim 1, characterized in that The obtaining of a first temperature rise value of the electronic device between a first time point and a second time point includes: Obtaining a second temperature rise value of the electronic device at a first time point; The first temperature rise value is obtained by calculation based on the second temperature rise value, the time interval between the first time point and the second time point, the heat dissipation capacity coefficient and the heat consumption curve.

3. The method according to claim 1, characterized in that The predicting, based on the first temperature rise value, the heat dissipation capacity coefficient, the heat consumption curve and the ambient temperature curve, of the first surface temperature of the electronic device at a second time point includes: Based on the first temperature rise value, the heat dissipation capacity coefficient, the heat consumption curve and the ambient temperature curve, a first temperature curve is obtained by fitting; The first surface temperature is calculated based on the second time point and the first temperature curve.

4. The method according to any one of claims 1 to 3, characterized in that After predicting the first surface temperature of the electronic device at a second time point, the method further includes: Acquire a second surface temperature of the electronic device at the first time point; The thermal margin corresponding to the second time point is calculated based on the second surface temperature and the first surface temperature.

5. The method according to claim 4, characterized in that The obtaining a second surface temperature of the electronic device at the first time point includes: Based on the heat dissipation capacity coefficient, the heat consumption curve and the ambient temperature curve, fitting to obtain a second temperature curve; The second surface temperature is calculated based on the first time point and the second temperature curve.

6. The method according to claim 4, characterized in that After the thermal margin corresponding to the second time point is obtained by calculation, the method further includes: When the thermal headroom is less than or equal to the first threshold, obtaining at least one voltage level corresponding to at least one core of a central processing unit (CPU) in the electronic device, each voltage level being used to characterize the power consumption of a core; When a first voltage level corresponding to a first core among the at least one core is greater than or equal to a second threshold, allocating a first load of the first core to a second core among the at least one core; The second core is a core whose voltage level is less than the second threshold, and the first load is a load whose voltage level exceeds the second threshold.

7. The method according to claim 6, characterized in that The obtaining of at least one voltage level corresponding to at least one core of a CPU in the electronic device includes: Get the static power consumption, dynamic power consumption and load factor of each core; Calculate the power consumption of each core based on the static power consumption, dynamic power consumption and load factor of each core; Based on the power consumption, static power consumption and dynamic power consumption of each core, the load size of each core is calculated; Based on the load size of each core, a voltage level corresponding to each core is determined.

8. A thermal prediction device, characterized in that: The thermal prediction device comprises: an acquisition module and a prediction module; The acquisition module is used to acquire a first temperature rise value of the electronic device between a first time point and a second time point; The prediction module is used to predict the first surface temperature of the electronic device at the second time point based on the first temperature rise value, the heat dissipation capacity coefficient, the heat consumption curve and the ambient temperature curve; Among them, the heat dissipation capacity coefficient is determined based on the hardware resources of the electronic device, the heat consumption curve is used to characterize the change range of the heat generated by the electronic device during use, and the ambient temperature curve is used to characterize the change range of the ambient temperature of the environment in which the electronic device is located.

9. An electronic device, characterized in that: The method comprises a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the steps of the thermal prediction method according to any one of claims 1 to 7.

10. A readable storage medium, characterized in that: The readable storage medium stores a program or an instruction, and when the program or the instruction is executed by a processor, the steps of the thermal prediction method according to any one of claims 1 to 7 are implemented.

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