Terminal heat dissipation method, terminal equipment and computer readable storage medium

Abstract

The invention discloses a terminal heat dissipation method, terminal equipment, a computer readable storage medium and a computer program product, and relates to the technical field of equipment heat dissipation, the terminal heat dissipation method is applied to the terminal equipment internally provided with an air cooling device and a liquid cooling device, the air cooling device has at least two rotating speed gears, and the liquid cooling device has at least two rotating speed gears. The liquid cooling device is provided with at least two flow speed gears, and the method comprises the steps that current operation state information of the terminal equipment is acquired, and the current operation state information comprises the current operation temperature and the current operation load; the AI model is predicted based on a convergent heat dissipation strategy, a target combined heat dissipation strategy matched with the current operation state information is obtained through prediction, and the target combined heat dissipation strategy comprises a target rotating speed gear and a target flow speed gear; and controlling the air cooling device to operate according to the target rotating speed gear, and controlling the liquid cooling device to operate according to the target flow speed gear. According to the invention, the cruising ability and the performance of the equipment can be considered.

Description

Technical Field

[0001] This application relates to the field of device heat dissipation technology, and in particular to terminal heat dissipation methods, terminal devices, and computer-readable storage media. Background Technology

[0002] In the field of modern mobile communications, the performance of smartphones and other smart terminal devices has reached unprecedented levels. The core components of these devices—the Central Processing Unit (CPU) and the Graphics Processing Unit (GPU)—have been undergoing rapid technological iteration and upgrades. With advancements in semiconductor manufacturing processes, from the initial trials of 8nm technology to the mature application of 6nm technology, and now to the cutting-edge technology of 4nm technology, processor performance and energy efficiency have been significantly improved.

[0003] However, this performance improvement comes at a cost. As CPU and GPU performance increases, so does the heat they generate under heavy loads. This heat not only affects user comfort but can also negatively impact the device's long-term performance and reliability. In high-performance scenarios such as mobile gaming, overheating is particularly problematic, degrading the user experience and potentially damaging the brand image.

[0004] To address this challenge, smart terminal devices need to more intelligently identify user operating scenarios and quickly implement effective heat dissipation measures. At the same time, these heat dissipation measures must not come at the expense of battery life. Currently, some solutions on the market, such as using more efficient heat dissipation materials, increasing heat dissipation area, adjusting CPU / GPU frequencies, and optimizing task scheduling, while alleviating the heat problem to some extent, often fail to balance battery life and performance, failing to achieve the optimal balance between performance and power consumption. Summary of the Invention

[0005] The main purpose of this application is to provide a terminal heat dissipation method, a terminal device, and a computer-readable storage medium, aiming to solve the technical problem that heat dissipation methods in related technologies cannot simultaneously take into account the device's battery life and performance.

[0006] To achieve the above objectives, this application provides a terminal heat dissipation method, applied to a terminal device equipped with an air-cooling device and a liquid-cooling device, wherein the air-cooling device has at least two speed settings and the liquid-cooling device has at least two flow rate settings, and the method includes:

[0007] Obtain the current operating status information of the terminal device, wherein the current operating status information includes the current operating temperature and the current operating load;

[0008] Based on a convergent heat dissipation strategy prediction AI model, a target combined heat dissipation strategy matching the current operating state information is predicted, wherein the target combined heat dissipation strategy includes a target speed level and a target flow rate level.

[0009] The operation of the air-cooling device is controlled according to the target speed setting, and the operation of the liquid-cooling device is controlled according to the target flow rate setting.

[0010] In addition, to achieve the above objectives, this application also provides a terminal device, the terminal device including: a memory, a processor, and a terminal heat dissipation program stored in the memory and executable on the processor, wherein when the terminal heat dissipation program is executed by the processor, it implements the steps of the terminal heat dissipation method as described above.

[0011] In addition, to achieve the above objectives, this application also provides a computer-readable storage medium storing a terminal heat dissipation program, which, when executed by a processor, implements the steps of the terminal heat dissipation method described above.

[0012] In addition, to achieve the above objectives, this application also provides a computer program product, which includes a terminal heat dissipation program. When the terminal heat dissipation program is executed by a processor, it implements the steps of the terminal heat dissipation method described above.

[0013] This application provides a terminal heat dissipation method, a terminal device, and a computer-readable storage medium. The terminal device includes an air-cooling device and a liquid-cooling device. The air-cooling device has at least two speed settings, and the liquid-cooling device has at least two flow rate settings. The technical solution of this application is to obtain the current operating status information of the terminal device, including the current operating temperature and the current operating load, and predict a target combined heat dissipation strategy matching the current operating status information based on a convergent heat dissipation strategy prediction AI model. The target combined heat dissipation strategy includes a target speed setting and a target flow rate setting. Then, the air-cooling device is controlled to operate according to the target speed setting, and the liquid-cooling device is controlled to operate according to the target flow rate setting. This controls the fan speed and micro-pump flow rate at different settings, enabling the terminal device to dissipate heat quickly and avoiding issues with the grip and performance of the terminal due to excessive heat, thus fully utilizing the chip performance of the terminal device. Furthermore, the intelligent heat dissipation control mechanism in this application embodiment can also avoid excessive power consumption. While controlling the heat dissipation of the terminal, it can also ensure the battery life of the terminal. It can effectively realize the ability to dynamically adjust the heat dissipation strategy according to the actual application scenario, achieve the best balance between performance and power consumption, and thus solve the technical problem in related technologies that heat dissipation methods cannot take into account both the battery life and performance of the device. Attached Figure Description

[0014] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0015] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0016] Figure 1 This is a flowchart illustrating an embodiment of the terminal heat dissipation method of this application.

[0017] Figure 2 This is a flowchart illustrating Embodiment 2 of the terminal heat dissipation method of this application;

[0018] Figure 3 This is a flowchart illustrating Embodiment 3 of the terminal heat dissipation method of this application;

[0019] Figure 4 A diagram of a terminal heat dissipation setting interface provided in a specific embodiment of this application;

[0020] Figure 5 This is a schematic diagram of a terminal heat dissipation process provided in a specific embodiment of this application;

[0021] Figure 6 This is a schematic diagram illustrating the acquisition of central control service information according to a specific embodiment of this application;

[0022] Figure 7 This is a schematic diagram of the device structure of the hardware operating environment involved in the terminal heat dissipation method in this application embodiment.

[0023] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0024] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0025] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0026] Currently, several commonly used heat dissipation methods in related technologies struggle to balance device battery life and performance. Passive cooling relies on natural convection or radiation, which has the advantage of requiring no additional energy input, but its heat dissipation efficiency is low, especially under high loads. It may fail to remove heat promptly, causing device temperature to rise and triggering frequency throttling protection, thus impacting performance. Active cooling typically involves mechanical devices such as fans or pumps, which effectively accelerate airflow or liquid circulation to quickly remove heat. However, these devices themselves require electrical power, increasing total power consumption and affecting battery life.

[0027] The main solution of this application embodiment is a terminal heat dissipation method, applied to a terminal device equipped with an air-cooling device and a liquid-cooling device. The air-cooling device has at least two speed settings, and the liquid-cooling device has at least two flow rate settings. The method includes: acquiring the current operating status information of the terminal device, wherein the current operating status information includes the current operating temperature and the current operating load; predicting a target combined heat dissipation strategy matching the current operating status information based on a convergent heat dissipation strategy prediction AI model, wherein the target combined heat dissipation strategy includes a target speed setting and a target flow rate setting; controlling the operation of the air-cooling device according to the target speed setting, and controlling the operation of the liquid-cooling device according to the target flow rate setting.

[0028] This application embodiment utilizes an intelligent heat dissipation control mechanism to control the fan speed and micro-pump flow rate at different levels, enabling rapid heat dissipation of the terminal device. This avoids issues with grip feel and performance caused by excessive heat, fully leveraging the chip performance of the terminal device (providing a better user experience in both gaming and other usage scenarios). While controlling terminal heat dissipation, it also avoids excessive power consumption, ensuring battery life. This effectively achieves the ability to dynamically adjust the heat dissipation strategy according to actual application scenarios, reaching the optimal balance between performance and power consumption. Consequently, it solves the technical problem in related technologies where heat dissipation methods struggle to balance device battery life and performance.

[0029] It should be noted that the executing entity of this application may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs (Televisions), desktop computers, etc., or any terminal device capable of performing the above functions. This application does not specifically limit this. The following description uses a terminal device as an example to illustrate the various embodiments of this application.

[0030] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0031] Please refer to Figure 1 , Figure 1 This is a flowchart illustrating an embodiment of the terminal heat dissipation method of this application.

[0032] In this embodiment, the terminal heat dissipation method is applied to a terminal device equipped with an air-cooling device and a liquid-cooling device. The air-cooling device has at least two speed settings, and the liquid-cooling device has at least two flow rate settings. The method includes steps S100 to S300:

[0033] Step S100: Obtain the current operating status information of the terminal device, wherein the current operating status information includes the current operating temperature and the current operating load;

[0034] Those skilled in the art will recognize that an air-cooled device is a heat dissipation device that uses airflow to remove heat. It typically includes one or more fans and heat sinks. The airflow generated by the fans carries heat away from the heat sinks, thereby achieving a cooling effect. A liquid-cooled device is a heat dissipation device that uses a liquid (usually water or other heat transfer medium) as a cooling medium. It absorbs and transfers heat through circulating liquid and then releases the heat to the external environment, achieving effective cooling of the internal components of the equipment.

[0035] It's important to note that "speed setting" refers to different settings for the fan's rotational speed in an air-cooled system, while "flow rate setting" refers to different settings for the coolant's flow rate in a liquid-cooled system. Generally, a higher setting means a higher speed or flow rate, providing better heat dissipation, but also consuming more power.

[0036] In this embodiment, the current operating status information refers to parameter information reflecting the operating status of the terminal device at the current moment, including the current operating temperature and the current operating load. The current operating temperature refers to the actual temperature of the terminal device at the current moment, specifically the processor temperature, battery temperature, etc., collected in real time by the terminal device's built-in temperature sensor. The current operating load refers to the load status of the terminal device at the current moment, specifically the processor utilization rate, the number of running applications, etc.

[0037] This embodiment collects current operating status information of the terminal device, including current operating temperature and current operating load, and analyzes the current operating status of the terminal device to determine which speed and flow rate settings should be used to control the operation of the air-cooling and liquid-cooling devices. This ensures that the terminal device can effectively dissipate heat without sacrificing its battery life, thus guaranteeing the performance of the terminal device and achieving the best balance between performance and power consumption.

[0038] It is worth mentioning that, in one feasible implementation, the current operating status information also includes the current charging status and the current performance mode. The charging status includes fast charging, slow charging and no charging. The performance mode includes a first performance mode and a second performance mode. The performance consumption of the first performance mode is greater than that of the second performance mode.

[0039] It should be noted that the current charging status refers to the charging status of the terminal device at the current moment, and the current performance mode refers to the performance mode of the terminal device at the current moment.

[0040] In this embodiment, the charging state includes at least a fast charging state, a slow charging state, and a no-charging state, wherein the charging power in the fast charging state is greater than that in the slow charging state. Taking a smartphone as an example, generally speaking, the standard charger for a smartphone has a charging power of 5 watts. When a smartphone is charged with a charging power of 10 watts or more, its charging state is a fast charging state; when it is charged with a charging power of less than 10 watts, its charging state is a slow charging state; and when it is not charging, its charging state is a no-charging state.

[0041] It is understandable that the standard chargers for different terminal devices have different charging power, and correspondingly, the criteria for judging fast charging and slow charging states are different. For example, the charging power of personal laptops is generally between 30 and 150 watts. Accordingly, the fast charging state of a personal laptop can be set to a charging state with a charging power greater than 100 watts, and the slow charging state can be set to a charging power less than or equal to 100 watts. The specific settings can be flexibly set according to the actual situation, and this embodiment does not make specific limitations on this.

[0042] Those skilled in the art will understand that terminal devices typically offer different performance modes, allowing users to adjust the device's performance and power consumption according to their current needs and usage scenarios. Common performance modes include high-performance mode, balanced mode, power-saving mode, and gaming mode. Different performance modes result in variations in processor frequency, screen brightness, and screen refresh rate. For example, generally speaking, the higher the processor frequency, the higher the performance and power consumption of the terminal device's current performance mode.

[0043] In this embodiment, the performance modes include at least a first performance mode and a second performance mode, wherein the performance consumption of the first performance mode is greater than that of the second performance mode. In this embodiment, performance consumption reflects the performance level and power consumption of the performance mode; a higher performance consumption indicates higher performance and higher power consumption of the terminal device in that performance mode. Specifically, the performance consumption can be the processor frequency. The processor frequency of the terminal device in the first performance mode is higher than that in the second performance mode, meaning the performance consumption of the first performance mode is greater than that of the second performance mode.

[0044] It's easy to understand that terminal devices generate additional heat when charging. The higher the charging power, the more heat is generated, and the more timely heat dissipation is needed. Correspondingly, the higher the performance consumption of the current performance mode, the higher the processor load and the more heat is generated.

[0045] In this embodiment, the current operating status information includes not only the current operating temperature and current operating load, but also the current charging status and current performance mode. Compared to analyzing the current operating status of the terminal device solely based on the current operating temperature and current operating load, this embodiment introduces the current charging status and current performance mode as decision factors, providing a more comprehensive understanding of the terminal device's overall operating status. This allows for a rapid response when the terminal device's operating status changes (e.g., starting or ending charging, switching performance modes, switching from slow charging to fast charging, etc.), enabling timely adjustments to the heat dissipation strategy. This results in more reasonable heat dissipation adjustments, achieving the required heat dissipation effect with lower power consumption. This leads to more intelligent and personalized heat dissipation management, improving the performance stability of the terminal device and extending its battery life. Ultimately, it achieves a balance between battery life and performance, reaching the optimal balance between performance and power consumption.

[0046] This embodiment, by detecting the charging status or charging power, can better determine the current charging status of the terminal device. When the charging power is high, the cooling device (including the split cooling device and liquid cooling device) can be adjusted in a timely manner (i.e., the speed and flow rate settings) to address the potential overheating risk caused by excessive charging power. Conversely, when the charging power is low or there is no charging, the cooling intensity can be appropriately reduced to save energy. Similarly, this embodiment also determines the current load of the terminal device by detecting the performance consumption or performance mode of the current performance mode. When the performance consumption of the current performance mode is high, the cooling device can be adjusted in a timely manner to address the potential overheating risk caused by high performance consumption. Conversely, when the performance consumption of the current performance mode is low, the cooling intensity can be appropriately reduced to save energy.

[0047] Furthermore, in another feasible implementation, the current running status information also includes the screen touch frequency counted within the most recent preset time period, and the background application information currently running in the background of the terminal device.

[0048] It should be noted that screen touch frequency refers to the number of times the screen of a terminal device is touched within a certain period of time, while background application information refers to information about applications running in the background of the terminal device, including their quantity, type, and resource usage.

[0049] In this embodiment, the terminal device can periodically or in real time count the number of times the terminal device's screen is touched within a preset time period. For example, the terminal device can count the number of times the terminal device's screen is touched within 3 seconds in real time as the screen touch frequency counted within the preset time period. Thus, when the current operating status information of the terminal device is obtained, the number of times the terminal device's screen is touched within the 3 seconds prior to the current moment is used as the screen touch frequency counted within the most recent preset time period.

[0050] For example, the terminal device can also count the number of times the screen is touched within any or specified 5 seconds every minute, so that when the current operating status information of the terminal device is obtained, the number of times the screen is touched within one minute before the current moment is used as the screen touch frequency counted within the most recent preset time period.

[0051] It's easy to understand that a higher screen touch frequency usually means the user is performing frequent operations on the device, which increases the processor load and generates a lot of heat. Similarly, the more background applications running and the higher their resource usage, the higher the processor load and the more heat generated.

[0052] Similar to the technical effects of the above embodiments, this embodiment further introduces the screen touch frequency statistically analyzed within the most recent preset time period, as well as the background application information currently running in the background of the terminal device, as decision factors. This provides a more comprehensive understanding of the overall operating status of the terminal device, enabling a rapid response when the operating status of the terminal device changes (e.g., a sudden increase in screen touch frequency, or the clearing of background applications). The device can then adjust its heat dissipation strategy in a timely manner, making more reasonable adjustments to the heat dissipation strategy. This achieves the required heat dissipation effect with lower power consumption, realizing more intelligent and personalized heat dissipation management, improving the performance stability of the terminal device, and extending its battery life. Ultimately, this achieves a balance between battery life and performance, reaching the best balance between performance and power consumption.

[0053] This embodiment detects screen touch frequency to better determine the current usage intensity of the terminal device. When the screen touch frequency is high, the cooling system (including the split cooling system and liquid cooling system) is adjusted in a timely manner (i.e., the rotation speed and flow rate) to address the potential overheating risk caused by frequent screen operations. Conversely, when the touch frequency is low, the cooling intensity can be appropriately reduced to save energy. Similarly, this embodiment also detects background application information to determine the current load of the terminal device. When there are many background applications and high resource utilization, the cooling system is adjusted in a timely manner to address the potential overheating risk caused by background application operation. Conversely, when there are few background applications and low resource utilization, the cooling intensity can be appropriately reduced to save energy.

[0054] Step S200: Based on the convergent heat dissipation strategy prediction AI model, predict the target combined heat dissipation strategy that matches the current operating state information, wherein the target combined heat dissipation strategy includes a target speed level and a target flow rate level.

[0055] It should be noted that a heat dissipation strategy refers to a set of rules or methods for effectively controlling the temperature of equipment under specific conditions. It generally includes choosing which heat dissipation method (such as air cooling or liquid cooling), when to start the heat dissipation device, and how to adjust the heat dissipation device's setting.

[0056] In this embodiment, the combined heat dissipation strategy refers to a set of rules or methods for effectively controlling the temperature of a terminal device by utilizing multiple heat dissipation methods (at least including air cooling and liquid cooling) under specific operating conditions. This includes the speed settings of each heat dissipation device in the combination, such as the rotation speed settings of the air cooling device and the liquid cooling device. The target combined heat dissipation strategy is a combined heat dissipation strategy for the current operating state of the terminal device. It aims to achieve optimal heat dissipation with minimal power consumption by rationally configuring the speed settings of the air cooling and liquid cooling devices, thus achieving a balance between the terminal device's performance and battery life. This solves the technical problem in related technologies where heat dissipation methods struggle to simultaneously consider both battery life and performance. The target combined heat dissipation strategy includes a target rotation speed setting and a target flow rate setting. The target rotation speed setting is the most suitable air cooling device speed setting for the current operating state of the terminal device under a combined heat dissipation method that includes at least air cooling and liquid cooling. Similarly, the target flow rate setting is the most suitable liquid cooling device flow rate setting for the current operating state of the terminal device under a combined heat dissipation method that includes at least air cooling and liquid cooling.

[0057] It should be noted that, in this embodiment, the convergent heat dissipation strategy prediction AI (Artificial Intelligence) model is a model trained by machine learning algorithms. It can predict the most suitable combination of heat dissipation strategies for the current situation, i.e., the target combination of heat dissipation strategies, based on the current operating status information of the device (such as current operating temperature, current operating load, current charging status, current performance mode, screen touch frequency statistics within the most recent preset time period, background application information currently running on the terminal device, etc.).

[0058] It is worth mentioning that, depending on the samples and labels used during training, the converged heat dissipation strategy prediction AI model can directly output the target combined heat dissipation strategy, or it can output an intermediate parameter information, and then match the corresponding combined heat dissipation strategy as the target combined heat dissipation strategy based on the intermediate parameter information.

[0059] For example, in this embodiment, the optimal combination of heat dissipation strategies can be designed and associated in advance for multiple different operating state information of the terminal device. Then, the operating state information is used as a sample, and the associated combination of heat dissipation strategies is used as a label to form a training set to train the heat dissipation strategy prediction AI model until it converges. This results in a converged heat dissipation strategy prediction AI model that can directly output the target combination of heat dissipation strategies that match the current operating state information based on the input current operating state information.

[0060] For example, in this embodiment, the heat generated by the terminal device per unit time under each different operating state can be measured in advance as intermediate parameter information. Then, for each intermediate parameter information, the optimal combination heat dissipation strategy is designed and associated. Then, the operating state information is used as a sample and the intermediate parameter information is used as a label to form a training set to train the heat dissipation strategy prediction AI model until it converges. This results in a converged heat dissipation strategy prediction AI model that can output intermediate parameter information based on the input current operating state information. Then, the combination heat dissipation strategy associated with the intermediate parameter information is queried as the target combination heat dissipation strategy that matches the current operating state information.

[0061] For example, this embodiment can score multiple different operating status information of the terminal device according to a preset scoring standard, and design the optimal combination heat dissipation strategy for different score ranges and associate them. Then, the operating status information is used as a sample and the score value is used as a label to form a training set to train the heat dissipation strategy prediction AI model until it converges. This results in a converged heat dissipation strategy prediction AI model that can output a score based on the input current operating status information. Then, the combination heat dissipation strategy associated with the score range to which the score value belongs is queried as the target combination heat dissipation strategy that matches the current operating status information.

[0062] Understandably, as the speed of a cooling device increases, the improvement in heat dissipation is generally less than the increase in power consumption. That is, at lower speeds, the cooling device dissipates 10 units of heat for every 10 units of energy consumed, while as the speed increases, it takes 11, 12, or even 15 units of energy to dissipate 10 units of heat. Taking an air-cooled device as an example, assuming the airflow generated is proportional to the heat dissipated, as the speed of the air-cooled device increases, the airflow generated per unit time increases, but this increase is not linear. According to fluid dynamics principles, air resistance increases with the square of velocity, meaning that as the speed increases, the rate of increase in airflow per unit time gradually slows down, and the rate of increase in heat dissipation per unit time also gradually slows down. Simultaneously, as the speed of the air-cooled device increases, the energy consumed per unit time also increases, but this increase is also not linear. Typically, energy consumption is proportional to the cube of the speed, meaning that as the speed increases, the rate of increase in energy consumption per unit time gradually accelerates. Therefore, as the speed setting increases, the energy consumption increase of the air-cooled device will gradually exceed the heat dissipation increase. Similarly, the liquid-cooled device also experiences a situation where, as the flow rate setting increases, the energy consumption increase gradually exceeds the heat dissipation increase.

[0063] In traditional thermal management, while increasing the cooling level of a heat dissipation device (such as an air-cooled or liquid-cooled device) improves the cooling effect, it also increases power consumption (i.e., energy consumption per unit time) by a greater margin. In other words, the cooling efficiency of the device decreases as the cooling level increases. However, this embodiment addresses the issue of disproportionate energy consumption and cooling effect. It uses a pre-trained, convergent AI model to predict the most suitable combined cooling strategy for the current operating state. This allows for low-power combined cooling using different heat dissipation devices, achieving a better balance between cooling performance and minimizing power consumption. This achieves the cooling effect that a single high-power device would otherwise require, thus optimizing power consumption and extending battery life while maintaining the performance of the terminal device.

[0064] In this embodiment, the converged heat dissipation strategy prediction AI model can predict the most suitable target combination of heat dissipation strategies for the current operating state based on current operating state information (such as temperature, load, charging status, performance mode, screen touch frequency, and background application information). This allows for real-time adjustment of the power levels of each heat dissipation device to adapt to constantly changing usage environments, ensuring the device maintains good heat dissipation performance under all circumstances. Even under high load, optimizing the combined heat dissipation strategy can avoid excessive power consumption, achieving similar or even better heat dissipation effects than a single heat dissipation device (e.g., a single air-cooled device or a single liquid-cooled device) at a lower total power consumption. As a result, even when higher heat dissipation performance is required, the device's battery life is not significantly affected, extending its battery life. This allows the device to find the optimal synergy between different heat dissipation methods, achieving the best balance between overall performance and power consumption.

[0065] Step S300: Control the operation of the air-cooling device according to the target speed setting, and control the operation of the liquid-cooling device according to the target flow rate setting.

[0066] In this embodiment, after predicting the target combination heat dissipation strategy that matches the current operating status information, the target combination heat dissipation strategy is executed. The air cooling device of the terminal device is controlled to operate at the target speed level in the target combination heat dissipation strategy, and the liquid cooling device of the terminal device is controlled to operate at the target flow rate level in the target combination heat dissipation strategy. By combining different heat dissipation devices, a heat dissipation effect similar to or even better than that of a single heat dissipation device at a high speed is achieved with lower total power consumption. While ensuring device performance, energy is saved as much as possible and the battery life is extended.

[0067] This embodiment uses a convergent heat dissipation strategy prediction AI model to process the current operating status information of the terminal device, predicts the target combination heat dissipation strategy that can achieve the optimal balance between heat dissipation effect and energy consumption under the current operating state, and then executes the target combination heat dissipation strategy to dynamically adjust the level of each heat dissipation device. This allows the terminal device to maintain good heat dissipation performance and be in a healthy working state in changing working environments. While ensuring device performance, it saves energy as much as possible, extends battery life, reduces the probability of failure due to overheating, and extends the service life of the device. Ultimately, it achieves the goal of optimizing power consumption while ensuring performance, realizing the best balance between device performance and battery life, and solving the technical problem in related technologies that heat dissipation methods cannot simultaneously take into account the device's battery life and performance.

[0068] This embodiment acquires the current operating status information of the terminal device, including the current operating temperature and current operating load. Based on a convergent heat dissipation strategy prediction AI model, it predicts a target combination heat dissipation strategy matching the current operating status information. This target combination heat dissipation strategy includes a target fan speed setting and a target flow rate setting. The air cooling device is controlled according to the target fan speed setting, and the liquid cooling device is controlled according to the target flow rate setting. This controls the fan speed and micro-pump flow rate at different levels, enabling the terminal device to dissipate heat quickly and avoiding issues with grip and performance caused by excessive heat. This fully utilizes the chip performance of the terminal device (providing a better user experience in gaming and other usage scenarios). Furthermore, the intelligent heat dissipation control mechanism of this embodiment also avoids excessive power consumption. While controlling terminal heat dissipation, it also ensures good battery life, effectively achieving the ability to dynamically adjust the heat dissipation strategy according to the actual application scenario, achieving the optimal balance between performance and power consumption. This solves the technical problem in related technologies where heat dissipation methods struggle to balance device battery life and performance.

[0069] In this embodiment, the convergent heat dissipation strategy prediction AI model can automatically infer and judge the current heat dissipation status of the terminal based on the terminal's current operating state information, predict the target combination of heat dissipation strategies matching the current operating state information, and determine an optimal fan speed and flow rate level based on the currently learned data, thereby intelligently selecting the fan speed and liquid cooling flow rate for the current scenario. This embodiment, through the convergent heat dissipation strategy prediction AI model, predicts which combination of heat dissipation strategies is more suitable for the terminal device under the current operating state information, thereby more intelligently controlling the fan speed and micro-pump flow rate level, ensuring terminal heat dissipation while reducing unnecessary power consumption waste.

[0070] Furthermore, in one feasible implementation, the method further includes step A10:

[0071] Step A10: When the intelligent heat dissipation mode of the terminal device is detected to be turned on, the steps of controlling the operation of the air-cooling device according to the target speed level and controlling the operation of the liquid-cooling device according to the target flow rate level are triggered.

[0072] It should be noted that the intelligent heat dissipation mode in this embodiment is a special operating mode pre-set on the terminal device. In this intelligent heat dissipation mode, the terminal device automatically executes the target combined heat dissipation strategy, controlling the air cooling device to operate at the target speed and the liquid cooling device to operate at the target flow rate, thereby performing combined heat dissipation on the terminal device. This intelligent heat dissipation mode can be manually activated by the user, or it can be automatically activated by the terminal device's control system when it detects that the current operating temperature is higher than a certain preset temperature, the processor utilization rate corresponding to the current operating load is higher than a certain threshold, or the terminal device is turned on.

[0073] It should be noted that when this intelligent heat dissipation mode is activated, the terminal device will obtain the current operating status information in real time or periodically and input it into the converged heat dissipation strategy prediction AI model to execute the target combination heat dissipation strategy that matches the predicted operating status information until the intelligent heat dissipation mode is turned off.

[0074] Accordingly, this intelligent heat dissipation mode can be manually turned off by the user, or it can be automatically turned off by the terminal device's control system when it detects that the current operating temperature is lower than a certain preset temperature, the processor utilization rate corresponding to the current operating load is less than a certain threshold, or the terminal device is shut down.

[0075] It's easy to understand that the automatic activation and deactivation of the intelligent cooling mode can be configured in the terminal device's settings interface, allowing users to adjust the timing and conditions for automatic activation and deactivation according to their own needs, thus providing users with greater flexibility.

[0076] Please refer to Figure 2 , Figure 2 This is a flowchart illustrating Embodiment 2 of the terminal heat dissipation method of this application.

[0077] In this embodiment, the same or similar content as in the above embodiments can be referred to the above description, and will not be repeated hereafter.

[0078] In this embodiment, the method further includes steps S400 to S600:

[0079] Step S400: Obtain multiple different operating status information and a calibration combination heat dissipation strategy matched with each of the operating status information. The calibration combination heat dissipation strategy refers to a combination heat dissipation strategy in which the operating performance of the terminal device meets the first condition and the heat dissipation power consumption of the terminal device meets the second condition. The combination heat dissipation strategy includes the calibration speed setting of the air cooling device and the calibration flow rate setting of the liquid cooling device.

[0080] It should be noted that, in this embodiment, the first condition refers to the condition that the terminal device's operating performance must meet, ensuring that the terminal device can maintain good performance under various operating states. The operating performance of the terminal device can be reflected by various performance indicators, such as processor frequency, network speed, graphics rendering time, frame rate, data read / write latency, etc. Accordingly, the first condition can be any one or more of the following: processor frequency greater than a certain preset frequency, network speed greater than a certain preset value, or graphics rendering time less than a certain preset duration, thereby ensuring that the terminal device's operating performance remains stable under the current operating state, without frequent performance fluctuations or processor frequency reduction.

[0081] For example, the first condition for mapping can be different under different operating states. For instance, when the current performance mode of the terminal device is game mode, the first condition can be that the graphics rendering time is less than 1 microsecond, while when the current performance mode of the terminal device is power saving mode, the first condition can be that the graphics rendering time is less than 1 millisecond.

[0082] It should be noted that, in this embodiment, the second condition refers to the condition that the heat dissipation power consumption of the terminal device must meet, which is used to ensure the battery life of the terminal device with good performance under various operating conditions. The heat dissipation power consumption of the terminal device refers to the sum of the energy consumed by each heat dissipation device per unit time when the terminal device dissipates heat through various heat dissipation devices, that is, the total power consumption of each heat dissipation device. This second condition can be that the heat dissipation power consumption of the terminal device is lower than a certain preset power consumption value, which can be flexibly set according to the actual situation.

[0083] For example, the second condition for mapping differs depending on the operating state.

[0084] It should also be noted that, in this embodiment, the calibrated speed setting refers to the speed setting that the air-cooling device should be set to under the premise that the first and second conditions are met, and the calibrated flow rate setting refers to the flow rate setting that the liquid-cooling device should be set to under the premise that the first and second conditions are met. These calibrated speed and flow rate settings can be determined through experiments or actual operating data, aiming to ensure that the equipment achieves both good heat dissipation and maintains a reasonable power consumption level under the current operating conditions.

[0085] It is worth mentioning that, in one feasible implementation, the calibration combination heat dissipation strategy refers to the combination heat dissipation strategy with the lowest heat dissipation power consumption when the operating performance of the terminal device reaches the preset performance standard.

[0086] It should be noted that in this embodiment, the first condition is that the operating performance of the terminal device reaches the preset performance standard, and the second condition is that the heat dissipation and power consumption are minimized when the operating performance of the terminal device reaches the preset performance standard. The preset performance standard is a threshold that must be reached for various performance indicators of the terminal device. The performance indicator can be one or more of the following: processor frequency, network speed, graphics rendering time, frame rate, and data read / write latency.

[0087] This embodiment pre-sets corresponding preset performance standards as first conditions for different operating states of the terminal device. This calibrates the calibrated speed and flow rate levels that minimize heat dissipation power consumption when the terminal device's operating performance reaches the preset performance standards. This results in a calibrated combined heat dissipation strategy matching the terminal device's different operating state information. A dataset is then constructed to train a heat dissipation strategy prediction AI model, resulting in a converged heat dissipation strategy prediction AI model. The converged heat dissipation strategy prediction AI model trained through this embodiment, when executed, predicts that the target combined heat dissipation strategy will enable the terminal device's operating performance to reach the preset performance standards while minimizing heat dissipation power consumption.

[0088] Step S500: Each of the operating state information is used as multiple samples, and the calibration combination heat dissipation strategy matched with each of the operating state information is used as the label corresponding to each sample.

[0089] Step S600: Based on each of the samples and their corresponding labels, train the heat dissipation strategy prediction AI model to obtain a converged heat dissipation strategy prediction AI model.

[0090] This embodiment collects multiple different operating status information of the terminal device under different usage scenarios in advance. This information includes, but is not limited to, operating temperature, operating load, charging status, performance mode, etc. Then, for different operating status information of the terminal device, corresponding first conditions and second conditions are set. Then, based on the first and second conditions corresponding to each operating status information, the calibration speed level and calibration flow rate level that satisfy the first and second conditions corresponding to each operating status information are determined through experiments or actual operating data. Thus, a combined heat dissipation strategy that satisfies the first and second conditions corresponding to each operating status information is designed as a calibration combined heat dissipation strategy matching each operating status information. Then, the operating status information is used as a sample, and the calibration combined heat dissipation strategy matching the operating status information is used as a label to construct the dataset required to train the heat dissipation strategy prediction AI model, so as to train a converged heat dissipation strategy prediction AI model. Finally, through the convergent heat dissipation strategy prediction AI model obtained through training, the target combined heat dissipation strategy is directly predicted based on the current operating status information of the terminal device in practical applications. The air cooling device and liquid cooling device are controlled to perform combined heat dissipation on the terminal device according to the target combined heat dissipation strategy. While ensuring the heat dissipation effect of the terminal device, the heat dissipation power consumption is optimized and unnecessary power waste is reduced. The heat dissipation effect required to ensure the performance of the terminal device is achieved with the least amount of energy consumption.

[0091] Please refer to Figure 3 , Figure 3 This is a flowchart illustrating Embodiment 3 of the terminal heat dissipation method of this application.

[0092] In this embodiment, the same or similar content as in the above embodiments can be referred to the above description, and will not be repeated hereafter.

[0093] In this embodiment, step S200, which predicts the target combined heat dissipation strategy matching the current operating state information based on a converged heat dissipation strategy prediction AI model, may include steps S210 to S230:

[0094] Step S210: Input the current running status information into the converged heat dissipation strategy prediction AI model to obtain the intermediate parameter information output by the heat dissipation strategy prediction AI model;

[0095] It should be noted that, in this embodiment, the intermediate parameter information refers to the information used in the output of the heat dissipation strategy prediction AI model to be further converted into the target combined heat dissipation strategy. Depending on different training methods and model designs, the intermediate parameter information can have different forms and meanings.

[0096] For example, in the heat dissipation strategy prediction AI model training method mentioned in the first embodiment above, which uses running status information as samples and scores as labels, the intermediate parameter information can refer to the scores. In the heat dissipation strategy prediction AI model training method, which uses running status information as samples and the heat generated by the terminal device per unit time as labels, the intermediate parameter information can refer to the heat generated by the terminal device per unit time.

[0097] Step S220: Based on the preset parameter mapping relationship, query the speed range and flow rate range mapped by the intermediate parameter information;

[0098] It should be noted that, in this embodiment, the parameter mapping relationship is the mapping relationship between intermediate parameter information and speed gear and flow rate gear. Each intermediate parameter information corresponds to a speed gear and flow rate gear.

[0099] In this embodiment, during the training phase of the heat dissipation strategy prediction AI model, a mapping relationship between each intermediate parameter and its speed and flow rate is pre-constructed as a parameter mapping relationship. Thus, after the heat dissipation strategy prediction AI model outputs the intermediate parameter information, the mapping relationship can be directly queried to obtain the mapped speed and flow rate.

[0100] Step S230: Determine the target combination heat dissipation strategy that matches the current operating status information based on the speed and flow rate levels mapped by the intermediate parameter information.

[0101] In this embodiment, after querying and obtaining the speed and flow rate levels mapped by the intermediate parameter information, the speed level is directly used as the target speed level and the flow rate level is used as the target flow rate level. Thus, the target speed level and target flow rate level can be directly used as the target combined heat dissipation strategy to match the current operating status information. The duration for which the air-cooling device operates at the target speed level and the duration for which the liquid-cooling device operates at the target flow rate level can be further set to obtain a more detailed and comprehensive combined heat dissipation strategy, which can then be used as the target combined heat dissipation strategy to match the current operating status information.

[0102] Compared to the converged heat dissipation strategy prediction AI model in Embodiment 2 above, which directly outputs the target combined heat dissipation strategy, the converged heat dissipation strategy prediction AI model in this embodiment outputs intermediate parameter information. This has higher versatility, not only for determining the target combined heat dissipation strategy, but also for displaying the mapping data table of the parameter relationship to the user. This gives the user a more intuitive understanding of the current heat dissipation requirements of the terminal device, making it easier for the user to understand the reasons for choosing the target combined heat dissipation strategy. It can also be used in enterprise-related applications. Moreover, this embodiment has stronger compatibility. When new heat dissipation devices or new operating status information are introduced in the future, requiring optimization and updates to the target combined heat dissipation strategy matching different operating status information, only the mapping data table needs to be updated, without retraining the entire model. This greatly simplifies model maintenance, making it more maintainable. It also simplifies model output, allowing the model to focus on generating intermediate parameter information without involving complex multi-output issues, thereby reducing the complexity of the heat dissipation strategy prediction AI model.

[0103] To facilitate understanding of the technical concept or principle of the terminal heat dissipation method of this application in the above embodiments, a specific embodiment is provided:

[0104] This specific embodiment takes a smartphone (i.e., a terminal device, also called a terminal) in a game scenario as an example. The smartphone is equipped with a fan (i.e., an air-cooling device) and micro-pump liquid cooling hardware (i.e., a liquid-cooling device). The smartphone is equipped with a central control system (also called a central control service) for monitoring the system status (i.e., the operating status of the terminal device) and controlling the fan speed and micro-pump flow rate.

[0105] like Figure 4 As shown, this specific embodiment provides different settings for fan speed and micro-pump flow rate (i.e., the air-cooling device has at least two speed settings, and the liquid-cooling device has at least two flow rate settings). For example, the fan speed can be set from 1 to 5, and the micro-pump flow rate provides three different settings: fast, medium, and slow. Different settings correspond to different speed or flow rate ranges. The higher the setting, the faster the fan speed or micro-pump flow rate; the lower the setting, the slower the fan speed or micro-pump flow rate. Users can customize different settings according to their own usage scenarios and the current state of the terminal, thus meeting their own usage habits.

[0106] Based on the above-mentioned gear settings, this specific embodiment also adds an option for intelligent mode (i.e., intelligent heat dissipation mode). Under this option setting, the fan speed and micro-pump flow rate are uniformly controlled by the central control system. The central control system can combine the parameters of different current terminal states (i.e., current operating status information) and user usage habits to perform AI learning and calculate which gear setting is more appropriate (i.e., based on the convergent heat dissipation strategy prediction AI model, predict the target combination heat dissipation strategy matching the current operating status information). It can more intelligently control the fan speed and micro-pump flow rate gears, which can not only ensure terminal heat dissipation but also reduce unnecessary power consumption waste of the terminal.

[0107] like Figure 5 As shown, in this specific embodiment, the terminal heat dissipation process is as follows:

[0108] Step S10: After detecting that the terminal is powered on, start the central control service;

[0109] Step S20: Determine whether to enable smart mode;

[0110] Step S30: Read CPU and GPU load information, identify current charging status, detect user touch screen frequency, identify whether it is a game scene and game type, read temperature sensor parameters, and read user-set performance mode.

[0111] Step S40: Based on the above information, a threshold is calculated using an AI model;

[0112] Step S50: Based on the threshold, set the corresponding fan speed setting and micro-pump flow rate setting.

[0113] In this specific embodiment, upon detecting that the terminal is powered on, the central control service is automatically started, and it is determined whether to enable smart mode. When smart mode is enabled, the central control service reads the CPU and GPU load (i.e., current operating load), identifies the current charging status, detects the user's touch screen frequency (i.e., the screen touch frequency counted within the most recent preset time period), identifies whether it is a game scene and the game type, reads the temperature sensor parameters (i.e., the current operating temperature), and reads the user-set performance mode (i.e., the current performance mode) to monitor the system status (i.e., obtain the current operating status information of the terminal device). This information is then input into the AI ​​model, which calculates a threshold (i.e., inputs the current operating status information into a convergent heat dissipation strategy prediction AI model to obtain heat dissipation...). The intermediate parameter information output by the thermal strategy prediction AI model is used to set the corresponding fan speed level (i.e., target speed level) and micro-pump flow rate level (i.e., target flow rate level) based on the threshold, and to perform combined heat dissipation on the terminal (i.e., based on the preset parameter mapping relationship, the speed level and flow rate level mapped by the intermediate parameter information are obtained, and the target combined heat dissipation strategy matching the current operating status information is determined according to the speed level and flow rate level mapped by the intermediate parameter information. The target combined heat dissipation strategy includes the target speed level and the target flow rate level. The operation of the air cooling device is controlled according to the target speed level, and the operation of the liquid cooling device is controlled according to the target flow rate level).

[0114] It should be noted that in this specific embodiment, AI learning is performed in advance based on the user's application scenario and the terminal's state parameters to establish a user-based hybrid heat dissipation model (i.e., a convergent heat dissipation strategy prediction AI model, also known as an AI model), which is used to intelligently adjust the fan speed and micro-pump flow rate.

[0115] like Figure 6 In this specific embodiment, the central control service periodically reads the current CPU and GPU load of the terminal, identifies the current charging status of the terminal, detects the user's touch screen frequency, identifies whether the user has entered a game scene and the type of game application (a specific embodiment of background application information), reads temperature sensor parameters, reads the performance mode set by the user, and other status parameters.

[0116] In this specific embodiment, the information obtained by the central control service is used to calculate a threshold through a trained AI model. This threshold is then used to determine the appropriate fan speed and micro-pump flow rate settings for the current operating state of the terminal. Based on the calculated threshold, the corresponding fan speed and micro-pump flow rate settings are determined. For example, if it is identified that the user is currently playing a demanding competitive game, the terminal's CPU and GPU loads are high, the screen refresh rate is high, and the device is charging, the AI ​​model can calculate that a higher fan speed and micro-pump flow rate should be set. However, if the terminal is low on battery and not charging, a lower setting will be calculated to avoid excessive power consumption and reduced battery life.

[0117] In this specific embodiment, the CPU and GPU load status is taken as condition S1, the charging status is taken as condition S2, the user touch screen frequency is taken as condition S3, the game scene and game type are taken as condition S4, the temperature sensor parameters are taken as condition S5, and the currently set performance mode is taken as condition S6.

[0118] In this specific embodiment, the AI ​​model algorithm is explained as follows:

[0119] (1) Computation logic:

[0120] By comprehensively calculating conditions s1, s2, s3, s4, s5, and s6, the range of the threshold value is determined.

[0121] If the value is in a low range, such as 0 to 1, then use a low fan speed and micro-pump flow rate.

[0122] If the value is in the middle range, such as 1 to 5, then use the medium fan speed and micro pump flow rate.

[0123] If the value is in a high range, such as 5 to 10, then use a high fan speed and micro-pump flow rate.

[0124] This specific embodiment uses an AI model to fit various scenario conditions and calculate the final specific gear level to be used. The calculation weight of each scenario can be flexibly set according to the actual situation, and a scenario condition is ignored if it is not triggered (for example, if the current terminal is not charging, then condition s2 is not included in the calculation). The scenario conditions calculated in this specific embodiment are dynamic and will be calculated based on multiple state parameters of the current terminal, and are not limited to the scenario conditions listed above.

[0125] In this specific embodiment, if the current terminal overheats severely, triggering the use of high fan speed and micro-pump flow rate, after running for a period of time and the terminal overheating is relieved, this specific embodiment will recalculate which range the current threshold is in. If it is in the low value range, it will automatically use low fan speed and micro-pump flow rate, thereby achieving the effect of intelligent automatic control and avoiding the high power consumption problem caused by always being in the high level.

[0126] (2) AI model algorithm principle:

[0127] In this specific embodiment, the AI ​​model algorithm enables the dynamic combination of various scenario conditions of the terminal (not limited to the six scenario conditions listed above). This specific embodiment can obtain the current terminal-related status parameters by reading the system status node file, listening to the Broadcast data reported by the system, and reading relevant system attribute values.

[0128] In this specific embodiment, relevant data is pre-set into the AI ​​model, which allows the AI ​​model to have initial judgment capabilities, such as:

[0129] 1. When the temperature sensor temperature is greater than 40 degrees Celsius, the AI ​​model judges it as a high temperature; when it is lower than this temperature, it judges it as a low temperature.

[0130] 2. When the touch frequency is greater than 30 touches per minute, the AI ​​model judges it as a high touch rate; otherwise, the AI ​​model judges it as a low touch rate.

[0131] 3. When the terminal is plugged into a fast charger, the AI ​​model judges it as a high-heat scenario; when it is not charging, it makes a judgment based on other scenario conditions.

[0132] 4. When the CPU or GPU load is greater than 50%, the AI ​​model judges it as high load; otherwise, the AI ​​model judges it as low load.

[0133] By using pre-set data, the AI ​​model in this specific embodiment can automatically infer and judge the current heat dissipation of the terminal, and then select an optimal setting based on the currently learned data, thereby determining whether to set the fan speed and micro-pump flow rate to a high or low setting. The AI ​​model in this specific embodiment can be continuously learned and trained by combining different scenario conditions, thereby further improving the recognition accuracy and reasoning ability of the AI ​​model.

[0134] It should be noted that the above specific embodiments are only used to assist in understanding this application and do not constitute a limitation on the terminal heat dissipation method of this application. Any simple modifications based on this technical concept are within the protection scope of this application.

[0135] In addition, please refer to Figure 7 , Figure 7 This is a schematic diagram of the device structure of the hardware operating environment involved in the terminal heat dissipation method in this application embodiment.

[0136] This application also provides a terminal device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, which are executed by the at least one processor to enable the at least one processor to perform the terminal heat dissipation method in the above embodiments.

[0137] The following is for reference. Figure 7 The diagram illustrates a structural schematic of a terminal device suitable for implementing the embodiments of this application. The terminal device in the embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones (e.g., cell phones), laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs (Televisions), desktop computers, or any electronic device capable of performing the above functions. Figure 7 The terminal device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0138] like Figure 7As shown, the terminal device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the terminal device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touchscreen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 1003 including, for example, magnetic tape, hard disk, etc.; and communication devices 1009. Communication device 1009 allows terminal devices to communicate wirelessly or wiredly with other devices to exchange data. Although terminal devices with various systems are shown in the figures, it should be understood that implementation or possession of all the systems shown is not required. More or fewer systems may be implemented alternatively.

[0139] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0140] The terminal device provided in this application, employing the terminal heat dissipation method described in the above embodiments, can solve the technical problem that heat dissipation methods in related technologies are difficult to balance with the device's battery life and performance. Compared with the prior art, the beneficial effects of the terminal device provided in this application are the same as those of the terminal heat dissipation method provided in the above embodiments, and other technical features of this terminal device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0141] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0142] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0143] In addition, this application also provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to perform the steps of the terminal heat dissipation method in the above embodiments.

[0144] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0145] The aforementioned computer-readable storage medium may be included in the terminal device; or it may exist independently and not assembled into the terminal device.

[0146] The aforementioned computer-readable storage medium carries one or more programs. When these programs are executed by a terminal device equipped with an air-cooling device and a liquid-cooling device, the terminal device causes the terminal device to: acquire current operating status information, wherein the current operating status information includes current operating temperature and current operating load; predict a target combined heat dissipation strategy matching the current operating status information based on a convergent heat dissipation strategy prediction AI model, wherein the target combined heat dissipation strategy includes a target speed setting and a target flow rate setting; control the operation of the air-cooling device according to the target speed setting, and control the operation of the liquid-cooling device according to the target flow rate setting.

[0147] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0148] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0149] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0150] The computer-readable storage medium provided in this application stores computer-readable program instructions (i.e., a computer program) for performing the steps of the above-described terminal heat dissipation method, which can solve the technical problem that heat dissipation methods in related technologies are difficult to balance the battery life and performance of devices. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the terminal heat dissipation method provided in the above embodiments, and will not be repeated here.

[0151] Furthermore, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the terminal heat dissipation method as described in the above embodiments.

[0152] The computer program product provided in this application can solve the technical problem that heat dissipation methods in related technologies are difficult to balance with the battery life and performance of devices. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as the beneficial effects of the terminal heat dissipation method provided in the above embodiments, and will not be repeated here.

[0153] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A terminal heat dissipation method, applied to a terminal device equipped with an air-cooling device and a liquid-cooling device, wherein the air-cooling device has at least two speed settings and the liquid-cooling device has at least two flow rate settings, the method comprising: Obtain the current operating status information of the terminal device, wherein the current operating status information includes the current operating temperature and the current operating load; Based on a convergent heat dissipation strategy prediction AI model, a target combined heat dissipation strategy matching the current operating state information is predicted, wherein the target combined heat dissipation strategy includes a target speed level and a target flow rate level. The operation of the air-cooling device is controlled according to the target speed setting, and the operation of the liquid-cooling device is controlled according to the target flow rate setting.

2. The terminal heat dissipation method as described in claim 1, characterized in that, The method further includes: Multiple different operating status information and calibration combination heat dissipation strategies matched with each of the operating status information are obtained. The calibration combination heat dissipation strategy refers to a combination heat dissipation strategy in which the operating performance of the terminal device meets a first condition and the heat dissipation power consumption of the terminal device meets a second condition. The combination heat dissipation strategy includes the calibration speed range of the air cooling device and the calibration flow rate range of the liquid cooling device. Each of the aforementioned operating status information is used as multiple samples, and the calibration combination heat dissipation strategy matched with each of the aforementioned operating status information is used as the label corresponding to each of the aforementioned samples. Based on each of the samples and their corresponding labels, the heat dissipation strategy prediction AI model is trained to obtain a converged heat dissipation strategy prediction AI model.

3. The terminal heat dissipation method as described in claim 2, characterized in that, The calibration combination heat dissipation strategy refers to the combination heat dissipation strategy with the lowest heat dissipation power consumption when the operating performance of the terminal device reaches the preset performance standard.

4. The terminal heat dissipation method as described in claim 1, characterized in that, Based on a convergent heat dissipation strategy prediction AI model, the target combination of heat dissipation strategies matching the current operating state information are predicted, including: The current operating status information is input into the converged heat dissipation strategy prediction AI model to obtain the intermediate parameter information output by the heat dissipation strategy prediction AI model. Based on the preset parameter mapping relationship, the speed range and flow rate range mapped by the intermediate parameter information are obtained by querying. Based on the speed and flow rate levels mapped by the intermediate parameter information, a target combination heat dissipation strategy matching the current operating status information is determined.

5. The terminal heat dissipation method as described in claim 1, characterized in that, The current operating status information also includes the current charging status and the current performance mode. The charging state includes fast charging, slow charging and no charging. The performance mode includes a first performance mode and a second performance mode, with the performance consumption of the first performance mode being greater than that of the second performance mode.

6. The terminal heat dissipation method as described in claim 5, characterized in that, The current operating status information also includes the screen touch frequency statistics within the most recent preset time period, as well as the background application information currently running in the background of the terminal device.

7. The terminal heat dissipation method according to any one of claims 1 to 6, characterized in that, The method further includes: When the intelligent heat dissipation mode of the terminal device is detected to be activated, the steps of controlling the operation of the air-cooling device according to the target speed level and controlling the operation of the liquid-cooling device according to the target flow rate level are triggered.

8. A terminal device, characterized in that, include: A memory, a processor, and a terminal cooling program stored on the memory and executable on the processor, wherein the terminal cooling program, when executed by the processor, implements the steps of the terminal cooling method as described in any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a terminal heat dissipation program, which, when executed by a processor, implements the steps of the terminal heat dissipation method as described in any one of claims 1 to 7.

10. A computer program product, characterized in that, The computer program product includes a terminal heat dissipation program, which, when executed by a processor, implements the steps of the terminal heat dissipation method as described in any one of claims 1 to 7.

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