Control methods, devices and electronic equipment

Abstract

This application discloses a control method, apparatus, and electronic device, belonging to the field of electronic device technology. The method includes: when the electronic device is running a game application and at least one other application, acquiring device temperature change information and game application performance information within a fixed monitoring period, where k is a natural number; determining a (k+1)th temperature control strategy for a (k+1)th monitoring period based on the device temperature change information and performance information acquired within the k-th monitoring period; and controlling the operating parameters of the processor of the electronic device according to the (k+1)th temperature control strategy within the (k+1)th monitoring period.

Description

Technical Field

[0001] This application belongs to the field of electronic equipment technology, specifically relating to a control method, device, and electronic equipment. Background Technology

[0002] With the rapid development of mobile electronic devices such as smartphones and tablets, users are placing higher demands on the performance and temperature control of these devices under high-load scenarios. Especially in gaming scenarios, users often run games in the foreground while simultaneously running auxiliary applications such as video playback, instant messaging, and live streaming in floating or small window modes, creating highly complex "game-on-demand scenarios." In such scenarios, the system-on-chip (SoC) of the electronic device bears the combined load from multiple applications, generating a significant amount of heat, posing challenges to maintaining stable performance and controlling temperature rise. Therefore, how to balance device temperature control and gaming performance in complex gaming scenarios is an urgent problem to be solved. Summary of the Invention

[0003] The purpose of this application is to provide a control method, device, and electronic device that can balance device temperature rise control and game performance in complex game scenarios.

[0004] In a first aspect, embodiments of this application provide a control method, the method comprising: When an electronic device is running a game application and at least one other application, the device temperature change information and the performance information of the game application are obtained within the k-th monitoring period, with a fixed duration as the monitoring period; where k is a natural number. Based on the equipment temperature change information and performance information obtained during the kth monitoring period, a k+1 temperature control strategy for the k+1th monitoring period is determined. During the (k+1)th monitoring period, the operating parameters of the processor of the electronic device are controlled according to the (k+1)th temperature control strategy.

[0005] Secondly, embodiments of this application provide a control device, the device comprising: The acquisition module is used to acquire device temperature change information and game application performance information within a fixed monitoring period (k-th monitoring period) when the electronic device is running a game application and at least one other application; where k is a natural number. The determination module is used to determine the (k+1)th temperature control strategy for the (k+1)th monitoring period based on the equipment temperature change information and performance information obtained during the (k)th monitoring period. The control module is used to control the operating parameters of the processor of the electronic device according to the (k+1)th temperature control strategy during the (k+1)th monitoring cycle.

[0006] Thirdly, embodiments of this application provide an electronic device, which includes a processor and a memory. The memory stores programs or instructions that can run on the processor, and when the programs or instructions are executed by the processor, they implement the steps of the control method as described in the first aspect.

[0007] Fourthly, embodiments of this application provide a computer-readable storage medium storing a program or instructions that, when executed by a processor, implement the steps of the control method as described in the first aspect.

[0008] Fifthly, embodiments of this application provide a chip, the chip including a processor and a communication interface, the communication interface being coupled to the processor, the processor being used to run programs or instructions to implement the control method as described in the first aspect.

[0009] In a sixth aspect, embodiments of this application provide a computer program product stored in a storage medium, which is executed by at least one processor to implement the control method as described in the first aspect.

[0010] In this embodiment of the application, when the electronic device is running a game application and at least one other application, the device temperature change information and the performance information of the game application within the k-th monitoring period are obtained with a fixed duration as the monitoring period; where k is a natural number; based on the device temperature change information and performance information obtained within the k-th monitoring period, a k+1 temperature control strategy for the k+1-th monitoring period is determined; within the k+1-th monitoring period, the operating parameters of the processor of the electronic device are controlled according to the k+1 temperature control strategy.

[0011] As can be seen, in this embodiment of the application, for the combined gaming scenario of an electronic device running a game and at least one other application, the device temperature change information and game performance information are collected and fused at a fixed monitoring cycle, load change characteristics are identified, and the temperature control strategy for the next cycle is dynamically adjusted in a forward-looking manner based on the load characteristics of the previous cycle. This achieves a real-time balance between temperature safety and game smoothness, and a fine balance between performance release and temperature rise control. Thus, in the combined gaming scenario, both device temperature control and game performance are taken into account, thereby improving the user experience. Attached Figure Description

[0012] Figure 1 This is one of the flowcharts of a control method provided in some embodiments of this application; Figure 2This is a second flowchart of a control method provided in some embodiments of this application; Figure 3 This is a structural block diagram of a control device provided in some embodiments of this application; Figure 4 This is a schematic diagram of the structure of an electronic device provided in some embodiments of this application; Figure 5 This is a schematic diagram of the hardware structure of an electronic device that implements the various embodiments of this application. Detailed Implementation

[0013] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0014] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such terms can be used interchangeably where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0015] The control method provided in the embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0016] It should be noted that the control method provided in this application embodiment is applicable to game composite scenarios. A game composite scenario refers to a scenario in which a game application runs in the foreground of an electronic device, while at least one other application (such as a video playback application or an instant messaging application) is superimposed on the game screen and is in an active state through a non-full-screen window such as a floating window, a small window, or a picture-in-picture.

[0017] Figure 1 This is one of the flowcharts of a control method provided in some embodiments of this application, such as... Figure 1 As shown, the method may include the following steps: step 101, step 102 and step 103.

[0018] In step 101, when the electronic device is running a game application and at least one other application, the device temperature change information and the performance information of the game application are obtained within the k-th monitoring period with a fixed duration; where k is a natural number.

[0019] In this embodiment, when the electronic device enters a game scene, a preset fixed duration (e.g., 5 seconds) is used as the monitoring cycle to periodically acquire device temperature change information and game application performance information within each monitoring cycle. The device temperature change information is a quantitative indicator reflecting the thermal dynamic trend of the device within the monitoring cycle. The game application performance information is a quantitative indicator reflecting the rendering smoothness of the game application within the monitoring cycle.

[0020] In this embodiment, the design of iteratively acquiring information with a fixed monitoring cycle has the following synergistic effects in multiple dimensions: First, at the physical and system level, considering that the temperature rise and fall of electronic devices is not instantaneous, but determined by thermal capacity and thermal resistance, there is an inherent thermal inertia or thermal time constant. For example, it usually takes tens of seconds to several minutes for a smartphone to rise from room temperature to a high-temperature equilibrium point. In this embodiment, the design of iteratively acquiring information with a fixed monitoring cycle accurately matches the inherent thermal inertia time constant of electronic devices. By setting the monitoring cycle to the same order of magnitude as the device's thermal response time (e.g., several seconds), high-frequency signal fluctuations caused by sensor noise or instantaneous load can be effectively filtered out, thereby stably capturing the temperature change rate and performance statistics that reflect the true load trend. This provides a reliable data basis for control decisions and avoids strategy oscillations caused by data noise.

[0021] Secondly, at the level of control algorithm implementation, periodic sampling constructs a stable discrete-time control system, providing the necessary conditions for the reliable application of subsequent classical control algorithms such as proportional-integral-derivative (PID): the fixed time step allows the discrete accumulation of the error integral term and the differential calculation of the derivative term to be carried out accurately and stably, thereby transforming the control theory of the continuous domain into an iterative algorithm that can run efficiently and stably on the device processor, ensuring the convergence and robustness of the control process.

[0022] Thirdly, at the level of engineering resource scheduling, by transforming high-frequency continuous monitoring into periodic batch processing tasks, electronic devices are only woken up at the end of each cycle to perform centralized calculations and policy updates, which reduces the average computing load and power consumption. This ensures timely management of the device's thermal state and performance experience (a delay of several seconds is acceptable in thermal control scenarios) while reducing interference with the performance of foreground applications and the device's battery life.

[0023] Fourth, at the level of intelligent decision-making logic, sufficient state information (such as trends rather than single points) is accumulated within each complete monitoring cycle, and a comprehensive judgment is made based on the overall statistical characteristics within the monitoring cycle (such as average frame drop rate and temperature change trend). This enables intelligent differentiation between instantaneous disturbances and continuous trends, allowing electronic devices to formulate robust and forward-looking temperature control strategies for the next cycle, rather than making inefficient reflective responses to single events, thereby improving the intelligence level and adaptability of temperature control management.

[0024] In this embodiment, by acquiring the device temperature change information of the electronic device, the electronic device can transform from merely "responding to whether the current temperature is too high" to "predicting the risk of temperature rise and intervening in advance," intelligently distinguishing between environmental fluctuations and dangerous temperature rises to avoid false triggering; at the same time, it provides standardized input information that can be compared collaboratively for multi-objective control such as temperature change trends and frame drop rate, thereby implementing differentiated regulation, realizing the transformation from passive response to forward-looking intelligent balance, and ultimately optimizing the game performance experience while ensuring the safety of device temperature rise.

[0025] In this embodiment, by acquiring the performance information of the game application, the transformation from monitoring hardware parameters to measuring user experience is realized, making the control target strongly correlated with the user's subjective feelings.

[0026] In this embodiment, by synchronously collecting and fusing temperature change information reflecting the risk of continuous heat generation with performance information reflecting instantaneous experience impairment, the spatiotemporal characteristics of the composite load can be decoupled, providing accurate input data for subsequent intelligent decision-making, thereby ensuring that the device's temperature control strategy always simultaneously considers both the safety of device temperature rise and the smoothness of user experience.

[0027] In step 102, based on the equipment temperature change information and performance information obtained during the kth monitoring period, the k+1th temperature control strategy for the k+1th monitoring period is determined.

[0028] In this embodiment, the (k+1)th temperature control strategy is a set of processor control rules that takes effect within the (k+1)th monitoring cycle. It is typically represented as a mapping table or function between temperature and processor operating parameter limits. The generation mechanism of this strategy is based on the feedforward-feedback composite control principle: the electronic device predicts the operating conditions of the next cycle and generates a corresponding strategy based on the load trend of the current monitoring cycle, rather than simply responding after the temperature exceeds the limit. This strategy serves as a stable control benchmark within each monitoring cycle, providing the underlying scheduler with a clear and consistent execution objective.

[0029] For example, the temperature control strategy is the mapping relationship between temperature and operating parameter limit values ​​shown in Table 1 below. The temperature control objects are the CPU and GPU, and the operating parameters include the maximum operating frequency of the CPU and the maximum operating frequency of the GPU. This is a discretized implementation that predefines the continuous temperature control logic into multiple levels, which has the advantages of high execution efficiency and easy configuration and verification.

[0030]

[0031] Table 1 In step 103, during the (k+1)th monitoring period, the operating parameters of the processor of the electronic device are controlled according to the (k+1)th temperature control strategy.

[0032] In this application embodiment, the processor includes, but is not limited to, CPU and GPU.

[0033] In this application embodiment, the operating parameters include, but are not limited to, manageable parameters such as maximum operating frequency, operating voltage, and core scheduling strategy.

[0034] In this embodiment, during the (k+1)th monitoring cycle, the electronic device adjusts the operating parameters of its processor (such as CPU or GPU) according to the (k+1)th temperature control strategy, for example, by limiting its maximum operating frequency to constrain performance release. After the strategy is executed, it will change the thermal behavior and performance output of the electronic device, and these changes will affect the data collected in step 101 of the next monitoring cycle, thus forming a complete adaptive iterative process of "perception (step 101) → decision (step 102) → execution (step 103)".

[0035] For example, the (k+1)th temperature control strategy is shown in Table 2 below, which defines a lookup table of the correspondence between device temperature and the maximum allowed CPU operating frequency.

[0036]

[0037] Table 2 In this embodiment, the electronic device adjusts the processor's operating parameters through a progressive control strategy that iterates at fixed intervals and fuses multi-source information. This ensures a smooth transition in the processor's operating state, making the temperature control intervention imperceptible to the user. Because the aforementioned control mechanism continuously optimizes itself, it can dynamically maintain the device at the optimal balance between smooth performance and temperature control safety under long-term high loads. This improves the stability and comfort of the gaming experience and resolves the contradiction between device heat generation and gaming performance in complex gaming scenarios.

[0038] As can be seen from the above embodiments, in this embodiment, for the combined gaming scenario of an electronic device running a game and at least one other application, the device temperature change information and game performance information are collected and fused at a fixed monitoring cycle to identify load change characteristics. Based on the load characteristics of the previous cycle, the temperature control strategy for the next cycle is dynamically adjusted in a forward-looking manner. This achieves a real-time balance between temperature safety and game smoothness, and a fine balance between performance release and temperature rise control. Thus, in the combined gaming scenario, both device temperature control and game performance are taken into account, thereby improving the user experience.

[0039] In some embodiments provided in this application, the device temperature change information is a temperature fluctuation factor. Accordingly, step 101 above may specifically include the following steps: step 1011 and step 1012. In step 1011, the device temperature at the start and end of the kth monitoring cycle is obtained; based on the device temperature at the start and end of the kth monitoring cycle, the temperature change rate within the kth monitoring cycle is calculated.

[0040] In this embodiment, discrete temperature sampling values ​​are converted into a temperature change rate that reflects the thermal dynamic trend of the equipment, thereby realizing the conversion from static temperature points to dynamic temperature slopes.

[0041] In this embodiment, device temperature refers to the temperature reading collected by a thermistor integrated at a specific location on the motherboard of an electronic device (typically near a system-on-a-chip, power management unit, or battery). This reading is used to characterize the real-time thermal state of critical areas of the device. For example, the start time of the monitoring period is denoted as t. start The end time of the monitoring period is denoted as t. end The monitoring period is denoted as T. window The equipment temperature collected at the start of the monitoring cycle is recorded as T. start The equipment temperature collected at the end of the monitoring cycle is recorded as T. end T start= 40.5℃, T end =42.3℃.

[0042] In this embodiment, the temperature change rate, denoted as ΔT / Δt, refers to the average rate of change of the equipment temperature within a unit monitoring period. The calculation formula is: ΔT / Δt = (T end -T start ) / (t end -t start ), where (t end -t start The monitoring period T is a fixed duration. windowA positive rate of temperature change indicates that the equipment is in a state of heat accumulation where heat generation exceeds heat dissipation, meaning the equipment is heating up. A negative rate of temperature change indicates that the equipment is in a cooling state dominated by heat dissipation, meaning the equipment is cooling down. When the rate of temperature change approaches zero, it indicates that the equipment is approaching thermal equilibrium. For example, if T... window =5 seconds, T start= 40.5℃, T end =42.3℃, then ΔT / Δt=(42.3-40.5) / 5=+0.36℃ / second, which means that the equipment is heating up at an average rate of 0.36℃ per second within 5 seconds.

[0043] In this embodiment, temperature change is represented as a concise scalar rate, providing a directly calculable trend input for subsequent control algorithms, which contains more forward-looking information than simply comparing absolute temperature values. By calculating the average rate of change over a time window, high-frequency noise caused by minute sensor fluctuations or instantaneous measurement errors can be effectively smoothed, improving data stability.

[0044] In step 1012, the temperature change rate is nonlinearly standardized to obtain a standardized temperature fluctuation factor. The larger the positive value of the temperature change rate, the closer the output value of the temperature fluctuation factor is to 1; the larger the absolute value of the negative value of the temperature change rate, the closer the output value of the temperature fluctuation factor is to -1; when the absolute value of the temperature change rate is close to zero, the output value of the temperature fluctuation factor is close to zero.

[0045] In this embodiment, a temperature fluctuation factor is generated by nonlinearly standardizing the linear temperature change rate, with its value range limited to the [-1, 1] interval, and capable of characterizing the temperature rise risk level. This temperature fluctuation factor can significantly amplify signals of dangerous trends such as rapid heating or cooling, while effectively suppressing normal small fluctuations caused by environmental or measurement noise, thereby improving the accuracy of the equipment's judgment on the timing of temperature control intervention.

[0046] In this embodiment, the rate of temperature change can be processed using a specific nonlinear mapping function, such as the sigmoid function, to transform it from a linear value into a standardized output with saturation characteristics. This function maps the input to a bounded interval such as [-1, 1] and possesses the characteristics of smooth response to small input changes and significantly enhanced response to large input changes, thereby achieving input... The nonlinear differential response of the output relationship.

[0047] For example, the Sigmoid function is used according to the following formula (1): (1) Where e is the natural exponential function.

[0048] The temperature fluctuation factor obtained after the above nonlinear standardization process exhibits an intelligent saturation correspondence between its value and the temperature change trend: when the equipment temperature shows a significant downward trend, the value of the temperature fluctuation factor approaches [value missing]. 1. When the equipment temperature rises rapidly, the temperature fluctuation factor approaches 1; while when the equipment temperature changes slightly, the temperature fluctuation factor approaches 0. This mapping relationship can effectively distinguish between normal environmental fluctuations and abnormal rapid temperature rises: the former only causes a smooth output response, which is conducive to maintaining strategy stability and avoiding unnecessary control oscillations; the latter triggers a sensitive and rapidly saturating response, significantly amplifying the control signal, thereby initiating timely temperature control intervention to prevent overheating risks. Therefore, when the factor approaches 1, it indicates that early intervention is needed to suppress the temperature rise, while when it approaches 0, it indicates that the current state is stable and the strategy can continue.

[0049] For example, temperature sampling values ​​at the start and end of the monitoring cycle are collected by a thermistor located near the motherboard system-on-a-chip, and the results are calculated according to the formula ΔT / Δt=(T end -T start ) / T window The rate of temperature change within the specified period is calculated. Then, a nonlinear normalization function (e.g., the sigmoid function) is used to map this rate of change to the interval [-1, 1], yielding the corresponding temperature fluctuation factor. This processing method enables electronic devices not only to sense the current absolute temperature but also to provide risk warnings based on changing trends. For example, when the input rate of temperature change ΔT / Δt is +0.1℃ / s (slight temperature rise), the output factor is approximately +0.1; when the input rate of temperature change reaches +1.0℃ / s (rapid temperature rise), the output factor rises to approximately +0.76, showing a significant amplification and saturation trend; when the input rate of temperature change is -0.8℃ / s (rapid temperature drop), the output factor is approximately -0.66. Thus, this factor intuitively and quantitatively characterizes the potential risk level of temperature changes in a nonlinear manner.

[0050] As can be seen, in this embodiment, by mapping the linear temperature change rate to a temperature fluctuation factor within the interval [-1, 1] through nonlinear normalization, intelligent classification of temperature rise risk is achieved, significantly enhancing the response signal to dangerous trends such as rapid temperature rise, while suppressing interference caused by normal environmental fluctuations, thereby improving the accuracy of the device's judgment on the timing of emergency intervention. Furthermore, this normalized output provides a unified mathematical scale for collaborative weighted decision-making with similar normalized indicators such as frame drop rate, enabling the device to comprehensively balance temperature rise risk and performance requirements within a coordinated framework.

[0051] It should be noted that the above-mentioned equipment temperature change information is not limited to temperature fluctuation factors, but may also include raw temperature sequences or temperature change rates, etc.; wherein, the raw temperature sequence is a series of equipment temperature sampling values ​​[T1, T2, T3, ..., T] collected at fixed intervals (e.g., per second) within the monitoring period. n These typically come from multiple thermal sensors on the motherboard, especially those near key heat sources such as the SoC, charging IC, and battery, which can provide the most basic temperature field data. This application will not elaborate further on this aspect in its embodiments.

[0052] In some embodiments provided in this application, the performance information is the frame drop rate. Accordingly, step 101 above may specifically include the following steps: step 1013 and step 1014. In step 1013, the frame rendering time, frame display synthesis time, and vertical synchronization signal period of the game application within the k-th monitoring period are obtained.

[0053] In this embodiment of the application, raw timing data for quantifying performance is collected from key stages of the graphics rendering pipeline, providing an accurate input benchmark for subsequent frame drop determination.

[0054] In this embodiment, frame rendering time is the total time consumed by a game application or game engine to generate a complete frame of screen content by performing all logical calculations, resource preparation, vertex processing, pixel shading, and other operations on the central processing unit and graphics processing unit. For example, it is the time interval from when the application layer calls the drawing command until all the graphics data of that frame is submitted to the system graphics buffer (such as GraphicBuffer), for example, 15 milliseconds.

[0055] In this embodiment, the frame display compositing time is the time consumed by the system display compositing service (such as SurfaceFlinger in Android system, i.e., the surface compositor) to blend, overlay, and convert the game screen layer of the current frame with other possible layers (such as floating windows, status bars, and navigation bars), and finally send it to the display controller for scanning and output. For example, the time interval from when the compositor starts processing the frame buffer submitted by the game to when it completes the compositing of all layers and is ready to send it for display is, for example, 5 milliseconds.

[0056] In this embodiment, the vertical synchronization signal period is a fixed time interval for the display hardware (screen) to refresh the image, determined by the screen's refresh rate. It defines the theoretical maximum available time window for each frame to be displayed on the screen from start to finish. For example, for a screen with a refresh rate of 60Hz, the vertical synchronization signal period is 16.67 milliseconds.

[0057] In this embodiment, by monitoring the entire graphics pipeline from application rendering to system compositing across the entire link, all potential bottlenecks causing frame latency can be fully captured, avoiding missed performance issues due to missing monitoring links. At the same time, by obtaining the frame rendering time and frame display compositing time, it is possible to initially distinguish at the data level whether the main source of performance problems is the application's own excessive computing load or the additional overhead caused by multi-task compositing at the system level, thus providing key data for subsequent precise resource scheduling and temperature control strategy adjustments.

[0058] In step 1014, if the frame rendering time exceeds the vertical synchronization signal period or the frame display synthesis time exceeds the vertical synchronization signal period, the number of frames dropped due to rendering timeout or synthesis timeout in the k-th monitoring period and the theoretical total number of display frames corresponding to the k-th monitoring period are counted; based on the number of dropped frames and the theoretical total number of display frames, the frame drop rate of the game application in the k-th monitoring period is calculated.

[0059] In this embodiment of the application, based on the collected accurate time-consuming data, by defining clear timeout judgment rules, continuous time-consuming information is transformed into discrete frame-dropping events, and finally a standardized performance index, namely the frame-dropping rate, is calculated.

[0060] In this embodiment, for each frame, if the frame rendering time or the frame display and compositing time is greater than the vertical synchronization signal period, then the frame is determined to be a "dropped frame". The principle is that the display refreshes at a fixed rhythm. If the complete preparation time of a frame (whether in the rendering or compositing stage) exceeds the maximum time the screen has to wait for it, then the frame will not be displayed on time, causing visual stuttering or frame skipping.

[0061] In this embodiment, the number of dropped frames refers to the total number of frames that are determined to be dropped according to the above rules within a given k-th monitoring period. For example, in a 5-second monitoring period (theoretically 300 frames), if 45 frames are marked as dropped due to rendering or compositing timeouts, then the number of dropped frames is 45.

[0062] In this embodiment, the theoretical total number of frames displayed refers to the maximum number of frames that can be perfectly displayed under the current monitoring period and fixed screen refresh rate. The calculation formula is: Theoretical total number of frames displayed = Monitoring period duration / Vertical synchronization signal period. For example, if the monitoring period is 5 seconds and the vertical synchronization signal period is 16.67 milliseconds, then the theoretical total number of frames is 5000 milliseconds / 16.67 milliseconds ≈ 300 frames.

[0063] In this embodiment, the frame drop rate is the ratio of the number of dropped frames to the theoretical total number of displayed frames. The calculation formula is: Frame Drop Rate = (Number of Dropped Frames / Theoretical Total Number of Displayed Frames) × 100%. This value is a normalized scalar ranging from [0, 100%], which can directly quantify the user's subjective perception of game stuttering. Since the frame drop rate is decoupled from specific hardware performance and game content complexity, it characterizes the achievement of the preset smoothness target under the current device load. By monitoring this indicator, electronic devices can directly identify performance bottlenecks from the user experience perspective, which is more accurate and intuitive than simply monitoring low-level resource parameters such as CPU / GPU processor utilization.

[0064] As can be seen, in this embodiment, by directly converting the underlying frame rendering and compositing time into a user-perceptible frame drop rate metric, a strong correlation between technical data and user subjective experience is achieved, ensuring a high degree of consistency between the device's temperature control target and user experience target. The calculated frame drop rate, as a standardized percentage value, provides a mathematical basis and fairness for subsequent weighted fusion and PID control with normalized parameters such as temperature fluctuation factors. Combining the separately collected rendering and compositing time data, the frame drop rate can be further used for precise attribution: if frame drops are mainly due to rendering timeouts, it points to application-layer computing power requirements; if they are mainly due to compositing timeouts, it indicates system-layer multi-task load, providing direction for refined resource scheduling. Simultaneously, the frame drop rate quantifies the degree of performance loss as a clear percentage, providing a precise basis for the device to judge the intervention intensity, thereby avoiding over-response or under-response during the control process and achieving a precise and appropriate balance between performance and temperature control.

[0065] It should be noted that the above performance information is not limited to frame drop rate, but may also include raw rendering pipeline time data; wherein, the rendering pipeline time data is used to provide raw timing data for each stage of the rendering pipeline, and is the basis for determining the location of performance bottlenecks, including but not limited to: frame rendering time, frame display composition time, vertical synchronization signal period, etc., which will not be elaborated further in this application embodiment.

[0066] Figure 2 This is a second flowchart of a control method provided in some embodiments of this application, such as... Figure 2 As shown, the method may include the following steps: step 201, step 202, step 203 and step 204.

[0067] In step 201, when the electronic device is running a game application and at least one other application, the device temperature change information and the performance information of the game application are obtained within the k-th monitoring period with a fixed duration; where k is a natural number.

[0068] The content of step 201 in this embodiment of the application is the same as... Figure 1The content of step 101 in the illustrated embodiment is similar and will not be repeated here.

[0069] In step 202, based on the equipment temperature change information and performance information obtained during the kth monitoring period, the adjustment amount of the kth temperature control strategy corresponding to the kth monitoring period is determined; wherein, the adjustment amount of the kth temperature control strategy is used to indicate the direction and magnitude of the adjustment of the kth temperature control strategy that is effective during the kth monitoring period.

[0070] In this embodiment, the k-th temperature control strategy is defined temporally as a set of temperature control rules that are continuously effective within the k-th monitoring period. The electronic device adjusts the processor's operating parameters according to this set of rules within the k-th period. Functionally, it is a set of mapping relationships between the device temperature and the maximum allowable processor operating parameters, constituting the performance temperature safety regulations that the electronic device must comply with within the k-th monitoring period. In terms of dynamic attributes, it is a state in an iterative evolution sequence, not static and unchanging, but rather obtained by adjusting the strategy of the previous period (k-1) according to the state at that time, and will also serve as the basis for generating the strategy of the next period (k+1).

[0071] In this embodiment, the k-th temperature control strategy adjustment amount is a scalar value used to quantify the direction and magnitude of adjustment required for the currently effective temperature control strategy (k-th temperature control strategy). The direction is represented by the sign of the adjustment amount: a positive value indicates that the strategy should be "relaxed" (e.g., increasing frequency limits) to improve performance; a negative value indicates that the strategy should be "tightened" (e.g., decreasing frequency limits) to strengthen temperature control. The magnitude is represented by the absolute value of the adjustment amount; the larger the absolute value, the greater the required adjustment. For example, an adjustment amount of +0.05 indicates a suggestion to increase all current frequency limits by 5%; an adjustment amount of -0.12 indicates a suggestion to decrease them by 12%.

[0072] In this embodiment, multi-dimensional sensing information is mapped to a one-dimensional adjustment quantity to achieve a gradual evolution of the temperature control strategy. This adjustment quantity, as a relative measure of the adjustment direction and magnitude, transforms the generation of the (k+1)th temperature control strategy from direct replacement to a gradual revision of the kth strategy, thereby maintaining the continuity of the strategy sequence and the smoothness of the user experience, and avoiding performance or temperature control abrupt changes caused by sudden strategy shifts. This design simplifies the multi-objective decision-making problem into the calculation and optimization of a single adjustment quantity, and provides constraint nodes for the safe limiting of the adjustment magnitude and smoothing filtering, ensuring both the device's adaptive capability and the robustness and stability of the control.

[0073] In step 203, the k-th temperature control strategy is adjusted according to the k-th temperature control strategy adjustment amount to obtain the k+1-th temperature control strategy for the k+1-th monitoring cycle.

[0074] In this embodiment of the application, the adjustment amount y is based on the k-th temperature control strategy.k The currently effective k-th temperature control strategy (usually represented as a temperature-to-processor maximum operating frequency mapping table) is globally revised to generate the k+1-th temperature control strategy for the next monitoring cycle.

[0075] In this embodiment, the (k+1)th temperature control strategy is an updated set of temperature control rules that will take effect during the (k+1)th monitoring period, generated based on the kth temperature control strategy after adjustments to its corresponding adjustment amount. This new strategy is a continuous and smooth evolution of the original strategy based on its existing structure, rather than a completely new strategy unrelated to it. All parameters are adjusted synchronously and progressively along the same baseline.

[0076] In some embodiments, where each temperature control strategy records the mapping relationship between the device temperature and the limit value of the processor operating parameters, the above step 203 may specifically include the following steps: Step 2031; In step 2031, the adjustment amount of the k-th temperature control strategy is converted into an adjustment coefficient for the mapping relationship; based on the adjustment coefficient, the limit value of the working parameter in the k-th temperature control strategy is scaled to obtain the k+1-th temperature control strategy for the k+1-th monitoring cycle.

[0077] In this embodiment, the adjustment amount can be directly used as a scaling factor to uniformly multiply the limit values ​​corresponding to each temperature threshold in the strategy table by (1 + adjustment amount) to achieve overall synchronous updates.

[0078] For example, if the maximum CPU operating frequency limit corresponding to 44℃ in the original temperature control strategy is 2.4GHz and the adjustment amount is +0.05, then in the new temperature control strategy, this value is adjusted to 2.4GHz×(1+0.05)=2.52GHz, and the other temperature levels are revised by the same proportion.

[0079] In this embodiment of the application, by using this global synchronous scaling method, the overall shape of the mapping relationship is kept stable while the strategy iterative evolution is realized, effectively avoiding performance bottlenecks or temperature control blind spots that may be introduced due to local parameter misalignment.

[0080] In some embodiments, the adjustment amount of the k-th temperature control strategy can be mapped to the adjustment range of a specific working parameter limit value, and the working parameter limit values ​​corresponding to each temperature threshold in the strategy table can be uniformly adjusted according to the range, thereby achieving overall synchronous update of the strategy.

[0081] For example, if the adjustment amount is 0.08 can be mapped to the frequency adjustment amplitude. 200MHz. Assuming the maximum CPU operating frequency limits for each temperature range in the original strategy table were: 2.8GHz for 40℃, 2.4GHz for 44℃, and 2.0GHz for 48℃, after a unified adjustment, the corresponding limits in the new strategy table will be updated to 2.6GHz, 2.2GHz, and 1.8GHz, respectively.

[0082] In this embodiment, the overall translation of the strategy structure along the vertical axis is maintained, ensuring that the relative relationship of the performance limits at each temperature point remains unchanged. This maintains the global consistency of the temperature control response and avoids local performance mismatch that may be caused by differences in the adjustment ratio of different gears.

[0083] In this embodiment, the new temperature control strategy is not generated independently, but is obtained by incrementally updating the existing strategy, thereby ensuring the continuity and predictability of temperature control behavior and avoiding inconsistent jumps in device performance.

[0084] In step 204, during the (k+1)th monitoring cycle, the operating parameters of the processor of the electronic device are controlled according to the (k+1)th temperature control strategy.

[0085] The content of step 204 in this embodiment of the application is the same as... Figure 1 The content of step 103 in the illustrated embodiment is similar and will not be repeated here.

[0086] As can be seen from the above embodiments, in this embodiment, a temperature control strategy for the (k+1)th monitoring cycle is generated based on the state data of the kth monitoring cycle, realizing proactive management of processor resources. The state feedback generated after the new strategy is executed is re-inputted into the decision-making process, forming a closed-loop control. By adjusting the continuity between the amount and the strategy generation, the processor performance adapts to the dynamic load in a gradual manner, avoiding performance fluctuations or thermal anomalies caused by sudden changes in the strategy.

[0087] In some embodiments provided in this application, the control method provided is... Figure 2 Based on the embodiment shown, step 200 may also be included: generating an effective temperature control strategy for the first monitoring cycle; The above step 200 may specifically include the following steps: step 2001, step 2002, step 2003 and step 2004; In step 2001, the type of game application is determined.

[0088] In this embodiment, by identifying the type of game application, differentiated initial temperature control management strategies are matched for different types of game applications. Specifically, based on the processor requirements of the game application and the user's expected preferences for performance / temperature control, the game applications are classified, and different temperature control starting points, ranging from aggressive to conservative, are configured for high-performance, balanced, and low-performance game applications. This provides an initial configuration that is closer to the scenario requirements before the adaptive adjustment cycle starts, achieving a personalized and precise initial performance and temperature control balance, effectively shortening the convergence time for the device to reach its optimal state and improving the initial user experience.

[0089] For example, game applications can be categorized as follows: high-performance demand type, such as first-person shooter (FPS) and multiplayer online battle arena (MOBA) games, which are highly sensitive to frame rate stability and touch latency, and users can usually accept a moderate temperature rise in exchange for an absolutely smooth experience; balanced demand type, such as open-world role-playing games (RPGs), which require both continuous and stable performance to ensure smooth exploration, and temperature control to avoid performance degradation due to overheating during long-term operation; and low-performance demand type, such as casual card games and turn-based strategy games, which have lower requirements for instantaneous peak performance, and users pay more attention to the device's battery life and the low temperature feel when holding it.

[0090] In this embodiment, the type of game application can be determined by reading the game application package name and matching it with a preset game package name-type mapping whitelist.

[0091] In this embodiment, by identifying the game type to achieve scenario-based initial strategy positioning, the device is provided with prior knowledge to understand the current load characteristics, thereby avoiding starting with a completely general and conservative temperature control strategy and effectively shortening the convergence cycle of adaptive adjustment. Simultaneously, this mechanism sets differentiated and personalized starting points for game application types with different performance requirements, enabling the device to approach the balance between performance release and temperature control safety expected by the user from the initial stage of operation, improving the relevance and satisfaction of the initial user experience.

[0092] In step 2002, the performance preference coefficient corresponding to the type of game application is determined according to the predefined mapping relationship; wherein the value of the performance preference coefficient is between 0 and 1.

[0093] In this embodiment of the application, the abstract game type is quantified into a computable parameter (i.e., performance preference coefficient) to accurately guide the synthesis of the initial temperature control strategy.

[0094] In this embodiment, the performance preference coefficient is a scalar coefficient λ between 0 and 1 (inclusive), used to characterize the initial performance aggressiveness that the device should allocate to the current game application type.

[0095] For example, a performance preference coefficient λ is configured for different game types through a preset mapping relationship: for FPS and MOBA games, λ=0.9 can be mapped, representing a high performance-priority control tendency; for open-world RPG games, λ=0.6 can be mapped, representing a control tendency that balances performance and temperature control; for casual card games, λ=0.2 can be mapped, representing a control tendency that prioritizes temperature control and battery life. This mapping relationship allows the initial temperature control strategy to be generated precisely to match the core requirements of different game categories.

[0096] In this embodiment, by transforming the qualitative judgment of game type into a quantitative performance preference coefficient, the generation process of the initial strategy is standardized and calculable. This coefficient, as a key parameter, maps complex application scenario semantics into mathematical inputs that the device can directly process. Simultaneously, the mapping relationship between game application type and performance preference coefficient is highly configurable, supporting pre-setting and dynamic updates online. This allows device manufacturers to continuously optimize initial temperature control strategies for different game application types based on actual market feedback or specific game performance, achieving refined dynamic tuning of the user's initial experience.

[0097] In step 2003, based on the performance preference coefficient, an interpolation operation is performed on the preset system general temperature control strategy and the preset game scene temperature control strategy to obtain the initial temperature control strategy.

[0098] In this embodiment, a performance preference coefficient is used to intelligently fuse two preset benchmark strategies.

[0099] In this embodiment, the system's general temperature control strategy is denoted as P. base This is a relatively conservative temperature control strategy designed to ensure the safety and battery life of devices in most everyday application scenarios. Its characteristics are that temperature control is prioritized and frequency limitation is relatively strict. For example, an early frequency reduction temperature point is set (such as starting frequency reduction at 42°C) to maintain a low casing temperature and power consumption.

[0100] In this embodiment, the game scene temperature control strategy is denoted as P. game This is a relatively aggressive temperature control strategy designed to meet the sustained high performance demands of gaming applications. Its characteristics are performance priority, allowing higher frequencies and temperatures under the premise of safety. For example, it delays the throttling temperature point (such as only significantly throttling at 48°C) to maintain a high frame rate for a longer period of time.

[0101] In this embodiment of the application, the interpolation operation refers to calculating P based on the performance preference coefficient λ. base and P game The weighted combination. The calculation formula is: Initial temperature control strategy P init =P base +λ×(P game -P base This calculation is typically performed separately for each corresponding parameter in the strategy table (temperature-frequency mapping table), such as the upper limit of frequency at each temperature threshold.

[0102] For example, at a certain temperature point, P base The upper frequency limit is 2.0 GHz, P game It is 2.8 GHz. If λ = 0.6, then P init The upper limit of the frequency at this temperature point is 2.0 + 0.6 × (2.8 - 2.0) = 2.48 GHz.

[0103] In this embodiment, by performing linear interpolation between the system's general temperature control strategy and the game's scene temperature control strategy based on a performance preference coefficient, an intermediate strategy with a continuous spectrum between conservative and aggressive endpoints can be generated. This provides a precisely adapted and differentiated initial starting point for games with different performance requirements. While achieving strategy diversity, this interpolation mechanism always uses the system's general temperature control strategy as a safety baseline. Even for high-performance games (λ approaches 1), the generated initial strategy is only moderately relaxed on this safe basis, avoiding safety risks such as device overheating that may be caused by an overly aggressive initial strategy setting.

[0104] In step 2004, the initial temperature control strategy is determined as the first temperature control strategy that takes effect in the first monitoring cycle.

[0105] In this embodiment of the application, the initial temperature control strategy P init The first temperature control strategy, set to take effect within the first monitoring cycle (k=1), provides a clear and reasonable initial state for the entire adaptive process, enabling the periodic adjustment cycle to begin. This first temperature control strategy will become the common benchmark for all subsequent iterative adjustments, ensuring the consistency and traceability of the entire control process. As can be seen, in this embodiment of the application, by introducing a differentiated initial strategy generation mechanism based on the type of game application, fine-grained and personalized temperature control initialization is achieved. The device does not need to start from the most conservative general strategy and gradually explore to the balance state that is suitable for the current game application through multiple monitoring cycles. Instead, it is in a working point that is closer to the needs of the scenario from the beginning stage, which improves the user experience.

[0106] In some embodiments provided in this application, step 202 may specifically include the following steps: step 2021, step 2022 and step 2023; In step 2021, the temperature deviation of the kth monitoring cycle is determined based on the equipment temperature at the end of the kth monitoring cycle and the preset target temperature.

[0107] In this embodiment of the application, by quantifying the instantaneous difference between the current device temperature and the ideal safety target, a precise real-time safety over-limit measurement signal, namely the temperature deviation, is provided to the device.

[0108] In this embodiment, the temperature deviation is denoted as T. over , is the equipment temperature T at the end of the kth monitoring cycle. end With preset target temperature T target The difference between them is usually calculated by considering only the over-temperature portion. The formula is: T over = max(0, T end -T target It directly reflects whether the equipment is currently at an unsafe temperature, and the severity of the exceedance. When T end ≤T target At that time, T over =0 indicates safety; when T end >T target At that time, T over >0, the larger the value, the more severe the overheating.

[0109] For example, if the preset target temperature T target =46℃, T was measured at the end of the monitoring period. end =48.5℃, then T over =max(0, 48.5-46)=2.5℃, which clearly indicates that the equipment has exceeded the safety target of 2.5℃.

[0110] In this embodiment, a clear absolute safety line is established by calculating the deviation between the current temperature of the device and the preset target temperature. Once the device temperature exceeds the target temperature, the electronic device will trigger mandatory temperature control intervention first, regardless of the current performance requirements.

[0111] In step 2022, the temperature change information, performance information and temperature deviation within the k-th monitoring period are weighted and summed according to the first weighting coefficient, the second weighting coefficient and the third weighting coefficient to obtain the comprehensive control error of the k-th monitoring period; wherein, the comprehensive control error is used to characterize the overall imbalance between the temperature rise risk and performance insufficiency of the electronic device at the end time.

[0112] In this embodiment, information from three different dimensions (trend risk, immediate experience, and security exceedance) is integrated into a single, operable "disequilibrium degree" indicator, namely, comprehensive control error.

[0113] In this embodiment, the comprehensive control error is denoted as E. k E is a scalar synthesized through weighted summation, used to comprehensively characterize the overall imbalance between the risk of temperature rise and insufficient performance of equipment. The calculation formula is: E k =ω1×F temp_sigmoid (k)+ω2×F frame (k)+β×T over (k); Here, k represents the kth monitoring period.

[0114] F temp_sigmoid (k) is the temperature fluctuation factor, reflecting the risk of future temperature rise trends. ω1 is its weighting coefficient, which is usually negative because: F temp_sigmoid (k) being positive indicates a temperature increase, which is a "bad" signal and should contribute a negative error, driving the processor to reduce its frequency.

[0115] F frame (k) represents the frame drop rate, reflecting the current level of performance inadequacy. ω2 is its weighting coefficient, typically a positive value, because: F frame (k) being positive indicates stuttering, which is a "bad" signal, but in order to improve performance, it should contribute positive error to drive the processor to increase its frequency.

[0116] T over (k) represents the temperature deviation, reflecting the immediate degree of exceeding safety limits. β is its weighting coefficient, typically negative with a large absolute value to indicate safety priority. This is because: T over (k) represents a serious security event that must generate a strong negative error, overriding other factors and forcing the processor to reduce its frequency.

[0117] For example, ω1=-0.4, ω2=0.6, β=-1.0, and the current F temp_sigmoid (k) = 0.3 (indicating moderate temperature rise), F frame (k)=0.1 (indicating slight frame dropping), T over (k)=0 (indicating no temperature exceedance), then E k =(-0.4×0.3)+(0.6×0.1)+(-1.0×0)=-0.12+0.06=-0.06, the result is negative, indicating that the "risk of warming" has a slight advantage.

[0118] In this embodiment, a comprehensive control error is generated by weighted fusion of temperature fluctuation factor, frame drop rate, and temperature deviation. This quantitatively balances temperature rise control and performance assurance, enabling the device to make multi-objective intelligent decisions based on a preset weighting strategy. After standardization, this error becomes a single scalar value, providing a standardized input for general control algorithms such as PID.

[0119] In step 2023, based on the comprehensive control error of the kth monitoring cycle, the adjustment amount of the kth temperature control strategy corresponding to the kth monitoring cycle is determined.

[0120] In this embodiment, calculating the temperature control strategy adjustment amount based on the comprehensive control error is a key step in realizing the transformation from state perception to execution control, following the basic principle of error-driven control. The comprehensive control error is a scalar that characterizes the degree of imbalance of multiple objectives of the equipment, and its non-zero state is the basis for generating adjustment commands. The process of generating the adjustment amount maps the multi-dimensional state space to a one-dimensional control action space, realizing compensation for the current deviation.

[0121] As can be seen, in this embodiment, the instantaneous temperature safety status is first quantified to obtain the deviation signal; then, through a weighted fusion mechanism, the multi-dimensional status information such as temperature rise trend, real-time performance and safety over-limit is comprehensively evaluated to generate a scalar index characterizing the overall degree of imbalance; finally, based on this index, after a constrained transformation process, the temperature control strategy adjustment amount with both directionality and smoothness is output, so that the equipment can autonomously maintain the optimal working range under dynamic load environment.

[0122] In some embodiments provided in this application, step 2023 may specifically include the following steps: step 20231, step 20232, and step 20233; In step 20231, the comprehensive control error of the kth monitoring cycle and the historical monitoring cycle is processed according to the proportional-integral-derivative control algorithm to obtain the preliminary adjustment amount.

[0123] In this embodiment, a classic proportional-integral-derivative (PID) control algorithm is used to process the combined error of the current and historical data, generating a preliminary adjustment value. The introduction of the PID algorithm enables the device to have response, memory, and prediction capabilities.

[0124] In this embodiment of the application, the proportional-integral-derivative (PID) control algorithm is a widely used linear control algorithm. It processes the input error signal by combining the three terms of proportional (P), integral (I), and derivative (D) to produce a stable and accurate control output.

[0125] The PID control algorithm uses a differential form, and the formulas for the proportional, integral, and derivative terms are as follows: Proportional term: P k =Kp ×E k ; Integral term: I k = I k-1 +K i ×E k ×T window ; Differential term: D k =K d ×(E k -E k-1 ) / T window ; The proportional term is used to immediately respond to the current error E. k The larger the error, the greater the output adjustment force. For example, K p =0.1, E k =-0.5 (temperature rise risk is dominant), then P k =-0.05, immediately generating a regulating force with a tendency to reduce frequency.

[0126] The integral term is used to accumulate all historical errors, eliminating the steady-state error of the equipment (i.e., small deviations that have existed for a long time and cannot be eliminated by the proportional term). For example, assume that E in the past few periods k The value remains slightly positive (performance is consistently slightly insufficient), I k It will gradually accumulate into a large positive number, even if the current E k Even if the integral term is 0, it will still output a positive adjustment force, continuously driving performance improvement until historical deviations are eliminated.

[0127] The differential term is used to respond to the rate of change of the error. When the error increases rapidly, the differential term outputs a stronger suppression signal to anticipate and prevent the error from increasing further. For example, if E k The temperature rapidly changed from -0.1 to -0.4 (accelerated risk of temperature rise), (E k -E k-1 If the value is negative and the absolute value is large, the differential term D k It will output a significant negative value, providing additional emergency braking force.

[0128] K p K i K d These are the proportional, integral, and differential coefficients, which can be preset based on engineering test data.

[0129] In this embodiment, the initial adjustment amount is denoted as u. k , is the algebraic sum of the three calculation results of the PID. k A positive value indicates that the performance ceiling can be moderately increased (frequency limit relaxed), u k A negative value indicates that the frequency needs to be reduced to control the temperature.

[0130] In this embodiment of the application, u k =P k +I k +D k , where D k It can be the unoptimized original differential term; or, considering that direct difference is sensitive to sampling noise, a first-order filter is used to smooth the original differential term. This filter can smooth high-frequency noise and retain only the temperature and performance variation trends, thereby preventing frequency adjustment jitter, i.e., D. k It is the differential term obtained after the original differential term has been smoothed by a first-order filter.

[0131] In this embodiment, by introducing proportional, integral, and derivative terms into the adjustment calculation, comprehensive optimization of temperature control performance is achieved. The addition of the integral term enables the device to eliminate steady-state deviations, ensuring that the overall control error can be driven close to zero over a long period, achieving zero steady-state error control. The proportional term provides an immediate response to the current error, ensuring the device's dynamic tracking speed; the derivative term prevents overshoot and oscillation by suppressing error change trends, thereby improving the overall stability of closed-loop control. Furthermore, by independently adjusting the proportional, integral, and derivative coefficients, the temperature control characteristics of the device can be finely configured, flexibly adapting to the differentiated needs of different hardware platforms or user scenarios for performance and temperature control balance.

[0132] In step 20232, the initial adjustment amount is subjected to amplitude limiting processing.

[0133] In this embodiment of the application, in order to prevent excessively large single adjustment range due to excessive instantaneous error or improper algorithm parameters, which could cause drastic fluctuations in performance or temperature, the initial adjustment amount can be subjected to amplitude limiting processing.

[0134] In this embodiment, amplitude limiting refers to the process of forcibly limiting the input value to a preset minimum and maximum value. The calculation formula is: u k_clipped =clamp(u k , u min , u max ), where the limiting range is: [u min , u max This setting needs to be set according to the equipment's tolerance. For example, [-0.25, 0.25] means that the single adjustment range is not allowed to exceed ±25% of the reference value.

[0135] For example, if the PID calculates u k =+0.35 (suggests significant performance improvement), while u max =+0.25, then after limiting, u k_clipped+0.25, the excess 0.1 is directly truncated.

[0136] In this embodiment, by applying amplitude limiting processing to the initial adjustment amount, abnormal adjustments caused by single misjudgments or instantaneous disturbances can be prevented, avoiding sudden changes in processor operating parameters due to sensor noise, load spikes, and other signals. By constraining the magnitude of each strategy adjustment within a preset range, the adaptive iteration process is ensured to have a controllable convergence step size, maintaining the dynamic stability of the system near the equilibrium point and preventing oscillations or divergences caused by excessive adjustments.

[0137] In step 20233, the initial adjustment amount after amplitude limiting is subjected to low-pass filtering to obtain the k-th temperature control strategy adjustment amount corresponding to the k-th monitoring cycle.

[0138] In this embodiment of the application, by performing low-pass filtering on the initial adjustment amount after amplitude limiting, high-frequency jitter or noise that may still exist after amplitude limiting can be filtered out, making the final output adjustment amount change more smoothly, thereby ensuring the smoothness of strategy adjustment.

[0139] In this embodiment, low-pass filtering is a filtering method that allows low-frequency signals to pass through while suppressing high-frequency signals. In practical applications, a first-order low-pass filter is often used, and its discrete form is as follows: y k =α×y k-1 +(1-α)×u k_clipped ; Here, α is the filter coefficient, ranging from 0 to 1, and determines the smoothness. The closer α is to 1, the smoother the historical output y. k-1 The larger the weight, the higher the output y. k The slower and smoother the change, the better. The α introduced by the filter ensures that the output of the adjustment quantity cannot change instantaneously, but must change along a smooth trajectory.

[0140] For example, α = 0.7, the adjustment amount y in the previous cycle k-1 =0.05, the current output u after limiting. k_clipped =0.10, then the final adjustment amount y k =0.7*0.05+0.3*0.10=0.035+0.03=0.065, the output smoothly transitions from 0.05 to 0.065, instead of jumping to 0.10.

[0141] In this embodiment, by performing low-pass filtering on the adjustment amount after amplitude limiting, the continuity of the adjustment output is ensured, so that the frequency limit value in the temperature control strategy can change smoothly and gradually. This ensures that the user cannot perceive the frame rate jump or operation lag caused by the intervention of temperature control, and achieves a seamless and smooth experience.

[0142] As can be seen, in this embodiment, a proportional-integral-differential algorithm based on error is first used as the core of the calculation to generate an initial adjustment amount reflecting the degree of imbalance and the trend of change. Then, an amplitude limiting function is used to constrain the output boundary, limiting the single adjustment amplitude to within a preset threshold. Finally, a low-pass filtering algorithm is used to smooth the frequency domain of the limited signal, filtering out high-frequency components to achieve asymptotic continuity of the output. The resulting k-th temperature control strategy adjustment amount is mathematically represented as a control vector with boundedness, continuity, and dynamic adaptability. This vector maps the multi-objective state evaluation results into hardware-executable instructions, transforming the iterative update process of the temperature control strategy from a discrete step response to a continuous state space asymptotic optimization, ensuring control stability while achieving device control that is intrusive to the user experience.

[0143] The control method provided in this application can be executed by a control device. This application uses a temperature control device as an example to illustrate the control device provided in this application.

[0144] Figure 3 This is a structural block diagram of a control device provided in some embodiments of this application, such as... Figure 3 As shown, the control device 300 may include: an acquisition module 301, a determination module 302, and a control module 303; The acquisition module 301 is used to acquire device temperature change information and game application performance information within a fixed monitoring period when the electronic device is running a game application and at least one other application; where k is a natural number. The determining module 302 is used to determine the (k+1)th temperature control strategy for the (k+1)th monitoring period based on the equipment temperature change information and performance information obtained during the (k)th monitoring period. The control module 303 is used to control the operating parameters of the processor of the electronic device according to the (k+1)th temperature control strategy during the (k+1)th monitoring cycle.

[0145] As can be seen from the above embodiments, in this embodiment, for the combined gaming scenario of an electronic device running a game and at least one other application, the device temperature change information and game performance information are collected and fused at a fixed monitoring cycle to identify load change characteristics. Based on the load characteristics of the previous cycle, the temperature control strategy for the next cycle is dynamically adjusted in a forward-looking manner. This achieves a real-time balance between temperature safety and game smoothness, and a fine balance between performance release and temperature rise control. Thus, in the combined gaming scenario, both device temperature control and game performance are taken into account, thereby improving the user experience.

[0146] Optionally, as an embodiment, the determining module 302 is specifically used to determine the adjustment amount of the k-th temperature control strategy corresponding to the k-th monitoring period based on the equipment temperature change information and performance information obtained within the k-th monitoring period; wherein, the adjustment amount of the k-th temperature control strategy is used to indicate the direction and magnitude of relaxing or tightening the k-th temperature control strategy that is effective within the k-th monitoring period; and the k-th temperature control strategy is adjusted according to the adjustment amount of the k-th temperature control strategy to obtain the k+1-th temperature control strategy for the k+1-th monitoring period.

[0147] Optionally, as an embodiment, the determining module 302 is further configured to determine the type of the game application; obtain the performance preference coefficient corresponding to the type according to a predefined mapping relationship; wherein the value range of the performance preference coefficient is between 0 and 1; based on the performance preference coefficient, perform interpolation operation on the preset system general temperature control strategy and the preset game scene temperature control strategy to obtain an initial temperature control strategy; and determine the initial temperature control strategy as the first temperature control strategy that takes effect in the first monitoring period.

[0148] Optionally, as an embodiment, the device temperature change information is a temperature fluctuation factor; The acquisition module 301 is specifically used to acquire the device temperature at the start and end times of the k-th monitoring cycle; calculate the temperature change rate within the k-th monitoring cycle based on the device temperature at the start and end times; perform nonlinear standardization processing on the temperature change rate to obtain a standardized temperature fluctuation factor; wherein, the larger the positive value of the temperature change rate, the closer the output value of the temperature fluctuation factor is to 1; the larger the absolute value of the negative value of the temperature change rate, the closer the output value of the temperature fluctuation factor is to -1; when the absolute value of the temperature change rate is close to zero, the output value of the temperature fluctuation factor is close to zero.

[0149] Optionally, as an embodiment, the determining module 302 is specifically used to determine the temperature deviation of the k-th monitoring cycle based on the device temperature at the end of the k-th monitoring cycle and the preset target temperature; to perform a weighted summation operation on the temperature change information, the performance information, and the temperature deviation within the k-th monitoring cycle based on the first weighting coefficient, the second weighting coefficient, and the third weighting coefficient to obtain the comprehensive control error of the k-th monitoring cycle; wherein, the comprehensive control error is used to characterize the overall imbalance between the temperature rise risk and performance insufficiency of the electronic device at the end of the cycle; and to determine the k-th temperature control strategy adjustment amount corresponding to the k-th monitoring cycle based on the comprehensive control error of the k-th monitoring cycle.

[0150] The control device in this application embodiment can be an electronic device or a component within an electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal or other devices besides a terminal. For example, the electronic device can be a mobile phone, tablet computer, laptop computer, PDA, in-vehicle electronic device, mobile internet device (MID), augmented reality (AR) / virtual reality (VR) device, robot, wearable device, ultra-mobile personal computer (UMPC), netbook, or personal digital assistant (PDA), etc. It can also be a server, network attached storage (NAS), personal computer (PC), television (TV), ATM, or self-service machine, etc. This application embodiment does not specifically limit the scope of the device.

[0151] The control device in this application embodiment can be a device with an operating system. This operating system can be Android, iOS, or other possible operating systems; this application embodiment does not specifically limit the specific operating system used.

[0152] The control device provided in this application embodiment can achieve the above-mentioned functions. Figure 1 or Figure 2 To avoid repetition, the various processes implemented in the method embodiment shown will not be described again here.

[0153] Optionally, such as Figure 4 As shown, this application embodiment also provides an electronic device 400, including a processor 401 and a memory 402. The memory 402 stores a program or instructions that can run on the processor 401. When the program or instructions are executed by the processor 401, they implement the various steps of the above-described control method embodiment and can achieve the same technical effect. To avoid repetition, they will not be described again here.

[0154] It should be noted that the electronic devices in the embodiments of this application include the mobile electronic devices and non-mobile electronic devices described above.

[0155] Figure 5 This is a schematic diagram of the hardware structure of an electronic device that implements the various embodiments of this application.

[0156] The electronic device 500 includes, but is not limited to, components such as: radio frequency unit 501, network module 502, audio output unit 503, input unit 504, sensor 505, display unit 506, user input unit 507, interface unit 508, memory 509, and processor 510.

[0157] Those skilled in the art will understand that the electronic device 500 may also include a power supply (such as a battery) for supplying power to various components. The power supply may be logically connected to the processor 510 through a power management system, thereby enabling functions such as managing charging, discharging, and power consumption through the power management system. Figure 5 The electronic device structure shown does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown, or combine certain components, or have different component arrangements, which will not be elaborated here.

[0158] In some embodiments, the processor 510 is configured to, when the electronic device is running a game application and at least one other application, acquire device temperature change information and game application performance information within a fixed monitoring period, wherein k is a natural number; based on the device temperature change information and performance information acquired within the k-th monitoring period, determine a k+1 temperature control strategy for the k+1-th monitoring period; and within the k+1-th monitoring period, control the operating parameters of the processor of the electronic device according to the k+1-th temperature control strategy.

[0159] As can be seen, in this embodiment of the application, for the combined gaming scenario of an electronic device running a game and at least one other application, the device temperature change information and game performance information are collected and fused at a fixed monitoring cycle, load change characteristics are identified, and the temperature control strategy for the next cycle is dynamically adjusted in a forward-looking manner based on the load characteristics of the previous cycle. This achieves a real-time balance between temperature safety and game smoothness, and a fine balance between performance release and temperature rise control. Thus, in the combined gaming scenario, both device temperature control and game performance are taken into account, thereby improving the user experience.

[0160] Optionally, as an embodiment, the processor 510 is specifically configured to determine the adjustment amount of the k-th temperature control strategy corresponding to the k-th monitoring cycle based on the device temperature change information and performance information obtained within the k-th monitoring cycle; wherein, the adjustment amount of the k-th temperature control strategy is used to indicate the direction and magnitude of loosening or tightening the k-th temperature control strategy that is effective within the k-th monitoring cycle; and adjust the k-th temperature control strategy according to the adjustment amount of the k-th temperature control strategy to obtain the k+1-th temperature control strategy for the k+1-th monitoring cycle.

[0161] Optionally, as an embodiment, the processor 510 is further configured to determine the type of the game application; determine a performance preference coefficient corresponding to the type according to a predefined mapping relationship; wherein the performance preference coefficient ranges from 0 to 1; based on the performance preference coefficient, perform interpolation operations on a preset system general temperature control strategy and a preset game scene temperature control strategy to obtain an initial temperature control strategy; and determine the initial temperature control strategy as the first temperature control strategy that takes effect in the first monitoring cycle.

[0162] Optionally, as an embodiment, the device temperature change information is a temperature fluctuation factor; The processor 510 is specifically configured to acquire the device temperature at the start and end times of the kth monitoring period; calculate the temperature change rate within the kth monitoring period based on the device temperature at the start and end times; perform nonlinear standardization processing on the temperature change rate to obtain a standardized temperature fluctuation factor; wherein, the larger the positive value of the temperature change rate, the closer the output value of the temperature fluctuation factor is to 1; the larger the absolute value of the negative value of the temperature change rate, the closer the output value of the temperature fluctuation factor is to -1; when the absolute value of the temperature change rate is close to zero, the output value of the temperature fluctuation factor is close to zero.

[0163] Optionally, as an embodiment, the processor 510 is specifically configured to: determine the temperature deviation of the k-th monitoring cycle based on the device temperature at the end of the k-th monitoring cycle and the preset target temperature; perform a weighted summation operation on the temperature change information, the performance information, and the temperature deviation within the k-th monitoring cycle based on a first weighting coefficient, a second weighting coefficient, and a third weighting coefficient to obtain the comprehensive control error of the k-th monitoring cycle; wherein, the comprehensive control error is used to characterize the overall imbalance between the temperature rise risk and performance insufficiency of the electronic device at the end of the monitoring cycle; and determine the k-th temperature control strategy adjustment amount corresponding to the k-th monitoring cycle based on the comprehensive control error of the k-th monitoring cycle.

[0164] It should be understood that, in this embodiment, the input unit 504 may include a graphics processing unit (GPU) 5041 and a microphone 5042. The GPU 5041 processes image data of still images or videos obtained by an image capture device (such as a camera) in video capture mode or image capture mode. The display unit 506 may include a display panel 5061, which may be configured in the form of a liquid crystal display, an organic light-emitting diode, or the like. The user input unit 507 includes at least one of a touch panel 5071 and other input devices 5072. The touch panel 5071 is also called a touch screen. The touch panel 5071 may include a touch detection device and a touch controller. Other input devices 5072 may include, but are not limited to, physical keyboards, function keys (such as volume control buttons, power buttons, etc.), trackballs, mice, and joysticks, which will not be described in detail here.

[0165] The memory 509 can be used to store software programs and various data. The memory 509 may primarily include a first storage area for storing programs or instructions and a second storage area for storing data. The first storage area may store the operating system, application programs or instructions required for at least one function (such as sound playback, image playback, etc.). Furthermore, the memory 509 may include volatile memory or non-volatile memory, or both. The non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM), static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (Synchlink DRAM, SLDRAM), and direct memory bus RAM (DRRAM). The memory 509 in this embodiment includes, but is not limited to, these and any other suitable types of memory.

[0166] Processor 510 may include one or more processing units; optionally, processor 510 integrates an application processor and a modem processor, wherein the application processor mainly handles operations involving the operating system, user interface, and applications, and the modem processor mainly handles wireless communication signals, such as a baseband processor. It is understood that the aforementioned modem processor may also not be integrated into processor 510.

[0167] This application also provides a readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the various processes of the above-described control method embodiments and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0168] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0169] This application embodiment also provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement the various processes of the above control method embodiments and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0170] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0171] This application provides a computer program product, which is stored in a storage medium and executed by at least one processor to implement the various processes of the control method embodiments described above, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0172] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0173] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), including several instructions to cause a terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0174] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A control method, characterized in that, The method includes: When an electronic device is running a game application and at least one other application, the device temperature change information and the performance information of the game application are obtained within the k-th monitoring period, with a fixed duration as the monitoring period; where k is a natural number. Based on the equipment temperature change information and performance information obtained during the kth monitoring period, a k+1 temperature control strategy for the k+1th monitoring period is determined. During the (k+1)th monitoring period, the operating parameters of the processor of the electronic device are controlled according to the (k+1)th temperature control strategy.

2. The method according to claim 1, characterized in that, The determination of the (k+1)th temperature control strategy for the (k+1)th monitoring period based on the equipment temperature change information and performance information obtained during the (k)th monitoring period includes: Based on the equipment temperature change information and performance information obtained during the kth monitoring period, the adjustment amount of the kth temperature control strategy corresponding to the kth monitoring period is determined; wherein, the adjustment amount of the kth temperature control strategy is used to indicate the direction and magnitude of relaxing or tightening the kth temperature control strategy that is effective during the kth monitoring period. Based on the adjustment amount of the kth temperature control strategy, the kth temperature control strategy is adjusted to obtain the k+1th temperature control strategy for the k+1th monitoring cycle.

3. The method according to claim 2, characterized in that, Before acquiring equipment temperature change information and performance information within the first monitoring cycle, the method further includes: Determine the type of the game application; Based on a predefined mapping relationship, determine the performance preference coefficient corresponding to the type; wherein the value of the performance preference coefficient is between 0 and 1; Based on the performance preference coefficient, interpolation is performed between the preset system general temperature control strategy and the preset game scene temperature control strategy to obtain the initial temperature control strategy. The initial temperature control strategy is determined as the first temperature control strategy that takes effect during the first monitoring cycle.

4. The method according to claim 1 or 2, characterized in that, The equipment temperature change information is a temperature fluctuation factor; obtaining the equipment temperature change information within the kth monitoring period includes: Obtain the device temperature at the start and end times of the kth monitoring cycle; Calculate the temperature change rate during the k-th monitoring period based on the device temperatures at the start and end times; The temperature change rate is subjected to nonlinear normalization to obtain a standardized temperature fluctuation factor. Specifically, the larger the positive value of the temperature change rate, the closer the output value of the temperature fluctuation factor is to 1; the larger the absolute value of the negative value of the temperature change rate, the closer the output value of the temperature fluctuation factor is to -1; when the absolute value of the temperature change rate is close to zero, the output value of the temperature fluctuation factor is close to zero.

5. The method according to claim 2, characterized in that, The step of determining the adjustment amount of the k-th temperature control strategy corresponding to the k-th monitoring period based on the equipment temperature change information and performance information obtained within the k-th monitoring period includes: The temperature deviation of the kth monitoring cycle is determined based on the equipment temperature at the end of the kth monitoring cycle and the preset target temperature. Based on the first weighting coefficient, the second weighting coefficient, and the third weighting coefficient, the temperature change information, the performance information, and the temperature deviation during the k-th monitoring period are weighted and summed to obtain the comprehensive control error of the k-th monitoring period; wherein, the comprehensive control error is used to characterize the overall imbalance between the temperature rise risk and performance insufficiency of the electronic device at the end time; Based on the comprehensive control error of the kth monitoring cycle, the adjustment amount of the kth temperature control strategy corresponding to the kth monitoring cycle is determined.

6. A control device, characterized in that, The device includes: The acquisition module is used to acquire device temperature change information and game application performance information within a fixed monitoring period (k-th monitoring period) when the electronic device is running a game application and at least one other application; where k is a natural number. The determination module is used to determine the (k+1)th temperature control strategy for the (k+1)th monitoring period based on the equipment temperature change information and performance information obtained during the (k)th monitoring period. The control module is used to control the operating parameters of the processor of the electronic device according to the (k+1)th temperature control strategy during the (k+1)th monitoring cycle.

7. The apparatus according to claim 6, characterized in that, The determining module is specifically used to determine the adjustment amount of the k-th temperature control strategy corresponding to the k-th monitoring period based on the equipment temperature change information and performance information obtained within the k-th monitoring period; wherein, the adjustment amount of the k-th temperature control strategy is used to indicate the direction and magnitude of loosening or tightening the k-th temperature control strategy that is effective within the k-th monitoring period; and the k-th temperature control strategy is adjusted according to the adjustment amount of the k-th temperature control strategy to obtain the k+1-th temperature control strategy for the k+1-th monitoring period.

8. The apparatus according to claim 7, characterized in that, The determining module is further configured to determine the type of the game application; determine the performance preference coefficient corresponding to the type according to a predefined mapping relationship; wherein the performance preference coefficient is between 0 and 1; based on the performance preference coefficient, perform interpolation operation on the preset system general temperature control strategy and the preset game scene temperature control strategy to obtain an initial temperature control strategy; and determine the initial temperature control strategy as the first temperature control strategy that takes effect in the first monitoring period.

9. The apparatus according to claim 6 or 7, characterized in that, The equipment temperature change information is a temperature fluctuation factor; The acquisition module is specifically used to acquire the device temperature at the start and end times of the kth monitoring cycle; calculate the temperature change rate within the kth monitoring cycle based on the device temperature at the start and end times; perform nonlinear standardization processing on the temperature change rate to obtain a standardized temperature fluctuation factor; wherein, the larger the positive value of the temperature change rate, the closer the output value of the temperature fluctuation factor is to 1; the larger the absolute value of the negative value of the temperature change rate, the closer the output value of the temperature fluctuation factor is to -1; when the absolute value of the temperature change rate is close to zero, the output value of the temperature fluctuation factor is close to zero.

10. The apparatus according to claim 7, characterized in that, The determining module is specifically used to determine the temperature deviation of the k-th monitoring cycle based on the device temperature at the end of the k-th monitoring cycle and the preset target temperature; to perform a weighted summation operation on the temperature change information, the performance information, and the temperature deviation within the k-th monitoring cycle based on a first weighting coefficient, a second weighting coefficient, and a third weighting coefficient to obtain the comprehensive control error of the k-th monitoring cycle; wherein, the comprehensive control error is used to characterize the overall imbalance between the temperature rise risk and performance insufficiency of the electronic device at the end of the monitoring cycle; and to determine the k-th temperature control strategy adjustment amount corresponding to the k-th monitoring cycle based on the comprehensive control error of the k-th monitoring cycle.

11. An electronic device, characterized in that, The electronic device includes a processor and a memory, the memory storing programs or instructions that can run on the processor, the programs or instructions being executed by the processor to implement the steps of the control method as described in any one of claims 1 to 5.

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