Mobile phone heat management heat dissipation method, device and equipment and storage medium

Abstract

The invention relates to a mobile phone heat management heat dissipation method, device and equipment and a storage medium, and the method comprises the following steps: carrying out the multi-point temperature scanning collection of the surface of a target mobile phone through a thermal imaging sensor array, and obtaining the surface temperature distribution data; performing heat flux density distribution calculation on the target mobile phone based on the surface temperature distribution data through a heat flux inversion algorithm to obtain a heat flux density distribution diagram; performing heat dissipation power distribution on the target mobile phone based on the heat flow density distribution diagram to obtain power control parameters of each heat dissipation unit; and performing heat management heat dissipation on the target mobile phone based on the power control parameter so as to enable the target mobile phone to be in a target heat dissipation state, thereby solving the technical problem that a heat dissipation strategy is not accurate enough because a mobile phone heat dissipation solution in the current market generally lacks detailed understanding of internal heat source distribution.

Description

Technical Field

[0001] The present invention relates to the technical field of mobile phone thermal management, and in particular to a mobile phone thermal management heat dissipation method, device, equipment and storage medium. Background Art

[0002] As smartphone functions become increasingly complex and their integration levels continue to increase, the heat generated by mobile phones when running high-performance applications or performing multitasking also increases accordingly. This not only affects the performance and user experience of the device, but may also shorten the life of the phone and even cause safety issues. Traditional heat dissipation methods, such as relying solely on heat conduction from a metal casing or small fans to assist in cooling, are inadequate in the face of the compact design and high-intensity workloads of today's smart devices. Therefore, it is urgent to develop a mobile phone thermal management and heat dissipation method that can accurately and in real time respond and adapt to different usage scenarios.

[0003] The current mobile phone cooling solutions on the market usually lack a detailed understanding of the internal heat source distribution, resulting in inaccurate cooling strategies. For example, most existing technologies can only monitor the temperature changes at a limited number of points, and cannot fully grasp the temperature conditions of the entire mobile phone surface or even the internal components. This limitation means that cooling measures can often only respond to overheating that has already occurred, and cannot be adjusted in advance to prevent overheating. In addition, due to the lack of understanding of the specific heat flux density distribution, cooling resources cannot be optimally configured, resulting in energy waste and failure to achieve ideal cooling effects.

[0004] In order to overcome the above challenges, a mobile phone thermal management and cooling method based on thermal imaging sensor array and heat flow inversion algorithm is proposed. This method realizes multi-point temperature scanning and acquisition on the surface of the mobile phone, constructs detailed surface temperature distribution data, and further calculates the heat flux density distribution map. This method can not only provide more accurate thermal information and support more efficient heat dissipation power allocation, but also dynamically adjust the working state of each heat dissipation unit according to actual needs, ensuring that the mobile phone always maintains a stable and safe temperature range, thereby improving the overall performance of the mobile phone and user satisfaction. Summary of the invention

[0005] The main purpose of the present invention is to provide a mobile phone thermal management and heat dissipation method, device, equipment and storage medium, which solves the technical problem that the mobile phone heat dissipation solutions on the current market usually lack a detailed understanding of the internal heat source distribution, resulting in an inaccurate heat dissipation strategy.

[0006] To achieve the above object, the present invention provides a mobile phone thermal management and heat dissipation method, comprising the following steps: The surface of the target mobile phone is scanned and collected at multiple points by a thermal imaging sensor array to obtain surface temperature distribution data; Using a heat flow inversion algorithm, based on the surface temperature distribution data, heat flow density distribution calculation is performed on the target mobile phone to obtain a heat flow density distribution map; Based on the heat flux density distribution diagram, heat dissipation power is allocated to the target mobile phone to obtain power control parameters of each heat dissipation unit; The target mobile phone is thermally managed and cooled based on the power control parameters, so that the target mobile phone is in a target cooling state.

[0007] Furthermore, the thermal imaging sensor array is used to perform multi-point temperature scanning and acquisition on the surface of the target mobile phone to obtain surface temperature distribution data, including: Performing grid scanning and sampling on the surface of the target mobile phone through a preset thermal imaging sensor array to obtain raw temperature sampling data, and performing Gaussian filtering on the raw temperature sampling data to obtain filtered temperature dot matrix data; Using a bicubic spline interpolation algorithm, a surface temperature interpolation calculation is performed on the target mobile phone based on the filtered temperature lattice data to obtain initial temperature field data, and boundary correction is performed on the initial temperature field data to obtain corrected temperature field data; Performing local weighted regression analysis on the corrected temperature field data to obtain temperature field smoothing data, and performing partition statistics on the temperature field smoothing data to obtain regional temperature characteristic data; wherein the regional temperature characteristic data includes the temperature mean and variance of each region in the target mobile phone; Based on the regional temperature characteristic data, reconstructing the temperature field of the surface of the target mobile phone to obtain reconstructed temperature field data; Performing time series correlation analysis on the reconstructed temperature field data to obtain dynamic temperature change characteristics, and performing spatiotemporal fusion on the dynamic temperature change characteristics to obtain a temperature field dynamic characteristic diagram; Isothermal surfaces are extracted based on the dynamic characteristic diagram of the temperature field to obtain the surface temperature distribution contour, and hot spot features are extracted from the surface temperature distribution contour to obtain surface temperature distribution data.

[0008] Furthermore, the heat flux density distribution of the target mobile phone is calculated based on the surface temperature distribution data by using a heat flux inversion algorithm to obtain a heat flux density distribution map, including: Reconstructing the three-dimensional temperature field of the target mobile phone based on the surface temperature distribution data to obtain a three-dimensional temperature field model, and performing finite element discretization on the three-dimensional temperature field model to obtain discretized temperature field data; Solving the heat conduction equation of the target mobile phone based on the discretized temperature field data by a preset conjugate gradient method to obtain internal temperature gradient field data, and performing inverse heat conduction calculation on the internal temperature gradient field data to obtain heat flux density vector field data; By using a preset divergence theorem, heat source identification is performed on the target mobile phone based on the heat flux density vector field data to obtain a heat source position and intensity information corresponding to the heat source position, and heat source area division is performed on the target mobile phone based on the heat source position and the intensity information to obtain a heat source area distribution map; Using a heat flow inversion algorithm, based on the heat source area distribution map, heat flow lines are traced on the target mobile phone to obtain a heat flow line distribution map, and heat flux density is calculated on the heat flow line distribution map to obtain an initial heat flux density distribution map; The initial heat flux density distribution diagram is divided into heat flux density areas to obtain a heat flux density distribution diagram.

[0009] Furthermore, the heat dissipation power of the target mobile phone is allocated based on the heat flux density distribution diagram to obtain the power control parameters of each heat dissipation unit, including: Based on the heat flux density distribution diagram, a heat dissipation unit load analysis is performed on the target mobile phone to obtain initial load distribution data, and a heat flux balance calculation is performed on the initial load distribution data to obtain a unit heat power demand map; Based on the unit thermal power demand map, a heat dissipation power constraint analysis is performed on the target mobile phone to obtain a power constraint condition set, and the power constraint condition set is decomposed by Lagrange multipliers to obtain power allocation boundary parameters; wherein the power allocation boundary parameters include a maximum power threshold and a minimum power threshold of the heat dissipation unit; Performing multi-objective optimization on the power allocation boundary parameters to obtain an initial power allocation scheme, and performing multi-dimensional evaluation on the initial power allocation scheme by using the Pareto optimality criterion to obtain a power allocation evaluation index; wherein the power allocation evaluation index includes a heat dissipation efficiency index and a power consumption balance index; Using a mixed integer programming algorithm, based on the power allocation evaluation index, dynamically allocate heat dissipation power to the target mobile phone to obtain a dynamic power allocation sequence; The dynamic power allocation sequence is optimally controlled and solved by Hamilton-Jacobi equation to obtain a power control trajectory, and the power control trajectory is piecewise linearized to obtain a discretized power control point set; wherein the discretized power control point set includes a power adjustment step and a control cycle parameter; Based on the discretized power control point set, power parameter mapping is performed on each heat dissipation unit of the target mobile phone to obtain power control parameters of each heat dissipation unit.

[0010] Furthermore, the heat dissipation power constraint analysis is performed on the target mobile phone based on the unit thermal power demand map to obtain a power constraint condition set, including: The unit thermal power demand map is segmented into power regions by using a spectral clustering algorithm to obtain a power partition sequence, and a heat flow conservation calculation is performed on the power partition sequence to obtain a regional power balance equation; Based on the regional power balance equation, a thermal network is constructed for the target mobile phone to obtain a heat dissipation power transfer network, and a topological analysis is performed on the heat dissipation power transfer network to obtain a power transfer path set; Extracting features from the power transfer path set by singular value decomposition to obtain a transfer feature matrix, and allocating boundary constraints to the transfer feature matrix to obtain a power allocation constraint set; Based on the power allocation constraint set, nonlinear programming is performed on the target mobile phone to obtain a nonlinear constraint equation group, and the nonlinear constraint equation group is solved by an interior point method to obtain a power adjustment parameter group; Performing variational analysis on the power regulation parameter group to obtain an optimal control equation, and solving the optimal control equation by using the Pontryagin maximum principle to obtain a control constraint sequence; Constraint integration is performed based on the control constraint sequence to obtain a power constraint condition set.

[0011] Furthermore, the heat flow conservation calculation is performed on the power partition sequence to obtain the regional power balance equation, including: Performing area decomposition on the power partition sequence by Green-Gauss theorem to obtain regional boundary flux, and performing divergence calculation on the regional boundary flux to obtain a heat flux distribution vector; Performing partition power integration on the target mobile phone based on the heat flux distribution vector to obtain a regional power density field, and performing divergence analysis on the regional power density field using the Gaussian divergence theorem to obtain a power flux field; Expanding the power flux field according to the first law of thermodynamics to obtain a group of energy conservation equations, and constructing constraint conditions for the group of energy conservation equations by Lagrange multiplier method to obtain a power constraint expression; wherein the power constraint expression includes a heat flux conduction term, a heat capacity integral term, and a boundary condition term; Based on the power constraint expression, the target mobile phone is solved by variational method to obtain the Euler-Lagrange equation, and the Euler-Lagrange equation is analyzed for symmetry by Noether's theorem to obtain a conservation quantity sequence; wherein the conservation quantity sequence includes energy conservation quantity, momentum conservation quantity and heat flow conservation quantity; Performing spectral analysis on the conserved quantity sequence through Fourier series expansion to obtain a harmonic component set, and constraining the harmonic component set by the second law of thermodynamics to obtain an entropy generation rate function; The regional power balance of the target mobile phone is derived based on the entropy generation rate function to obtain a regional power balance equation.

[0012] Further, the performing thermal management and heat dissipation on the target mobile phone based on the power control parameter to achieve the target mobile phone being in a target heat dissipation state includes: Dynamically allocating power to each cooling unit of the target mobile phone according to the power control parameter to obtain a real-time power control instruction for each cooling unit; Performing time sequence encoding on the real-time power control instruction to obtain a power control instruction sequence; Performing power control signal modulation on each heat dissipation unit of the target mobile phone based on the power control instruction sequence to obtain a modulated power control signal; Carrier synchronization is performed on the modulated power control signal to obtain a synchronous power control signal; Through a preset multiplexing technology, heat management and heat dissipation are performed on each heat dissipation unit of the target mobile phone based on the synchronous power control signal, so that the target mobile phone is in a target heat dissipation state.

[0013] The present invention also provides a mobile phone thermal management and heat dissipation device, comprising: The acquisition module is used to perform multi-point temperature scanning and acquisition on the surface of the target mobile phone through a thermal imaging sensor array to obtain surface temperature distribution data; A calculation module, configured to calculate the heat flux density distribution of the target mobile phone based on the surface temperature distribution data by using a heat flux inversion algorithm to obtain a heat flux density distribution map; wherein the heat flux density distribution map includes heat transfer direction and intensity data; An allocation module, configured to allocate heat dissipation power to the target mobile phone based on the heat flux density distribution diagram, and obtain power control parameters of each heat dissipation unit; The heat dissipation module is used to perform thermal management and heat dissipation on the target mobile phone based on the power control parameter to achieve a target heat dissipation state for the target mobile phone.

[0014] The present invention also provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of any one of the above methods when executing the computer program.

[0015] The present invention also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of any of the above-mentioned methods are implemented.

[0016] The mobile phone thermal management and heat dissipation method provided by the present invention comprises the following steps: performing multi-point temperature scanning and collection on the surface of the target mobile phone through a thermal imaging sensor array to obtain surface temperature distribution data; performing heat flux density distribution calculation on the target mobile phone based on the surface temperature distribution data through a heat flux inversion algorithm to obtain a heat flux density distribution map; performing heat dissipation power allocation on the target mobile phone based on the heat flux density distribution map to obtain power control parameters of each heat dissipation unit; performing thermal management and heat dissipation on the target mobile phone based on the power control parameters to achieve the target mobile phone in a target heat dissipation state. Through the above technical solution, the technical problem that the mobile phone heat dissipation solutions on the current market usually lack detailed understanding of the internal heat source distribution, resulting in the heat dissipation strategy being not accurate enough, is solved, and the accurate power control parameter setting of each heat dissipation unit can be achieved according to the heat flux density distribution map. This means that the heat dissipation system can dynamically adjust the working state according to actual needs, concentrate the heat dissipation resources in the most needed places, avoid unnecessary energy consumption, and thus improve the technical effect of the energy efficiency of the entire system. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 Schematic diagram of the steps of a mobile phone thermal management and heat dissipation method according to an embodiment of the present invention; Figure 2 This is a structural block diagram of a mobile phone thermal management and heat dissipation device in one embodiment of the present invention; Figure 3 It is a schematic block diagram of the structure of a computer device according to an embodiment of the present invention.

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

[0019] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0020] like Figure 1 As shown, Figure 1 This is a schematic diagram of the steps of a mobile phone thermal management and heat dissipation method in one embodiment of the present invention; In one embodiment of the present invention, a method for thermal management and heat dissipation of a mobile phone is provided, comprising the following steps: Step S1, performing multi-point temperature scanning and collection on the surface of the target mobile phone through a thermal imaging sensor array to obtain surface temperature distribution data.

[0021] Specifically, in order to achieve the step of scanning and collecting multi-point temperature on the surface of the target mobile phone and obtaining the surface temperature distribution data, the thermal imaging sensor array technology is first used. This technology utilizes the characteristic of thermistors that can sense infrared radiation. Each sensor can be regarded as an independent measurement unit. When they are arranged in a certain pattern to form an array, the temperature of multiple positions on the surface of the mobile phone can be measured synchronously at the same time. For example, in the application scenario of smartphone heat dissipation management, the thermal imaging sensor array will fit closely or close to the mobile phone casing, and evaluate the heat conditions of various parts by capturing infrared rays emitted from the surface of the mobile phone. Once the thermal imaging sensor array starts working, it will start the process of performing multi-point temperature scanning and collection on the surface of the target mobile phone. In this process, each sensor unit will record the temperature information of the corresponding area and transmit these raw data to the processing system. As the sensor array continues to scan different parts of the mobile phone surface, a data set consisting of a large number of temperature data points is gradually formed. This is like using a brush to draw a picture on a canvas stroke by stroke, except that the temperature map of the mobile phone surface is drawn here. Ultimately, by integrating all the collected data points, we can obtain a detailed surface temperature distribution map, which not only shows the overall temperature conditions of the phone surface, but also clearly indicates which areas are high-temperature hotspots and which areas are relatively cool. For example, when a user is playing a graphics-intensive game or making a long video call, key components such as the processor and screen inside the phone may generate a lot of heat. At this time, the thermal imaging sensor array can accurately detect the location of these high-heat areas and their temperature change trends, providing reliable basic data for subsequent heat flux density distribution calculations. In this way, based on accurate surface temperature distribution data, the thermal management system can adjust the heat dissipation strategy more specifically to ensure that the phone can operate within an ideal temperature range under various usage conditions.

[0022] Step S2, using a heat flow inversion algorithm, based on the surface temperature distribution data, calculate the heat flow density distribution of the target mobile phone to obtain a heat flow density distribution map.

[0023] Specifically, in order to calculate the heat flux density distribution of the target mobile phone and obtain the heat flux density distribution map, it is necessary to rely on the key technology of the heat flow inversion algorithm. In the above steps, we have obtained the surface temperature distribution data of the mobile phone through the thermal imaging sensor array, which provides the basis for the subsequent calculations. The heat flow inversion algorithm is a mathematical modeling method that can reversely deduce the mode and path of heat transfer inside the object based on the known surface temperature distribution. In this process, the algorithm will comprehensively consider the influence of various aspects such as the thermal conductivity characteristics of the material, boundary conditions and environmental factors to ensure the accuracy of the calculation results. When the heat flow inversion algorithm starts to process the data obtained from the thermal imaging sensor array, it first spatially interpolates and smoothes these discrete temperature measurements to construct a continuous temperature field model. Then, using this model as input and combining the heat conduction equation in physics, the heat flow inversion algorithm can simulate the flow of heat between the components inside the mobile phone. For example, in the application scenario where the user plays graphics-intensive games or makes long video calls, the processor and screen may become the main sources of heat. At this point, through the heat flow inversion algorithm, we can accurately estimate the amount of heat dissipated from these two areas and its propagation direction, and then draw a detailed heat flux density distribution map. The importance of this step is that it not only reveals the specific flow of heat inside the phone, but also helps identify which parts are the key bottlenecks for heat dissipation. With such information, the subsequent heat dissipation power allocation can be adjusted more specifically to ensure that each heat dissipation unit can perform at its maximum efficiency. For example, if the heat flux density around the processor is found to be abnormally high, the system can increase the speed of the cooling fan in the area or enhance the thermal conductivity of the heat sink to alleviate the problem of local overheating. In this way, the heat flux density distribution map not only provides a scientific basis for optimizing the heat dissipation design, but also lays a solid foundation for improving the overall thermal management performance of the mobile phone. Ultimately, this method helps maintain the stability and safety of the device under high-performance operation while improving the user experience.

[0024] Step S3, distributing heat dissipation power to the target mobile phone based on the heat flux density distribution diagram, and obtaining power control parameters of each heat dissipation unit.

[0025] Specifically, the target mobile phone is allocated heat dissipation power based on the heat flux density distribution map to obtain the power control parameters of each heat dissipation unit. This process is the core link of the entire thermal management system. In the previous steps, we have used the thermal imaging sensor array and the heat flow inversion algorithm to obtain detailed surface temperature distribution data and calculated the heat flux density distribution map. This step is to convert the theoretical heat flow information into a practical and operational heat dissipation strategy. When we have the heat flux density distribution map, we can clearly see which areas are the main heat sources and how the heat is transferred inside the mobile phone. Next, based on these key information, the system will formulate a heat dissipation plan according to the preset target heat dissipation state. For example, when the user plays a graphic-intensive game or makes a long video call, parts such as the processor and the screen may become hot spots. At this time, by analyzing the heat flux density distribution map, it can be determined that these areas need more heat dissipation support. Then, based on the detailed information provided by the heat flux density distribution map, the system will reasonably allocate power to each heat dissipation unit. Specifically, the process of heat dissipation power allocation involves the collaborative work arrangement of different heat dissipation components such as heat sinks, fans, heat pipes, etc. The system calculates the optimal power output required for each heat dissipation unit to ensure that they can provide the necessary cooling effect without wasting energy. For areas with high heat flux density, the power setting of the heat dissipation unit may be increased, such as increasing the fan speed or enhancing the heat exchange efficiency between the heat sink and the air; while for those areas with relatively low temperatures, the activity intensity of the heat dissipation unit can be appropriately reduced to save power and reduce unnecessary noise. To achieve this, engineers usually reserve a certain amount of adjustment space for the heat dissipation system during the design phase, so that it can dynamically adjust the working state of each heat dissipation unit according to the real-time heat flux density distribution map. This flexibility allows the system to not only respond to the current thermal situation, but also predict future temperature change trends and make heat dissipation preparations in advance. Ultimately, through precise power control of the heat dissipation unit, the mobile phone can operate within an ideal temperature range under high-load tasks, which not only ensures stable performance but also improves the user experience. In addition, this approach also helps to extend the service life of the device because it reduces the risk of hardware damage caused by overheating and effectively avoids energy waste.

[0026] Step S4, performing thermal management and heat dissipation on the target mobile phone based on the power control parameter, so as to achieve that the target mobile phone is in a target heat dissipation state.

[0027] Specifically, the target mobile phone is thermally managed and cooled based on the power control parameters to achieve the target mobile phone in the target cooling state. This process is the final execution stage of the entire intelligent cooling system. Prior to this, we have obtained the surface temperature distribution data through the thermal imaging sensor array, and calculated the heat flux density distribution map using the heat flow inversion algorithm, and then accurately allocated the power control parameters of each cooling unit based on this information. Now, the results of all preparatory work will be applied to actual operations to ensure that the mobile phone can be maintained in an ideal temperature range in different usage scenarios. When the various components of the cooling system receive specific power control parameters, they will adjust their own operating modes according to preset instructions. For example, in the application scenario where the user plays graphics-intensive games or makes long video calls, parts such as the processor and the screen may generate a lot of heat. At this time, the cooling fan will increase the speed according to the power control parameters to enhance air circulation; the heat sink will increase the heat exchange efficiency with the surrounding environment and accelerate heat dissipation; and the heat pipe will more efficiently transfer heat from the heat source to the heat dissipation area. All of this is to ensure that key components will not overheat, thereby affecting performance or causing hardware damage. At the same time, this dynamic cooling strategy is not limited to high-load tasks. Even under daily use conditions, such as browsing the web, sending and receiving emails, or light social software interactions, the cooling system can still flexibly adjust its working intensity according to the temperature changes monitored in real time. If the temperature in a certain area is detected to have risen but has not yet reached the warning level, the system can respond in advance and slightly increase the working efficiency of the cooling unit near the area to prevent potential overheating risks. On the contrary, for those areas that always maintain a low temperature, unnecessary cooling activities can be reduced, energy can be saved, and noise can be reduced. In addition, through the precise regulation of the cooling unit, not only the cooling efficiency is improved, but also the goal of energy conservation and emission reduction is achieved. Each cooling component operates in the most optimized state, which not only meets the cooling needs but also avoids resource waste. This enables the mobile phone to operate stably in various complex working environments, prolongs the service life of the device, and also brings users a smoother and more comfortable use experience. Finally, through such a complete set of thermal management processes, the mobile phone can always maintain the target cooling state set by the designer, and can provide the best performance regardless of the application scenario.

[0028] In a specific embodiment, the method of performing multi-point temperature scanning and collecting on the surface of the target mobile phone by means of a thermal imaging sensor array to obtain surface temperature distribution data includes: Performing grid scanning and sampling on the surface of the target mobile phone through a preset thermal imaging sensor array to obtain raw temperature sampling data, and performing Gaussian filtering on the raw temperature sampling data to obtain filtered temperature dot matrix data; Using a bicubic spline interpolation algorithm, a surface temperature interpolation calculation is performed on the target mobile phone based on the filtered temperature lattice data to obtain initial temperature field data, and boundary correction is performed on the initial temperature field data to obtain corrected temperature field data; Performing local weighted regression analysis on the corrected temperature field data to obtain temperature field smoothing data, and performing partition statistics on the temperature field smoothing data to obtain regional temperature characteristic data; wherein the regional temperature characteristic data includes the temperature mean and variance of each region in the target mobile phone; Based on the regional temperature characteristic data, reconstructing the temperature field of the target mobile phone surface to obtain reconstructed temperature field data; Performing time series correlation analysis on the reconstructed temperature field data to obtain dynamic temperature change characteristics, and performing spatiotemporal fusion on the dynamic temperature change characteristics to obtain a temperature field dynamic characteristic diagram; Isothermal surfaces are extracted based on the dynamic characteristic diagram of the temperature field to obtain the surface temperature distribution contour, and hot spot features are extracted from the surface temperature distribution contour to obtain surface temperature distribution data.

[0029] Specifically, in order to realize the complex process of multi-point temperature scanning and acquisition on the surface of the target mobile phone to obtain the surface temperature distribution data, it is first necessary to use a preset thermal imaging sensor array to perform grid scanning and sampling on the surface of the target mobile phone. In this step, the thermal imaging sensor array covers the entire surface of the mobile phone according to a predetermined pattern to form a dense measurement network. Each sensor node serves as a sampling point and is responsible for capturing the temperature information at its corresponding position. These raw temperature sampling data are the basis for all subsequent processing, and they reflect the temperature state of the mobile phone surface at a specific moment. However, due to interference factors in the actual environment and the errors of the sensor itself, the directly acquired data may contain noise and inaccurate information. Therefore, after obtaining the raw temperature sampling data, the system will perform Gaussian filtering on these data. Gaussian filtering is a common signal processing technology that can effectively smooth data, reduce the impact of random noise, and keep the original features unchanged as much as possible. By applying Gaussian filtering, we can extract more reliable filtered temperature dot matrix data from the raw data. These preliminarily processed data provide a more stable basis for the subsequent analysis. Next, based on the filtered temperature dot matrix data, the system uses the bicubic spline interpolation algorithm to interpolate the surface temperature of the target mobile phone. Bicubic spline interpolation is an accurate interpolation method that can construct a smooth and continuous surface between known data points to estimate the temperature value of the unknown position. This method not only improves the resolution of the temperature field, but also ensures the natural transition of the temperature change trend. After completing the interpolation calculation, we get the initial temperature field data, but this is not the final result. Because outliers or data points that do not conform to the actual situation may appear in the edge area, the initial temperature field data needs to be corrected at the boundary. This process involves identifying and adjusting those boundary temperature values ​​that deviate from the normal range so that the overall temperature field is more in line with the laws of physics, and finally obtaining the corrected temperature field data. With the corrected temperature field data, the next step is to perform local weighted regression analysis on the corrected temperature field data. Local weighted regression is a non-parametric statistical method that allows the model to give different weights according to the importance of neighboring data points, so as to better adapt to local characteristics. Through this analysis, smooth temperature field data can be obtained, which further reduces the fluctuations and noise in the data. Subsequently, the system will perform partition statistics on the temperature field smoothing data to obtain regional temperature characteristic data. The regional temperature characteristic data mentioned here includes the temperature mean and variance of each area in the target mobile phone. These two indicators represent the average temperature level in the area and its degree of change. Such statistical information is crucial for understanding the thermal characteristics of different parts. Based on the above regional temperature characteristic data, the system will reconstruct the temperature field on the surface of the target mobile phone to obtain reconstructed temperature field data. The purpose of temperature field reconstruction is to use all the information obtained previously to reconstruct a temperature distribution model that is as close to the actual situation as possible.This model is not just static, it also needs to reflect the temperature changes over time. Therefore, the system will perform a time-series correlation analysis on the reconstructed temperature field data to reveal the temperature correlation between different time points. By deeply mining the dynamic temperature change characteristics, the system can capture the trend and development direction of temperature changes, and combine this information with the spatial position, perform spatiotemporal fusion, and finally obtain the dynamic characteristic map of the temperature field. This picture shows how the temperature moves and evolves on the surface of the mobile phone over time, providing an important basis for deeper analysis. Finally, based on the dynamic characteristic map of the temperature field, the system will perform isothermal surface extraction, which is an important visualization step for identifying the boundaries of regions with the same temperature level. In this way, we can clearly see where high temperature or low temperature areas are formed. Next, the hot spot feature extraction is performed on the surface temperature distribution contour to obtain the final surface temperature distribution data. Hot spot feature extraction aims to highlight key areas where the temperature rises abnormally, which is particularly important for identifying potential problem sources or optimizing heat dissipation strategies. For example, in application scenarios where users play graphics-intensive games or make long video calls, parts such as processors and screens may become major heat hotspots. At this point, through the above series of carefully designed steps, the thermal management system can not only accurately monitor the temperature changes in these areas, but also predict future temperature trends and take measures in advance to prevent overheating. For example, when it is detected that the temperature around the processor is gradually rising, the system can reduce the temperature in time by increasing the working intensity of the heat dissipation unit in this area to avoid performance degradation or hardware damage due to overheating. In addition, by continuously monitoring the dynamic characteristic diagram of the temperature field, some subtle temperature anomalies can be discovered, helping engineers to continuously improve the heat dissipation design of the product and ensure that the equipment can operate stably in various complex working environments. In this way, not only the user experience is improved, but also the safety and reliability of the equipment are effectively guaranteed.

[0030] In a specific embodiment, the heat flux inversion algorithm is used to calculate the heat flux density distribution of the target mobile phone based on the surface temperature distribution data to obtain a heat flux density distribution map, including: Reconstructing the three-dimensional temperature field of the target mobile phone based on the surface temperature distribution data to obtain a three-dimensional temperature field model, and performing finite element discretization on the three-dimensional temperature field model to obtain discretized temperature field data; Solving the heat conduction equation of the target mobile phone based on the discretized temperature field data by a preset conjugate gradient method to obtain internal temperature gradient field data, and performing inverse heat conduction calculation on the internal temperature gradient field data to obtain heat flux density vector field data; By using a preset divergence theorem, heat source identification is performed on the target mobile phone based on the heat flux density vector field data to obtain a heat source position and intensity information corresponding to the heat source position, and heat source area division is performed on the target mobile phone based on the heat source position and the intensity information to obtain a heat source area distribution map; Using a heat flow inversion algorithm, based on the heat source area distribution map, heat flow lines are traced on the target mobile phone to obtain a heat flow line distribution map, and heat flux density is calculated on the heat flow line distribution map to obtain an initial heat flux density distribution map; The initial heat flux density distribution diagram is divided into heat flux density areas to obtain a heat flux density distribution diagram.

[0031] Specifically, in order to calculate the heat flux density distribution of the target mobile phone and obtain the heat flux density distribution map, a series of complex and precise steps are required. This process first reconstructs the three-dimensional temperature field of the target mobile phone based on the surface temperature distribution data to obtain a three-dimensional temperature field model. In the application scenario where the user plays graphic-intensive games or makes long video calls, the processor and screen may generate a lot of heat, which causes the temperature of different areas on the surface of the mobile phone to change. Through the surface temperature distribution data obtained previously, we can use mathematical modeling methods to expand these two-dimensional temperature information to three-dimensional space and construct a three-dimensional temperature field model that fully reflects the temperature condition inside the mobile phone. Once the three-dimensional temperature field model is established, it is necessary to perform finite element discretization on it to obtain discretized temperature field data. The finite element method is a numerical analysis tool widely used in engineering. It can divide a complex continuum into many simple units so that the physical quantity (such as temperature) in each unit can be approximated as a constant or a low-order polynomial. In this way, we can simplify the problem while ensuring accuracy, which is convenient for subsequent calculations. For the heat dissipation problem of mobile phones, the discretized temperature field data not only contains the temperature information of each discrete point, but also retains the relationship between them, which lays the foundation for the next step of solving the heat conduction equation. When the discretized temperature field data is obtained, the system will apply the preset conjugate gradient method to solve the heat conduction equation. The conjugate gradient method is an efficient iterative algorithm that is particularly suitable for solving large sparse linear equations. In this context, it is used to accurately calculate the internal temperature gradient field data. The temperature gradient is a key indicator for measuring the rate of temperature change, which reveals the direction and intensity of heat transfer. After solving the heat conduction equation, the system also needs to perform inverse heat conduction calculation on the internal temperature gradient field data to obtain the heat flux density vector field data. Inverse heat conduction calculation is a reverse solution process, the purpose of which is to derive the heat flow that causes these temperature changes from the known temperature field. The heat flux density vector field data describes in detail the specific path and flow rate of heat flowing in various places inside the mobile phone, which is crucial for understanding the location of the heat source and its range of influence. With the heat flux density vector field data, the system will further apply the preset divergence theorem to identify the heat source. The divergence theorem connects the flux of a vector field with its divergent source, and here it helps us determine which areas are the main heat sources and evaluate the location and corresponding intensity information of these heat sources. For example, during high-load tasks, the processor and screen may be the most significant sources of heat. Through heat source identification, we can accurately locate these hotspots and divide the target phone into heat source areas accordingly to obtain a heat source area distribution map. This figure clearly shows the distribution of different heat sources inside the phone and their respective influences, providing an important reference for subsequent heat dissipation strategies.Next, the system will use the heat flow inversion algorithm combined with the heat source area distribution map to track the heat flow lines of the target mobile phone to obtain the heat flow line distribution map. Heat flow line tracking is a technology that aims to depict the actual flow path of heat inside an object. In this process, each heat flow line represents the path of a stream of heat from the heat source to the dissipation. By tracking the heat flow lines, we can more intuitively understand how heat is propagated inside the mobile phone and identify the key paths that are critical to the heat dissipation effect. On this basis, the system will calculate the heat flux density of the heat flow line distribution map and finally obtain the initial heat flux density distribution map. This distribution map preliminarily reflects the concentration of heat in different areas inside the mobile phone, but in order to more accurately guide the heat dissipation measures, it needs to be further optimized. Finally, in order to ensure the effectiveness and pertinence of the heat dissipation solution, the system will divide the initial heat flux density distribution map into heat flux density areas to obtain the final heat flux density distribution map. This division process involves dividing the surface and interior of the mobile phone into several areas with similar characteristics according to different levels of heat flux density. This not only helps identify which areas are the "hot spots" that need to be cooled, but also allows a personalized cooling power allocation strategy to be developed for each area. For example, if the heat flux density around the processor is found to be abnormally high, the speed of the cooling fan in that area can be increased accordingly or the heat conduction capacity of the heat sink can be enhanced; for those areas with relatively low temperatures, the working intensity of the cooling unit can be appropriately reduced to save energy and reduce unnecessary noise. Through this fine partition management, the thermal management system can provide the necessary cooling effect without wasting resources, ensuring that the mobile phone can operate within an ideal temperature range in various application scenarios, which not only ensures stable performance but also improves user experience. In summary, from the reconstruction of the three-dimensional temperature field to the generation of the heat flux density distribution map, the entire process is closely linked, and each link is to more accurately understand and predict the thermal behavior inside the mobile phone, thereby achieving optimal heat dissipation control. This method not only improves the heat dissipation efficiency and extends the service life of the device, but also effectively avoids hardware damage caused by overheating, providing users with a smoother and safer user experience.

[0032] In a specific embodiment, the heat dissipation power of the target mobile phone is allocated based on the heat flux density distribution diagram to obtain the power control parameters of each heat dissipation unit, including: Based on the heat flux density distribution diagram, a heat dissipation unit load analysis is performed on the target mobile phone to obtain initial load distribution data, and a heat flux balance calculation is performed on the initial load distribution data to obtain a unit heat power demand map; Based on the unit thermal power demand map, a heat dissipation power constraint analysis is performed on the target mobile phone to obtain a power constraint condition set, and the power constraint condition set is decomposed by Lagrange multipliers to obtain power allocation boundary parameters; wherein the power allocation boundary parameters include a maximum power threshold and a minimum power threshold of the heat dissipation unit; Performing multi-objective optimization on the power allocation boundary parameters to obtain an initial power allocation scheme, and performing multi-dimensional evaluation on the initial power allocation scheme by using the Pareto optimality criterion to obtain a power allocation evaluation index; wherein the power allocation evaluation index includes a heat dissipation efficiency index and a power consumption balance index; Using a mixed integer programming algorithm, based on the power allocation evaluation index, dynamically allocate heat dissipation power to the target mobile phone to obtain a dynamic power allocation sequence; The dynamic power allocation sequence is optimally controlled and solved by Hamilton-Jacobi equation to obtain a power control trajectory, and the power control trajectory is piecewise linearized to obtain a discretized power control point set; wherein the discretized power control point set includes a power adjustment step and a control cycle parameter; Based on the discretized power control point set, power parameter mapping is performed on each heat dissipation unit of the target mobile phone to obtain power control parameters of each heat dissipation unit.

[0033] Specifically, in order to achieve the heat dissipation power allocation of the target mobile phone based on the heat flux density distribution map to obtain the power control parameters of each heat dissipation unit, this process requires a series of precise and interlocking steps. First, the system will perform heat dissipation unit load analysis on the target mobile phone based on the heat flux density distribution map to obtain initial load distribution data. This step is to understand the workload of each heat dissipation unit under the current thermal environment. For example, in the application scenario where the user plays a graphic-intensive game or makes a long video call, the processor and screen and other parts may generate a lot of heat, which is clearly displayed through the heat flux density distribution map. Through in-depth analysis of this information, we can determine which heat dissipation units are under high load and which are relatively relaxed. After having the initial load distribution data, the system will perform a heat flux balance calculation on it to obtain a unit thermal power demand map. Heat flux balance calculation is a method to ensure energy conservation within the system, which can help us accurately evaluate the energy consumed by each heat dissipation unit to maintain temperature stability. Through this calculation, the working intensity of each heat dissipation component under different conditions can be accurately quantified, and then a unit thermal power demand map can be drawn. This map not only shows the demand level of each heat dissipation unit, but also reveals the relationship between them, which is crucial for formulating a reasonable heat dissipation strategy. Next, based on the unit thermal power demand map, the system will perform a heat dissipation power constraint analysis on the target mobile phone to obtain a power constraint set. The power constraint set is a limitation on the operating range of the heat dissipation system, which ensures that the operation of all heat dissipation units does not exceed their physical limits or violate design specifications. In order to handle these constraints more effectively, the system will perform Lagrange multiplier decomposition on the power constraint set and finally obtain the power allocation boundary parameters. The power allocation boundary parameters here include the maximum power threshold and the minimum power threshold of the heat dissipation unit. These two indicators define the acceptable power range of each heat dissipation unit, which prevents damage caused by excessive use and avoids waste of resources. Once the power allocation boundary parameters are determined, the system will enter the multi-objective optimization solution stage to obtain the initial power allocation plan. In this process, the system must not only consider the heat dissipation efficiency, but also take into account the power consumption balance, and strive to find an optimal balance point. The Pareto optimality criterion plays a key role here. It allows us to find non-inferior solutions between multiple conflicting objectives, that is, those solutions that cannot be further improved without compromising other objectives. In this way, we can obtain a set of power allocation evaluation indicators that meet the requirements of heat dissipation efficiency and power consumption balance, which provide a basis for subsequent dynamic adjustments. Subsequently, the system will use a mixed integer programming algorithm to dynamically allocate the heat dissipation power of the target mobile phone based on the above power allocation evaluation indicators to obtain a dynamic power allocation sequence.Mixed integer programming is an effective tool for solving discrete decision problems. It can handle continuous variables (such as power) and discrete variables (such as switch states) at the same time, making the cooling strategy more flexible and adaptable. The dynamic power allocation sequence reflects the power settings of the cooling unit that are adjusted over time, ensuring that the system can maintain optimal performance under different working conditions. Finally, in order to make these dynamic adjustments accurate, the system will solve the dynamic power allocation sequence through the Hamilton-Jacobi equation to obtain the power control trajectory. The Hamilton-Jacobi equation is a classic mathematical model that is suitable for describing the optimal path selection problem of the system. By solving the dynamic power allocation sequence, we obtain the ideal path that describes the power change of the cooling unit - the power control trajectory. However, it is not realistic to directly apply such a continuous trajectory in actual operation, so it is also necessary to piecewise linearize it to obtain a discretized power control point set. These discretized power control point sets include power adjustment step size and control cycle parameters, which define the specific amplitude and frequency of each adjustment, ensuring that the cooling unit can reach the expected power level within a specified time interval. Based on the discretized power control point set, the system finally performs power parameter mapping on each cooling unit of the target mobile phone and obtains the power control parameters of each cooling unit. This means that each cooling unit will receive a specific power setting value according to its own thermal condition and overall cooling demand. For example, when the temperature rise around the processor is detected, the corresponding cooling fan may receive an instruction to increase the speed; while for those areas with lower temperatures, the working intensity of the heat sink may be reduced. This fine power parameter mapping ensures that the cooling system can not only effectively deal with hot spots, but also save energy, reduce noise, and provide a more comfortable user experience. In summary, from the analysis of the heat dissipation unit load to the final power parameter mapping, the entire cooling power allocation process involves a series of complex transformations from static to dynamic, from theory to practice. Through scientific methods and advanced algorithms, the system not only achieves precise control of the internal thermal behavior of the mobile phone, but also provides users with a stable and energy-saving use environment. This method not only improves the overall performance of the device, but also extends its service life, providing a new solution for thermal management of smart mobile devices.

[0034] In a specific embodiment, the heat dissipation power constraint analysis of the target mobile phone based on the unit thermal power demand map is performed to obtain a power constraint condition set, including: The unit thermal power demand map is segmented into power regions by using a spectral clustering algorithm to obtain a power partition sequence, and a heat flow conservation calculation is performed on the power partition sequence to obtain a regional power balance equation; Based on the regional power balance equation, a thermal network is constructed for the target mobile phone to obtain a heat dissipation power transfer network, and a topological analysis is performed on the heat dissipation power transfer network to obtain a power transfer path set; Extracting features from the power transfer path set by singular value decomposition to obtain a transfer feature matrix, and allocating boundary constraints to the transfer feature matrix to obtain a power allocation constraint set; Based on the power allocation constraint set, nonlinear programming is performed on the target mobile phone to obtain a nonlinear constraint equation group, and the nonlinear constraint equation group is solved by an interior point method to obtain a power adjustment parameter group; Performing variational analysis on the power regulation parameter group to obtain an optimal control equation, and solving the optimal control equation by using the Pontryagin maximum principle to obtain a control constraint sequence; Constraint integration is performed based on the control constraint sequence to obtain a power constraint condition set.

[0035] Specifically, in order to perform heat dissipation power constraint analysis on the target mobile phone based on the unit thermal power demand map and finally obtain the power constraint condition set, this process requires a series of precise and complex steps. First, the system will segment the unit thermal power demand map into power regions through the spectral clustering algorithm to obtain the power partition sequence. Spectral clustering is an advanced data mining technology that can divide the entire data set into several clusters with internal similarities and external differences based on the similarity between data points. In the context of heat dissipation power allocation, this algorithm can help us identify clusters of heat dissipation units that show similar characteristics in thermal power demand. For example, in application scenarios where users play graphic-intensive games or make long video calls, parts such as the processor and screen may generate a lot of heat. These hot spots will be identified by the spectral clustering algorithm and classified into one category, while other relatively low-temperature areas will be classified into another category. Once the power partition sequence is determined, the system will further perform heat flux conservation calculations on it to obtain the regional power balance equation. Heat flux conservation calculations are the process of ensuring that the energy input in each region is equal to the output energy plus the stored energy, which ensures the energy balance of the system. By performing a detailed heat flow analysis on the heat dissipation units within each power partition, we can establish a set of regional power balance equations that describe the basic laws of heat transfer between different regions. This step is crucial to understanding the thermal characteristics of each region because it reveals which regions are the main sources of heat and which regions are the main receivers of heat. Next, based on the regional power balance equations, the system will construct a thermal network for the target phone to obtain a heat dissipation power transfer network. The heat dissipation power transfer network is an abstract model that simulates the flow path of heat between different components inside the phone. By performing a topological analysis on this network, we can identify all possible sets of power transfer paths. Topological analysis not only considers how the network structure is connected, but also evaluates the importance of each path and its impact on the overall thermal behavior. For example, some paths may be the main path for heat to flow from the processor to the heat sink, while other paths may only play a supporting role. Knowing this information helps optimize the cooling strategy to ensure that the heat on the critical path can be dissipated quickly and effectively. Once the set of power transfer paths is obtained, the system will extract features from these paths through singular value decomposition (SVD) to obtain a transfer feature matrix. Singular value decomposition is a linear algebra tool that can reveal the main patterns and structures in the data set. In this process, the transfer characteristic matrix concentrates on the key characteristics of the power transfer path, such as direction, strength, and frequency. Subsequently, the system will assign boundary constraints to the transfer characteristic matrix to obtain a power allocation constraint set. The boundary constraint assignment here is to set the maximum and minimum power limits that each cooling unit must comply with within its operating range to prevent overuse or waste of resources. Based on the above power allocation constraint set, the system will perform nonlinear programming to obtain a set of nonlinear constraint equations.Nonlinear programming is a mathematical optimization method that is suitable for dealing with problems that contain nonlinear relationships. In this way, we can more accurately describe the complex interactions between cooling units and ensure that they work together under various constraints. To solve these nonlinear constraint equations, the system uses an efficient numerical algorithm called the interior point method, which ultimately results in a set of power regulation parameters. These parameters define the specific power settings of each cooling unit so that they can achieve the best cooling effect without violating any constraints. Further, the system will perform variational analysis on the power regulation parameter set to obtain the optimal control equation. Variational analysis is a method for finding the extreme values ​​of a function, which helps us identify control strategies that can maximize cooling efficiency while minimizing energy consumption. The Pontryagin maximum principle plays an important role in this case. It provides a theoretical framework that allows us to find the most effective cooling path by solving the optimal control equation. In this way, we obtain a sequence of control constraints that specifies in detail the power changes of each cooling unit at different time points. Finally, constraint integration is performed based on the control constraint sequence to obtain the final set of power constraints. Constraint integration refers to merging all individual control constraints into a unified whole to ensure that all cooling units can operate in a coordinated and consistent framework. This final set of power constraints is not only the basis for heat dissipation power allocation, but also the key to ensuring stable system operation. For example, when the temperature around the processor is detected to rise, the cooling fan can quickly adjust the speed according to these conditions; and for those areas with lower temperatures, the working intensity of the heat sink can be appropriately reduced. This fine power management not only improves the heat dissipation efficiency, but also saves energy, reduces noise, and provides users with a smoother and safer user experience. In summary, from power area segmentation to the final constraint integration, the entire heat dissipation power constraint analysis process involves a series of complex transformations from data analysis to mathematical modeling to optimization solution. Through scientific methods and advanced algorithms, the system not only achieves precise control of the internal thermal behavior of the mobile phone, but also provides users with a stable and energy-saving use environment. This method not only improves the overall performance of the device, but also extends its service life, providing a new solution for the thermal management of smart mobile devices.

[0036] In a specific embodiment, the heat flux conservation calculation is performed on the power partition sequence to obtain the regional power balance equation, including: Performing area decomposition on the power partition sequence by Green-Gauss theorem to obtain regional boundary flux, and performing divergence calculation on the regional boundary flux to obtain a heat flux distribution vector; Based on the heat flux distribution vector, the target mobile phone is subjected to partition power integration to obtain a regional power density field, and the regional power density field is subjected to divergence analysis by Gaussian divergence theorem to obtain a power flux field; Expanding the power flux field according to the first law of thermodynamics to obtain a group of energy conservation equations, and constructing constraint conditions for the group of energy conservation equations by Lagrange multiplier method to obtain a power constraint expression; wherein the power constraint expression includes a heat flux conduction term, a heat capacity integral term, and a boundary condition term; Based on the power constraint expression, the target mobile phone is solved by variational method to obtain the Euler-Lagrange equation, and the Euler-Lagrange equation is analyzed for symmetry by Noether's theorem to obtain a conservation quantity sequence; wherein the conservation quantity sequence includes energy conservation quantity, momentum conservation quantity and heat flow conservation quantity; Performing spectral analysis on the conserved quantity sequence through Fourier series expansion to obtain a harmonic component set, and constraining the harmonic component set by the second law of thermodynamics to obtain an entropy generation rate function; The regional power balance of the target mobile phone is derived based on the entropy generation rate function to obtain a regional power balance equation.

[0037] Specifically, in order to realize the heat flux conservation calculation of the power partition sequence to obtain the regional power balance equation, this process requires a series of precise and interlocking steps. First, the system performs area decomposition of the power partition sequence through the Green-Gauss theorem to obtain the regional boundary flux. In application scenarios where users play graphics-intensive games or make long video calls, parts such as processors and screens may generate a lot of heat, which causes significant changes in temperature in different regions. The Green-Gauss theorem is a method for converting volume integrals into surface integrals, and here it helps us transfer the heat flow information in each power partition from the inside to the boundary. By calculating the divergence of the flux at the boundaries of these regions, we can obtain the heat flux distribution vector. This vector not only describes the flow direction and intensity of heat at the boundaries of each region, but also reveals how heat is transferred from one region to another. With the heat flux distribution vector, the system will further perform partition power integration on the target mobile phone based on this to obtain the regional power density field. Partition power integration is the process of cumulative summation of the heat flux distribution vector in each region, which can provide a more comprehensive perspective to understand the energy state of each region. The power flux field is then obtained by performing a divergence analysis on the regional power density field using the Gaussian divergence theorem. The Gaussian divergence theorem acts as a bridge here, connecting the relationship between energy changes within a volume and surface flux. The power flux field shows the specific path and intensity of heat flow between different regions, which is critical to understanding the thermal behavior of the entire system. For example, when the temperature around the processor rises, the power flux field can clearly show how heat is transferred from the processor to the heat sink and finally dissipated to the outside environment. Next, the system will expand the power flux field using the first law of thermodynamics to obtain the energy conservation equations. The first law of thermodynamics is the basic principle of energy conservation, which states that in a closed system, energy can neither be created nor destroyed, but can only be converted from one form to another. By applying this principle, we can establish a set of energy conservation equations that describe in detail the transfer of heat between various regions. To ensure that these equations can accurately reflect the actual situation, the system constructs constraints on them through the Lagrange multiplier method, and finally obtains the power constraint expression. The power constraint expression here includes the heat flux conduction term, the heat capacity integral term and the boundary condition term, which together define the basic rules that must be followed in the heat transfer process. Based on the above power constraint expression, the system will perform a variational solution on the target mobile phone to obtain the Euler-Lagrange equation. Variational solution is a mathematical method that solves optimization problems by finding the extreme values ​​of a function. In this context, the Euler-Lagrange equation provides a theoretical framework for finding the optimal heat dissipation path. Furthermore, the system performs a symmetry analysis on the Euler-Lagrange equation through Noether's theorem and obtains a sequence of conserved quantities.Noether's theorem reveals the profound connection between symmetry and conservation laws in physical systems. The sequence of conservation quantities here includes energy conservation, momentum conservation, and heat flow conservation. These conservation quantities not only reflect the intrinsic characteristics of the system, but also provide important references for subsequent analysis. In order to have a deeper understanding of the changing laws of these conservation quantities, the system performs spectral analysis on the conservation quantity sequence through Fourier series expansion to obtain a set of harmonic components. Fourier series expansion is a technique that represents a periodic function as the sum of sine and cosine functions, which can help us identify the main frequency components in the signal. By constraining the harmonic component set with the second law of thermodynamics, we can obtain the entropy generation rate function. The second law of thermodynamics states that in natural processes, the total entropy of the system always increases. This step aims to evaluate the impact of different heat dissipation strategies on the system entropy. The entropy generation rate function quantifies the degree of irreversible loss during heat transfer, which is an important indicator for measuring heat dissipation efficiency. Finally, based on the entropy generation rate function, the system will derive the regional power balance of the target mobile phone to obtain the regional power balance equation. The regional power balance equation takes into account all known information, including heat flux distribution, power flux, energy conservation, and entropy generation, and sets the power allocation rules that each area must follow. For example, when the temperature rise around the processor is detected, the cooling fan can quickly adjust the speed according to these equations; and for those areas with lower temperatures, the working intensity of the heat sink can be appropriately reduced. This sophisticated power management not only improves the heat dissipation efficiency, but also saves energy, reduces noise, and provides users with a smoother and safer user experience. In summary, from area decomposition to the final regional power balance derivation, the entire heat flux conservation calculation process involves a series of complex transformations from data analysis to mathematical modeling to the application of physical principles. Through scientific methods and advanced algorithms, the system not only achieves precise control of the internal thermal behavior of the mobile phone, but also provides users with a stable and energy-saving use environment. This approach not only improves the overall performance of the device, but also extends its service life, providing a new solution for thermal management of smart mobile devices. In this way, even during high-intensity task processing, such as graphics-intensive games or long video calls, the mobile phone can be kept running within an ideal temperature range, ensuring the comfort of the user and the safety of the device.

[0038] In a specific embodiment, the step of performing thermal management and heat dissipation on the target mobile phone based on the power control parameter to achieve a target heat dissipation state of the target mobile phone includes: Dynamically allocating power to each cooling unit of the target mobile phone according to the power control parameter to obtain a real-time power control instruction for each cooling unit; Performing time sequence encoding on the real-time power control instruction to obtain a power control instruction sequence; Performing power control signal modulation on each heat dissipation unit of the target mobile phone based on the power control instruction sequence to obtain a modulated power control signal; Carrier synchronization is performed on the modulated power control signal to obtain a synchronous power control signal; Through a preset multiplexing technology, heat management and heat dissipation are performed on each heat dissipation unit of the target mobile phone based on the synchronous power control signal, so that the target mobile phone is in a target heat dissipation state.

[0039] Specifically, in order to achieve thermal management and heat dissipation of the target mobile phone based on the power control parameters to ensure that the target mobile phone is in the target heat dissipation state, this process requires a series of precise and coordinated steps. First, the system dynamically allocates power to each heat dissipation unit of the target mobile phone through the power control parameters, thereby obtaining real-time power control instructions for each heat dissipation unit. In application scenarios where users play graphic-intensive games or make long video calls, parts such as the processor and screen may generate a lot of heat, which causes significant changes in the temperature of different areas. The power control parameters are calculated based on the previous complex heat flux density distribution map, and they provide specific power setting values ​​for each heat dissipation unit. For example, when the temperature around the processor is detected to rise, the cooling fan may receive an instruction to increase the speed; while for those areas with lower temperatures, the working intensity of the heat sink may be reduced. This dynamic power allocation ensures that the heat dissipation resources can be concentrated where they are most needed, which not only improves the heat dissipation efficiency but also avoids unnecessary energy consumption. Once the real-time power control instructions are determined, the system will perform time-series encoding on these instructions to obtain a power control instruction sequence. Time-series encoding is a technology that converts information into time series signals, and here it is used to ensure that each heat dissipation unit can receive the corresponding power setting command at the right time. In this way, we can precisely control the working cycle of each cooling unit to ensure that they are adjusted according to a preset schedule. For example, during a high-load task, some cooling units may need to adjust power frequently, while other units can maintain a relatively stable output. The power control instruction sequence not only contains the specific operating instructions for each cooling unit, but also implies the collaborative working relationship between them, which is crucial to maintaining the overall stability of the system. Next, based on the power control instruction sequence, the system modulates the power control signal of each cooling unit of the target mobile phone to obtain a modulated power control signal. Power control signal modulation refers to converting the original power control instruction into a form suitable for transmission so that they can be effectively communicated to each cooling unit in the actual environment. In this process, the modulation technology can select different methods according to specific needs, such as amplitude modulation, frequency modulation or phase modulation. The modulated power control signal not only retains all the information of the original instruction, but also enhances its anti-interference ability and transmission distance. For example, in a noisy electromagnetic environment, the modulated signal can be transmitted to the cooling unit more stably, ensuring that each instruction can be executed accurately and without error. After having the modulated power control signal, the system will further perform carrier synchronization processing on it to obtain a synchronous power control signal. Carrier synchronization is a technology that ensures that the receiving end and the transmitting end work on the same time reference. In this context, it ensures that all cooling units can receive and respond to instructions from the control system at the same time.The generation of synchronous power control signals involves precise time calibration and frequency matching, which is particularly critical for the efficient operation of multi-cooling unit systems. Through carrier synchronization, we can ensure that even under complex working conditions, each cooling unit can adjust its power according to a unified schedule, avoiding coordination problems caused by time differences. Finally, through the preset multiplexing technology, the cooling units of the target mobile phone are thermally managed and cooled based on the synchronous power control signal to achieve the target cooling state of the target mobile phone. Multiplexing technology allows multiple independent data streams to be transmitted simultaneously on a shared channel, thereby improving communication efficiency. In thermal management, this means that we can use limited physical connections to control multiple cooling units without having to wire each unit separately. This approach not only simplifies hardware design, but also reduces cost and complexity. For example, through a multiplexer, we can distribute the synchronous power control signal to all cooling units, ensuring that they can receive the same instructions at the same time and adjust their respective working states accordingly. In this way, the entire cooling system is like a coordinated whole, and each cooling unit plays its due role and works together to maintain the mobile phone in an ideal temperature range. In summary, from dynamic power allocation to the final application of multiplexing technology, the entire thermal management and heat dissipation process involves a series of complex transformations from data processing to signal transmission to system integration. Through scientific methods and advanced algorithms, the system not only achieves precise control of the internal thermal behavior of the mobile phone, but also provides users with a stable and energy-saving use environment. This approach not only improves the overall performance of the device, but also extends its service life, providing a new solution for thermal management of smart mobile devices. In this way, even during high-intensity task processing, such as graphics-intensive games or long video calls, the mobile phone can remain in an ideal temperature range, ensuring the comfort of the user and the safety of the device.

[0040] The above describes the mobile phone thermal management and heat dissipation method in the embodiment of the present invention. The following describes the mobile phone thermal management and heat dissipation system in the embodiment of the present invention. Figure 2 In one embodiment of the present invention, a mobile phone thermal management and heat dissipation system includes: The acquisition module 21 is used to perform multi-point temperature scanning and acquisition on the surface of the target mobile phone through a thermal imaging sensor array to obtain surface temperature distribution data; A calculation module 22, configured to calculate the heat flux density distribution of the target mobile phone based on the surface temperature distribution data by using a heat flux inversion algorithm to obtain a heat flux density distribution map; wherein the heat flux density distribution map includes heat transfer direction and intensity data; An allocation module 23, configured to allocate heat dissipation power to the target mobile phone based on the heat flux density distribution diagram, and obtain power control parameters of each heat dissipation unit; The heat dissipation module 24 is used to perform thermal management and heat dissipation on the target mobile phone based on the power control parameters, so as to achieve a target heat dissipation state for the target mobile phone.

[0041] In this embodiment, for the specific implementation of each unit in the above system embodiment, please refer to the above method embodiment, which will not be repeated here.

[0042] Reference Figure 3 The present invention also provides a computer device in an embodiment, wherein the internal structure of the computer device can be as follows: Figure 3 As shown. The computer device includes a processor, a memory, a display screen, an input device, a network interface and a database connected through a system bus. Among them, the processor designed by the computer is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the corresponding data in this embodiment. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the above method is implemented.

[0043] Those skilled in the art will understand that Figure 3 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied.

[0044] An embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the above method is implemented. It can be understood that the computer-readable storage medium in this embodiment can be a volatile readable storage medium or a non-volatile readable storage medium.

[0045] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media provided by the present invention and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double-speed data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM.

[0046] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0047] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A mobile phone thermal management and heat dissipation method, characterized in that: The following steps are involved: The surface of the target mobile phone is scanned and collected at multiple points by a thermal imaging sensor array to obtain surface temperature distribution data; Using a heat flow inversion algorithm, based on the surface temperature distribution data, heat flow density distribution calculation is performed on the target mobile phone to obtain a heat flow density distribution map; Based on the heat flux density distribution diagram, heat dissipation power is allocated to the target mobile phone to obtain power control parameters of each heat dissipation unit; The target mobile phone is thermally managed and cooled based on the power control parameters, so that the target mobile phone is in a target cooling state.

2. The mobile phone thermal management and heat dissipation method according to claim 1, characterized in that: The method of performing multi-point temperature scanning and acquisition on the surface of the target mobile phone through the thermal imaging sensor array to obtain surface temperature distribution data includes: Performing grid scanning and sampling on the surface of the target mobile phone through a preset thermal imaging sensor array to obtain raw temperature sampling data, and performing Gaussian filtering on the raw temperature sampling data to obtain filtered temperature dot matrix data; Using a bicubic spline interpolation algorithm, a surface temperature interpolation calculation is performed on the target mobile phone based on the filtered temperature lattice data to obtain initial temperature field data, and boundary correction is performed on the initial temperature field data to obtain corrected temperature field data; Performing local weighted regression analysis on the corrected temperature field data to obtain temperature field smoothing data, and performing partition statistics on the temperature field smoothing data to obtain regional temperature characteristic data; wherein the regional temperature characteristic data includes the temperature mean and variance of each region in the target mobile phone; Based on the regional temperature characteristic data, reconstructing the temperature field of the surface of the target mobile phone to obtain reconstructed temperature field data; Performing time series correlation analysis on the reconstructed temperature field data to obtain dynamic temperature change characteristics, and performing spatiotemporal fusion on the dynamic temperature change characteristics to obtain a temperature field dynamic characteristic diagram; Isothermal surfaces are extracted based on the dynamic characteristic diagram of the temperature field to obtain the surface temperature distribution contour, and hot spot features are extracted from the surface temperature distribution contour to obtain surface temperature distribution data.

3. The mobile phone thermal management and heat dissipation method according to claim 1, characterized in that: The heat flux inversion algorithm is used to calculate the heat flux density distribution of the target mobile phone based on the surface temperature distribution data to obtain a heat flux density distribution map, including: Reconstructing the three-dimensional temperature field of the target mobile phone based on the surface temperature distribution data to obtain a three-dimensional temperature field model, and performing finite element discretization on the three-dimensional temperature field model to obtain discretized temperature field data; Solving the heat conduction equation of the target mobile phone based on the discretized temperature field data by a preset conjugate gradient method to obtain internal temperature gradient field data, and performing inverse heat conduction calculation on the internal temperature gradient field data to obtain heat flux density vector field data; By using a preset divergence theorem, heat source identification is performed on the target mobile phone based on the heat flux density vector field data to obtain a heat source position and intensity information corresponding to the heat source position, and heat source area division is performed on the target mobile phone based on the heat source position and the intensity information to obtain a heat source area distribution map; Using a heat flow inversion algorithm, based on the heat source area distribution map, heat flow lines are traced on the target mobile phone to obtain a heat flow line distribution map, and heat flux density is calculated on the heat flow line distribution map to obtain an initial heat flux density distribution map; The initial heat flux density distribution diagram is divided into heat flux density areas to obtain a heat flux density distribution diagram.

4. The mobile phone thermal management and heat dissipation method according to claim 1, characterized in that: The distributing the heat dissipation power of the target mobile phone based on the heat flux density distribution diagram to obtain the power control parameters of each heat dissipation unit includes: Based on the heat flux density distribution diagram, a heat dissipation unit load analysis is performed on the target mobile phone to obtain initial load distribution data, and a heat flux balance calculation is performed on the initial load distribution data to obtain a unit heat power demand map; Based on the unit thermal power demand map, a heat dissipation power constraint analysis is performed on the target mobile phone to obtain a power constraint condition set, and the power constraint condition set is decomposed by Lagrange multipliers to obtain power allocation boundary parameters; wherein the power allocation boundary parameters include a maximum power threshold and a minimum power threshold of the heat dissipation unit; Performing multi-objective optimization on the power allocation boundary parameters to obtain an initial power allocation scheme, and performing multi-dimensional evaluation on the initial power allocation scheme by using the Pareto optimality criterion to obtain a power allocation evaluation index; wherein the power allocation evaluation index includes a heat dissipation efficiency index and a power consumption balance index; Using a mixed integer programming algorithm, based on the power allocation evaluation index, dynamically allocate heat dissipation power to the target mobile phone to obtain a dynamic power allocation sequence; The dynamic power allocation sequence is optimally controlled and solved by Hamilton-Jacobi equation to obtain a power control trajectory, and the power control trajectory is piecewise linearized to obtain a discretized power control point set; wherein the discretized power control point set includes a power adjustment step and a control cycle parameter; Based on the discretized power control point set, power parameter mapping is performed on each heat dissipation unit of the target mobile phone to obtain power control parameters of each heat dissipation unit.

5. The mobile phone thermal management and heat dissipation method according to claim 4, characterized in that: The heat dissipation power constraint analysis of the target mobile phone is performed based on the unit thermal power demand map to obtain a power constraint condition set, including: The unit thermal power demand map is segmented into power regions by using a spectral clustering algorithm to obtain a power partition sequence, and a heat flow conservation calculation is performed on the power partition sequence to obtain a regional power balance equation; Based on the regional power balance equation, a thermal network is constructed for the target mobile phone to obtain a heat dissipation power transfer network, and a topological analysis is performed on the heat dissipation power transfer network to obtain a power transfer path set; Extracting features from the power transfer path set by singular value decomposition to obtain a transfer feature matrix, and allocating boundary constraints to the transfer feature matrix to obtain a power allocation constraint set; Based on the power allocation constraint set, nonlinear programming is performed on the target mobile phone to obtain a nonlinear constraint equation group, and the nonlinear constraint equation group is solved by an interior point method to obtain a power adjustment parameter group; Performing variational analysis on the power regulation parameter group to obtain an optimal control equation, and solving the optimal control equation by using the Pontryagin maximum principle to obtain a control constraint sequence; Constraint integration is performed based on the control constraint sequence to obtain a power constraint condition set.

6. The mobile phone thermal management and heat dissipation method according to claim 5, characterized in that: The heat flow conservation calculation is performed on the power partition sequence to obtain the regional power balance equation, including: Performing area decomposition on the power partition sequence by Green-Gauss theorem to obtain regional boundary flux, and performing divergence calculation on the regional boundary flux to obtain a heat flux distribution vector; Performing partition power integration on the target mobile phone based on the heat flux distribution vector to obtain a regional power density field, and performing divergence analysis on the regional power density field using the Gaussian divergence theorem to obtain a power flux field; Expanding the power flux field according to the first law of thermodynamics to obtain a group of energy conservation equations, and constructing constraint conditions for the group of energy conservation equations by Lagrange multiplier method to obtain a power constraint expression; wherein the power constraint expression includes a heat flux conduction term, a heat capacity integral term, and a boundary condition term; Based on the power constraint expression, the target mobile phone is solved by variational method to obtain the Euler-Lagrange equation, and the Euler-Lagrange equation is analyzed for symmetry by Noether's theorem to obtain a conservation quantity sequence; wherein the conservation quantity sequence includes energy conservation quantity, momentum conservation quantity and heat flow conservation quantity; Performing spectral analysis on the conserved quantity sequence through Fourier series expansion to obtain a harmonic component set, and constraining the harmonic component set by the second law of thermodynamics to obtain an entropy generation rate function; The regional power balance of the target mobile phone is derived based on the entropy generation rate function to obtain a regional power balance equation.

7. The mobile phone thermal management and heat dissipation method according to claim 1, characterized in that: The step of performing thermal management and heat dissipation on the target mobile phone based on the power control parameter to achieve a target heat dissipation state of the target mobile phone includes: Dynamically allocating power to each cooling unit of the target mobile phone according to the power control parameter to obtain a real-time power control instruction for each cooling unit; Performing time sequence encoding on the real-time power control instruction to obtain a power control instruction sequence; Performing power control signal modulation on each heat dissipation unit of the target mobile phone based on the power control instruction sequence to obtain a modulated power control signal; Carrier synchronization is performed on the modulated power control signal to obtain a synchronous power control signal; Through a preset multiplexing technology, heat management and heat dissipation are performed on each heat dissipation unit of the target mobile phone based on the synchronous power control signal, so that the target mobile phone is in a target heat dissipation state.

8. A mobile phone thermal management and heat dissipation device, characterized in that: include: The acquisition module is used to perform multi-point temperature scanning and acquisition on the surface of the target mobile phone through a thermal imaging sensor array to obtain surface temperature distribution data; A calculation module, configured to calculate the heat flux density distribution of the target mobile phone based on the surface temperature distribution data by using a heat flux inversion algorithm to obtain a heat flux density distribution map; wherein the heat flux density distribution map includes heat transfer direction and intensity data; An allocation module, configured to allocate heat dissipation power to the target mobile phone based on the heat flux density distribution diagram, and obtain power control parameters of each heat dissipation unit; The heat dissipation module is used to perform thermal management and heat dissipation on the target mobile phone based on the power control parameter to achieve a target heat dissipation state for the target mobile phone.

9. A computer device comprising a memory and a processor, wherein a computer program is stored in the memory, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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