A notebook computer waste heat recovery system and method based on thermoelectric conversion effect

Abstract

This invention relates to the field of thermoelectric conversion and discloses a waste heat recovery system and method for laptop computers based on the thermoelectric conversion effect. The system includes: an intelligent detection module that detects the internal temperature of the laptop computer through multiple temperature sensors and feeds it back to the power management chip; a thermal management module that dynamically adjusts the system's operating area; a waste heat recovery module that increases the temperature difference between the heat-generating area and the cold end, and uses a target power generation unit to convert the heat energy of the laptop computer during operation into electrical energy; a current stabilization module that converts the unstable low-voltage DC output into stable electrical energy; an intelligent energy storage control module that uses an energy storage device to store stable electrical energy, displays the energy recovery status on the laptop computer, and automatically determines the usage mode of the recovered energy according to user needs; and an analysis and reminder module that performs user behavior analysis and laptop computer component status analysis, performs intelligent configuration of the power generation unit, and issues component status reminders based on the component status analysis results.

Description

Technical Field

[0001] This invention relates to the field of thermoelectric conversion, and more particularly to a waste heat recovery system and method for laptop computers based on the thermoelectric conversion effect. Background Technology

[0002] During high-load operation of laptops, core hardware components such as the central processing unit (CPU), graphics processing unit (GPU), and power management module continuously release a large amount of waste heat, the heat density of which increases exponentially with performance demands. Traditional cooling architectures use a physical combination of metal heat pipes, aluminum heat sinks, and centrifugal fans to simply expel heat from the chassis through unidirectional conduction and forced convection. This linear cooling mode only focuses on alleviating the pressure of instantaneous temperature rise, but ignores the energy conversion potential contained in waste heat. Under prolonged high-load scenarios, the unidirectional dissipation of heat not only accelerates the efficiency decline caused by the aging of the cooling system, but also creates a continuous energy loss loop inside the device—electrical energy is converted into computing power by the chip, and ultimately dissipates into the environment in the form of disordered heat energy. This extensive "generation-emission" thermal management logic neither attempts to build a reverse coupling link between heat energy and electrical energy, nor does it convert local high temperatures into added value that can serve the system itself. It may even form hot spots on the surface of the chassis, affecting the user experience and exposing the limitations of traditional solutions in terms of energy cycle concepts and sustainable design dimensions. Regarding the above situation, the problems are as follows:

[0003] 1. Existing cooling methods for laptops have limited heat dissipation efficiency, resulting in ineffective utilization of heat energy, exacerbating greenhouse gas emissions and thermal pollution, further increasing the environmental burden and wasting resources;

[0004] 2. If heat energy recovery is implemented, the additional hardware such as the TEG (thermoelectric conversion module) array and energy storage module used will take up internal space in the laptop, which may reduce battery capacity or sacrifice a thin and light design.

[0005] 3. Due to its size, laptops generate relatively little electrical energy from internal temperature differences, requiring intelligent charging and discharging management strategies to make effective use of it. Summary of the Invention

[0006] To address the problems mentioned above, this invention provides a waste heat recovery system and method for laptop computers based on thermoelectric conversion effects, thereby solving the aforementioned problems.

[0007] A waste heat recovery system for laptop computers based on thermoelectric conversion effect, characterized in that it comprises:

[0008] The intelligent detection module is used to detect the internal temperature of the laptop through multiple temperature sensors located in high-heat areas inside the laptop and feed it back to the power management chip;

[0009] The thermal management module is used to dynamically adjust the system's working area based on temperature sensor data using the power management chip, and to issue working instructions by selecting the area with the largest current temperature difference.

[0010] The waste heat recovery module is used to increase the temperature difference between the area and the cold end by using a thermally conductive silicone layer and micro heat dissipation fins. According to the working instructions, it determines the target power generation unit in the area and uses the target power generation unit to convert the heat energy of the laptop during operation into electrical energy.

[0011] A current stabilization module is used to convert the unstable low-voltage DC power output from the target power generation unit into stable electrical energy using a rectifier circuit and a DC-DC boost chip;

[0012] The intelligent energy storage control module is used to use the stable electrical energy stored by the energy storage device, display the energy recovery status on the laptop, and automatically determine the usage mode of the recovered electrical energy according to user needs.

[0013] The analysis and alert module is used to perform user behavior analysis based on power generation status, analyze the status of the laptop components based on temperature detection results, intelligently configure the power generation unit according to the behavior analysis results, and issue component status alerts according to the component status analysis results.

[0014] Preferably, the intelligent detection module includes:

[0015] The determination submodule is used to detect the heat generation of multiple components of the laptop during operation using a temperature detection device, determine the heat-generating components and high-temperature locations of the laptop, and determine the location of the temperature sensor based on the high-temperature locations.

[0016] The detection submodule is used to detect the internal temperature of the laptop during operation using the multiple temperature sensors, and generate multiple temperature detection signals at different locations to be fed back to the power management chip.

[0017] The parsing submodule is used to parse the temperature detection signal using the power management chip to determine the internal temperature distribution of the laptop during operation.

[0018] Preferably, the thermal management module includes:

[0019] The acquisition submodule is used to acquire the internal temperature distribution of the laptop during operation and update it dynamically in real time.

[0020] The temperature difference determination submodule is used to determine the current temperature reference value based on the internal cold end temperature of the laptop, and to determine the temperature difference between the internal temperature of the laptop and the cold end based on the current internal temperature distribution during laptop operation.

[0021] The judgment submodule is used to determine the high heat generation area with the largest heat output inside the laptop in real time based on the temperature difference, and to determine whether the power generation efficiency of the high heat generation area is greater than the current energy consumption of the entire waste heat recovery system. If so, the high heat generation area is determined as the system working area and a power generation command is issued.

[0022] The instruction generation submodule is used to obtain multiple micro thermoelectric power generation units existing in the determined system working area, identify the multiple micro thermoelectric power generation units as target power generation units, and issue corresponding dynamic power generation instructions.

[0023] Preferably, the waste heat recovery module includes:

[0024] The optimization submodule is used to enhance the thermal conductivity of the hot ends of multiple micro thermoelectric power generation units in the high-heat area inside the laptop through a thermally conductive silicone layer, enhance the heat dissipation efficiency of the cold ends inside the laptop through micro heat dissipation fins, and optimize the power generation efficiency of the heat source.

[0025] The receiving submodule is used to receive the dynamic power generation command, determine the target power generation unit that needs to perform heat energy recovery, and real-time adjustment information.

[0026] The heat recovery submodule is used to enable the target power generation unit to dynamically adjust its workload based on the real-time temperature difference data provided by the thermal management module.

[0027] Preferably, the waste heat recovery module is integrated into the heat dissipation module inside the laptop computer and is integrated with the heat dissipation components in the heat dissipation module.

[0028] Preferably, the current stabilization module includes:

[0029] The rectifier and filter submodule is used to adjust the current output by the target power generation unit using a rectifier circuit and to smooth the rectified current using filter components.

[0030] The boost current stabilization submodule is used to use a DC-DC boost chip to increase the voltage to a preset voltage, and uses the power management chip to determine the switching between constant voltage mode and constant current mode according to the state of the target power generation unit.

[0031] The feedback adjustment submodule is used to detect the specific parameters of the target power generation unit using current detection and feedback loop, and adjust the corresponding parameters of the boost chip according to the specific parameters.

[0032] The protection submodule is used to perform overvoltage and overcurrent protection using safety protection circuitry, and over-temperature protection is provided by a thermistor mounted near the DC-DC boost chip.

[0033] Preferably, the intelligent energy storage control module includes:

[0034] Energy storage submodule, used to recover electrical energy by connecting batteries and energy storage capacitors in parallel;

[0035] The power management submodule is used to set up multi-source charging and discharging through the power management chip. When the recovered power is greater than the current load demand of the equipment that needs to be powered, it is first stored in the energy storage device. When it is insufficient, it is first used to supply power to the equipment that needs to be powered.

[0036] The visualization submodule is used to update the energy storage device's power level in real time on the laptop's display page via a system plugin;

[0037] The automatic control submodule is used to dynamically adjust the laptop components that need to use recycled energy based on the user's usage behavior of the laptop.

[0038] Preferably, the analysis and alert module is configured as follows:

[0039] The operation status of the power generation unit is obtained, the power generation curve is recorded, the peak power generation period is marked as a high load period, the temperature data of the high heat-generating area inside the laptop is obtained and read through the temperature sensor, and the temperature change curve of each high heat-generating area is recorded.

[0040] Based on the power generation curve, user scenarios are classified. Based on the amount of power generation, the scenarios are divided into standby mode, low load mode, and high load mode. User behavior profiles are constructed based on local power generation data. Based on the user behavior profiles, lightweight Markov chains are used to predict possible usage scenarios in the next stage.

[0041] Based on the predicted usage scenario, high-temperature areas are matched, and the power generation units within the high-temperature areas are dynamically switched to high-priority power generation units. The power supply mode is automatically matched according to the load of the user's usage scenario.

[0042] Obtain the temperature change curve for each high-heat area, and perform data analysis on the temperature change curve;

[0043] Based on the data analysis results, the health of the components in each high-heat area is assessed. The difference between the historical and current temperatures under the same usage load is compared. If the difference exceeds a preset threshold, the component in that area is determined to have poor health. A component health reminder is then sent to the corresponding component through the laptop display port.

[0044] Based on the data analysis results, anomaly analysis is performed on the real-time temperature of the high-heat area. When the real-time temperature shows a sustained high temperature or a temperature jump, the corresponding high-heat area is identified as an abnormal area. The abnormal area component is obtained, and a component abnormality alert is issued through the laptop display port.

[0045] Based on the component health assessment results and the anomaly analysis results, behavior optimization suggestions are generated.

[0046] Preferably, the system further includes an extension module for user-defined system functions and performance verification of the system according to user needs.

[0047] Obtain the adjustable system parameter types and determine the adjustment range of the safety parameters for each system parameter type;

[0048] A system function customization page is generated based on the adjustable system parameter type and the safety parameter adjustment range. The system function customization page has multiple adjustable system parameters and is equipped with on / off and adjustment range options.

[0049] Create a custom page that allows users to create multiple configuration files, each of which stores a different combination of system parameters;

[0050] Based on the system parameters adjusted by the user, predict the system behavior after the parameter adjustment, display the changing trend of key indicators, automatically identify contradictory parameter adjustments, and prompt the user to optimize the logic;

[0051] When a user confirms the parameter adjustment, the adjusted parameter is set as the confirmed value of the target parameter, and the user-defined system function is applied.

[0052] After applying the user-defined system function, the old and new configurations are applied alternately within a safe range to obtain real-time data of the system, record key data differences, and use the built-in algorithm to calculate the performance improvement range.

[0053] The performance improvement range is compared with user needs to determine whether the user needs are met. If the user needs are not met, system parameters that can be optimized are identified, the parameters are optimized, and a performance optimization reminder is sent to the user through the custom page.

[0054] A method for recovering waste heat from laptop computers based on thermoelectric conversion effect, characterized by comprising:

[0055] The temperature inside the laptop is detected by multiple temperature sensors located in high-heat areas inside the laptop and fed back to the power management chip.

[0056] The power management chip is used to dynamically adjust the system's working area based on temperature sensor data, and a working command is issued by selecting the area with the largest current temperature difference.

[0057] The thermally conductive silicone layer and micro heat dissipation fins are used to increase the temperature difference between the area and the cold end. The target power generation unit in the area is determined according to the working instructions. The target power generation unit is used to convert the heat energy of the laptop during operation into electrical energy.

[0058] The unstable low-voltage DC power output from the target power generation unit is converted into stable electrical energy using a rectifier circuit and a DC-DC boost chip.

[0059] The stable electrical energy stored using the energy storage device is displayed on the laptop computer to show the energy recovery status, and the method of using the recovered energy is automatically determined according to the user's needs.

[0060] User behavior is analyzed based on power generation, the status of the laptop components is analyzed based on temperature detection results, the power generation unit is intelligently configured based on the behavior analysis results, and component status reminders are issued based on the component status analysis results.

[0061] Through the above-mentioned technical means, the present invention achieves the following beneficial effects:

[0062] 1) By integrating a micro TEG (thermoelectric conversion module) unit into the high-heat area of ​​the laptop, the waste heat generated during the operation of the laptop is effectively utilized, which improves the existing heat dissipation efficiency of the laptop, making it green, low-carbon, energy-saving and environmentally friendly.

[0063] 2) The TEG unit is embedded inside the heat dissipation module and integrated with the heat pipe and heat spreader to avoid occupying extra space;

[0064] 3) Through temperature sensors and switch matrix, the TEG unit group is intelligently activated and managed to improve overall efficiency. The power management module is linked with the equipment power management system to reduce the battery burden.

[0065] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings.

[0066] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0067] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof.

[0068] Figure 1 A schematic diagram of a waste heat recovery system for laptop computers based on thermoelectric conversion effect provided by the present invention;

[0069] Figure 2 A schematic diagram of an intelligent detection module in a laptop waste heat recovery system based on thermoelectric conversion effect provided by the present invention;

[0070] Figure 3 A flowchart illustrating the workflow of a waste heat recovery method for laptop computers based on thermoelectric conversion effect provided by this invention;

[0071] Figure 4 This invention provides an integrated structural diagram of a waste heat recovery module and a heat dissipation module inside a laptop computer. Detailed Implementation

[0072] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0073] During high-load operation of laptops, core hardware components such as the central processing unit (CPU), graphics processing unit (GPU), and power management module continuously release a large amount of waste heat, the heat density of which increases exponentially with performance demands. Traditional cooling architectures use a physical combination of metal heat pipes, aluminum heat sinks, and centrifugal fans to simply expel heat from the chassis through unidirectional conduction and forced convection. This linear cooling mode only focuses on alleviating the pressure of instantaneous temperature rise, but ignores the energy conversion potential contained in waste heat. Under prolonged high-load scenarios, the unidirectional dissipation of heat not only accelerates the efficiency decline caused by the aging of the cooling system, but also creates a continuous energy loss loop inside the device—electrical energy is converted into computing power by the chip, and ultimately dissipates into the environment in the form of disordered heat energy. This extensive "generation-emission" thermal management logic neither attempts to build a reverse coupling link between heat energy and electrical energy, nor does it convert local high temperatures into added value that can serve the system itself. It may even form hot spots on the surface of the chassis, affecting the user experience and exposing the limitations of traditional solutions in terms of energy cycle concepts and sustainable design dimensions. Regarding the above situation, the problems are as follows:

[0074] 1. Existing cooling methods for laptops have limited heat dissipation efficiency, resulting in ineffective utilization of heat energy, exacerbating greenhouse gas emissions and thermal pollution, further increasing the environmental burden and wasting resources;

[0075] 2. If heat energy recovery is implemented, the additional hardware such as the TEG array and energy storage module will take up internal space in the laptop, which may reduce battery capacity or sacrifice a thin and light design.

[0076] 3. Due to its size, laptops generate relatively little electrical energy from internal temperature differences, requiring intelligent charging and discharging management strategies to make effective use of it.

[0077] To address the problems mentioned above, this invention provides a waste heat recovery system and method for laptop computers based on thermoelectric conversion effects, thereby solving the aforementioned problems.

[0078] A waste heat recovery system for laptop computers based on thermoelectric conversion effect, such as Figure 1 As shown, the feature is that it includes:

[0079] The intelligent detection module 101 is used to detect the temperature inside the laptop through multiple temperature sensors located in the high-heat area inside the laptop and feed it back to the power management chip;

[0080] In some embodiments, this module distributes miniature digital temperature sensors in high-heat-sensitive areas of the laptop, such as the CPU core packaging layer, GPU memory power supply circuit, and motherboard inductor array, to achieve synchronous acquisition and transmission of temperature data from multiple nodes. It uses a built-in noise suppression algorithm to filter the raw signal in real time and feeds back the calibrated and accurate temperature field information to the power management chip, thereby achieving a refined improvement in energy efficiency ratio while ensuring the thermal safety threshold of core components.

[0081] The thermal management module 102 is used to dynamically adjust the system working area based on temperature sensor data using the power management chip, and to issue working instructions by selecting the area with the largest current temperature difference.

[0082] In some embodiments, this module analyzes the synchronous data stream of multiple temperature sensors in real time through a power management chip, calculates the instantaneous thermal gradient difference of each high-heat-generating unit, such as the CPU core cluster, GPU rendering engine, memory controller, etc., based on a dynamic temperature difference algorithm, and when it detects that the temperature difference value (ΔT = hot end temperature - cold end temperature) of a certain area exceeds a preset threshold, it is marked as the thermal management focus area, and the heat generation area is selected according to the size of the temperature difference.

[0083] The waste heat recovery module 103 is used to increase the temperature difference between the area and the cold end by using a thermally conductive silicone layer and micro heat dissipation fins, and to determine the target power generation unit in the area according to the working instruction, and to use the target power generation unit to convert the heat energy of the laptop computer during operation into electrical energy.

[0084] In some embodiments, this module establishes a low thermal resistance heat transfer path by tightly attaching a high thermal conductivity silicone layer to the surface of the high-heat-generating unit. Combined with microfabrication technology, an array of copper-magnesium alloy heat dissipation fins are integrated at the hot end of the thermoelectric module to forcibly expand the steady-state temperature difference gradient between the module and the cold end heat dissipation module. When the thermal management center determines that a certain area has reached the maximum effective temperature difference (ΔT_max), it activates the thin-film thermoelectric unit at the corresponding coordinate and uses the Seebeck effect to convert the directional heat flow into pulsating DC, which is then fed into the energy storage bus after multi-stage filtering and voltage regulation.

[0085] The current stabilization module 104 is used to convert the unstable low-voltage DC power output by the target power generation unit into stable electrical energy using a rectifier circuit and a DC-DC boost chip;

[0086] In some embodiments, this module performs polarity correction and initial smoothing of the bidirectional pulsating current output by the thermoelectric unit through a full-bridge rectifier circuit, and then connects to a wide input range DC-DC boost chip. The fluctuating low-voltage DC is boosted to a stable 5V output through the built-in synchronous rectification architecture. An adaptive algorithm is embedded in the boost topology to track the maximum power point in real time, and a filter network is used to eliminate switching noise. At the same time, reverse cutoff and overvoltage protection modules are integrated, and finally the purified electrical energy is injected into the energy storage device according to priority.

[0087] The intelligent energy storage control module 105 is used to use the stable electrical energy stored by the energy storage device, display the energy recovery status on the laptop, and automatically determine the usage mode of the recovered electrical energy according to user needs.

[0088] In some embodiments, this module uses a composite energy storage module, such as a lithium polymer battery and a supercapacitor connected in parallel, to receive stabilized electrical energy. It has a built-in bidirectional DC-DC controller to achieve dynamic switching of charging and discharging paths. Simultaneously, a visual interactive interface is built at the operating system layer to display the dynamic recovery power curve, energy storage capacity percentage, and cumulative energy saving time statistics in real time. The underlying strategy engine intelligently schedules the priority of recovered electrical energy use based on the user's preset mode and real-time load requirements.

[0089] The analysis and reminder module 106 is used to perform user behavior analysis based on power generation status, analyze the status of the laptop components based on temperature detection results, perform intelligent configuration of the power generation unit based on the behavior analysis results, and issue component status reminders based on the component status analysis results.

[0090] In some embodiments, this module tracks user usage patterns in real time through a thermoelectric conversion efficiency matrix and builds a behavioral feature library. It simultaneously integrates multi-dimensional temperature sensing data streams, such as chip temperature, PCB board temperature rise rate, and heat dissipation module gradient temperature difference, to perform coupled analysis of hardware aging coefficient and instantaneous thermal stress. When it is identified that the user is continuously in a high power generation demand scenario, the activation topology of the thermoelectric unit array is dynamically reconstructed, and the module with the optimal Seebeck coefficient is prioritized to the heat flux density peak area. When the temperature is abnormal, the status of the laptop components is analyzed and an alert is issued.

[0091] The working principle of the above technical solution is as follows: Multiple temperature sensors installed in the high-heat area inside the laptop detect the internal temperature of the laptop and feed it back to the power management chip. Based on the temperature sensor data, the system's working area is dynamically adjusted. The area with the largest current temperature difference is selected and a working command is issued to increase the temperature difference between this area and the cold end. The target power generation unit converts the heat energy of the laptop during operation into electrical energy. The unstable low-voltage DC power output is converted into stable electrical energy using a rectifier circuit and a DC-DC boost chip. Stable electrical energy is stored using an energy storage device. The energy recovery status is displayed on the laptop, and the method of using the recovered energy is automatically determined according to user needs. User behavior analysis is performed based on the power generation status. The status of the laptop components is analyzed based on the temperature detection results. The power generation unit is intelligently configured based on the behavior analysis results. The component status reminder is issued based on the component status analysis results.

[0092] The beneficial effects of the above technical solution are as follows: Multiple temperature sensors detect the internal temperature of the laptop and feed it back to the power management chip, reducing the number of temperature sensors while improving detection efficiency; dynamically adjusting the system's working area based on temperature sensor data enhances system intelligence and reduces heat waste; increasing the temperature difference between the heat-generating and cold-generating areas, and using a target power generation unit to convert the laptop's heat energy into electrical energy, effectively improves heating efficiency; converting unstable low-voltage DC output into stable electrical energy improves system safety; using an energy storage device to store stable electrical energy, displaying the energy recovery status on the laptop, and automatically determining the usage method of the recovered energy based on user needs enhances system intelligence; performing user behavior analysis and laptop component status analysis, intelligently configuring the power generation unit, and issuing component status reminders based on component status analysis results improves system usability and security, making the system more intelligent.

[0093] In one embodiment, such as Figure 2 As shown, the intelligent detection module includes:

[0094] The determination submodule 1011 is used to detect the heat generation of multiple components of the laptop computer during operation using a temperature detection device, determine the heat generation components and high-temperature locations of the laptop computer, and determine the location of the temperature sensor based on the high-temperature locations.

[0095] In some embodiments, this embodiment locates high-temperature areas using a thermal imager or existing heat dissipation design documents, and identifies key heat-generating components such as CPU, GPU, power module, SSD, and battery. Combined with the device structure, space is reserved for sensor installation to avoid interfering with the original heat dissipation system, such as fans and heat pipes.

[0096] The detection submodule 1012 is used to detect the internal temperature of the laptop computer during operation using the multiple temperature sensors, and generate multiple temperature detection signals at different locations to be fed back to the power management chip.

[0097] The parsing submodule 1013 is used to parse the temperature detection signal using the power management chip to determine the internal temperature distribution of the laptop during operation.

[0098] In some embodiments, the power management chip acquires temperature sensor signals distributed on the CPU, GPU and key nodes of the motherboard in real time through a multi-channel interface, converts the analog voltage signal into a digital temperature value, combines digital filtering algorithm to eliminate environmental noise interference, and uses thermal field modeling technology to reconstruct a three-dimensional temperature distribution map. Based on the preset temperature control strategy and dynamic threshold analysis, it accurately locates the local overheating area and updates it to the system temperature control center simultaneously.

[0099] The beneficial effects of the above technical solution are as follows: Using a temperature detection device to detect the heat generation of multiple components during laptop operation, identifying the heat-generating components and high-temperature locations of the laptop, and determining the location of temperature sensors based on these high-temperature locations, improves detection efficiency. Using multiple temperature sensors to detect the internal temperature of the laptop during operation generates multiple temperature detection signals from different locations, which are then fed back to the power management chip, improving data accuracy and real-time performance. The power management chip analyzes the temperature detection signals to determine the internal temperature distribution of the laptop during operation, facilitating targeted selection of power generation areas and improving system efficiency.

[0100] In one embodiment, the thermal management module includes:

[0101] The acquisition submodule is used to acquire the internal temperature distribution of the laptop during operation and update it dynamically in real time.

[0102] The temperature difference determination submodule is used to determine the current temperature reference value based on the internal cold end temperature of the laptop, and to determine the temperature difference between the internal temperature of the laptop and the cold end based on the current internal temperature distribution during laptop operation.

[0103] In some embodiments, this embodiment captures the absolute temperature scale data of the cold end of the heat dissipation module, such as the fan outlet or the heat pipe condensation section, in real time through an embedded temperature sensor network, and uses it as a dynamic reference temperature source; it simultaneously calculates the distributed temperature matrix information of key areas such as the CPU and GPU memory power supply layer, constructs a three-dimensional thermal field distribution model based on the thermodynamic gradient field algorithm, and compares the instantaneous temperature difference between each heat-generating unit and the cold end reference frame by frame.

[0104] The judgment submodule is used to determine the high heat generation area with the largest heat output inside the laptop in real time based on the temperature difference, and to determine whether the power generation efficiency of the high heat generation area is greater than the current energy consumption of the entire waste heat recovery system. If so, the high heat generation area is determined as the system working area and a power generation command is issued.

[0105] In some embodiments, this embodiment uses a thermal gradient tracking algorithm to analyze multi-node temperature difference data streams in real time, dynamically lock the peak region of instantaneous heat flux density, such as the CPU core or GPU memory power supply area under overclocking conditions, and evaluate the theoretical power generation of this region based on the Seebeck coefficient matrix and thermoelectric conversion efficiency model; at the same time, it calculates the energy consumption of the waste heat recovery system itself, including boost chip loss, heat dissipation boost power consumption and standby power consumption of the control unit. If the net energy gain threshold is exceeded, the region is marked as an effective working area through the priority arbitration engine, and adaptive voltage regulation is performed to maximize output, while the thermoelectric units in the low ΔT region are turned off to reduce losses;

[0106] The instruction generation submodule is used to obtain multiple micro thermoelectric power generation units existing in the determined system working area, identify the multiple micro thermoelectric power generation units as target power generation units, and issue corresponding dynamic power generation instructions.

[0107] The beneficial effects of the above technical solution are as follows: It acquires and dynamically updates the internal temperature distribution of the laptop during operation, improving data timeliness and enhancing system accuracy; it determines the current temperature baseline based on the cold end temperature inside the laptop and the temperature difference between the laptop's internal temperature and the cold end based on the current internal temperature distribution, enhancing data accuracy and practicality; it identifies the highest heat-generating area inside the laptop based on the temperature difference and determines whether the power generation efficiency of this high-heat-generating area is greater than the energy consumption of the entire waste heat recovery system. If so, it designates the high-heat-generating area as the system's working area and issues a power generation command. The system only starts working when the power generation efficiency exceeds the system's energy consumption, reducing resource waste and component wear; it acquires multiple micro-thermal power generation units within the identified system working area, designates these units as target power generation units, and issues corresponding dynamic power generation commands, improving the system's intelligence.

[0108] In one embodiment, the waste heat recovery module includes:

[0109] The optimization submodule is used to enhance the thermal conductivity of the hot ends of multiple micro thermoelectric power generation units in the high-heat area inside the laptop through a thermally conductive silicone layer, enhance the heat dissipation efficiency of the cold ends inside the laptop through micro heat dissipation fins, and optimize the power generation efficiency of the heat source.

[0110] In some embodiments, this embodiment establishes a low thermal resistance heat transfer channel by tightly attaching a high thermal conductivity medium layer to the surface of the high heat generation element, efficiently transferring the chip waste heat to the hot end of the thermoelectric unit array. At the same time, a micro heat dissipation structure is deployed at the cold end to enhance the environmental heat exchange capacity. The temperature difference gradient between the hot and cold ends is maximized through the synergistic effect of forced convection and radiation.

[0111] The receiving submodule is used to receive the dynamic power generation command, determine the target power generation unit that needs to perform heat energy recovery, and real-time adjustment information.

[0112] The heat recovery submodule is used to enable the target power generation unit to dynamically adjust its workload based on the real-time temperature difference data provided by the thermal management module.

[0113] In some embodiments, this embodiment provides real-time temperature difference data through a thermal management module. After receiving the data, the target power generation unit adjusts the workload through a specific algorithm, such as a dynamic MPPT algorithm, by changing the load impedance or adjusting the parameters of the boost circuit to optimize the Seebeck effect and maximize power output. At the same time, closed-loop control is combined to ensure system stability, prevent overheating, and ultimately improve overall energy efficiency and system lifespan.

[0114] The beneficial effects of the above technical solution are as follows: by strengthening the thermal conductivity of the hot ends of multiple micro thermoelectric power generation units in the high-heat area inside the laptop through the thermally conductive silicone layer, and by strengthening the heat dissipation efficiency of the cold ends inside the laptop through the use of micro heat dissipation fins, the power generation efficiency of the heat source is optimized, the temperature difference between the hot and cold ends is enhanced, and the power generation efficiency of the system is improved; by receiving dynamic power generation commands, determining the target power generation unit that needs to recover heat energy and the real-time adjustment information, and making intelligent adjustments according to the commands, the intelligence level of the system is improved; and by enabling the target power generation unit to dynamically adjust its workload according to the real-time temperature difference data provided by the thermal management module, the workload of the power generation unit is reduced, and the durability and practicality of the system are improved.

[0115] In one embodiment, such as Figure 4 As shown, the waste heat recovery module is integrated into the heat dissipation module inside the laptop computer, and is integrated with the heat dissipation components in the heat dissipation module.

[0116] The beneficial effects of the above technical solution are: embedding the thermoelectric power generation unit inside the heat dissipation module and integrating it with the heat pipe and heat spreader to avoid occupying extra space.

[0117] In one embodiment, the current stabilization module includes:

[0118] The rectifier and filter submodule is used to adjust the current output by the target power generation unit using a rectifier circuit and to smooth the rectified current using filter components.

[0119] The boost current stabilization submodule is used to use a DC-DC boost chip to increase the voltage to a preset voltage, and uses the power management chip to determine the switching between constant voltage mode and constant current mode according to the state of the target power generation unit.

[0120] In some embodiments, a wide-input-range DC-DC boost chip boosts the millivolt-level fluctuating voltage output by the thermoelectric unit to a preset standard voltage. Its built-in synchronous rectification architecture and algorithm optimize the boost efficiency in real time. The power management chip continuously monitors the internal resistance change, output current ripple, and cold-end heat dissipation status of the power generation unit and dynamically executes control mode switching. When the input voltage is stable and the load demand is constant, it switches to constant voltage mode to maintain the bus voltage. If it detects that the input source fluctuates violently or the energy storage unit is close to full capacity, it switches to constant current mode to limit the peak current.

[0121] The feedback adjustment submodule is used to detect the specific parameters of the target power generation unit using current detection and feedback loop, and adjust the corresponding parameters of the boost chip according to the specific parameters.

[0122] In some embodiments, this embodiment uses a high-precision Hall current sensor and a differential amplifier circuit to capture the output current ripple characteristics and dynamic internal resistance changes of the target power generation unit in real time, simultaneously monitors the voltage transient response and power factor offset at the input of the boost chip, feeds the parameter set back to the digital control core, constructs a closed-loop adjustment model, dynamically calculates the optimal switching frequency and duty cycle combination of the boost topology, and performs adaptive parameter adjustment based on the Seebeck coefficient decay curve of the thermoelectric unit.

[0123] The protection submodule is used to perform overvoltage and overcurrent protection using safety protection circuitry, and over-temperature protection is provided by a thermistor mounted near the DC-DC boost chip.

[0124] In some embodiments, the overvoltage protection module constructs a two-stage clamping defense line through transient voltage suppression diodes and resettable fuses to cut off abnormal high-voltage pulses at the input and output terminals in real time; the overcurrent protection adopts a high-precision current mirror sampling and comparator triggering architecture to cut off the main power path when the load is short-circuited; simultaneously, a thermistor array is mounted on the key heat points of the DC-DC chip to map the junction temperature state in real time through the temperature-resistance characteristic curve. When a local temperature rise is detected to exceed the safety threshold, the frequency reduction protection or forced shutdown command is immediately triggered, and the system log records the fault code.

[0125] The beneficial effects of the above technical solution are as follows: A rectifier circuit is used to adjust the current output by the target power generation unit, and a filter component is used to smooth the rectified current. Furthermore, a DC-DC boost chip is used to increase the voltage to a preset voltage, and the power management chip is used to determine the switching between constant voltage and constant current modes based on the state of the target power generation unit. Current detection and feedback loops are used to detect the specific parameters of the target power generation unit, and the corresponding parameters of the boost chip are adjusted according to these parameters. Overvoltage and overcurrent protection are implemented using a safety protection circuit, and over-temperature protection is provided by a thermistor mounted near the DC-DC boost chip, thus improving the safety and stability of the system.

[0126] In one embodiment, the intelligent energy storage control module includes:

[0127] Energy storage submodule, used to recover electrical energy by connecting batteries and energy storage capacitors in parallel;

[0128] The power management submodule is used to set up multi-source charging and discharging through the power management chip. When the recovered power is greater than the current load demand of the equipment that needs to be powered, it is first stored in the energy storage device. When it is insufficient, it is first used to supply power to the equipment that needs to be powered.

[0129] In some embodiments, a multi-source energy routing hub is constructed through a power management chip to monitor the input power of waste heat recovery energy, main battery and external adapter and system load demand in real time. When the instantaneous power of the recovered energy exceeds the total load demand, the surplus energy is injected into the supercapacitor-lithium battery hybrid energy storage bus through a bidirectional DC-DC controller, and a trickle optimization algorithm is enabled to extend the life of the energy storage unit. If the recovered power is insufficient to support the current load, it seamlessly switches to the main battery or external power supply to make up the gap. At the same time, the power supply path is intelligently allocated based on the load type, and reverse cut-off and overcharge protection circuits are integrated in the charging and discharging link.

[0130] The visualization submodule is used to update the energy storage device's power level in real time on the laptop's display page via a system plugin;

[0131] In some embodiments, a dynamic energy information prompt module is built in the right side of the taskbar or the floating window on the desktop through a lightweight plug-in architecture that is deeply integrated into the operating system. By polling the energy storage bus charge data of the power management chip in real time, a dynamic charge and discharge rate curve is drawn using a rendering engine. The click interaction layer is embedded synchronously, and users can bring up the secondary panel to view the historical recovered energy distribution heat map, instantaneous power generation and energy saving contribution statistics. When a sudden change in energy storage capacity is detected (such as instantaneous high current charge and discharge), a smooth animation transition and abnormal status flashing prompt are triggered.

[0132] The automatic control submodule is used to dynamically adjust the laptop components that need to use recycled energy based on the user's usage behavior of the laptop.

[0133] The beneficial effects of the above technical solution are as follows: using batteries and energy storage capacitors in parallel for energy recovery improves energy recovery efficiency; the power management chip enables multi-source charging and discharging settings, prioritizing the storage of energy when the recovered energy exceeds the load demand of the current power-requiring equipment, and prioritizing power supply to the equipment when it is insufficient, thus improving system usability and lifespan; the energy storage device's power level is updated in real time on the laptop's display page via a system plugin; and the laptop components that require the use of recovered energy are dynamically adjusted based on the user's usage behavior, allowing for real-time interaction with the user and enhancing the user experience.

[0134] In one embodiment, the analysis alert module is configured as follows:

[0135] The operation status of the power generation unit is obtained, the power generation curve is recorded, the peak power generation period is marked as a high load period, the temperature data of the high heat-generating area inside the laptop is obtained and read through the temperature sensor, and the temperature change curve of each high heat-generating area is recorded.

[0136] Based on the power generation curve, user scenarios are classified. Based on the amount of power generation, the scenarios are divided into standby mode, low load mode, and high load mode. User behavior profiles are constructed based on local power generation data. Based on the user behavior profiles, lightweight Markov chains are used to predict possible usage scenarios in the next stage.

[0137] In some embodiments, the standby mode, low load mode, and high load mode are respectively: Standby mode: near zero power generation, temperature maintained within +5°C; Low load mode: low power generation (<2W), medium-low frequency temperature fluctuation (40-60°C); High load mode: high power generation demand (>8W), GPU / CPU temperature surges synchronously (>75°C); Local power generation data includes charging frequency, duration, power generation efficiency, etc.; A Markov chain is a set of discrete random variables with Markov properties, possessing irreducibility, recurrence, periodicity, and ergodicity;

[0138] Based on the predicted usage scenario, high-temperature areas are matched, and the power generation units within the high-temperature areas are dynamically switched to high-priority power generation units. The power supply mode is automatically matched according to the load of the user's usage scenario.

[0139] In some embodiments, the automatic load matching power supply mode based on the user's usage scenario is to automatically adjust the power generation unit and efficiency based on the user's behavior; for example, when the user enters game mode, the entire TEG array is activated and the efficiency of the boost chip is improved, sacrificing quietness for power generation.

[0140] Obtain the temperature change curve for each high-heat area, and perform data analysis on the temperature change curve;

[0141] Based on the data analysis results, the health of the components in each high-heat area is assessed. The difference between the historical and current temperatures under the same usage load is compared. If the difference exceeds a preset threshold, the component in that area is determined to have poor health. A component health reminder is then sent to the corresponding component through the laptop display port.

[0142] In some embodiments, this embodiment mainly uses the following methods: heat dissipation efficiency calculation: comparing the historical and current temperature differences under the same load; battery aging detection: combining the charging efficiency (charging time / capacity growth) detection of the battery by the power generation module to determine the health of the components;

[0143] Based on the data analysis results, anomaly analysis is performed on the real-time temperature of the high-heat area. When the real-time temperature shows a sustained high temperature or a temperature jump, the corresponding high-heat area is identified as an abnormal area. The abnormal area component is obtained, and a component abnormality alert is issued through the laptop display port.

[0144] Based on the component health assessment results and the anomaly analysis results, behavior optimization suggestions are generated.

[0145] In some embodiments, the component status alert design incorporates a real-time notification mechanism. When an anomaly is detected, the system notifies the user via a notification or indicator light and provides suggested actions.

[0146] The beneficial effects of the above technical solution are as follows: It acquires the operating status of the power generation unit, records the power generation curve, classifies user scenarios based on the power generation curve, constructs user behavior profiles based on local power generation data, predicts possible usage scenarios in the next stage, matches high-temperature areas according to predicted usage scenarios, dynamically switches power generation units within high-temperature areas to high-priority power generation units, improves system response speed and power generation efficiency through priority adjustment, and enhances practicality. It automatically matches the power supply mode according to the load of the user's usage scenario, acquires the temperature change curve of the high-heat area, performs data analysis, assesses the component health of components in the high-heat area based on the data analysis results, sends component health reminders to corresponding components through the laptop display port, performs anomaly analysis on the real-time temperature of the high-heat area based on the data analysis results, identifies abnormal components, sends component anomaly reminders through the laptop display port, improving the system's safety factor, and generates behavior optimization suggestions based on the component health assessment results and anomaly analysis results, improving the system's intelligence and practicality.

[0147] In one embodiment, the system further includes an extension module for user-defined system functions and for performance verification of the system based on user requirements.

[0148] Obtain the adjustable system parameter types and determine the adjustment range of the safety parameters for each system parameter type;

[0149] In some embodiments, the system configurable parameter space, including voltage regulation slope, temperature control threshold, fan curve base point, etc., is traversed through the hardware abstraction layer. Combined with calibration values, thermodynamic simulation boundaries and measured aging coefficients, a multi-dimensional parameter safety domain model is established to dynamically define the legal adjustment range of each parameter in the time domain, spatial domain and operating conditions.

[0150] A system function customization page is generated based on the adjustable system parameter type and the safety parameter adjustment range. The system function customization page has multiple adjustable system parameters and is equipped with on / off and adjustment range options.

[0151] In some embodiments, the adjustable parameter metadata provided by the hardware abstraction layer is parsed by the dynamic rendering engine to generate a tree-structured hierarchical visual configuration interface. The top level is divided by functional domains, such as power consumption strategy, temperature control logic, and recycling intensity. The secondary menu displays parameter items in a card layout, such as voltage offset, fan start-up temperature, and thermoelectric unit activation threshold. Each parameter item is embedded with a dynamic range slider and a mode switch for automatic / manual operation. User configuration schemes can be saved as multiple preset modes.

[0152] Create a custom page that allows users to create multiple configuration files, each of which stores a different combination of system parameters;

[0153] Based on the system parameters adjusted by the user, predict the system behavior after the parameter adjustment, display the changing trend of key indicators, automatically identify contradictory parameter adjustments, and prompt the user to optimize the logic;

[0154] In some embodiments, when the user adjusts system parameters, such as fan speed offset, this embodiment dynamically calculates the quantitative relationship between power consumption, temperature, and noise, and generates visual feedback such as three-dimensional heat map, energy efficiency curve, and noise spectrum. When conflicting logic is detected, such as the parallel selection of "maximize performance" and "force silent mode", the conflicting items are automatically highlighted in red and optimization suggestions are pushed. At the same time, multiple feasible solutions are pre-simulated using the gradient descent method, and the core indicators under different configurations, such as the predicted trends of battery life change rate, peak temperature, and regenerative power, are displayed in a dynamic comparison view.

[0155] When a user confirms the parameter adjustment, the adjusted parameter is set as the confirmed value of the target parameter, and the user-defined system function is applied.

[0156] After applying the user-defined system function, the old and new configurations are applied alternately within a safe range to obtain real-time data of the system, record key data differences, and use the built-in algorithm to calculate the performance improvement range.

[0157] In some embodiments, this embodiment applies new and old configurations alternately within a safe range, such as running each for 15 minutes, records key data differences, and performs statistical significance analysis: a local t-test algorithm is used to determine whether the performance improvement exceeds the error range, and the performance improvement range is determined based on the error range;

[0158] The performance improvement range is compared with user needs to determine whether the user needs are met. If the user needs are not met, system parameters that can be optimized are identified, the parameters are optimized, and a performance optimization reminder is sent to the user through the custom page.

[0159] In some embodiments, this embodiment tracks the deviation between user-preset performance optimization goals, such as battery life extension rate, and actual system indicators in real time. When a key indicator is detected to have failed to reach the expected threshold, parameter space traversal analysis is automatically initiated to filter out adjustable variables strongly correlated with the target, such as thermoelectric unit activation density. Combined with historical parameter tuning data and hardware health status assessment, a progressive optimization scheme is generated. A dynamic pop-up prompt is triggered on a custom page to display the adjustable range of the current bottleneck parameter, the expected gain curve, and the potential risk level. A "one-click trial run" function is embedded to allow users to verify the adjustment effect in a simulation environment, while retaining the manual fine-tuning entry.

[0160] The beneficial effects of the above technical solution are as follows: It obtains adjustable system parameter types and safety parameter adjustment ranges; generates a system function customization page based on these parameters; creates multiple configuration files, each storing different system parameter combinations, supporting personalized configuration adjustments by users, thus improving user experience; predicts system behavior based on user-adjusted system parameters, displays key indicator trends, automatically identifies contradictory parameter adjustments, prompts users to optimize logic, ensuring system efficiency; when user confirmation is detected, the user-customized system function is applied, alternating between old and new configurations within a safe range, acquiring real-time system data, allowing for high freedom in customization and ensuring system security; uses a built-in algorithm to calculate the performance improvement range, compares the performance improvement range with user needs; if user needs are not met, identifies optimizable system parameters, optimizes them, and sends performance optimization reminders to users through the customization page, balancing flexibility and security; provides powerful customization options while ensuring system stability; and uses localized performance verification tools to help users optimize settings, improving system usability.

[0161] This embodiment also discloses a method for recovering waste heat from laptop computers based on the thermoelectric conversion effect, such as... Figure 3 As shown, the feature is that it includes:

[0162] S101 detects the internal temperature of the laptop through multiple temperature sensors located in high-heat areas inside the laptop and feeds the feedback to the power management chip.

[0163] S102 uses the power management chip to dynamically adjust the system working area based on temperature sensor data, and selects the area with the largest current temperature difference to issue a working command.

[0164] S103 uses a thermally conductive silicone layer and micro heat dissipation fins to increase the temperature difference between the area and the cold end, determines the target power generation unit in the area according to the working instruction, and uses the target power generation unit to convert the heat energy of the laptop during operation into electrical energy.

[0165] S104 uses a rectifier circuit and a DC-DC boost chip to convert the unstable low-voltage DC power output from the target power generation unit into stable electrical energy;

[0166] S105 uses the stable electrical energy stored by the energy storage device to display the energy recovery status on the laptop and automatically determines the usage method of the recovered energy according to the user's needs;

[0167] S106 performs user behavior analysis based on power generation status, analyzes the status of the laptop components based on temperature detection results, intelligently configures the power generation unit according to the behavior analysis results, and issues component status reminders according to the component status analysis results.

[0168] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the following claims.

[0169] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A waste heat recovery system for laptop computers based on thermoelectric conversion effect, characterized in that, include: The intelligent detection module is used to detect the internal temperature of the laptop through multiple temperature sensors located in high-heat areas inside the laptop and feed it back to the power management chip. The thermal management module is used to adjust the system's working area and select the area with the largest current temperature difference to issue a working command. This includes: parsing the synchronous data stream of multiple temperature sensors through the power management chip, calculating each high-heat-generating unit based on the dynamic temperature difference algorithm; determining the high-heat-generating area based on the temperature difference, and judging whether the power generation efficiency of the high-heat-generating area is greater than the current energy consumption of the entire waste heat recovery system. If so, it is determined as the system's working area, and a power generation command is issued. The waste heat recovery module uses a thermally conductive silicone layer and micro heat dissipation fins to increase the temperature difference between the area and the cold end. It determines the target power generation unit in the area according to the work instructions and converts the heat energy of the laptop during operation into electrical energy. The current stabilization module is used to convert the unstable low-voltage DC power output from the target power generation unit into stable electrical energy. This includes: using a DC-DC boost chip to increase the voltage to a preset voltage, and determining the switching between constant voltage mode and constant current mode based on the state of the target power generation unit; using current detection and feedback loop to detect the specific parameters of the target power generation unit and adjusting the corresponding parameters of the boost chip. The intelligent energy storage control module is used to utilize stable electrical energy, display the status of energy recovery, and determine the usage mode of recovered electrical energy according to user needs. The analysis and alert module is used to classify user scenarios based on power generation curves, build user behavior profiles based on local power generation data, and use lightweight Markov chains to predict the next stage of usage scenarios. It matches high-temperature areas based on predicted usage scenarios, switches power generation units within high-temperature areas to high-priority power generation units, matches power supply modes according to the load of user scenarios, analyzes the status of laptop components based on temperature detection results, intelligently configures power generation units based on behavior analysis results, and issues component status alerts based on component status analysis results.

2. The waste heat recovery system for laptop computers based on thermoelectric conversion effect according to claim 1, characterized in that, The intelligent detection module includes: The determination submodule is used to detect the heat generation of multiple components of the laptop during operation using a temperature detection device, determine the heat-generating components and high-temperature locations of the laptop, and determine the location of the temperature sensor based on the high-temperature locations. The detection submodule is used to detect the internal temperature of the laptop during operation using the multiple temperature sensors, and generate multiple temperature detection signals at different locations to be fed back to the power management chip. The parsing submodule is used to parse the temperature detection signal using the power management chip to determine the internal temperature distribution of the laptop during operation.

3. The waste heat recovery system for laptop computers based on thermoelectric conversion effect according to claim 1, characterized in that, The thermal management module includes: The acquisition submodule is used to acquire the internal temperature distribution of the laptop during operation and update it dynamically in real time. The temperature difference determination submodule is used to determine the current temperature reference value based on the internal cold end temperature of the laptop, and to determine the temperature difference between the internal temperature of the laptop and the cold end based on the current internal temperature distribution during laptop operation. The judgment submodule is used to determine the high heat generation area with the largest heat output inside the laptop in real time based on the temperature difference, and to determine whether the power generation efficiency of the high heat generation area is greater than the current energy consumption of the entire waste heat recovery system. If so, the high heat generation area is determined as the system working area and a power generation command is issued. The instruction generation submodule is used to obtain multiple micro thermoelectric power generation units existing in the determined system working area, identify the multiple micro thermoelectric power generation units as target power generation units, and issue corresponding dynamic power generation instructions.

4. The waste heat recovery system for laptop computers based on thermoelectric conversion effect according to claim 3, characterized in that, The waste heat recovery module includes: The optimization submodule is used to enhance the thermal conductivity of the hot ends of multiple micro thermoelectric power generation units in the high-heat area inside the laptop through a thermally conductive silicone layer, enhance the heat dissipation efficiency of the cold ends inside the laptop through micro heat dissipation fins, and optimize the power generation efficiency of the heat source. The receiving submodule is used to receive the dynamic power generation command, determine the target power generation unit that needs to perform heat energy recovery, and real-time adjustment information. The heat recovery submodule is used to enable the target power generation unit to dynamically adjust its workload based on the real-time temperature difference data provided by the thermal management module.

5. The waste heat recovery system for laptop computers based on thermoelectric conversion effect according to claim 4, characterized in that, The waste heat recovery module is integrated into the heat dissipation module inside the laptop computer, and is integrated with the heat dissipation components in the heat dissipation module.

6. The waste heat recovery system for laptop computers based on thermoelectric conversion effect according to claim 1, characterized in that, The current stabilization module includes: The rectifier and filter submodule is used to adjust the current output by the target power generation unit using a rectifier circuit and to smooth the rectified current using filter components. The boost current stabilization submodule is used to use a DC-DC boost chip to increase the voltage to a preset voltage, and uses the power management chip to determine the switching between constant voltage mode and constant current mode according to the state of the target power generation unit. The feedback adjustment submodule is used to detect the specific parameters of the target power generation unit using current detection and feedback loop, and adjust the corresponding parameters of the boost chip according to the specific parameters. The protection submodule is used to perform overvoltage and overcurrent protection using safety protection circuitry, and over-temperature protection is provided by a thermistor mounted near the DC-DC boost chip.

7. The waste heat recovery system for laptop computers based on thermoelectric conversion effect according to claim 1, characterized in that, The intelligent energy storage control module includes: Energy storage submodule, used to recover electrical energy by connecting batteries and energy storage capacitors in parallel; The power management submodule is used to set up multi-source charging and discharging through the power management chip. When the recovered power is greater than the current load demand of the equipment that needs to be powered, it is first stored in the energy storage device. When it is insufficient, it is first used to supply power to the equipment that needs to be powered. The visualization submodule is used to update the energy storage device's power level in real time on the laptop's display page via a system plugin; The automatic control submodule is used to dynamically adjust the laptop components that need to use recycled energy based on the user's usage behavior of the laptop.

8. The waste heat recovery system for laptop computers based on thermoelectric conversion effect according to claim 1, characterized in that, The analysis and alert module is configured as follows: The operation status of the power generation unit is obtained, the power generation curve is recorded, the peak power generation period is marked as a high load period, the temperature data of the high heat-generating area inside the laptop is obtained and read through the temperature sensor, and the temperature change curve of each high heat-generating area is recorded. Based on the power generation curve, user scenarios are classified. Based on the amount of power generation, the scenarios are divided into standby mode, low load mode, and high load mode. User behavior profiles are constructed based on local power generation data. Based on the user behavior profiles, lightweight Markov chains are used to predict possible usage scenarios in the next stage. Based on the predicted usage scenario, high-temperature areas are matched, and the power generation units within the high-temperature areas are dynamically switched to high-priority power generation units. The power supply mode is automatically matched according to the load of the user's usage scenario. Obtain the temperature change curve for each high-heat area, and perform data analysis on the temperature change curve; Based on the data analysis results, the health of the components in each high-heat area is assessed. The difference between the historical and current temperatures under the same usage load is compared. If the difference exceeds a preset threshold, the component in that area is determined to have poor health. A component health reminder is then sent to the corresponding component through the laptop display port. Based on the data analysis results, anomaly analysis is performed on the real-time temperature of the high-heat area. When the real-time temperature shows a sustained high temperature or a temperature jump, the corresponding high-heat area is identified as an abnormal area. The abnormal area component is obtained, and a component abnormality alert is issued through the laptop display port. Based on the component health assessment results and the anomaly analysis results, behavior optimization suggestions are generated.

9. The waste heat recovery system for laptop computers based on thermoelectric conversion effect according to claim 1, characterized in that, It also includes extension modules for users to customize system functions and perform system performance verification based on user needs: Obtain the adjustable system parameter types and determine the adjustment range of the safety parameters for each system parameter type; A system function customization page is generated based on the adjustable system parameter type and the safety parameter adjustment range. The system function customization page has multiple adjustable system parameters and is equipped with on / off and adjustment range options. Create a custom page that allows users to create multiple configuration files, each of which stores a different combination of system parameters; Based on the system parameters adjusted by the user, predict the system behavior after the parameter adjustment, display the changing trend of key indicators, automatically identify contradictory parameter adjustments, and prompt the user to optimize the logic; When a user confirms the parameter adjustment, the adjusted parameter is set as the confirmed value of the target parameter, and the user-defined system function is applied. After applying the user-defined system function, the old and new configurations are applied alternately within a safe range to obtain real-time data of the system, record key data differences, and use the built-in algorithm to calculate the performance improvement range. The performance improvement range is compared with user needs to determine whether the user needs are met. If the user needs are not met, system parameters that can be optimized are identified, the parameters are optimized, and a performance optimization reminder is sent to the user through the custom page.

10. A method for recovering waste heat from laptop computers based on thermoelectric conversion effect, characterized in that, include: The internal temperature of the laptop is detected by multiple temperature sensors placed in high-heat areas inside the laptop and fed back to the power management chip. Adjust the system's working area, select the area with the largest current temperature difference and issue a working command, including: parsing the synchronous data stream of multiple area temperature sensors through the power management chip, calculating each high-heat-generating unit based on the dynamic temperature difference algorithm; determining the high-heat-generating area based on the temperature difference, and judging whether the power generation efficiency of the high-heat-generating area is greater than the current energy consumption of the entire waste heat recovery system. If so, determine it as the system's working area and issue a power generation command. The thermally conductive silicone layer and micro heat dissipation fins are used to increase the temperature difference between the area and the cold end. The target power generation unit in the area is determined according to the working instructions, and the heat energy of the laptop during operation is converted into electrical energy. The process of converting the unstable low-voltage DC power output from the target power generation unit into stable electrical energy includes: using a DC-DC boost chip to increase the voltage to a preset voltage, and determining the switching between constant voltage mode and constant current mode based on the state of the target power generation unit; using current detection and feedback loop to detect the specific parameters of the target power generation unit, and adjusting the corresponding parameters of the boost chip. Uses stable electrical energy, displays the status of energy recovery, and determines the usage method of recovered electrical energy according to user needs; User scenarios are categorized based on power generation curves, user behavior profiles are built based on local power generation data, and lightweight Markov chains are used to predict the next stage of usage scenarios. High-temperature areas are matched according to the predicted usage scenarios, and power generation units within high-temperature areas are switched to high-priority power generation units. Power supply modes are matched according to the load of user scenarios, laptop component status is analyzed based on temperature detection results, power generation units are intelligently configured based on behavior analysis results, and component status reminders are issued based on component status analysis results.

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