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

Abstract

The invention relates to the field of thermoelectric conversion, and discloses a notebook computer waste heat recovery system and method based on the thermoelectric conversion effect, and the system comprises an intelligent detection module which detects the internal temperature of a notebook computer through a plurality of temperature sensors and feeds back the internal temperature to a power management chip; the thermal management module dynamically adjusts the working area of the system; the waste heat recovery module is used for increasing the temperature difference between a heating area and a cold end and converting heat energy generated when the notebook computer works into electric energy by using a target power generation unit; the current stabilization module is used for converting the output unstable low-voltage direct current into stable electric energy; the intelligent energy storage control module is used for storing stable electric energy by using an electric energy storage device, displaying an electric energy recovery state on the notebook computer and automatically determining a recovery electric energy use mode according to user requirements; and the analysis reminding module is used for performing user behavior analysis and notebook computer component state analysis, performing intelligent configuration of the power generation unit and sending component state reminding according to a component state analysis result.

Description

Technical Field

[0001] The present invention relates to the field of thermoelectric conversion, and in particular to a system and method for recovering waste heat from a notebook computer based on a thermoelectric conversion effect. Background Art

[0002] When a laptop computer is running at high load, core hardware components such as the central processing unit (CPU), graphics processing unit (GPU), and power management module continuously release large amounts of waste heat. This heat density increases exponentially as performance demands rise. Traditional cooling architectures, through a physical combination of metal heat pipes, aluminum heat sink fins, and centrifugal fans, simply remove heat from the body through unidirectional conduction and forced convection. This linear cooling model only focuses on alleviating the pressure of transient 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 degradation caused by aging of the cooling system, but also creates a continuous energy loss loop within the device. After the electrical energy is converted into computing power by the chip, it is ultimately dissipated into the environment as disordered heat energy. This extensive "generate-discharge" thermal management logic neither attempts to establish a reverse coupling link between thermal energy and electrical energy nor converts localized high temperatures into added value that can serve the system itself. It can even form hot spots on the surface of the body, affecting the user experience and exposing the limitations of traditional solutions in terms of energy recycling concepts and sustainable design dimensions. Regarding the above situation, the following problems exist:

[0003] 1. The existing cooling mode of laptop computers has limited heat dissipation efficiency, and heat energy is not effectively utilized, which increases greenhouse gas emissions and thermal pollution, further increasing the environmental burden and wasting resources;

[0004] 2. If heat recovery is used, the additional hardware, such as the TEG (thermoelectric conversion module) array and energy storage module, will occupy the internal space of the notebook, possibly reducing battery capacity or sacrificing the lightweight design.

[0005] 3. Due to the size of laptop computers, the electricity generated by internal temperature differences is relatively small, and intelligent charging and discharging management strategies are required to effectively utilize it. Summary of the Invention

[0006] In response to the above-mentioned problems, the present invention provides a system and method for recovering waste heat from a laptop computer based on a thermoelectric conversion effect, so as to solve the above-mentioned problems.

[0007] A notebook computer waste heat recovery system based on thermoelectric conversion effect, characterized by comprising:

[0008] An intelligent detection module is used to detect the temperature inside the laptop computer through multiple temperature sensors set in high-heat areas inside the laptop computer and feed back the temperature to the power management chip;

[0009] A thermal management module is used to use the power management chip to dynamically adjust the system working area according to the temperature sensor data, and select the area with the largest current temperature difference to issue a working instruction;

[0010] a waste heat recovery module, configured to increase the temperature difference between the region and the cold end using a thermally conductive silicone layer and micro-heat sink fins, determine a target power generation unit within the region according to the operating instruction, and convert thermal energy generated by the laptop computer during operation into electrical energy using the target power generation unit;

[0011] A current stabilization module, configured to convert the unstable low-voltage direct current outputted by the target power generation unit into stable electrical energy using a rectifier circuit and a DC-DC boost chip;

[0012] an intelligent energy storage control module, configured to use the stable electric energy stored by the electric storage device to display the electric energy recovery status on the laptop computer and automatically determine the use mode of the recovered electric energy according to user needs;

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

[0014] Preferably, the intelligent detection module includes:

[0015] a determination submodule, configured to use a temperature detection device to detect the heating conditions of multiple components of the laptop computer when the laptop computer is running, determine the heating components and high-temperature positions of the laptop computer, and determine the position of the temperature sensor based on the high-temperature position;

[0016] A detection submodule, configured to use the multiple temperature sensors to detect the internal temperature of the laptop computer during operation, and generate multiple temperature detection signals at different positions to feed back to the power management chip;

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

[0018] Preferably, the thermal management module includes:

[0019] An acquisition submodule, configured to acquire the temperature distribution inside the laptop computer during operation and dynamically update the temperature in real time;

[0020] a temperature difference determination submodule, configured to determine a current temperature reference value based on the internal cold end temperature of the laptop computer, and to determine a temperature difference between the internal temperature of the laptop computer and the cold end based on the current internal temperature distribution of the laptop computer during operation;

[0021] a judgment submodule, configured to determine in real time a high-heating area within the laptop computer that currently generates the most heat based on the temperature difference, and to determine whether the power generation efficiency of the high-heating area is greater than the current energy consumption of the entire waste heat recovery system; if so, to determine the high-heating area as a system working area and to issue a power generation instruction;

[0022] The instruction generation submodule is used to obtain multiple micro thermoelectric power generation units existing in the determined system working area, determine 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 comprises:

[0024] An optimization submodule is used to enhance the thermal conductivity of the hot ends of multiple micro-thermoelectric power generation units in the high-heating area inside the laptop computer through a thermally conductive silicone layer, and to enhance the heat dissipation efficiency of the cold end inside the laptop computer using micro-heat dissipation fins, thereby optimizing the power generation efficiency of the heat source;

[0025] A receiving submodule, configured to receive the dynamic power generation instruction, determine the target power generation unit requiring heat energy recovery, and real-time adjustment information;

[0026] The heat energy recovery submodule is used to enable the target power generation unit to dynamically adjust the workload of the target power generation unit according to 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 flow stabilization module includes:

[0029] A rectifier and filter submodule, configured to adjust the current output by the target power generation unit using a rectifier circuit and smooth the rectified current using filter components;

[0030] A boost and current stabilization submodule, configured to use a DC-DC boost chip to boost the voltage to a preset voltage, and use the power management chip to determine switching between a constant voltage mode and a constant current mode according to the state of the target power generation unit;

[0031] A feedback regulation submodule, configured to detect specific parameters of the target power generation unit using current detection and a feedback loop, and adjust corresponding parameters of the boost chip according to the specific parameters;

[0032] The protection submodule is used to implement overvoltage protection and overcurrent protection using a safety protection circuit, and to provide overtemperature protection through 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 electric energy using 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 load demand of the current power supply equipment, it is first stored in the energy storage device. When it is insufficient, it is first supplied to the power supply equipment;

[0036] A visualization submodule, configured to update the power of the energy storage device in real time on the display page of the laptop computer through a system plug-in;

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

[0038] Preferably, the analysis and reminder module is configured to:

[0039] Obtaining the working condition of the power generation unit, recording the power generation curve, marking the peak power generation period as a high-load period, obtaining and reading the temperature data of the high-heating area inside the laptop computer through the temperature sensor, and recording the temperature change curve of each high-heating area;

[0040] Classify user usage scenarios based on the power generation curve, and categorize usage scenarios into standby mode, low-load mode, and high-load mode based on power generation. Build user behavior profiles based on local power generation data, and use a lightweight Markov chain to predict possible usage scenarios for the next stage based on the user behavior profiles.

[0041] Matching the high-temperature area according to the predicted usage scenario, dynamically switching the power generation unit in the high-temperature area to a high-priority power generation unit, and automatically matching the power supply mode according to the load of the user usage scenario;

[0042] Obtaining the temperature change curve of each high-heat-generating area, and performing data analysis on the temperature change curve;

[0043] Based on the data analysis results, the component health of each high-heat area is evaluated, and the historical and current temperature differences under the same usage load are compared. If the temperature exceeds a preset threshold, it is determined that the component health in the area is poor, and a component health reminder is issued to the corresponding component through the laptop display port;

[0044] Based on the data analysis results, an abnormal analysis is performed on the real-time temperature of the high-heating area. When the real-time temperature is continuously high or the temperature jumps, the corresponding high-heating area is determined as an abnormal area, the components in the abnormal area are obtained, and a component abnormality reminder is issued through the display port of the laptop;

[0045] Generate behavior optimization suggestions based on the component health assessment results and the abnormality analysis results.

[0046] Preferably, the system further includes an expansion module for users to customize system functions and perform performance verification of the system according to user requirements:

[0047] Obtaining adjustable system parameter types and determining a security parameter adjustment range for each of the system parameter types;

[0048] Generate a system function customization page according to the adjustable system parameter type and the security parameter adjustment range, wherein the system function customization page has multiple adjustable system parameters and is provided with switch and adjustment range options;

[0049] Create a custom page, wherein the custom page allows the user 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 trend of key indicators, automatically identify conflicting parameter adjustments, and prompt the user to optimize the logic;

[0051] When a confirmation operation of the user on the parameter adjustment is detected, the adjusted parameter is set as a confirmed value of the target parameter, and the user-defined system function is applied;

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

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

[0054] A method for recovering waste heat from a laptop computer based on a thermoelectric conversion effect, comprising:

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

[0056] Using the power management chip to dynamically adjust the system working area according to the temperature sensor data, select the area with the largest current temperature difference to issue a working instruction;

[0057] using a thermally conductive silicone layer and micro-heat sink fins to increase the temperature difference between the region and the cold end, determining a target power generation unit in the region according to the work instruction, and using the target power generation unit to convert thermal energy generated by the laptop computer during operation into electrical energy;

[0058] Using a rectifier circuit and a DC-DC boost chip to convert the unstable low-voltage direct current output by the target power generation unit into stable electrical energy;

[0059] The stable electric energy stored in the electric storage device is used to display the electric energy recovery status on the laptop computer, and automatically determine the use mode of the recovered electric energy according to user needs;

[0060] User behavior analysis is performed based on power generation conditions, component status analysis of the laptop computer is performed based on temperature detection results, power generation units are intelligently configured according to the behavior analysis results, and component status reminders are issued according to the component status analysis results.

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

[0062] 1) By integrating a micro TEG (thermoelectric conversion module) unit in the high-heat area of ​​the laptop, the waste heat generated during the operation of the laptop is effectively utilized, thereby improving the existing heat dissipation efficiency of the laptop, achieving green, low-carbon, energy-saving and environmental protection;

[0063] 2) The TEG unit is embedded in the heat dissipation module and integrated with the heat pipe and heat spreader to avoid taking up additional space;

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

[0065] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0066] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

[0068] Figure 1 This is a schematic diagram of a notebook computer waste heat recovery system based on thermoelectric conversion effect provided by the present invention;

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

[0070] Figure 3 This is a workflow diagram of a method for recovering waste heat from a laptop computer based on the thermoelectric conversion effect provided by the present invention;

[0071] Figure 4 This is an integrated structural diagram of a waste heat recovery module and a heat dissipation module inside a laptop computer provided by the present invention. DETAILED DESCRIPTION

[0072] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all possible embodiments consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.

[0073] When a laptop computer is running at high load, core hardware components such as the central processing unit (CPU), graphics processing unit (GPU), and power management module continuously release large amounts of waste heat. This heat density increases exponentially as performance demands rise. Traditional cooling architectures, through a physical combination of metal heat pipes, aluminum heat sink fins, and centrifugal fans, simply remove heat from the body through unidirectional conduction and forced convection. This linear cooling model only focuses on alleviating the pressure of transient 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 degradation caused by aging of the cooling system, but also creates a continuous energy loss loop within the device. After the electrical energy is converted into computing power by the chip, it is ultimately dissipated into the environment as disordered heat energy. This extensive "generate-discharge" thermal management logic neither attempts to establish a reverse coupling link between thermal energy and electrical energy nor converts localized high temperatures into added value that can serve the system itself. It can even form hot spots on the surface of the body, affecting the user experience and exposing the limitations of traditional solutions in terms of energy recycling concepts and sustainable design dimensions. Regarding the above situation, the following problems exist:

[0074] 1. The existing cooling mode of laptop computers has limited heat dissipation efficiency, and heat energy is not effectively utilized, which increases greenhouse gas emissions and thermal pollution, further increasing the environmental burden and wasting resources;

[0075] 2. If heat recovery is used, the additional hardware, such as the TEG array and energy storage module, will occupy the internal space of the notebook, possibly reducing battery capacity or sacrificing a lightweight design.

[0076] 3. Due to the size of laptop computers, the electricity generated by internal temperature differences is relatively small, and intelligent charging and discharging management strategies are required to effectively utilize it.

[0077] In response to the above-mentioned problems, the present invention provides a system and method for recovering waste heat from a laptop computer based on a thermoelectric conversion effect, so as to solve the above-mentioned problems.

[0078] A notebook computer waste heat recovery system based on thermoelectric conversion effect, such as Figure 1 As shown, it is characterized by comprising:

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

[0080] In some embodiments, this module achieves synchronous acquisition and transmission of multi-node temperature data by distributing 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. It relies on a built-in noise suppression algorithm to filter the original 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 while ensuring the thermal safety threshold of core components.

[0081] Thermal management module 102, configured to use the power management chip to dynamically adjust the system operating area according to temperature sensor data, and select the area with the largest current temperature difference to issue a working instruction;

[0082] In some embodiments, this module uses the power management chip to analyze the synchronized data streams of multi-region temperature sensors in real time. Based on the dynamic temperature difference algorithm, it calculates the real-time thermal gradient difference of each high-heat generating unit, such as the CPU core cluster, GPU rendering engine, memory controller, etc. When it detects that the temperature difference value of a certain area (ΔT = hot end temperature - cold end temperature) exceeds the preset threshold, it is preferentially marked as a thermal management focus area, and the focus area is selected based on the size of the temperature difference.

[0083] a waste heat recovery module 103 for increasing the temperature difference between the region and the cold end using a thermally conductive silicone layer and micro-heat sink fins, determining a target power generation unit within the region according to the work instruction, and using the target power generation unit to convert thermal energy generated by the laptop computer during operation into electrical energy;

[0084] In some embodiments, this module closely adheres to the surface of the high-heat-generating unit through a high-thermal-conductivity silicone layer to establish a low-resistance heat transfer path. Micromachining technology is used to integrate an array of copper-magnesium alloy heat sink fins at the hot end of the thermoelectric module, forcing a larger steady-state temperature gradient with 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 direct current, which is then fed into the energy storage bus after multi-stage filtering and voltage stabilization.

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

[0086] In some embodiments, this module uses a full-bridge rectifier circuit to perform polarity correction and preliminary smoothing on the bidirectional pulsating current output by the thermoelectric unit. It then connects to a wide-input-range DC-DC boost chip, boosting the fluctuating low-voltage DC to a stable 5V output through a built-in synchronous rectification architecture. An adaptive algorithm is embedded in the boost topology to track the maximum power point in real time, combined with a filter network to eliminate switching noise. Reverse cutoff and overvoltage protection modules are also integrated, ultimately prioritizing the purified electrical energy into the energy storage device.

[0087] an intelligent energy storage control module 105 for using the stable electric energy stored in the electric storage device to display the electric energy recovery status on the laptop computer and automatically determine the use mode of the recovered electric 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 in parallel, to receive stabilized power. A built-in bidirectional DC-DC controller enables dynamic switching of charge and discharge paths. Simultaneously, a visual interactive interface is built at the operating system layer to display a real-time floating display of the dynamic recovery power curve, energy storage pool capacity percentage, and accumulated energy saving time statistics. The underlying policy engine intelligently schedules the use priority of recovered power based on user preset modes and real-time load demand.

[0089] The analysis and reminder module 106 is used to perform user behavior analysis based on power generation conditions, perform component status analysis of the laptop computer based on temperature detection results, perform intelligent configuration of power generation units based on behavior analysis results, and issue component status reminders based on 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, while simultaneously integrating multi-dimensional temperature sensor data streams, such as chip temperature, PCB board temperature rise rate, and heat dissipation module gradient temperature difference, to perform a 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 preferentially deployed to the heat flux density peak area. When the temperature is abnormal, the status of the laptop components is analyzed and a reminder is issued.

[0091] The working principle of the above technical solution is: multiple temperature sensors are set in the high-heat area inside the laptop computer to detect the temperature inside the laptop computer and feed it back to the power management chip, the system working area is dynamically adjusted according to the temperature sensor data, the area with the largest current temperature difference is selected to issue a work instruction, the temperature difference between this area and the cold end is increased, and the target power generation unit is used to convert the thermal energy of the laptop computer when it is working into electrical energy; the output unstable low-voltage direct current is converted into stable electrical energy using a rectifier circuit and a DC-DC boost chip, the stable electrical energy is stored using a power storage device, the power recovery status is displayed on the laptop computer, and the use method of the recovered electrical energy is automatically determined according to user needs, user behavior analysis is performed based on the power generation situation, the laptop computer component status analysis is performed based on the temperature detection results, the power generation unit is intelligently configured according to the behavior analysis results, and a component status reminder is issued according to the component status analysis results.

[0092] The beneficial effects of the above technical solution are: the temperature inside the laptop is detected by multiple temperature sensors and fed back to the power management chip, which improves the detection efficiency while reducing the number of temperature sensors; the system working area is dynamically adjusted according to the temperature sensor detection data, which improves the intelligence of the system and reduces the waste of heat energy; the temperature difference between the heating area and the cold end is increased, and the target power generation unit is used to convert the heat energy of the laptop when it is working into electrical energy, which can effectively improve the heating efficiency; the output unstable low-voltage direct current is converted into stable electrical energy, which improves the safety of the system; the stable electrical energy is stored in the power storage device, the power recovery status is displayed on the laptop, and the use method of the recovered electrical energy is automatically determined according to user needs, which improves the intelligence of the system; user behavior analysis and laptop component status analysis are performed, the power generation unit is intelligently configured, and component status reminders are issued according to the component status analysis results, which improves the practicality and safety of the system and makes the system more intelligent.

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

[0094] a determination submodule 1011, configured to use a temperature detection device to detect heating conditions of multiple components of the laptop computer during operation, determine heating components and high-temperature locations of the laptop computer, and determine a temperature sensor location based on the high-temperature location;

[0095] In some embodiments, this embodiment uses a thermal imager or existing thermal design documents to locate high-temperature areas and identify key heat-generating components, such as the CPU, GPU, power module, SSD, battery, etc., and reserves space for sensor installation based on the device structure to avoid interfering with existing cooling systems, such as fans and heat pipes.

[0096] A detection submodule 1012 is configured to use the multiple temperature sensors to detect the internal temperature of the laptop computer during operation, and generate multiple temperature detection signals at different locations to feed back to the power management chip;

[0097] The analysis submodule 1013 is configured to analyze the temperature detection signal using a power management chip to determine the internal temperature distribution of the laptop computer during operation.

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

[0099] The beneficial effects of the above technical solution are: using a temperature detection device to detect the heating conditions of multiple components when the laptop is running, determining the heating components and high-temperature positions of the laptop, and determining the temperature sensor position based on the high-temperature position, and determining the sensor position according to the high-temperature area during the operation of the laptop, thereby improving the detection efficiency; using multiple temperature sensors to detect the internal temperature of the laptop when it is running, generating multiple temperature detection signals at different positions and feeding them back to the power management chip to improve the accuracy and real-time level of the data; using the power management chip to analyze the temperature detection signal, determine the temperature distribution inside the laptop when it is running, facilitate targeted selection of power generation areas, and improve the work efficiency of the system.

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

[0101] An acquisition submodule, configured to acquire the temperature distribution inside the laptop computer during operation and dynamically update the temperature in real time;

[0102] a temperature difference determination submodule, configured to determine a current temperature reference value based on the internal cold end temperature of the laptop computer, and to determine a temperature difference between the internal temperature of the laptop computer and the cold end based on the current internal temperature distribution of the laptop computer during operation;

[0103] In some embodiments, this embodiment uses an embedded temperature sensor network to capture the absolute temperature data of the cold end of the heat dissipation module, such as the fan outlet or the condenser section of the heat pipe, in real time and uses it as a dynamic reference temperature source. The distributed temperature lattice information of key areas such as the CPU, GPU memory power supply layer, etc. is simultaneously calculated. A three-dimensional thermal field distribution model is constructed based on a thermodynamic gradient field algorithm, and the real-time temperature difference between each heating unit and the cold end reference is compared frame by frame.

[0104] a judgment submodule, configured to determine in real time a high-heating area within the laptop computer that currently generates the most heat based on the temperature difference, and to determine whether the power generation efficiency of the high-heating area is greater than the current energy consumption of the entire waste heat recovery system; if so, to determine the high-heating area as a system working area and to issue a power generation instruction;

[0105] In some embodiments, this embodiment uses a thermal field gradient tracking algorithm to analyze multi-node temperature difference data streams in real time, dynamically locks onto the instantaneous heat flux density peak area, such as the CPU core or GPU memory power supply area in an overclocked state, and estimates the theoretical power generation power of this area based on the Seebeck coefficient matrix and the thermoelectric conversion efficiency model. Simultaneously, the waste heat recovery system's own energy consumption is calculated, which includes boost chip losses, heat dissipation and boost power consumption, and control unit standby power consumption. If the net energy gain threshold is exceeded, the priority arbitration engine marks the area as an effective working area, performs adaptive voltage regulation to maximize output, and simultaneously shuts down thermoelectric units in low ΔT areas 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, determine 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: obtaining the internal temperature distribution of the laptop computer when it is running and dynamically updating it in real time, thereby improving the timeliness of the data and enhancing the accuracy of the system operation; determining the current temperature reference value according to the internal cold end temperature of the laptop computer, and determining the temperature difference between the internal temperature of the laptop computer and the cold end according to the current internal temperature distribution of the laptop computer when it is running, thereby enhancing the accuracy and practicality of the data; determining the high-heating area with the largest current heat generation inside the laptop computer in real time according to the temperature difference, and judging whether the power generation efficiency of the high-heating area is greater than the current energy consumption of the entire waste heat recovery system. If so, determining the high-heating area as the system working area, issuing a power generation instruction, and starting the system only when the power generation efficiency is greater than the system energy consumption, thereby reducing resource waste and parts loss; obtaining multiple micro thermoelectric power generation units existing in the determined system working area, determining the multiple micro thermoelectric power generation units as target power generation units, issuing corresponding dynamic power generation instructions, and issuing power generation instructions in a targeted manner, thereby improving the intelligence of the system.

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

[0109] An optimization submodule is used to enhance the thermal conductivity of the hot ends of multiple micro-thermoelectric power generation units in the high-heating area inside the laptop computer through a thermally conductive silicone layer, and to enhance the heat dissipation efficiency of the cold end inside the laptop computer using micro-heat dissipation fins, thereby optimizing the power generation efficiency of the heat source;

[0110] In some embodiments, this embodiment closely adheres a high thermal conductivity medium layer to the surface of a high-heat-generating component, establishing a low-thermal-resistance heat transfer channel to efficiently transfer 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 ambient heat exchange capacity. Forced convection and radiation synergize to maximize the temperature gradient between the hot and cold ends.

[0111] A receiving submodule, configured to receive the dynamic power generation instruction, determine the target power generation unit requiring heat energy recovery, and real-time adjustment information;

[0112] The heat energy recovery submodule is used to enable the target power generation unit to dynamically adjust the workload of the target power generation unit according to 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 the target power generation unit receives the data, it adjusts the workload through a specific algorithm, such as a dynamic MPPT algorithm, such as changing the load impedance or adjusting the boost circuit parameters to optimize the Seebeck effect and maximize the power output. At the same time, it combines closed-loop control to ensure system stability and prevent overheating, ultimately improving overall energy efficiency and system life.

[0114] The beneficial effects of the above technical solution are: the thermal conductivity efficiency of the hot ends of multiple micro-thermoelectric power generation units in the high-heating area inside the laptop computer is enhanced by the thermal conductive silicone layer, and the heat dissipation efficiency of the cold end inside the laptop computer is enhanced by using micro-heating fins, thereby optimizing the heat source power generation efficiency, enhancing the temperature difference between the hot end and the cold end, and improving the power generation efficiency of the system; receiving dynamic power generation instructions, determining the target power generation unit that needs to recover heat energy and real-time adjustment information, and performing intelligent adjustment according to the instructions, thereby improving the intelligence level of the system; enabling the target power generation unit to dynamically adjust the workload of the target power generation unit according to the real-time temperature difference data provided by the thermal management module, thereby reducing the workload of the power generation unit and improving the durability and practicality of the system.

[0115] In one embodiment, 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 effect of the above technical solution is: the thermoelectric power generation unit is embedded in the heat dissipation module and integrated with the heat pipe and the heat spreader to avoid taking up additional space.

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

[0118] A rectifier and filter submodule, configured to adjust the current output by the target power generation unit using a rectifier circuit and smooth the rectified current using filter components;

[0119] A boost and current stabilization submodule, configured to use a DC-DC boost chip to boost the voltage to a preset voltage, and use the power management chip to determine switching between a constant voltage mode and a 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 boost efficiency in real time. The power management chip continuously monitors the internal resistance changes, output current ripple, and cold-end heat dissipation status of the power generation unit, dynamically switching control modes. 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 drastically or the energy storage unit is nearing full capacity, it switches to constant current mode to limit peak current.

[0121] A feedback regulation submodule, configured to detect specific parameters of the target power generation unit using current detection and a feedback loop, and adjust 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, builds a closed-loop regulation model, dynamically solves the optimal switching frequency and duty cycle combination of the boost topology, and simultaneously performs adaptive parameter adjustment based on the Seebeck coefficient attenuation curve of the thermoelectric unit;

[0123] The protection submodule is used to implement overvoltage protection and overcurrent protection using a safety protection circuit, and to provide overtemperature protection through 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 ends in real time; the overcurrent protection adopts high-precision current mirror sampling and comparator triggering architecture to cut off the main power path when the load is short-circuited; thermistor arrays are simultaneously mounted at the key hot points of the DC-DC chip, and the junction temperature status is mapped in real time through the temperature-resistance characteristic curve. When it is detected that the local temperature rise exceeds the safety threshold, the frequency reduction protection or forced shutdown instruction is immediately triggered, and the system log is linked to record the fault code.

[0125] The beneficial effects of the above technical solution are: using a rectifier circuit to adjust the current output by the target power generation unit, and using filter components to smooth the rectified current; further, using a DC-DC boost chip to increase the voltage to a preset voltage, and using 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, using a 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 according to the specific parameters; using a safety protection circuit to complete overvoltage protection and overcurrent protection, and using a thermistor mounted near the DC-DC boost chip to perform over-temperature protection, thereby 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 electric energy using 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 load demand of the current power supply equipment, it is first stored in the energy storage device. When it is insufficient, it is first supplied to the power supply equipment;

[0129] In some embodiments, a multi-source energy routing hub is constructed using a power management chip to monitor the input power and system load requirements of waste heat recovery electricity, the main battery, and the external adapter in real time. When the instantaneous power of the recovered electricity 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 activated 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 fill the gap. At the same time, the power supply path is intelligently allocated based on the load type, and reverse cutoff and overcharge protection circuits are integrated into the charge and discharge link.

[0130] A visualization submodule, configured to update the power of the energy storage device in real time on the display page of the laptop computer through a system plug-in;

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

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

[0133] The beneficial effects of the above technical solution are: using batteries and energy storage capacitors in parallel to recover electric energy, thereby improving the efficiency of electric energy recovery; the power management chip performs multi-source charging and discharging settings, and when the recovered electric energy is greater than the load demand of the current power-supply equipment, it is stored in the energy storage device first, and when it is insufficient, the power supply to the power-supply equipment is given priority, and intelligent power supply selection is used to improve the practicality and service life of the system; the power of the energy storage device is updated in real time on the display page of the laptop computer through the system plug-in; the laptop computer components that need to use recycled energy are dynamically adjusted according to the user's usage behavior of the laptop computer, and can interact with the user in real time, thereby enhancing the user experience.

[0134] In one embodiment, the analysis and reminder module is configured to:

[0135] Obtaining the working condition of the power generation unit, recording the power generation curve, marking the peak power generation period as a high-load period, obtaining and reading the temperature data of the high-heating area inside the laptop computer through the temperature sensor, and recording the temperature change curve of each high-heating area;

[0136] Classify user usage scenarios based on the power generation curve, and categorize usage scenarios into standby mode, low-load mode, and high-load mode based on power generation. Build user behavior profiles based on local power generation data, and use a lightweight Markov chain to predict possible usage scenarios for the next stage based on the user behavior profiles.

[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-to-low frequency temperature fluctuations (40-60°C); high-load mode: high power generation demand (>8W), GPU / CPU temperature surges (>75°C); local power generation data includes charging frequency, duration, power generation efficiency, etc.; Markov chain is a set of discrete random variables with Markov properties, which have irreducibility, recurrence, periodicity, and ergodicity;

[0138] Matching the high-temperature area according to the predicted usage scenario, dynamically switching the power generation unit in the high-temperature area to a high-priority power generation unit, and automatically matching the power supply mode according to the load of the user usage scenario;

[0139] In some embodiments, the automatic matching of power supply modes based on the load of the user's usage scenario is to automatically adjust the power generation unit and efficiency according to the user's behavior; for example, when it is detected that the user enters the game mode, the entire TEG array is enabled and the efficiency of the boost chip is improved, thereby sacrificing silence in exchange for power generation;

[0140] Obtaining the temperature change curve of each high-heat-generating area, and performing data analysis on the temperature change curve;

[0141] Based on the data analysis results, the component health of each high-heat area is evaluated, and the historical and current temperature differences under the same usage load are compared. If the temperature exceeds a preset threshold, it is determined that the component health in the area is poor, and a component health reminder is issued to the corresponding component through the laptop display port;

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

[0143] Based on the data analysis results, an abnormal analysis is performed on the real-time temperature of the high-heating area. When the real-time temperature is continuously high or the temperature jumps, the corresponding high-heating area is determined as an abnormal area, the components in the abnormal area are obtained, and a component abnormality reminder is issued through the display port of the laptop;

[0144] Generate behavior optimization suggestions based on the component health assessment results and the abnormality analysis results.

[0145] In some embodiments, a real-time notification mechanism is designed for component status reminders. When an anomaly is detected, the user is prompted through system notifications or indicator lights and suggested actions are given.

[0146] The beneficial effects of the above technical solution are: obtaining the working status of the power generation unit, recording the power generation curve, classifying user usage scenarios according to the power generation curve, building user behavior portraits based on local power generation data, predicting possible usage scenarios in the next stage, matching high-temperature areas according to the predicted usage scenarios, and dynamically switching the power generation units inside the high-temperature areas to high-priority power generation units. The system response speed and power generation efficiency are improved through priority adjustment, and practicality is improved. The power supply mode is automatically matched according to the load of the user usage scenario, the temperature change curve of the high-heat area is obtained, and data analysis is performed. Based on the data analysis results, the component health of the components in the high-heat area is evaluated, and a component health reminder is issued to the corresponding components through the laptop display port. Based on the data analysis results, an abnormal analysis is performed on the real-time temperature of the high-heat area, the abnormal area components are obtained, and a component abnormality reminder is issued through the laptop display port, thereby improving the safety factor of the system, generating behavior optimization suggestions based on the component health evaluation results and the abnormal analysis results, and improving the intelligence and practicality of the system.

[0147] In one embodiment, the system further includes an expansion module for users to customize system functions and perform performance verification of the system according to user requirements:

[0148] Obtaining adjustable system parameter types and determining a security parameter adjustment range for each of the system parameter types;

[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 working conditions;

[0150] Generate a system function customization page according to the adjustable system parameter type and the security parameter adjustment range, wherein the system function customization page has multiple adjustable system parameters and is provided with switch and adjustment range options;

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

[0152] Create a custom page, wherein the custom page allows the user 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 trend of key indicators, automatically identify conflicting parameter adjustments, and prompt the user to optimize the logic;

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

[0155] When a confirmation operation of the user on the parameter adjustment is detected, the adjusted parameter is set as a confirmed value of the target parameter, and the user-defined system function is applied;

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

[0157] In some embodiments, this embodiment alternately applies the new and old configurations within a safe range, for example, running each for 15 minutes, records the 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 the user requirements to determine whether the user requirements are met. If the user requirements are not met, system parameters that can be optimized are found, the parameters are optimized, and a performance optimization reminder is issued to the user through the custom page.

[0159] In some embodiments, this embodiment tracks the performance optimization goals preset by the user, such as the battery life extension rate, and the deviation from the actual system indicators in real time. When it is detected that the key indicators have not reached the expected threshold, the parameter space traversal analysis is automatically started to screen out adjustable variables that are strongly correlated with the goals, such as the activation density of the thermoelectric unit. The historical parameter adjustment data and the hardware health status assessment are combined to generate a progressive optimization plan, trigger a dynamic pop-up prompt on the custom page, and display the adjustable range of the current bottleneck parameter, the expected gain curve and the potential risk level. The "one-click trial run" function is embedded to allow the user to verify the adjustment effect in the simulation environment, while retaining the manual fine-tuning entry.

[0160] The beneficial effects of the above technical solution are as follows: obtaining adjustable system parameter types and security parameter adjustment ranges, generating a system function customization page based on the adjustable system parameter types and security parameter adjustment ranges, creating multiple configuration files, each of which stores different system parameter combinations, supporting users to perform personalized customized configuration adjustments, improving user experience, predicting system behavior based on user-adjusted system parameters, displaying key indicator change trends, automatically identifying conflicting parameter adjustments, prompting users to optimize logic, and ensuring system efficiency. When a user confirmation operation is detected, the user-defined system function is applied, and the new and old configurations are alternately applied within a safe range to obtain real-time data of the system, allowing high degree of freedom in customized debugging while ensuring system security. A built-in algorithm is used to calculate the performance improvement range, and the performance improvement range is compared with user requirements. If the user requirements are not met, system parameters that can be optimized are found, the parameters are optimized, and a performance optimization reminder is issued to the user through the customized page. This takes into account flexibility and security, provides powerful customization options while ensuring system stability, and helps users optimize settings through localized performance verification tools to improve system practicality.

[0161] This embodiment also discloses a method for recovering waste heat from a laptop computer based on the thermoelectric conversion effect. Figure 3 As shown, it is characterized by comprising:

[0162] S101 detects the temperature inside the laptop computer through multiple temperature sensors set in high-heat areas inside the laptop computer and feeds back the temperature to the power management chip;

[0163] S102 uses the power management chip to dynamically adjust the system working area according to the temperature sensor data, and selects the area with the largest current temperature difference to issue a working instruction;

[0164] S103 uses a thermally conductive silicone layer and micro-heat sink fins to increase the temperature difference between the region and the cold end, determines a target power generation unit in the region according to the work instruction, and uses the target power generation unit to convert thermal energy generated by the laptop computer during operation into electrical energy;

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

[0166] S105 uses the stable electric energy stored in the electric storage device, displays the electric energy recovery status on the laptop computer, and automatically determines the use method of the recovered electric energy according to the user's needs;

[0167] S106 performs user behavior analysis based on power generation conditions, performs component status analysis on the laptop computer based on temperature detection results, performs intelligent configuration of power generation units based on the behavior analysis results, and issues component status reminders based on the component status analysis results.

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

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

Claims

1. A notebook computer waste heat recovery system based on thermoelectric conversion effect, characterized in that: include: An intelligent detection module, configured to detect the temperature inside the laptop computer through a plurality of temperature sensors disposed in high-heat areas inside the laptop computer and feed the temperature back to the power management chip; A thermal management module is used to use the power management chip to dynamically adjust the system working area according to the temperature sensor data, and select the area with the largest current temperature difference to issue a working instruction; a waste heat recovery module, configured to increase the temperature difference between the region and the cold end using a thermally conductive silicone layer and micro-heat sink fins, determine a target power generation unit within the region according to the operating instruction, and convert thermal energy generated by the laptop computer during operation into electrical energy using the target power generation unit; A current stabilization module, configured to convert the unstable low-voltage direct current outputted by the target power generation unit into stable electrical energy using a rectifier circuit and a DC-DC boost chip; an intelligent energy storage control module, configured to use the stable electric energy stored by the electric storage device to display the electric energy recovery status on the laptop computer and automatically determine the use mode of the recovered electric energy according to user needs; The analysis and reminder module is used to perform user behavior analysis based on power generation conditions, analyze the status of laptop components based on temperature detection results, intelligently configure the power generation unit according to the behavior analysis results, and issue component status reminders according to the component status analysis results.

2. The notebook computer waste heat recovery system based on thermoelectric conversion effect according to claim 1, characterized in that: The intelligent detection module includes: a determination submodule, configured to use a temperature detection device to detect the heating conditions of multiple components of the laptop computer when the laptop computer is running, determine the heating components and high-temperature positions of the laptop computer, and determine the position of the temperature sensor based on the high-temperature position; A detection submodule, configured to use the multiple temperature sensors to detect the internal temperature of the laptop computer during operation, and generate multiple temperature detection signals at different positions to feed back to the power management chip; The analysis submodule is used to analyze the temperature detection signal using a power management chip to determine the temperature distribution inside the laptop computer when the laptop computer is running.

3. The notebook computer waste heat recovery system based on thermoelectric conversion effect according to claim 1, characterized in that: The thermal management module comprises: An acquisition submodule, configured to acquire the temperature distribution inside the laptop computer during operation and dynamically update the temperature in real time; a temperature difference determination submodule, configured to determine a current temperature reference value based on the internal cold end temperature of the laptop computer, and to determine a temperature difference between the internal temperature of the laptop computer and the cold end based on the current internal temperature distribution of the laptop computer during operation; a judgment submodule, configured to determine in real time a high-heating area within the laptop computer that currently generates the most heat based on the temperature difference, and to determine whether the power generation efficiency of the high-heating area is greater than the current energy consumption of the entire waste heat recovery system; if so, to determine the high-heating area as a system working area and to issue a power generation instruction; The instruction generation submodule is used to obtain multiple micro thermoelectric power generation units existing in the determined system working area, determine the multiple micro thermoelectric power generation units as target power generation units, and issue corresponding dynamic power generation instructions.

4. The notebook computer waste heat recovery system based on thermoelectric conversion effect according to claim 1, characterized in that: The waste heat recovery module comprises: An optimization submodule is used to enhance the thermal conductivity of the hot ends of multiple micro-thermoelectric power generation units in the high-heating area inside the laptop computer through a thermally conductive silicone layer, and to enhance the heat dissipation efficiency of the cold end inside the laptop computer using micro-heat dissipation fins, thereby optimizing the power generation efficiency of the heat source; A receiving submodule, configured to receive the dynamic power generation instruction, determine the target power generation unit requiring heat energy recovery, and real-time adjustment information; The heat energy recovery submodule is used to enable the target power generation unit to dynamically adjust the workload of the target power generation unit according to the real-time temperature difference data provided by the thermal management module.

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

6. The notebook computer waste heat recovery system based on thermoelectric conversion effect according to claim 1, characterized in that: The flow stabilization module comprises: A rectifier and filter submodule, configured to adjust the current output by the target power generation unit using a rectifier circuit and smooth the rectified current using filter components; A boost and current stabilization submodule, configured to use a DC-DC boost chip to boost the voltage to a preset voltage, and use the power management chip to determine switching between a constant voltage mode and a constant current mode according to the state of the target power generation unit; A feedback regulation submodule, configured to detect specific parameters of the target power generation unit using current detection and a feedback loop, and adjust corresponding parameters of the boost chip according to the specific parameters; The protection submodule is used to implement overvoltage protection and overcurrent protection using a safety protection circuit, and to provide overtemperature protection through a thermistor mounted near the DC-DC boost chip.

7. The notebook computer waste heat recovery system 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 electric energy using 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 load demand of the current power supply equipment, it is first stored in the energy storage device. When it is insufficient, it is first supplied to the power supply equipment; A visualization submodule, configured to update the power of the energy storage device in real time on the display page of the laptop computer through a system plug-in; The automatic control submodule is used to dynamically adjust the notebook computer components that need to use recycled energy according to the user's usage behavior of the notebook computer.

8. The notebook computer waste heat recovery system based on thermoelectric conversion effect according to claim 1, characterized in that: The analysis and reminder module is configured to: Obtaining the working condition of the power generation unit, recording the power generation curve, marking the peak power generation period as a high-load period, obtaining and reading the temperature data of the high-heating area inside the laptop computer through the temperature sensor, and recording the temperature change curve of each high-heating area; Classify user usage scenarios based on the power generation curve, and categorize usage scenarios into standby mode, low-load mode, and high-load mode based on power generation. Build user behavior profiles based on local power generation data, and use a lightweight Markov chain to predict possible usage scenarios for the next stage based on the user behavior profiles. Matching the high-temperature area according to the predicted usage scenario, dynamically switching the power generation unit in the high-temperature area to a high-priority power generation unit, and automatically matching the power supply mode according to the load of the user usage scenario; Obtaining the temperature change curve of each high-heat-generating area, and performing data analysis on the temperature change curve; Based on the data analysis results, the component health of each high-heat area is evaluated, and the historical and current temperature differences under the same usage load are compared. If the temperature exceeds a preset threshold, it is determined that the component health in the area is poor, and a component health reminder is issued to the corresponding component through the laptop display port; Based on the data analysis results, an abnormal analysis is performed on the real-time temperature of the high-heating area. When the real-time temperature is continuously high or the temperature jumps, the corresponding high-heating area is determined as an abnormal area, the components in the abnormal area are obtained, and a component abnormality reminder is issued through the display port of the laptop; Generate behavior optimization suggestions based on the component health assessment results and the abnormality analysis results.

9. The notebook computer waste heat recovery system based on thermoelectric conversion effect according to claim 1, characterized in that: It also includes expansion modules for users to customize system functions and verify system performance according to user needs: Obtaining adjustable system parameter types and determining a security parameter adjustment range for each of the system parameter types; Generate a system function customization page according to the adjustable system parameter type and the security parameter adjustment range, wherein the system function customization page has multiple adjustable system parameters and is provided with switch and adjustment range options; Create a custom page, wherein the custom page allows the user 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 trend of key indicators, automatically identify conflicting parameter adjustments, and prompt the user to optimize the logic; When a confirmation operation of the user on the parameter adjustment is detected, the adjusted parameter is set as a confirmed value of the target parameter, and the user-defined system function is applied; After applying the user-defined system function, alternately apply the old and new configurations within a safe range, obtain real-time data of the system, record key data differences, and use built-in algorithms to calculate the performance improvement range; The performance improvement range is compared with the user requirements to determine whether the user requirements are met. If the user requirements are not met, system parameters that can be optimized are found, the parameters are optimized, and a performance optimization reminder is issued to the user through the custom page.

10. A method for recovering waste heat from a laptop computer based on thermoelectric conversion effect, characterized in that: include: The temperature inside the laptop is detected by multiple temperature sensors arranged in high-heat areas inside the laptop and the temperature is fed back to the power management chip; Using the power management chip to dynamically adjust the system working area according to the temperature sensor data, select the area with the largest current temperature difference to issue a working instruction; using a thermally conductive silicone layer and micro-heat sink fins to increase the temperature difference between the region and the cold end, determining a target power generation unit in the region according to the work instruction, and using the target power generation unit to convert thermal energy generated by the laptop computer during operation into electrical energy; Using a rectifier circuit and a DC-DC boost chip to convert the unstable low-voltage direct current output by the target power generation unit into stable electrical energy; The stable electric energy stored in the electric storage device is used to display the electric energy recovery status on the laptop computer, and automatically determine the use mode of the recovered electric energy according to user needs; User behavior analysis is performed based on power generation conditions, component status analysis of the laptop computer is performed based on temperature detection results, power generation units are intelligently configured according to the behavior analysis results, and component status reminders are issued according to the component status analysis results.

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