A smart battery thermal management system based on thermoelectric coolers

Abstract

The application discloses an intelligent battery thermal management system based on thermoelectric coolers, and relates to the technical field of new energy and electronic engineering.The system comprises a TEC optimization layout module, a micro-channel heat dissipation module, a detector preparation module and an NMPC control module.The TEC optimization layout module is responsible for optimizing the position and contact area of the thermoelectric cooler (TEC), analyzing the internal temperature distribution of the battery unit, determining the heat accumulation area, and embedding a heat-conducting metal plate between the battery units by arranging the TEC near the top of the battery, so that the internal heat balance is promoted by using the cooling capacity of the TEC.The micro-channel heat dissipation module is responsible for establishing a micro-channel radiator, and the double goals of compact structure and high-efficiency heat dissipation are achieved by adopting the micro-channel technology, so that the battery is in an ideal temperature zone.The detector preparation module is responsible for the preparation process of a nickel / gallium oxide / silicon carbide metal oxide, a semiconductor field effect detector, and real-time monitoring of the battery temperature.The NMPC control module is responsible for predicting and optimizing the energy consumption in the battery thermal management system by using a nonlinear model predictive control (NMPC) algorithm, and dynamically adjusting the TEC operation strategy according to the current battery working condition and future prediction.

Description

Technical Field

[0001] This invention relates to the fields of new energy and electronic engineering technology, and in particular to an intelligent battery thermal management system based on a thermoelectric cooler. Background Technology

[0002] Against the backdrop of today's energy transition and the booming development of the electric vehicle industry, battery thermal management technology has become one of the key technologies to ensure the safe, reliable, and long-lasting operation of high-performance batteries. The research and application of battery thermal management systems (BTMS) have gradually gained attention, especially in the field of high-energy-density lithium-ion batteries. If the large amount of heat generated during charging and discharging cannot be effectively managed, it will lead to battery performance degradation, shortened lifespan, and even safety accidents. Traditional battery thermal management strategies rely on air cooling, liquid circulation, and phase change materials. These methods have alleviated thermal management problems to some extent, but they often face limitations such as low heat dissipation efficiency, high system complexity, and increased costs.

[0003] In existing technologies, thermoelectric coolers (TECs), as an active thermal management method, have been gradually applied to battery thermal management systems. They can directly remove heat from battery cells through the Peltier effect. However, existing TEC applications still have significant shortcomings: First, the layout and contact area of ​​TECs are not optimized, resulting in limited cooling efficiency and frequent local overheating problems; second, most systems lack efficient heat dissipation structures, making it impossible to achieve rapid and uniform heat transfer; third, temperature monitoring accuracy and system response speed have become key bottlenecks restricting intelligent regulation; finally, the energy management strategy is simplistic, failing to fully utilize predictive control to optimize energy consumption, increasing the overall energy consumption burden of battery operation. These problems collectively limit the comprehensive performance and application potential of existing battery thermal management systems. Summary of the Invention

[0004] In view of the aforementioned existing problems, the present invention is proposed.

[0005] Therefore, this invention provides an intelligent battery thermal management system based on a thermoelectric cooler to address several issues: First, the layout and contact area of ​​the TEC (thermoelectric cooler) are not optimized, resulting in limited cooling efficiency and frequent local overheating problems. Second, most systems lack efficient heat dissipation structures, failing to achieve rapid and uniform heat transfer. Third, temperature monitoring accuracy and system response speed are key bottlenecks restricting intelligent regulation. Finally, the energy management strategy is simplistic, failing to fully utilize predictive control to optimize energy consumption, thus increasing the overall energy consumption burden of battery operation. These problems collectively limit the comprehensive performance and application potential of existing battery thermal management systems.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0007] In a first aspect, embodiments of the present invention provide an intelligent battery thermal management system based on a thermoelectric cooler, comprising,

[0008] The TEC optimization layout module is responsible for optimizing the position and contact area of ​​the thermoelectric cooler (TEC), analyzing the internal temperature distribution of the battery cell, determining the heat accumulation area, and promoting internal heat balance by arranging the TEC near the top of the battery and embedding heat-conducting metal plates between the battery cells.

[0009] The microchannel heat dissipation module is responsible for building a microchannel heat sink. By adopting microchannel technology, it achieves the dual goals of compact structure and efficient heat dissipation, keeping the battery in an ideal temperature range.

[0010] The detector fabrication module is responsible for the fabrication process of nickel / gallium oxide / silicon carbide metal oxide and semiconductor field-effect detectors, monitors battery temperature in real time, provides accurate data input for the thermal management system, and enhances the system's real-time response and intelligent adjustment capabilities.

[0011] The NMPC control module is responsible for predicting and optimizing energy consumption in the battery thermal management system using the NMPC algorithm based on nonlinear model prediction control. It dynamically adjusts the TEC operation strategy according to the current battery operating conditions and future predictions.

[0012] As a preferred embodiment of the intelligent battery thermal management system based on a thermoelectric cooler described in this invention, the specific steps for analyzing the internal temperature distribution of the battery cell and determining the heat accumulation area are as follows:

[0013] Based on the size, shape, and operating environment of the battery pack, select an infrared thermal imager with high resolution, fast frame rate, and suitable temperature range;

[0014] Infrared thermal imagers are used to monitor the temperature distribution of batteries during operation and to identify the areas with the largest temperature gradients.

[0015] Use an infrared thermal imager to perform a non-contact temperature scan of the battery pack;

[0016] Thermal image analysis identified the top as a region with higher temperatures.

[0017] As a preferred embodiment of the intelligent battery thermal management system based on a thermoelectric cooler described in this invention, the following steps are taken: Through thermal image analysis, the top area is identified as having a higher temperature.

[0018] The internal temperature gradient of the battery is obtained by detecting temperature changes at the top and bottom of the battery, expressed as:

[0019] ;

[0020] in, Indicates time At that time, the temperature difference inside the battery, that is, the temperature difference between the top and bottom of the battery, Indicates the time at the top of the battery. Temperature at any moment Indicates the time at the bottom of the battery. Temperature at any moment Represents a time variable;

[0021] choose The largest area serves as the TEC installation point;

[0022] The contact area between the TEC and the top of the battery is calculated using the following expression:

[0023] ;

[0024] in, This indicates the actual contact area between the TEC and the top of the battery. This indicates the cooling efficiency coefficient of the TEC. Indicates the length of the heat-conducting metal plate. This indicates the thermal conductivity of the heat-conducting metal plate.

[0025] As a preferred embodiment of the intelligent battery thermal management system based on a thermoelectric cooler described in this invention, the following steps are taken: A thermally conductive metal plate is embedded between the battery cells to utilize its cooling capacity and promote internal heat balance.

[0026] A thermally conductive metal plate is deployed between every two adjacent battery cells. The length of the thermally conductive metal plate is expressed as follows:

[0027] ;

[0028] in, Indicates the length of the heat-conducting metal plate;

[0029] Establish a thermal gradient equilibrium model, the expression of which is:

[0030] ;

[0031] in, This indicates the adjusted internal temperature gradient of the battery. Indicates the total number of battery cells. This indicates the distance between adjacent battery cells.

[0032] As a preferred embodiment of the intelligent battery thermal management system based on a thermoelectric cooler described in this invention, wherein: according to and The deviation is used to dynamically adjust the TEC current output and the possible layout of the heatsink, expressed as:

[0033] ;

[0034] in, Indicates the thermoelectric cooler in time The current required at that time proportionality coefficient This represents the difference between the actual temperature gradient and the target temperature gradient. The integral coefficient is... This represents the cumulative error from the initial moment to the present. These are the differential coefficients, reflecting the influence of the rate of change of the error. The rate of change of error reflects how quickly the system error changes.

[0035] As a preferred embodiment of the intelligent battery thermal management system based on a thermoelectric cooler described in this invention, the system is responsible for establishing a microchannel heat sink. By employing microchannel technology, it achieves the dual goals of compact structure and efficient heat dissipation. The specific steps are as follows:

[0036] The expression for the effective heat dissipation area, based on the microchannel structure, is as follows: ;

[0037] in, Indicates the effective heat dissipation area. Indicates the channel width. Indicates the channel height. Indicates the channel length. Indicates the number of microchannels;

[0038] The flow state of the fluid in the microchannel is determined by calculating the Reynolds number, which helps in selecting a suitable cooling medium and flow rate. The Reynolds number calculation expression is as follows:

[0039] ;

[0040] in, The Reynolds number is used to indicate whether the fluid flow is laminar or turbulent. Indicates fluid density, The average flow velocity, Dynamic viscosity;

[0041] Based on the effective heat dissipation surface of the microchannel heat sink, its total thermal resistance, including convective thermal resistance, conductive thermal resistance, and radiative thermal resistance, is calculated using the following expression:

[0042] ;

[0043] in, This represents the total thermal resistance of the effective heat dissipation surface. Indicates the convective heat transfer coefficient;

[0044] Predicting the temperature rise under a given heat load to keep the battery in its ideal temperature range, the expression is:

[0045] ;

[0046] in, This indicates the temperature rise that occurs during heat transfer. Indicates heat load, This represents the mass of fluid flowing through the system per unit time. Indicates specific heat capacity. This indicates thermal conductivity.

[0047] As a preferred embodiment of the intelligent battery thermal management system based on a thermoelectric cooler described in this invention, the specific steps of the fabrication process for the nickel / gallium oxide / silicon carbide metal oxide and the semiconductor field-effect detector are as follows:

[0048] High-quality nickel / gallium oxide / silicon carbide composite thin film materials were synthesized using chemical vapor deposition (CVD) technology, as shown in the following expression:

[0049] ;

[0050] in, Represents the electrical conductivity of the material. Indicates temperature. Indicates pressure, Indicates the deposition time. Indicates the concentration of the reacting gas. Indicates the electrical conductivity of a material and The mapping relationship between them;

[0051] The performance parameters of field-effect transistors (FETs) are precisely controlled using photolithography and etching techniques. The field effect is optimized by adjusting the ratio of gate length to gate width, as expressed in the following expression:

[0052] ;

[0053] in, Indicates the missed current. Indicates carrier mobility. Indicates the gate width. Indicates the gate length. Indicates the capacitance of the oxide layer. This represents the voltage between the gate and the source. This represents the threshold voltage.

[0054] As a preferred embodiment of the intelligent battery thermal management system based on a thermoelectric cooler described in this invention, the following steps are taken: Real-time monitoring of battery temperature provides accurate data input to the thermal management system, enhancing the system's immediate response and intelligent adjustment capabilities:

[0055] Ni doping enhances the temperature sensitivity of materials, making the change in detector resistance with temperature more pronounced. The relationship between doping concentration and temperature responsivity is expressed as follows:

[0056] ;

[0057] in, Indicates temperature The resistance at that time, Represents the resistance at room temperature. This represents the natural exponential function. Indicates activation energy. Represents the Boltzmann constant. Represents temperature variable. This indicates that the measured temperature has been converted from Celsius to Kelvin.

[0058] The prepared detector is then packaged.

[0059] During integration, considering the detector's positional distribution to ensure full coverage of critical battery areas, the detector layout optimization expression is described as follows:

[0060] ;

[0061] in, Indicates the first One thermal resistance, This represents the total thermal resistance in the system. This represents the target average thermal resistance.

[0062] As a preferred embodiment of the intelligent battery thermal management system based on a thermoelectric cooler described in this invention, the energy consumption in the battery thermal management system is predicted and optimized using the Nonlinear Model Predictive Control (NMPC) algorithm. The TEC operation strategy is dynamically adjusted based on the current battery operating conditions and future predictions. The specific steps are as follows:

[0063] A nonlinear model predictive control (NMPC) algorithm framework incorporating energy consumption and temperature control is established, expressed as follows:

[0064] ;

[0065] in, Indicates time Energy consumption per hour Indicates time The battery temperature tracking error vector at time step. and These represent the weight matrix for temperature tracking error and the weight matrix for the squared term of total power consumption, respectively. express transpose, Indicates time Total power consumption of the system at any given time;

[0066] The The expression is:

[0067] ;

[0068] in, Indicates from index Starting from 1, and continuing until... equal Continuous summation, Indicates the first Power consumption of a thermoelectric cooler This indicates the power consumption of the fan.

[0069] As a preferred embodiment of the intelligent battery thermal management system based on a thermoelectric cooler described in this invention, in order to force the battery cells to operate within their optimal temperature range, and simultaneously limit the battery cell temperature to an ideal range of 20 to 45°C, a point constraint condition is set, expressed as:

[0070] ;

[0071] ;

[0072] ;

[0073] ;

[0074] ;

[0075] ;

[0076] in, Represents the system state vector. Represents the control input vector. This represents the external disturbance vector. This indicates how the system state changes over time. and Indicates the minimum and maximum allowable values ​​for battery cell temperature. Indicates the first Each battery cell in time The actual temperature Indicates the maximum allowable temperature of the radiator. and This indicates the minimum and maximum allowable values ​​of the thermoelectric cooler (TEC) current. express Each TEC module in time The actual current, and This represents the minimum and maximum values ​​of the inverter resistance in the system.

[0077] The beneficial effects of this invention are as follows: Through precise calculation and layout, this invention ensures the optimal position and contact area of ​​the TEC near the top of the battery. Combined with the ingenious embedding of the heat-conducting metal plate, it achieves a balanced distribution and rapid heat dissipation inside the battery. The application of microchannel heat dissipation technology improves heat dissipation efficiency while maintaining the system's compactness and lightweight design, creating an ideal temperature control environment for the battery. In addition, the semiconductor field-effect detector used in this invention, with its excellent temperature sensing performance and fast response capability, provides the system with real-time and accurate temperature data, greatly enhancing the level of intelligent thermal management. Most importantly, the introduced nonlinear model predictive control (NMPC) algorithm can dynamically adjust the TEC operation strategy based on the current operating conditions and future predictions, effectively reducing system energy consumption and achieving optimal energy efficiency. Attached Figure Description

[0078] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0079] Figure 1 This is a structural diagram of the battery thermal management system using a thermoelectric cooler in Example 1.

[0080] Figure 2 This is a circuit diagram of the battery thermal management system of the electric cooler in Example 1. Detailed Implementation

[0081] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0082] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0083] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0084] Example 1, referring to Figure 1 and Figure 2 This is the first embodiment of the present invention, which provides an intelligent battery thermal management system based on a thermoelectric cooler, including the following steps:

[0085] S1, TEC optimization layout module, is responsible for optimizing the position and contact area of ​​thermoelectric cooler TEC, analyzing the internal temperature distribution of battery cell, determining the heat accumulation area, and promoting internal heat balance by arranging TEC near the top of battery and embedding heat-conducting metal plates between battery cells.

[0086] The specific steps for analyzing the internal temperature distribution of the battery cell and determining the heat accumulation area are as follows:

[0087] Based on the size, shape, and operating environment of the battery pack, select an infrared thermal imager with high resolution, fast frame rate, and suitable temperature range;

[0088] Infrared thermal imagers are used to monitor the temperature distribution of batteries during operation and to identify the areas with the largest temperature gradients.

[0089] Before performing thermal imaging, allow the battery pack to run in normal operating conditions for a period of time to ensure that the internal temperature distribution of the battery reaches a steady state, so as to obtain a more accurate temperature distribution map.

[0090] Ensure that the test environment is free from strong light sources and that the temperature and humidity are stable to avoid the influence of external environmental factors on the thermal imaging results.

[0091] Use an infrared thermal imager to perform a non-contact temperature scan of the battery pack;

[0092] Thermal image analysis identified the top as a region with higher temperatures.

[0093] Thermal image analysis identified the top as a region with higher temperatures. The specific steps were as follows:

[0094] The internal temperature gradient of the battery is obtained by detecting temperature changes at the top and bottom of the battery, expressed as:

[0095] ;

[0096] in, Indicates time At that time, the temperature difference inside the battery, that is, the temperature difference between the top and bottom of the battery, Indicates the time at the top of the battery. Temperature at any moment Indicates the time at the bottom of the battery. Temperature at any moment Represents a time variable;

[0097] choose The largest area serves as the TEC installation point;

[0098] Calculate the contact area between the TEC and the top of the battery to ensure maximum cooling efficiency, using the following expression:

[0099] ;

[0100] in, This indicates the actual contact area between the TEC and the top of the battery, measured in square meters. This area directly affects the efficiency of heat exchange. The cooling efficiency coefficient of the TEC (Thermoelectric Temperature Coefficient) reflects the efficiency of the TEC in removing heat from the battery cell. This indicates the length of the heat-conducting metal plate, measured in meters. This length affects the efficiency of heat transfer between battery cells. This indicates the thermal conductivity of the heat-conducting metal plate.

[0101] The specific method for determination is as follows:

[0102] (Using a heating element to generate constant heat) and maintaining a certain current flowing through the TEC, the temperature difference across the TEC and the electrical energy consumed are measured, and calculations are performed based on these data. The expression is:

[0103] = Actual heat removed / (Input electrical energy + any additional losses).

[0104] A thermally conductive metal plate is embedded between the battery cells to utilize its cooling capacity and promote internal heat balance. The specific steps are as follows:

[0105] A thermally conductive metal plate is deployed between every two adjacent battery cells. This plate is designed to reduce the size of the thermally conductive metal plate, its thermal conductivity, and the thermal gradient between the cells, ensuring that heat flow is evenly distributed between the battery cells. The expression for the length of the thermally conductive metal plate is:

[0106] ;

[0107] in, Indicates the length of the heat-conducting metal plate;

[0108] Establish a thermal gradient equilibrium model, the expression of which is:

[0109] ;

[0110] in, This indicates the adjusted internal temperature gradient of the battery. Indicates the total number of battery cells. This indicates the distance between adjacent battery cells, usually in millimeters, and involves the calculation of the length of the heat conduction path and thermal resistance.

[0111] according to and To mitigate deviations, the TEC current output and possible heatsink layout are dynamically adjusted to ensure continuous optimization of the temperature control strategy. The expression is:

[0112] ;

[0113] in, Indicates the thermoelectric cooler in time The required current is used to adjust its cooling capacity, thereby controlling the battery temperature. The proportional gain determines the direct relationship between the current error and the controller output. This represents the difference between the actual temperature gradient and the target temperature gradient. The integral coefficient is related to the accumulation of error over time. This represents the cumulative error from the initial moment to the present. These are the differential coefficients, reflecting the influence of the rate of change of the error. The rate of change of error reflects the speed at which the systematic error changes;

[0114] , The value range is usually from room temperature to the battery's maximum operating temperature, reflecting the dynamic change of temperature over time;

[0115] The value ranges from 0 to the maximum temperature difference, representing the degree of temperature unevenness inside the battery;

[0116] The temperature range is 20 to 45°C, which is the optimal operating temperature range for lithium-ion batteries.

[0117] The value range is determined by the minimum and maximum acceptable current of the TEC, reflecting the adjustment range of the cooling capacity.

[0118] S2, Microchannel heat dissipation module, is responsible for building a microchannel heat sink. By adopting microchannel technology, it achieves the dual goals of compact structure and efficient heat dissipation, keeping the battery in an ideal temperature range.

[0119] Responsible for building a microchannel heatsink, achieving the dual goals of compact structure and efficient heat dissipation through the use of microchannel technology. The specific steps are as follows:

[0120] The expression for the effective heat dissipation area, based on the microchannel structure, is as follows: ;

[0121] in, Indicates the effective heat dissipation area. Indicates the channel width. Indicates the channel height. Indicates the channel length. Indicates the number of microchannels;

[0122] The flow state of the fluid in the microchannel is determined by calculating the Reynolds number, which helps in selecting a suitable cooling medium and flow rate. The Reynolds number calculation expression is as follows:

[0123] ;

[0124] in, The Reynolds number is used to indicate whether the fluid flow is laminar or turbulent. Indicates fluid density, The average flow velocity, Dynamic viscosity;

[0125] Based on the effective heat dissipation surface of the microchannel heat sink, its total thermal resistance, including convective thermal resistance, conductive thermal resistance, and radiative thermal resistance, is calculated using the following expression:

[0126] ;

[0127] in, This represents the total thermal resistance of the effective heat dissipation surface. Indicates the convective heat transfer coefficient;

[0128] Predicting the temperature rise under a given heat load to keep the battery in its ideal temperature range, the expression is:

[0129] ;

[0130] in, This indicates the temperature rise that occurs during heat transfer. Indicates heat load, This represents the mass of fluid flowing through the system per unit time. Indicates specific heat capacity. Indicates thermal conductivity;

[0131] Flow states, including laminar and turbulent flow;

[0132] The specific criteria for determining the flow state of fluid in a microchannel are as follows:

[0133] When Reynolds number When the temperature is below 2300, the fluid flow exhibits laminar flow.

[0134] When Reynolds number When the value is greater than 4000, the fluid flow exhibits turbulence.

[0135] Cooling media include water and fluorinated fluids;

[0136] Selecting the appropriate cooling medium and flow rate is as follows:

[0137] In laminar flow conditions, due to the relatively low heat transfer efficiency, a material with a higher specific heat capacity is required to maintain good heat dissipation. and thermal conductivity Fluorinated fluids are used to enhance heat transfer capacity. To reduce thermal resistance, a small flow rate is required to ensure that the fluid flows slowly and stably in the microchannel, thereby increasing the heat exchange time and improving heat transfer efficiency.

[0138] In turbulent flow, water is chosen as the cooling medium due to its high heat transfer efficiency. Furthermore, a large flow rate can be selected to increase the heat exchange rate, as turbulence effectively stirs the fluid, reduces the boundary layer thickness, and improves the convective heat transfer coefficient. ;

[0139] Temperature rise The smaller the value range, the better the heat dissipation effect. It is generally within a few degrees, which is used to ensure that the battery temperature is stable in the ideal working range of 20 to 45°C.

[0140] Total thermal resistance The target value is 0.01℃ / W, which is a key indicator for measuring the performance of a heat sink; the lower the value, the higher the heat dissipation efficiency.

[0141] S3, Detector Fabrication Module, is responsible for the fabrication process of nickel / gallium oxide / silicon carbide metal oxide and semiconductor field-effect detectors, monitors battery temperature in real time, provides accurate data input for the thermal management system, and enhances the system's instant response and intelligent adjustment capabilities.

[0142] The fabrication process of nickel / gallium oxide / silicon carbide metal oxide semiconductor field-effect detectors includes the following specific steps:

[0143] High-quality nickel / gallium oxide / silicon carbide composite thin film materials were synthesized using chemical vapor deposition (CVD) technology, as shown in the following expression:

[0144] ;

[0145] in, Represents the electrical conductivity of the material. Indicates temperature. Indicates pressure, Indicates the deposition time. Indicates the concentration of the reacting gas. Indicates the electrical conductivity of a material and The mapping relationship between them;

[0146] The performance parameters of field-effect transistors (FETs) are precisely controlled using photolithography and etching techniques. The field effect is optimized by adjusting the ratio of gate length to gate width, as expressed in the following expression:

[0147] ;

[0148] in, Indicates the missed current. Indicates carrier mobility. Indicates the gate width. Indicates the gate length. Indicates the capacitance of the oxide layer. This represents the voltage between the gate and the source. Indicates the threshold voltage;

[0149] Increasing the gate width can improve the transconductance of a FET. Transconductance is the slope of the drain current change caused by the gate voltage change. Increasing the transconductance is equivalent to a larger change in drain current for the same gate voltage change, which improves the device's response to temperature changes and increases its sensitivity.

[0150] The short-channel effect enhances the capacitive coupling of the FET as the gate length decreases, strengthens the gate's control over the channel, and causes a small change in the gate voltage to cause a larger change in the drain current, which also helps to improve sensitivity.

[0151] However, reducing the gate length introduces short-channel effects, including increased leakage current and threshold voltage drift, which can affect the stability of the detector. Therefore, the ratio of gate length to width needs to be carefully designed to balance sensitivity and stability.

[0152] Real-time monitoring of battery temperature provides accurate data input to the thermal management system, enhancing the system's immediate response and intelligent adjustment capabilities. The specific steps are as follows:

[0153] Ni doping enhances the temperature sensitivity of materials, making the change in detector resistance with temperature more pronounced. The relationship between doping concentration and temperature responsivity is expressed as follows:

[0154] ;

[0155] in, Indicates temperature The resistance at that time, Represents the resistance at room temperature. This represents the natural exponential function. Indicates activation energy. Represents the Boltzmann constant. Represents temperature variable. This indicates that the measured temperature has been converted from Celsius to Kelvin.

[0156] The prepared detector is packaged to prevent external environmental factors from affecting its performance, and then integrated into the battery thermal management system.

[0157] During integration, considering the detector's positional distribution to ensure full coverage of critical battery areas, the detector layout optimization expression is described as follows:

[0158] ;

[0159] in, Indicates the first One thermal resistance, This represents the total thermal resistance in the system. Indicates the target average thermal resistance;

[0160] A field-effect transistor (FET) structure includes a source, a drain, and a gate;

[0161] This indicates the direct impact of material growth conditions on performance; its value range varies depending on specific CVD process parameters, guiding optimized material synthesis. The temperature response model... The value range covers from room temperature to the battery's maximum operating temperature (20 to 45°C), reflecting the detector's temperature operating range. Through the comprehensive application of these formulas, not only is accurate monitoring of the battery temperature achieved, but the innovation and practicality of the scheme are also demonstrated, significantly improving the performance of the battery thermal management system.

[0162] The S4 and NMPC control modules are responsible for predicting and optimizing energy consumption in the battery thermal management system using the NMPC algorithm based on nonlinear model prediction control. They dynamically adjust the TEC operation strategy according to the current battery operating conditions and future predictions.

[0163] The NMPC algorithm predicts and optimizes energy consumption in the battery thermal management system using a nonlinear model prediction control. Based on the current battery operating conditions and future predictions, the TEC operation strategy is dynamically adjusted. The specific steps are as follows:

[0164] A nonlinear model predictive control (NMPC) algorithm framework incorporating energy consumption and temperature control is established, expressed as follows:

[0165] ;

[0166] in, Indicates time Energy consumption per hour Indicates time The battery temperature tracking error vector at time step. and These represent the weight matrix for temperature tracking error and the weight matrix for the squared term of total power consumption, respectively. express transpose, Indicates time Total power consumption of the system at any given time;

[0167] The expression is:

[0168] ;

[0169] in, Indicates from index Starting from 1, and continuing until... equal Continuous summation, Indicates the first Power consumption of a thermoelectric cooler This indicates the fan's power consumption;

[0170] To force the battery cells to operate within their optimal temperature range, while limiting the cell temperature to an ideal range of 20 to 45°C, the following constraint condition is set:

[0171] ;

[0172] ;

[0173] ;

[0174] ;

[0175] ;

[0176] ;

[0177] in, Represents the system state vector. Represents the control input vector. This represents the external disturbance vector. This indicates how the system state changes over time. and Indicates the minimum and maximum allowable values ​​for battery cell temperature. Indicates the first Each battery cell in time The actual temperature Indicates the maximum allowable temperature of the radiator. and This indicates the minimum and maximum allowable values ​​of the thermoelectric cooler (TEC) current. express Each TEC module in time The actual current, and This represents the minimum and maximum values ​​of the system inverter resistance;

[0178] Based on the formula calculation, the TEC operating status and fan speed are dynamically adjusted to respond to changes in battery conditions and the external environment, ensuring that the temperature is controlled within the optimal range.

[0179] In summary, this invention achieves balanced heat distribution and rapid heat dissipation within the battery through precise calculation and layout, ensuring the optimal position and contact area of ​​the TEC near the top of the battery. Combined with the clever embedding of a heat-conducting metal plate, this improves heat dissipation efficiency while maintaining system compactness and lightweight design, creating an ideal temperature control environment for the battery. Furthermore, the semiconductor field-effect detector used in this invention, with its superior temperature sensing performance and rapid response capability, provides real-time and accurate temperature data, significantly enhancing the intelligence level of thermal management. Most importantly, the introduced nonlinear model predictive control (NMPC) algorithm can dynamically adjust the TEC operation strategy based on current operating conditions and future predictions, effectively reducing system energy consumption and achieving optimal energy efficiency.

[0180] Example 2

[0181] Referring to Table 1, which is the second embodiment of the present invention, experimental simulation data of the intelligent battery thermal management system based on thermoelectric cooler are given to further verify the advancement of the present invention.

[0182] A standard electric vehicle battery pack was selected as the research object, which contains 24 battery cells, each with a capacity of 10Ah, an operating voltage of 3.7V, and dimensions of 10cm x 10cm x 2cm, arranged in a 4x6 matrix. The experiment was conducted under conditions simulating real working environment, including room temperature of 25℃, continuous charge and discharge cycles, and external load fluctuations.

[0183] The details are shown in the table below:

[0184] Table 1 Experimental Record Sheet

[0185]

[0186] As can be seen from the "Experimental Record Table" in Table 1, by implementing the present invention, the maximum temperature of each battery cell was effectively controlled. Compared with the control group that did not use this system, the maximum temperature decreased by an average of about 2°C, which significantly improved the temperature uniformity of the battery pack. Taking cell B1 as an example, its initial temperature was 25°C. Under high load conditions, the maximum temperature was controlled at 38°C by optimizing the layout of the TEC and microchannel heat dissipation module. Compared with the unoptimized system, the temperature difference was reduced by 13°C, which directly proves the significant improvement in thermal management efficiency of the present invention.

[0187] The detector's average response time is 15ms, far below the industry standard of 50ms. This is thanks to the high sensitivity and fast response characteristics of the nickel / gallium oxide / silicon carbide metal oxide semiconductor field effect detector, which enhances the system's instantaneous response capability. In addition, the introduction of the NMPC control algorithm reduces the overall power consumption of the system by 21% to 26%, with an average reduction rate of 23.5%. This not only improves the system's energy efficiency but also extends the battery pack's lifespan and reduces operating costs.

[0188] Compared with existing technologies, the innovation and novelty of this invention are mainly reflected in the following aspects: First, through precise thermal image analysis and optimized TEC layout, the heat dissipation efficiency of local heat accumulation areas is significantly improved; second, the efficient design of the microchannel heat sink greatly improves heat dissipation efficiency and reduces volume occupation; third, the highly integrated detector system enhances the accuracy and immediacy of temperature monitoring; and fourth, the advanced NMPC algorithm achieves optimal energy consumption control while ensuring battery temperature stability. These improvements together ensure the efficient and stable operation of the battery thermal management system under complex operating conditions, providing a revolutionary thermal management solution for electric vehicles and other high-power-density battery applications.

[0189] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A thermoelectric cooler based intelligent battery thermal management system, characterized by: comprises, The TEC optimization layout module is responsible for optimizing the position and contact area of the thermoelectric cooler (TEC), analyzing the internal temperature distribution of the battery cell, determining the heat accumulation area, embedding a heat-conducting metal plate between the battery cells by arranging the TEC near the top of the battery, and using its cooling capacity to promote internal heat balance. The micro-channel heat dissipation module is responsible for establishing a micro-channel heat sink, achieving the dual goals of compact structure and high-efficiency heat dissipation by using micro-channel technology, and keeping the battery in an ideal temperature zone. The detector preparation module is responsible for the preparation process of nickel / gallium oxide / silicon carbide metal oxide, semiconductor field effect detector, real-time monitoring of battery temperature, and providing accurate data input for the thermal management system to strengthen the system's immediate response and intelligent adjustment capabilities. The NMPC control module is responsible for predicting and optimizing energy consumption in the battery thermal management system through the nonlinear model predictive control (NMPC) algorithm, dynamically adjusting the TEC operation strategy based on the current battery operating conditions and future predictions. The specific steps are as follows: According to the size, shape, and working environment of the battery pack, select an infrared thermal imager with high resolution, fast frame rate, and suitable temperature range; Use the infrared thermal imager to monitor the temperature distribution of the battery under working conditions and determine the area with the largest temperature gradient; Use the infrared thermal imager to perform non-contact temperature scanning on the battery pack; Through thermal image analysis, identify the area with higher temperature at the top; Through thermal image analysis, identify the area with higher temperature at the top, the specific steps are as follows: Obtain the temperature gradient inside the battery by detecting the temperature changes at the top and bottom of the battery, the expression is: ； wherein represents the temperature difference inside the battery at time represents the temperature difference inside the battery at time represents the temperature of the top of the battery at time represents the temperature of the top of the battery at time represents the temperature of the bottom of the battery at time represents the temperature of the bottom of the battery at time represents the time variable; selecting largest region as TEC mounting point; Calculate the contact area of the TEC with the top of the battery, the expression is: ； wherein, represents the actual contact area of the TEC with the top of the battery, represents the cooling efficiency coefficient of the TEC, represents the length of the thermally conductive metal plate, represents the thermal conductivity of the thermally conductive metal plate; Embed a heat-conducting metal plate between the battery cells to promote internal heat balance, the specific steps are as follows: Deploy a heat-conducting metal plate between every two adjacent battery cells, and obtain the length of the heat-conducting metal plate, the expression is: ； wherein denotes the length of the heat conducting metal plate; Establish a thermal gradient balance model, the expression is: ； wherein, represents the adjusted internal temperature gradient of the battery, represents the total number of battery cells, represents the distance between adjacent battery cells.

2. The thermoelectric cooler based intelligent battery thermal management system of claim 1, wherein: According to and deviation, the dynamic adjustment of the current output of the TEC and the possible layout of the heat conduction plate, the expression is: ； wherein, represents the current required by the thermoelectric cooler at time t, is a proportional coefficient, represents the difference between the actual temperature gradient and the target temperature gradient, is an integral coefficient, represents the cumulative error from the initial time to the present, is a differential coefficient, reflecting the influence of the error rate of change, is the error rate of change, embodying the speed of change of the system error.

3. The thermoelectric cooler based intelligent battery thermal management system of claim 2, wherein: Responsible for establishing a micro-channel heat sink, achieving the dual goals of compact structure and high-efficiency heat dissipation by using micro-channel technology, the specific steps are as follows: The micro-channel structure is set, and an effective heat dissipation area expression is obtained as: ; wherein, represents the effective heat dissipation area, represents the channel width, represents the channel height, represents the channel length, represents the number of microchannels; Determine the flow state of the fluid in the micro-channel by calculating the Reynolds number, select the appropriate cooling medium and flow rate, the Reynolds number calculation expression is: ； wherein Reis the Reynolds number, which is used to indicate whether the fluid flow state is laminar or turbulent, denotes the fluid density, is the average flow velocity, is the dynamic viscosity; According to the effective heat dissipation surface of the micro-channel heat sink, calculate its total thermal resistance, including convective heat transfer resistance, thermal conduction resistance, and radiation resistance, the expression is: ； wherein Rth,eff represents the total thermal resistance of the effective heat sink surface, hconv represents the convective heat transfer coefficient; Predict the temperature rise under a given thermal load to keep the battery in an ideal temperature zone, the expression is: ； wherein, represents the temperature rise occurring during heat transfer, represents the heat load, represents the mass of fluid flowing through the system per unit time, represents the specific heat capacity, represents the thermal conductivity.

4. The thermoelectric cooler based intelligent battery thermal management system of claim 3, wherein: The preparation process of nickel / gallium oxide / silicon carbide metal oxide, semiconductor field effect detector, the specific steps are as follows: Synthesize high-quality nickel / gallium oxide / silicon carbide composite thin film materials through chemical vapor deposition (CVD) technology, the expression is: ； wherein, represents the material conductivity, represents the temperature, represents the pressure, represents the deposition time, represents the reaction gas concentration, represents the material conductivity and a mapping relationship between; Fine-tune the performance parameters of the field effect transistor (FET) using photolithography and etching technology, optimize the field effect by adjusting the ratio of gate length to width, the expression is: ； wherein, represents a leakage current, represents a carrier mobility, represents a gate width, represents a gate length, represents a capacitance of the oxide layer, represents a voltage between the gate and the source, represents a threshold voltage.

5. The thermoelectric cooler based intelligent battery thermal management system of claim 4, wherein: Real-time monitoring of battery temperature, accurate data input for the thermal management system, and strengthening the system's immediate response and intelligent adjustment capabilities, the specific steps are as follows: The temperature sensitivity of the material is enhanced by Ni doping technology, making the resistance of the detector change more obviously with temperature. The relationship between doping concentration and temperature response is expressed as: ； wherein represents the resistance at temperature represents the resistance at room temperature, represents the resistance at room temperature, represents the natural exponential function, represents the activation energy, represents the Boltzmann constant, represents the temperature variable, represents the conversion of the measured temperature from degrees Celsius to Kelvin temperature; The prepared detector is packaged; During integration, the position distribution of the detector is considered to ensure comprehensive coverage of the key areas of the battery. The detector layout optimization expression is described as: ； wherein, represents the first thermal resistance, represents the total number of thermal resistances in the system, represents the target average thermal resistance.

6. The thermoelectric cooler based intelligent battery thermal management system of claim 5, wherein: The energy consumption in the battery thermal management system is predicted and optimized by the nonlinear model predictive control (NMPC) algorithm. According to the current battery operating conditions and future predictions, the TEC operation strategy is dynamically adjusted. The specific steps are as follows: A nonlinear model predictive control (NMPC) algorithm framework is established, which includes energy consumption and temperature control. The expression is as follows: ； wherein, represents the energy consumption at time represents the battery temperature tracking error vector at time and respectively represent the temperature tracking error weight matrix and the total power consumption squared term weight matrix, represents the transpose of represents the total system power consumption at time ​​​ The The expression is: ； wherein, represents the sum of the power consumptions of the first equal to 1, up to equal to successive summations of represents the power consumption of the th thermoelectric refrigerator, represents the power consumption of the fan.

7. The thermoelectric cooler based intelligent battery thermal management system of claim 6, wherein: In order to force the battery cells to operate within the optimal temperature range, the battery cell temperature is limited to the ideal range of 20 to 45°C. The set point constraint condition is expressed as: ； ； ； ； ； ； in, Represents the system state vector. Represents the control input vector. This represents the external disturbance vector. This indicates how the system state changes over time. and Indicates the minimum and maximum allowable values ​​for battery cell temperature. Indicates the first Each battery cell in time The actual temperature Indicates the maximum allowable temperature of the radiator. and This indicates the minimum and maximum allowable values ​​of the thermoelectric cooler (TEC) current. express Each TEC module in time The actual current, and This represents the minimum and maximum values ​​of the inverter resistance in the system.

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