Technology suitable for automatically regulating and controlling constant temperature of energy storage bin

Abstract

The invention discloses a technology suitable for automatically regulating and controlling the constant temperature of an energy storage bin. Belongs to the field of energy storage bin energy regulation and automation, and comprises a green energy temperature control module, a compound serpentine channel cold liquid cooling module, an electric energy temperature control module, a phase change material temperature control unit and a temperature sensing measurement and judgment module, and the invention discloses technologies of parallel ventilation cooling, electric energy temperature control, compound cold liquid cooling, solar heat transfer, supercooled phase change material temperature control and the like. The parallel ventilation cooling technology and the compound cooling liquid cooling technology can only solve the problem that the temperature of the energy storage bin is higher than the optimum temperature independently, the solar heat supplementing technology can solve the problem that the temperature of the energy storage bin is lower than the optimum temperature independently, and the other two temperature control technologies can solve the problems. Aiming at the problem of power output of the power energy storage bin, the problem that the power energy storage bin is overheated and is out of control due to overheat in high-temperature weather is solved, and the problems that the energy storage bin is prone to loss in cold weather, the service life of the energy storage bin is shortened, and power conversion energy storage exists are also solved.

Description

Technical Field

[0001] The present invention belongs to the field of energy regulation and automation of energy storage bins, and relates to a big data intelligent green energy regulation technology; specifically, it relates to a technology suitable for automatically regulating the constant temperature of an energy storage bin. Background Art

[0002] At present, new energy electric vehicles are developing rapidly, and the impact of the endurance and temperature of their energy storage bins on their performance has also become a key focus. Electric vehicles usually use lithium-ion energy storage bins nowadays, and such energy storage bins are often greatly affected by temperature. On the one hand, it will reduce the lifespan, endurance, and performance of the energy storage bin. On the other hand, it will also pose potential safety hazards to the normal driving of users. Therefore, this technology elaborates on temperature regulation in detail to enable the energy storage bin to maintain a constant optimal temperature under different conditions.

[0003] In addition, with the rapid development of cities and the large number of gasoline vehicles, etc., the problem of excessive carbon emissions urgently needs to be alleviated. Therefore, the rational use of clean energy by the energy storage bin of electric vehicles is also very important. Summary of the Invention

[0004] In view of the above problems, the object of the present invention is to provide a technology suitable for automatically regulating the constant temperature of an energy storage bin for problems such as how to maintain the performance of the energy storage bin at a constant temperature. Firstly, the internal coolant and phase change materials, etc. all have the advantages of high cost performance and no excessive adverse effects on the environment. Secondly, it specifically processes the temperature and determination results data in the temperature sensing measurement and determination module and transmits it to the other four modules; independent method processing and specific module combination processing are carried out according to the current adjustment requirements of the energy storage bin, and finally, in the operation stage, the temperature sensing measurement and determination module performs optimization and micro-adjustment using the honey badger algorithm again.

[0005] The technical solution of the present invention is: A technology suitable for automatically regulating the constant temperature of an energy storage bin according to the present invention includes a green energy temperature control module, a compound serpentine channel cold liquid cooling module, an electric energy temperature control module, a phase change material temperature control unit, and a temperature sensing measurement and determination module that are interconnected.

[0006] Further, the compound serpentine channel cold liquid cooling module includes a coolant and a compound serpentine cold liquid plate;

[0007] The coolant is composed of 50% ethanol and 50% water. The temperature value of the coolant is calculated from the optimal temperature of the energy storage bin and the temperature of the liquid cooling plate, and it uses the heat energy conservation formula of the coolant, liquid cooling plate, and energy storage bin, as shown in the following formula:

[0008] Coolant:

[0009] Liquid cooling plate:

[0010] Energy storage bin:

[0011] k 1 T l +k 2 T d =k 3 T c +T gen (4)

[0013] In the formula, ρ l , c pl , k l , T l are the density, specific heat capacity, thermal conductivity, and temperature of the coolant; ρ d , c pd , T d , k d are the density, specific heat capacity, temperature, and thermal conductivity of the liquid cooling plate; ρ c , c pc , k cx , k cy , k cz , T c are the density, specific heat capacity, thermal conductivity along the x-axis, thermal conductivity along the y-axis, thermal conductivity along the z-axis, and temperature of the energy storage bin; k 1 , k 2 , k 3 are the proportionality coefficient of the three in heat conservation; T gen is the temperature dissipation value;

[0014] The internal channel of the compound serpentine cooling liquid plate is of a compound type, which is provided with an inlet and an outlet. The channel between the inlet and the outlet is similar to a snake shape, and a V-shaped channel is inserted between every two of them on the basis of the snake shape.

[0015] Furthermore, the green energy temperature control module is divided into air-cooled heat dissipation and solar heating PTC resistor ceramic sheet heat transfer;

[0016] Among them, the air-cooled heat dissipation adopts serial ventilation. The installed fan extracts the cold air outside the energy storage bin and allows the cold air to flow in from one side of the energy storage bin group and flow out from the other side; and according to the data transmitted by the temperature sensing measurement and determination module, it judges whether it is higher than the optimum temperature; if it is higher than the optimum temperature, when using parallel ventilation, a solar-driven fan is used to increase the natural wind force to complete the air-cooled heat dissipation.

[0017] Furthermore, the solar heating PTC resistor ceramic sheet heat transfer uses a monocrystalline silicon solar panel to convert electrical energy and a PTC thermistor type ceramic sheet to heat the air and protect the energy storage bin;

[0018] The monocrystalline silicon solar panel converts solar energy into electrical energy, which on the one hand provides energy for the PTC resistor ceramic sheet and the fan, and on the other hand stores it in the energy storage bin;

[0019] According to the data transmitted by the temperature sensing and measurement determination module, it is judged whether the temperature is lower than the optimal temperature; if it is lower than the optimal temperature, the electrical energy converted from solar energy is used to heat the PTC resistor ceramic sheet, and its heat is transferred to the energy storage bin; at the same time, the surrounding air is heated, and then the fan is started to use parallel ventilation to transfer the heat to the energy storage bin.

[0020] Furthermore, the electrical energy temperature control module releases and absorbs the heat energy brought by the charge and discharge of the energy storage bin itself;

[0021] Among them, the heat transfer method inside the energy storage bin is heat conduction.

[0022] Furthermore, the phase change material temperature control unit uses the melting and condensation of the supercooled phase change material to cause the on-off of the thermal switch, respectively allowing the energy storage bin to transfer its own heat to the phase change material for absorption or allowing the temperature released by the phase change material to be indirectly transferred to the energy storage bin.

[0023] Furthermore, the supercooled phase change material refers to the phenomenon that under a certain pressure condition, when the temperature of the liquid phase is lower than the theoretical condensation point temperature, it does not solidify and needs to be cooled below the condensation point to start solidifying;

[0024] A thermal switch is a device that adjusts the closing of its own switch according to temperature. It controls the contact area through the thermal expansion of solids, gases or liquids, allowing the regulated object to passively maintain the temperature at the optimal value and realizing effective switching when there is a heat conduction rate;

[0025] Since the thermal conductivity of the phase change material changes with the liquid phase rate, as shown in Equations (7)-(8):

[0026]

[0027] In the formula, β is the liquid phase rate; T s , T 1 are the temperature at which the phase change material starts to melt and the temperature at which it is completely melted, respectively;

[0028] λ PCM =λ s -β(λ s -λ 1 ) (8)

[0029] In the formula, λ PCM is the true thermal conductivity of the phase change material, λ s is its thermal conductivity in the solid state, and λ 1 is its thermal conductivity in the liquid state;

[0030] In addition, the heat transfer between the phase change material, the liquid cooling plate, the moving plate surface, and the energy storage bin is expressed by the following formula:

[0031]

[0032]

[0033]

[0034]

[0035] In the formula, T c is the temperature of the energy storage bin; T PCM is the temperature of the phase change material; T plate is the temperature of the liquid cooling plate; T cop is the temperature of the moving plate surface; T air is the air temperature; n is the reference direction coefficient; λ c 、λ PCM 、λ cop 、λ air are the thermal conductivities of the energy storage bin, the phase change material, the moving plate surface, and the air, respectively.

[0036] Furthermore, the determination basis of the temperature sensing measurement and determination module is the temperature T 1 of the energy storage bin and the internal air temperature T 2 , the external air temperature T 3 . The temperature of each part is measured by a specific temperature sensor of each part. The remaining components are a small computing server, a controller, and a pulse signaler, and pulse signals are sent to each module to make it operate by satisfying the determination basis of each part.

[0037] Furthermore, the determination bases of the temperature sensing measurement and determination module for the green energy temperature control module, the double - serpentine channel liquid cooling module, the electric energy temperature control module, and the phase change material temperature control unit are as follows:

[0038] (1): First, determine whether T 1 is lower than or higher than the optimal temperature. If it is lower than the optimal temperature, for the green energy temperature control module, open the air circulation with the outside, use solar energy - electric energy heat conversion and parallel ventilation heating; for the electric energy temperature control module, use the energy storage bin to discharge heat for heating; for the phase change material temperature control unit, carry out phase change material solidification exotherm;

[0039] If it is higher than the optimal temperature, for the double - serpentine channel liquid cooling module, use liquid cooling treatment of the coolant to flow through the liquid cooling plate to cool down; for the green energy temperature control module, open the air circulation with the outside and use parallel ventilation; for the electric energy temperature control module, use the energy storage bin to charge and absorb heat; for the phase change material temperature control unit, carry out phase change material melting endotherm;

[0040] (2): On the basis of the above step (1), if T2 If the temperature is lower than the optimal temperature, the above heating method is adopted; if it is higher than the optimal temperature, the heat absorption and cooling method is adopted.

[0041] (3): On the basis of the above steps (1) and (2), if T 3 is always opposite to the regulation requirement, when using the green energy temperature control module, it is always not in communication with the external air, unless the internal air is insufficient.

[0042] Furthermore, due to the different time and requirement for temperature control of each part of the module and the energy storage bin, there is the following honey badger algorithm, and this part will be processed by the temperature measurement and determination module;

[0043] Among them, the steps of the honey badger algorithm are as follows:

[0044] (1) Population initialization: The model of the HBA algorithm is established by simulating the intelligent behavior of honey badgers, and it optimizes by simulating the foraging behavior of honey badgers; the size of the honey badger population is N, and the HBA algorithm randomly initializes the population within a certain upper and lower limit range, as shown in the following formula (13):

[0045] X i = l lb.i + r i × (u ub.i - l lb.i ) (13)

[0046] In the formula, X i represents the required temperature; while u ub.i and l lb.i represent the upper and lower bounds of the search temperature range respectively; r i is a random number in [0, 1];

[0047] (2) Environmental impact factor: The foraging ability of honey badgers is related to the distance of the i-th honey badger, the concentration intensity of the prey, and the odor intensity; I i is the odor intensity of the prey; when I i increases, the speed of the honey badger increases accordingly; among them, the specific definition of I i is shown in the following formula (14):

[0048]

[0049] In the formula, r 2 is a random number in [0, 1]; S is the concentration intensity of the prey; d i represents the distance between the prey and the i-th honey badger;

[0050] (3) Density factor: The non-linear density factor α constrains the optimization path that changes over time, making the algorithm evolution process more stable; the non-linear density factor α decreases with the number of iterations, and its definition is shown in the following formula (15):

[0051]

[0052] In the formula, t max represents the maximum number of iterations; C ≥ 1;

[0053] (4) Particle position update: The optimization path of the HBA algorithm is divided into a mining mode and a honey mode, and these two modes have different movement trajectories;

[0054] (5) Mining mode: In the mining mode, the movement trajectory of the honey badger is similar to a heart shape, and the movement route trajectory is simulated by the following formula (16):

[0055]

[0056] In the formula, x new represents the temperature that is currently considered to be adjusted; x prey represents the optimal temperature in the environment; β ≥ 1 reflects the ability of the honey badger individual to obtain food; F1 is used as a sign that the search direction changes continuously; r3, r4, and r5 represent three random values between 0 and 1; among them, the definition of F1 is shown in the following formula (17):

[0057]

[0058] In the formula, r6 is a random number between 0 and 1; the search path of the honey badger in the mining mode is affected by the distance d i of the prey, the olfactory intensity I i of the prey, and the non-linear density factor α;

[0059] (6) Honey mode: In the honey mode, the honey badger changes the optimization path and follows the honey guide bird to reach the target honeycomb, and the simulation of its route trajectory is shown in formula (18):

[0060] x new = x prey + F 1 × r 7 × α × d i (18)

[0061] Among them: r7 is a random number between 0 and 1; α and F1 are determined by formulas (15) and (17); in this stage, the optimization path of the honey badger is related to the distance d i between the prey and the i-th honey badger, the optimal temperature x prey , and α, and the honey badger explores near x prey ;

[0062] To solve the problems existing in the HBA algorithm, an adaptive weight factor is added to balance global and local searches; a starvation search strategy is added to enhance the algorithm's search ability;

[0063] Among them, the adaptive weight factor is as follows:

[0064]

[0065] In the formula, t is the current iteration number; t max is the maximum number of iterations;

[0066] After introducing the adaptive weight factor, the search routes of the mining pattern and the honey pattern in HBA are as follows:

[0067]

[0068] x new = x prey × ω + F 1 × r 7 × α × d i

[0069] The starvation search strategy is as follows:

[0070] x new = x prey × ω + F 1 × r 7 × α × d i × exp(x worse - x i )

[0071] In the formula, x worse represents the globally worst position; x i is the position of the current population individual.

[0072] The beneficial effects of the present invention are as follows: The present invention discloses parallel ventilation cooling technology, electric energy temperature control technology, compound cold liquid cooling technology, solar energy heat conversion technology, and subcooled phase change material temperature control technology; among them, the parallel ventilation cooling technology and the compound cold liquid cooling technology can only separately solve the situation where the temperature of the energy storage bin is higher than the optimal temperature, and the solar energy heat supplement technology can separately solve the situation where the temperature of the energy storage bin is lower than the optimal temperature, and the remaining two temperature control technologies can solve both situations; the present invention is applied to the rapidly developing electric vehicle industry, and in response to the problem of power output of the power energy storage bin, it solves the problem that the power energy storage bin overheats and gets out of control due to overheating in high-temperature weather, and also solves the problem that the energy storage bin is easily damaged in cold weather, shortens the service life of the energy storage bin, and has problems of power conversion and energy storage. Brief Description of the Drawings

[0073] Figure 1 is the overall operation block diagram of the present invention;

[0074] Figure 2 is the structural diagram of the compound serpentine channel cold liquid cooling module in the present invention;

[0075] Figure 3 is the ventilation flow diagram of the green energy temperature control module in the present invention; among them, (a) is the serial ventilation flow diagram, and (b) is the parallel ventilation flow diagram;

[0076] Figure 4 is the operation flow chart of the honey badger algorithm in the present invention. Specific embodiments

[0077] The following further elaborates on the specific technical solutions of the present invention in combination with specific examples.

[0078] As shown in the figure, a technology for automatically regulating the constant temperature of an energy storage bin according to the present invention includes a compound serpentine channel cold liquid cooling module, a green energy temperature control module, an electric energy temperature control module, a phase change material temperature control unit, and a temperature sensing measurement and determination module that are interconnected.

[0079] Furthermore, the compound serpentine channel cold liquid cooling module includes a coolant and a compound serpentine cold liquid plate; the coolant used is composed of 50% ethanol and 50% water. This composition not only has a small specific heat capacity, is easy to obtain, and has a low cost, but also is easy to change its own temperature and can effectively solve the problem of being difficult to freeze under general temperature conditions;

[0080] The temperature value of the coolant is calculated from the optimal temperature of the energy storage bin and the temperature of the liquid cooling plate. The heat energy conservation formula of the three parts of the coolant, the liquid cooling plate, and the energy storage bin is used in this part:

[0081] Coolant: Liquid cooling plate: Energy storage bin:

[0082] k 1 T l +k 2 T d =k 3 T c +T gen (4)

[0083] In the formula, ρ l 、c pl 、k l 、T l are the density, specific heat capacity, thermal conductivity, and temperature of the coolant; ρ d 、c pd 、T d 、kd are the density, specific heat capacity, temperature, and thermal conductivity of the liquid cooling plate; ρ c , c pc , k cx , k cy , k cz , T c are the density, specific heat capacity, thermal conductivity along the x-axis, thermal conductivity along the y-axis, thermal conductivity along the z-axis, and temperature of the energy storage bin; k 1 , k 2 , k 3 is the proportionality coefficient of the three in heat conservation; T gen is the temperature dissipation value;

[0084] The internal channels of the liquid cooling plate are of a compound type, as shown in Figure 2 ; this design has an inlet and an outlet. Meanwhile, the channels between the inlet and the outlet are similar to a snake shape, and V-shaped channels are inserted between every two of them on the basis of the snake shape. On the one hand, it optimizes the flow channels, reduces the pressure drop, and reduces the need for external assistance, making the area through which the coolant flows through the liquid cooling plate larger, enhancing the heat transfer and temperature uniformity, and at the same time strengthening the internal heat dissipation and volatilization; this module has great advantages in terms of cost control and heat dissipation and temperature control efficiency compared with ordinary liquid cooling.

[0085] Furthermore, the green energy temperature control module is divided into air-cooled heat dissipation and heat transfer by a solar heating PTC resistor ceramic sheet;

[0086] Generally, serial ventilation is traditionally used for air-cooled heat dissipation. Generally, a fan extracts the cold air outside the energy storage bin and allows the cold air to flow in from one side of the energy storage bin group and flow out from the other side; as shown in Figure 3 Figure (a), the cold air is blown in from the left port and goes out from the right port. However, during the process, it is continuously heated, causing the air temperature to continuously rise, reducing its heat transfer coefficient and the heat dissipation effect. Therefore, the heat dissipation on the right side is worse, resulting in uneven temperature distribution in the energy storage bin group and an increase in the temperature difference within the energy storage bin group. So, parallel ventilation is adopted in this energy storage bin; the parallel ventilation method is as shown in Figure 3 Figure (b). It allows the cold air to be blown in together from the ventilation openings. In this case, the air in contact with the surface of the energy storage bin has fluctuations and the flow rate is relatively average, making the temperature drop of each energy storage bin monomer the same. Therefore, the parallel ventilation method is more beneficial to reducing the temperature difference between the individuals within the energy storage bin group;

[0087] According to the data transmitted by the temperature sensing measurement and determination module, it is judged whether it is higher than the optimum temperature; if it is higher than the optimum temperature, when parallel ventilation is used, a solar-driven fan is further used to increase the natural wind force to complete air-cooled heat dissipation in the true sense.

[0088] The solar heating PTC resistor ceramic sheet uses a monocrystalline silicon solar panel to convert electrical energy and a PTC thermistor ceramic sheet to heat air and protect the energy storage bin; the monocrystalline silicon solar panel has high conversion efficiency, is durable, and has a high cost performance; it converts solar energy into electrical energy, on the one hand, providing energy for the PTC resistor ceramic sheet and the fan, and on the other hand, storing it in the energy storage bin.

[0089] For PTC materials, they have the advantages of rapid response to overload current, stable performance, strong impact resistance, long service life, and can be used for both AC and DC without polarity.

[0090] According to the data transmitted by the temperature sensing measurement and determination module, it is judged whether the temperature is lower than the optimum temperature; if it is lower than the optimum temperature, the electrical energy converted from solar energy is used to heat the PTC resistor ceramic sheet, and its heat is directly transferred to the energy storage bin; at the same time, the surrounding air is heated, and then the fan is started to use parallel ventilation to transfer the heat to the energy storage bin.

[0091] Furthermore, the essence of the electrical energy temperature control module is to release and absorb heat energy brought about by the charge and discharge of the energy storage bin itself, and the main heat transfer method inside the energy storage bin is heat conduction.

[0092] Furthermore, the phase change material temperature control unit uses the melting and condensation of supercooled phase change materials to cause the switching of the thermal switch, respectively allowing the energy storage bin to transfer its own heat to the phase change material for absorption or allowing the temperature released by the phase change material to be indirectly transferred to the energy storage bin.

[0093] During the process of changing physical properties, the phase change material absorbs or releases a large amount of heat. Compared with traditional materials, the latent heat energy storage using phase change materials has the advantages of large heat storage density, easy control of the working temperature range, and high safety, and is considered the most effective form of storing thermal energy.

[0094] Supercooled phase change material refers to the phenomenon that under a certain pressure condition, when the temperature of the liquid phase is lower than the theoretical condensation point temperature, it does not solidify and needs to be cooled below the condensation point to start solidifying; in the present invention, the use of supercooled phase change materials can achieve storing heat when the temperature of the energy storage bin rises and releasing heat when the temperature of the energy storage bin is lower, so as to control the temperature of the energy storage bin within a reasonable working range.

[0095] A thermal switch is a device that adjusts the closing of its own switch according to temperature, controls the contact area through the thermal expansion of solids, gases or liquids, so that the regulated object can passively maintain the temperature at the optimal value, and can achieve effective switching when there is a heat conduction rate; it can realize the functions of heat dissipation or adiabatic temperature maintenance of the device according to different temperature conditions; when the temperature is higher than a certain temperature, the thermal switch is enabled, and heat is efficiently transferred between the hot end and the cold end, with a high effective thermal conductivity, and the thermal switch operates as a heat dissipation device; when the temperature is lower than a certain temperature, the thermal switch is closed, with a low effective thermal conductivity, and the thermal switch operates as an adiabatic device.

[0096] Its working process: combining a subcooled phase change material with a thermal switch; when the temperature of the energy storage bin is higher than the melting point of the phase change material, the phase change material melts and absorbs heat, converting the heat dissipated by the energy storage bin into heat stored in the phase change material; at the same time, the phase change material changes from a solid state to a liquid state, its volume increases, the thermal switch is activated, the moving plate surface fits against the liquid cooling plate, and heat exchange is carried out by means of the liquid cooling plate;

[0097] When the energy storage bin returns to the normal temperature, due to the characteristics of the subcooled phase change material, the stored heat will not be released; when the temperature of the energy storage bin continues to decrease, the phase change material reaches the freezing point, solidifies and releases heat, its volume decreases, the thermal switch is turned off, the moving plate surface separates from the liquid cooling plate, enabling the heat stored in the phase change material to be conducted to the energy storage bin to the greatest extent, increasing the temperature of the energy storage bin and enabling the energy storage bin to still work properly in a low-temperature environment.

[0098] The specific relationship between the phase change material and the heat of the energy storage bin is described in combination with (7)-(12).

[0099] Since the thermal conductivity of the phase change material changes with the liquid fraction, its relationship is described by equations (7) and (8):

[0100]

[0101] In the formula, β is the liquid fraction; T s , T 1 are the starting melting temperature and the complete melting temperature of the phase change material respectively;

[0102] λ PCM = λ s - β(λ s - λ 1 ) (8)

[0103] In the formula, λ PCM is the true thermal conductivity of the phase change material, λ s is its thermal conductivity in the solid state, and λ 1 is its thermal conductivity in the liquid state;

[0104] In addition, the heat transfer between the phase change material, the liquid cooling plate, the moving plate surface, and the energy storage bin can be expressed by the following formula:

[0105]

[0106]

[0107]

[0108]

[0109] In the formula, Tc is the temperature of the energy storage bin; T PCM is the temperature of the phase change material; T plate is the temperature of the liquid cooling plate; T cop is the temperature of the moving plate surface; T air is the air temperature; n is the reference direction coefficient; λ c and λ PCM and λ cop and λ air are the thermal conductivities of the energy storage bin, the phase change material, the moving plate surface, and the air respectively.

[0110] Furthermore, the determination basis of the temperature sensing measurement and determination module is mainly the temperature T of the energy storage bin 1 and the internal air temperature T 2 , the external air temperature T 3 , which will collect the temperatures of other parts such as the liquid cooling plate, cooling, phase change material, etc. The temperature of each part is measured by a specific temperature sensor of each part; the remaining components are a small computing server, a controller, and a pulse signaler, and pulse signals are sent to each module to make it operate by meeting the determination basis of each part;

[0111] The determination bases of the dual - liquid cooling module, the green energy temperature control module, the electric energy temperature control module, and the phase change material temperature control unit are as follows:

[0112] (1), First, judge whether T 1 is lower than or higher than the optimal temperature. If it is lower than the optimal temperature, then for the green energy temperature control module, open the air circulation with the outside, use solar energy - electric energy heat conversion and parallel ventilation heating; for the electric energy temperature control module, use the energy storage bin to discharge heat for heating; for the phase change material temperature control unit, carry out solidification heat release of the phase change material; if it is higher than the optimal temperature, then for the dual - liquid cooling module, use coolant cooling treatment to make it flow through the liquid cooling plate to cool down; for the green energy temperature control module, open the air circulation with the outside and use parallel ventilation; for the electric energy temperature control module, use the energy storage bin to charge and absorb heat; for the phase change material temperature control unit, carry out melting heat absorption of the phase change material;

[0113] (2), On the basis of the above determination (1), if T 2 is lower than the optimal temperature, then adopt the above - mentioned heating method, and if it is higher than the optimal temperature, then adopt the heat absorption and cooling method;

[0114] (3), On the basis of the above determinations (1) and (2), if T 3 is always contrary to the adjustment requirement, then when using the green energy temperature control module, it is always not in air circulation with the outside, unless the internal air is insufficient.

[0115] Furthermore, since there are different temperature control requirements for each part of the module and the energy storage bin at different times, it is necessary to optimize the calculation to obtain the optimal current temperature so that they can cooperate better. Therefore, the following Honey Badger Algorithm is proposed, and this part will be processed by the temperature sensing and measurement judgment module;

[0116] Among them, as Figure 4 shown, the steps of the Honey Badger Algorithm are as follows:

[0117] Population initialization: The model of the HBA algorithm is established by simulating the intelligent behavior of honey badgers, and it optimizes by simulating the foraging behavior of honey badgers; the size of the honey badger population is N, and the HBA algorithm randomly initializes the population within a certain upper and lower limit range, as shown in Equation (13):

[0118] X i = l lb.i + r i × (u ub.i - l lb.i ) (13)

[0119] In the formula, X i represents the required temperature; while u ub.i and l lb.i represent the upper and lower bounds of the search temperature range respectively; r i is a random number in [0, 1];

[0120] Environmental impact factor: The foraging ability of honey badgers is related to the distance of the i-th honey badger, the concentration intensity of prey, and the odor intensity. I i is the odor intensity of prey. When I i increases, the speed of honey badgers increases accordingly. The specific definition of I i is as follows in Equation (14):

[0121]

[0122] In the formula, r 2 is a random number in [0, 1]; S is the concentration intensity of prey; d i represents the distance between the prey and the i-th honey badger;

[0123] Density factor: The non-linear density factor α constrains the optimization path that changes with time, making the algorithm evolution process more stable. The non-linear density factor α decreases with the number of iterations, and its definition is as shown in Equation (15):

[0124]

[0125] In the formula, t max represents the maximum number of iterations; C ≥ 1 (the default value is set to 2);

[0126] Particle position update: The optimization path of the HBA algorithm is divided into a mining mode and a honey mode, and these two modes have different movement trajectories;

[0127] Mining mode: In the mining mode, the action trajectory of the honey badger is similar to a heart shape, and the action route trajectory can be simulated by Equation (16):

[0128]

[0129] where, x new represents the temperature that is currently considered to be adjusted; x prey represents the optimal temperature in the environment; β≥1 (default value is 6) reflects the ability of the honey badger individual to obtain food; F1 is used as a sign of the continuously changing search direction; r3, r4, and r5 represent three random values between 0 and 1; among them, the definition of F1 is shown in Equation (17):

[0130]

[0131] where, r6 is a random number between 0 and 1; the search path of the honey badger in the mining mode is mainly affected by the distance d i of the prey, the olfactory intensity I i of the prey, and the nonlinear density factor α;

[0132] Honey mode: In the honey mode, the honey badger changes the optimization path and follows the honey guide bird to reach the target honeycomb, and the simulation of its route trajectory is shown in Equation (18):

[0133] x new = x prey + F 1 × r 7 × α × d i (18)

[0134] where, r7 is a random number between 0 and 1; α and F1 are determined by Equation (15) and Equation (17); in this stage, the optimization path of the honey badger is related to the distance d i between the prey and the i-th honey badger, the optimal temperature x prey , and α, and the honey badger explores near x prey ;

[0135] To solve the problems of slow convergence speed and difficult effective optimization in the HBA algorithm; an adaptive weight factor is added to balance global and local searches, improve the optimization performance and stability of the algorithm, and a starvation search strategy is added to enhance the search ability of the algorithm;

[0136] Among them, the adaptive weight factor is as follows:

[0137]

[0138] where \(t\) is the current iteration number; \(t\) max is the maximum number of iterations;

[0139] An adaptive weight factor is introduced, and the search routes of the mining mode and the honey mode in HBA are as follows:

[0140]

[0141] The starvation search strategy is as follows:

[0142] \(x\) new \( = x\) prey \(\times\omega+F\) 1 \(\times r\) 7 \(\times\alpha\times d\) i \(\times\exp(x\) worse \(-x\) i )

[0143] where \(x\) worse represents the globally worst position; \(x\) i is the position of the current population individual; the starvation search strategy improves the original search path based on the globally worst position, enabling the honey badger to perform a more extensive search on the basis of the original search path when it is in a starvation state, enhancing its ability to jump out of the local optimum.

Claims

1. A technology suitable for automatically controlling the constant temperature of an energy storage bin, characterized in that: It includes interconnected green energy temperature control modules, compound serpentine channel cold liquid cooling modules, electric energy temperature control modules, phase change material temperature control units and temperature sensing measurement and judgment modules.

2. A technology suitable for automatically controlling the constant temperature of an energy storage bin according to claim 1, characterized in that: The compound serpentine channel cold liquid cooling module includes a coolant and a compound serpentine cold liquid plate; The coolant is composed of 50% ethanol and 50% water. The temperature of the coolant is calculated by the optimum temperature of the energy storage bin and the temperature of the liquid cooling plate. The heat energy conservation formula of the coolant, liquid cooling plate and energy storage bin is as follows: Coolant: Liquid cooling plate: Energy storage warehouse: k1T l +k2T d =k3T c +T gen (4) In the formula, ρ l 、c pl , k l , T l is the density, specific heat capacity, thermal conductivity and temperature of the coolant; ρ d 、c pd , T d , k d is the density, specific heat capacity, temperature and thermal conductivity of the liquid cooling plate; ρ c 、c pc , k cx , k cy , k cz , T c is the density, specific heat capacity, thermal conductivity along the x-axis, thermal conductivity along the y-axis, thermal conductivity along the z-axis, and temperature of the energy storage bin; k1, k2, and k3 are the proportional relationship coefficients of the three in the heat conservation; T gen is the temperature volatilization value; The internal channel of the compound serpentine cold liquid plate is a compound type, which is provided with an inlet and an outlet. The channel between the inlet and the outlet is similar to a serpentine shape, and V-shaped channels are inserted between two of them on the basis of the serpentine shape.

3. The technology for automatically controlling the constant temperature of an energy storage bin according to claim 1, characterized in that: The green energy temperature control module is divided into air cooling and solar heating PTC resistor ceramic heat transfer; Among them, the air-cooling heat dissipation adopts serial ventilation, and the installed fan draws cold air outside the energy storage bin, and allows the cold air to flow in from one side of the energy storage bin group and out from the other side; and based on the data transmitted by the temperature sensing measurement judgment module, it is judged whether it is higher than the optimum temperature; if it is higher than the optimum temperature, solar energy is used to drive the fan to increase the natural wind force while using parallel ventilation to complete air-cooling heat dissipation.

4. A technology suitable for automatically controlling the constant temperature of an energy storage bin according to claim 3, characterized in that: The solar heating PTC resistor ceramic piece heat transfer uses a single crystal silicon solar panel to convert electrical energy and a PTC thermistor-type ceramic piece to heat the air and protect the energy storage bin; Monocrystalline silicon solar panels convert solar energy into electrical energy, which provides energy for PTC resistor ceramic sheets and wind turbines on the one hand, and stores it in energy storage warehouses on the other hand; Based on the data transmitted by the temperature sensing measurement and judgment module, it is determined whether the temperature is lower than the optimum temperature. If the temperature is lower than the optimum temperature, the electric energy converted from solar energy is used to heat the PTC resistor ceramic sheet, so that the heat is transferred to the energy storage bin. At the same time, the surrounding air is heated, and then the fan is started to use parallel ventilation to transfer the heat to the energy storage bin.

5. The technology for automatically controlling the constant temperature of an energy storage bin according to claim 1 is characterized in that: The electric energy temperature control module releases and absorbs the heat energy brought by the charging and discharging of the energy storage bin itself; Among them, the heat transfer method inside the energy storage bin is heat conduction.

6. The technology for automatically controlling the constant temperature of an energy storage bin according to claim 1, characterized in that: The phase change material temperature control unit uses the melting and condensation states of the supercooled phase change material to cause the switching of the thermal switch, allowing the energy storage bin to transfer its own heat to the phase change material for absorption or to allow the temperature released by the phase change material to be indirectly transferred to the energy storage bin.

7. A technology suitable for automatically controlling the constant temperature of an energy storage bin according to claim 6, characterized in that: The supercooled phase change material refers to the phenomenon that under certain pressure conditions, when the temperature of the liquid phase is lower than the theoretical freezing point temperature, it will not solidify, and needs to be cooled below the freezing point before it starts to solidify; A thermal switch is a device that adjusts its own switch closure according to temperature. It controls the contact area through the thermal expansion of solids, gases or liquids, allowing the regulated object to passively maintain the temperature at the optimal value, achieving effective switching when there is thermal conductivity; Since the thermal conductivity of the phase change material changes with the liquid phase ratio, as shown in equations (7) and (8): Where, β is the liquid phase ratio; T s , T1 are the temperatures at which the phase change material begins to melt and completely melts, respectively; l PCM =λ s -b(l s -λ1) (8) In the formula, λ PCM is the actual thermal conductivity of the phase change material, λ s is the thermal conductivity of its solid state, and λ1 is the thermal conductivity of its liquid state; In addition, the heat transfer between the phase change material, liquid cooling plate, mobile plate surface, and energy storage bin is expressed by the following formula: Where, T c is the temperature of the energy storage bin; T PCM is the phase change material temperature; T plate is the temperature of the liquid cooling plate; T cop is the moving plate surface temperature; T air is the air temperature; n is the reference directional coefficient; λ c , PCM , cop , air They are the thermal conductivity of energy storage bin, phase change material, moving plate surface and air respectively.

8. The technology for automatically controlling the constant temperature of an energy storage bin according to claim 1, characterized in that: The temperature sensing measurement and judgment module makes its judgment based on the temperature T1 of the energy storage bin, the internal air temperature T2, and the external air temperature T3. The temperature of each part is measured by a specific temperature sensor of each part. The remaining components are a small computing server, a controller, and a pulse signal device. By meeting the judgment basis of each part, a pulse signal is sent to each module to enable it to operate.

9. A technology suitable for automatically controlling the constant temperature of an energy storage bin according to claim 8, characterized in that: in, The temperature sensing measurement and determination module determines the green energy temperature control module, the compound serpentine channel cold liquid cooling module, the electric energy temperature control module and the phase change material temperature control unit based on the following: (1): First, determine whether T1 is lower or higher than the optimal temperature. If it is lower than the optimal temperature, open the green energy temperature control module to the outside air, use solar energy heat conversion and parallel ventilation heating; for the electric energy temperature control module, use the energy storage bin to discharge and heat; for the phase change material temperature control unit, the phase change material solidifies and releases heat; If the temperature is higher than the optimal temperature, the compound serpentine channel cold liquid cooling module is treated with cooling liquid to flow through the cold liquid plate for cooling; the green energy temperature control module is opened to the outside air circulation and parallel ventilation is used; the electric energy temperature control module uses energy storage bin charging to absorb heat; the phase change material temperature control unit is melted to absorb heat; (2): Based on the above step (1), if T2 is lower than the optimal temperature, the above heating method is used; if it is higher than the optimal temperature, the endothermic cooling method is used; (3): Based on the above steps (1) and (2), if T3 is always opposite to the adjustment demand, the green energy temperature control module will not be circulated with external air unless the internal air is insufficient.

10. The technology for automatically controlling the constant temperature of an energy storage bin according to claim 1, characterized in that: Since each module and energy storage bin has different time requirements for temperature control, the following Honey Badger algorithm is used, and this part is processed by the temperature measurement and judgment module; Among them, the steps of the honey badger algorithm are as follows: (1) Population initialization: The model of the HBA algorithm is established by simulating the intelligent behavior of honey badgers. It seeks the best solution by simulating the predation behavior of honey badgers. The size of the honey badger population is N. The HBA algorithm randomly initializes the population within a certain upper and lower limit, as shown in the following formula (13): X i =l lb.i +r i ×(u ub.i -l lb.i ) (13) Where X i represents the required temperature; and u ub.i and l lb.i Respectively represent the upper and lower bounds of the search temperature range; r i is a random number in [0, 1]; (2) Environmental influencing factors: The predation ability of honey badgers is related to the distance to the i-th honey badger, the concentration intensity of prey and the intensity of odor; i is the odor intensity of the prey; when I i As the size increases, the speed of the honey badger increases; i The specific definition of is shown in formula (14): Where r2 is a random number between 0 and 1; S is the concentration intensity of the prey; d i represents the distance between the prey and the i-th honey badger; (3) Density factor: The nonlinear density factor α constrains the optimization path that changes over time, making the algorithm evolution process more stable. The nonlinear density factor α decreases with the number of iterations, and its definition is shown in the following formula (15): Where, t max Indicates the maximum number of iterations; C ≥ 1; (4) Particle position update: The HBA algorithm's optimal path search is divided into mining mode and honey mode, and these two modes have different motion trajectories; (5) Digging mode: In the digging mode, the movement trajectory of the honey badger is similar to a heart shape, and the movement trajectory is simulated by the following formula (16): Where x new Represents the temperature that needs to be adjusted to; x prey represents the optimal temperature in the environment; β≥1 reflects the ability of the honey badger to obtain food; F1 is a sign of the continuous change of search direction; r3, r4 and r5 represent three random values ​​between 0 and 1; where F1 is defined as shown in the following formula (17): Where: r6 is a random number between 0 and 1; the search path of the honey badger in the digging mode is affected by the distance d from the prey. i 、Smell intensity of prey I i and the influence of nonlinear density factor α; (6) Honey mode: In the honey mode, the honey badger changes the optimal path and follows the honey guide bird to reach the target hive. The simulation of its route trajectory is shown in formula (18): x new =x prey +F1×r7×α×d i (18) Where: r7 is a random number between 0 and 1; α and F1 are determined by equations (15) and (17); at this stage, the optimal path of the honey badger is the distance d between the prey and the i-th honey badger. i , optimal temperature x prey And α, honey badger in x prey Explore nearby; To solve the problems existing in the HBA algorithm, an adaptive weight factor is added to balance global and local searches; a starvation search strategy is added to enhance the algorithm's search capabilities; Among them, the adaptive weight factor is as follows: Where t is the current iteration number; t max is the maximum number of iterations; Introducing the adaptive weight factor, the search routes of mining mode and honey mode in HBA are as follows: x new =x prey ×ω+F1×r7×α×d i The hungry search strategy is as follows: x new =x prey ×ω+F1×r7×α×d i ×exp(x worse -x i ) In the formula, x worse represents the global worst position; x i is the position of the current population individual.

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