Laminated fabric-type heating core, and heating core manufacturing device and control system therefor

Abstract

The present invention relates to the technical field of heaters, and in particular to a laminated fabric-type heating core, and a heating core manufacturing device and a control system therefor. The laminated fabric-type heating core comprises warp yarns and weft yarns made of a conductive composite fiber, wherein the warp yarns and the weft yarns are woven on a loom into the laminated fabric-type heating core; and the conductive composite fiber is formed by laminating a conductive material and fiber substrate materials. In the laminated fabric-type heating core provided by the present invention, uniform weaving of flexible conductive composite fibers enables uniform heat distribution in a fabric, thereby preventing local overheating or overcooling; and consumption of electrical energy for heating is reduced due to the low resistance of the conductive composite fibers.

Description

Layered fabric heating cell, heating cell manufacturing equipment and control system thereof TECHNICAL FIELD

[0001] The present application relates to the technical field of heaters, in particular to a layered fabric heating cell, a heating cell manufacturing equipment and a control system thereof. BACKGROUND

[0002] Layered fabric heating technology is widely used in modern life. Traditional heating methods mainly rely on conductive materials such as metal wires or carbon fibers. These materials need to be evenly distributed in the fabric to ensure uniform heat transfer.

[0003] Patent application No. CN101437332A discloses an electric blanket. The invention provides an electric blanket with adjustable temperature and electromagnetic shielding device, which comprises a blanket, heating wires and a temperature controller. The blanket is three layers, and the four edges of the outer two layers are connected to form a bag. There is an opening on one side of the bag, and a closable sealing device on the opening. The third layer of the blanket is attached to one side of the bag, and the two are connected together along parallel and alternating straight lines. The heating wires pass through each channel in turn and are connected to the temperature controller and power supply line in turn. The temperature is adjustable.

[0004] As in the above application, the existing electric blanket metal wire or carbon fiber is in the form of a flexible tube line as a heating body. The power heating mode is linear heating, so there is a phenomenon that the temperature of the tube area is high and the temperature of other areas is low. The linear heating mode needs higher temperature to conduct to the whole surface, increasing the energy consumption. Moreover, the higher temperature will affect the user experience. The heating flexible line material mainly relies on the external plastic tube for insulation. After long-term high-temperature use, the plastic is prone to aging and cracking, causing safety hazards such as electric leakage. At the same time, in order to achieve the insulation effect, the wall thickness of the plastic tube needs to meet certain requirements, which causes the area with the flexible tube to be felt, affecting the flexibility and comfort of the fabric. SUMMARY

[0005] In order to solve the above problems, the present application provides a layered fabric heating cell, a heating cell manufacturing equipment and a control system thereof.

[0006] The present application adopts the following technical scheme. The heating cell manufacturing equipment is used for manufacturing a heating cell composed of conductive composite fibers, which is woven into a layered fabric by a loom. The heating cell manufacturing equipment comprises:

[0007] The laminated tank is composed of a tank body and an upper cover.

[0008] The fiber line arrangement assembly is arranged on the upper cover, and is used for arranging and laying the conductive composite fiber cloth to ensure the stability of the conductive composite fiber position.

[0009] The booster assembly comprises a booster pump and an air guide pipe, one end of the air guide pipe is in communication with the air outlet of the booster pump, and the other end of the air guide pipe is in communication with the tank body.

[0010] As a further description of the above technical solution: the fiber line arrangement assembly comprises an arrangement base body, the arrangement base body is a spindle structure, and a plurality of winding mechanisms are arranged at equal intervals on the outer wall of the arrangement base body from bottom to top and from one side to the other side in the circumferential direction.

[0011] The winding mechanism comprises a strip-shaped seat, one end of the strip-shaped seat is inserted into a limiting groove formed in the arrangement base body, a limiting block is welded to the end of the strip-shaped seat located in the limiting groove, a spring is arranged between the limiting block and the inner wall of the limiting groove, and the other end of the strip-shaped seat is rotatably connected with a winding roller.

[0012] As a further description of the above technical solution: a pressure sensor is arranged on the upper cover, an electric heating plate is installed in the arrangement base body, and a supporting leg is installed on the outer wall of the laminated tank.

[0013] As a further description of the above technical solution: a base is installed on the upper part of the outer wall of the laminated tank, an L-shaped frame is rotatably connected to the base, an electric telescopic rod is installed on the upper surface of the horizontal end of the L-shaped frame, the bottom end of the electric telescopic rod is welded and fixed to the upper cover, and a driving mechanism is arranged on the base and used for driving the L-shaped frame to rotate along the vertical end shaft thereof.

[0014] The driving mechanism comprises a linkage gear fixed to the vertical end of the L-shaped frame and a driving motor embeddedly installed in the base, a driving gear is fixed to the output shaft of the driving motor, and the driving gear is in meshing connection with the linkage gear.

[0015] The layered fabric heating cell is prepared by using the heating cell manufacturing equipment, the layered fabric heating cell comprises warp yarns and weft yarns composed of conductive composite fibers, the warp yarns and the weft yarns are woven into the heating cell in the form of layered fabric by using a loom, and the conductive composite fibers are prepared by laminating conductive materials and fiber matrix materials.

[0016] As a further description of the above technical solution: the conductive material is one of carbon nanotubes, graphene and conductive polymers.

[0017] The fiber matrix material is one of polypropylene, polyacrylonitrile, PET and polyethylene terephthalate.

[0018] A control system of a heating battery manufacturing apparatus includes: the heating battery manufacturing apparatus and a control unit, the control unit including:

[0019] A data acquisition module acquires historical lamination training data of the conductive composite fiber, the historical lamination training data being acquired in a case where the conductive composite fiber meets a lamination processing standard, the historical lamination training data including first historical training data and second historical training data;

[0020] The first historical training data includes material composition of the conductive composite fiber, heating coefficient of the conductive composite fiber, and heating temperature;

[0021] The second historical training data includes material composition of the conductive composite fiber, diameter of the conductive composite fiber, heating temperature, and lamination control parameters;

[0022] A temperature prediction module trains a machine learning model for predicting the heating temperature based on the first historical training data, acquires material composition of the conductive composite fiber to be laminated and the heating coefficient of the conductive composite fiber, and predicts the heating temperature based on the trained machine learning model;

[0023] A parameter prediction module trains a lamination control parameter recommendation model based on the second historical training data, acquires material composition of the conductive composite fiber to be processed, diameter of the conductive composite fiber, and heating temperature, inputs the acquired data into the trained lamination control parameter recommendation model, obtains a lamination control parameter recommendation set label, and further acquires a lamination control parameter recommendation set corresponding to the lamination control parameter recommendation set label, and controls the lamination tank based on the lamination control parameters in the lamination control parameter recommendation set.

[0024] As a further description of the above technical solutions: the parameters affecting the heating coefficient of the conductive composite fiber include melting point of the conductive material, thermal expansion coefficient of the fiber matrix material, and diameter of the conductive composite fiber;

[0025] The expression of the heating coefficient of the conductive composite fiber is:

[0026] ;

[0027] In the formula, is the heating coefficient of the conductive composite fiber, is the melting point of the conductive material, is the thermal expansion coefficient of the fiber matrix material, is the diameter of the conductive composite fiber, , and are weight factors, , and are all greater than zero.

[0028] As a further description of the above technical solution: the method for training a machine learning model to predict heating temperature based on the first historical training data includes:

[0029] The first set of historical training data collected is converted into a corresponding set of feature vectors;

[0030] Each set of feature vectors is used as input to the machine learning model. The machine learning model outputs the material composition of each set of collected conductive composite fibers and the heating temperature corresponding to the heating coefficient of the conductive composite fibers. The material composition of each set of collected conductive composite fibers and the actual heating temperature corresponding to the heating coefficient of the conductive composite fibers are used as prediction targets. The training objective is to minimize the loss function value of the machine learning model. Training stops when the loss function value of the machine learning model is less than or equal to the preset first target loss value.

[0031] As a further description of the above technical solution: the recommended set of lamination control parameters is as follows: , The collection label is The corresponding pressurization pressure at that time The collection label is The corresponding pressurization time;

[0032] Methods for training a lamination control parameter recommendation model based on second historical training data include:

[0033] Pre-assign corresponding numbers to the recommended set of lamination control parameters;

[0034] The second set of historical training data is converted into a corresponding set of second feature vectors. Each set of second feature vectors is used as input to the lamination control parameter recommendation model. The lamination control parameter recommendation model outputs a set of recommended lamination control parameters corresponding to the material composition, diameter, and heating temperature of the conductive composite fiber. The actual set of recommended lamination control parameters corresponding to the material composition, diameter, and heating temperature of each set of conductive composite fibers is used as the prediction target. The training objective is to minimize the loss function value of the lamination control parameter recommendation model. Training stops when the loss function value of the lamination control parameter recommendation model is less than or equal to the preset second target loss value.

[0035] Beneficial effects:

[0036] The laminated fabric heating electric core provided by the application is prepared by laminating conductive material and fiber matrix material to form conductive composite fibers, and then the conductive composite fibers are used to weave the heating electric core in the form of a laminated fabric formed by warp yarns and weft yarns, the uniform weaving of the flexible conductive composite fibers enables the heat to be uniformly distributed in the fabric, avoiding the problems of local overheating or overcooling, and due to the low resistance of the conductive composite fibers, the power consumption required for heating is reduced, the energy utilization efficiency is improved, and the phenomenon that the temperature of the wire tube area is high and the temperature of other areas is low in the prior art is improved.

[0037] Further, the conductive composite fibers to be laminated are uniformly and staggered arranged on the outside of the arrangement matrix through the arrangement assembly, and the arrangement matrix is in the form of a spindle, so that the conductive composite fibers arranged on the winding mechanism outside the arrangement matrix are staggered with each other, ensuring that the conductive composite fibers are uniformly distributed during lamination, and when the conductive composite fibers are arranged by the winding mechanism, the strip-shaped seat is inserted into the limiting groove in the arrangement matrix, and the spring is arranged, so that the tension of the conductive composite fibers wound on the winding mechanism can be self-adaptively adjusted according to the elastic contraction of the spring during use, so as to keep the tension and position of the conductive composite fibers stable. BRIEF DESCRIPTION OF DRAWINGS

[0038] The application will be further explained in combination with the drawings and examples:

[0039] Fig. 1 is a structural schematic view of the laminated fabric heating electric core provided by the embodiment 1 of the application;

[0040] Fig. 2 is a structural schematic view of the conductive composite fiber provided by the embodiment 1 of the application;

[0041] Fig. 3 is a structural schematic view of the heating electric core manufacturing equipment provided by the embodiment 2 of the application;

[0042] Fig. 4 is an enlarged view of the area A in Fig. 3 provided by the embodiment 2 of the application;

[0043] Fig. 5 is a structural schematic view of the lamination tank provided by the embodiment 2 of the application;

[0044] Fig. 6 is a structural schematic view of the fiber line arrangement assembly provided by the embodiment 2 of the application;

[0045] Fig. 7 is an enlarged view of the area B in Fig. 6 provided by the embodiment 2 of the application;

[0046] Fig. 8 is a module connection diagram of the control unit provided by the embodiment 3 of the application.

[0047] 101, heating cell; 102, weft yarn; 103, warp yarn; 104, conductive composite fiber; 105, fiber matrix material; 106, conductive material; 1, laminated tank; 11, pressure sensor; 2, tank body; 3, upper cover; 31, arrangement base; 32, winding mechanism; 33, strip-shaped seat; 34, winding roller; 35, limiting groove; 36, spring; 37, limiting block; 38, electric heating plate; 41, linkage gear; 42, driving motor; 43, driving gear; 5, support leg; 6, base; 7, L-shaped frame; 8, electric telescopic rod; 9, air guide pipe; 10, booster pump. DETAILED DESCRIPTION

[0048] In order to make the technical means, creative features, purposes and effects realized by the present application easy to understand, the present application is further described below in combination with specific drawings. It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict.

[0049] Embodiment 1

[0050] Please refer to FIG. 1-2, the embodiment of the present application provides a technical solution: laminated fabric heating cell, comprising warp yarn 103 and weft yarn 102 composed of conductive composite fiber 104, the warp yarn 103 and the weft yarn 102 are woven into a laminated fabric heating cell 101 by a loom.

[0051] The conductive composite fiber 104 is prepared by laminating the conductive material 106 and the fiber matrix material 105.

[0052] The conductive material 106 is one of carbon nanotubes, graphene and conductive polymer.

[0053] The fiber matrix material 105 is one of polypropylene, polyacrylonitrile, PET and polyethylene terephthalate.

[0054] In this embodiment, the conductive composite fiber 104 is prepared by laminating the conductive material 106 and the fiber base material 105, and then the heating electric core 101 formed by the layer fabric woven by the warp yarn 103 and the weft yarn 102 is composed of the conductive composite fiber 104. The uniform weaving of the flexible conductive composite fiber 104 makes the heat uniformly distributed in the fabric, avoiding the problems of local overheating or overcooling. Since the resistance of the conductive composite fiber 104 is low, the power consumption required for heating is reduced, the energy utilization efficiency is improved, and the phenomenon that the temperature of the wire tube area is high and the temperature of other areas is low in the prior art is improved. The heating soft wire material mainly relies on the external plastic tube for insulation. After long-term high-temperature use, the plastic is prone to aging and cracking, causing the safety hazard of electric leakage. At the same time, in order to achieve the insulation effect, the wall thickness of the plastic tube needs to meet certain requirements, which causes the area with the soft wire tube to be felt, affecting the flexibility and comfort of the fabric.

[0055] Embodiment 2

[0056] Please refer to FIG. 3-7, the embodiment of the present application provides a technical solution: a heating electric core manufacturing equipment for manufacturing a layer fabric heating electric core, comprising:

[0057] The laminating tank 1 is composed of a tank body 2 and an upper cover 3.

[0058] The fiber line arrangement assembly is arranged on the upper cover 3, and is used for arranging and laying the conductive composite fiber 104 to ensure the stable position of the conductive composite fiber 104.

[0059] The pressurizing assembly comprises a pressurizing pump 10 and a gas guide pipe 9. One end of the gas guide pipe 9 is in communication with the gas outlet of the pressurizing pump 10, and the other end of the gas guide pipe 9 is in communication with the tank body 2.

[0060] The fiber line arrangement assembly comprises an arrangement base 31, which is a spindle structure. A plurality of winding mechanisms 32 are arranged on the outer wall of the arrangement base 31 in an equidistant staggered manner along the circumferential direction from bottom to top on one side.

[0061] The winding mechanism 32 comprises a strip-shaped seat 33, one end of which is inserted into the limiting groove 35 formed in the arrangement base 31. The end of the strip-shaped seat 33 located in the limiting groove 35 is welded with a limiting block 37. The limiting block 37 and the inner wall of the limiting groove 35 are provided with a spring 36. The other end of the strip-shaped seat 33 is rotatably connected with a winding roller 34.

[0062] Specifically, when arranging the conductive composite fiber 104 through the winding mechanism 32, first, the winding roller 34 is rotated and connected in the strip-shaped seat 33, the strip-shaped seat 33 is inserted into the limiting groove 35 provided in the arrangement base 31, and the spring 36 is arranged. In use, according to the elastic contraction of the spring 36, the tension of the conductive composite fiber 104 wound on the winding mechanism 32 can be self-adaptively adjusted to maintain the tension and position stability of the conductive composite fiber 104.

[0063] The upper cover 3 is provided with a pressure sensor 11, the arrangement base 31 is provided with an electric heating plate 38, and the outer wall of the laminated tank 1 is provided with a supporting leg 5.

[0064] The outer wall of the laminated tank 1 is provided with a base 6, the base 6 is rotatably connected with an L-shaped frame 7, the horizontal end of the L-shaped frame 7 is provided with an electric telescopic rod 8, the bottom end of the electric telescopic rod 8 is welded and fixed with the upper cover 3, and the base 6 is provided with a driving mechanism for driving the L-shaped frame 7 to rotate along the vertical end thereof;

[0065] The driving mechanism comprises a linkage gear 41 fixed on the vertical end of the L-shaped frame 7 and a driving motor 42 embeddedly installed in the base 6, and a driving gear 43 is fixedly connected to the output shaft of the driving motor 42 and is in meshing connection with the linkage gear 41.

[0066] Specifically, through the arrangement of the base 6 and the L-shaped frame 7, the position of the winding mechanism 32 is adjusted. In use, first, the electric telescopic rod 8 is controlled to contract, driving the upper cover 3 to move upwards, so that the fiber line arrangement assembly arranged below the upper cover 3 is moved out of the tank body 2, then the driving mechanism is controlled to drive the L-shaped frame 7 to rotate, thereby driving the fiber line arrangement assembly to be dislocated with the tank body 2, then the electric telescopic rod 8 is controlled to extend, driving the fiber line arrangement assembly to move downwards, and the height of the fiber line arrangement assembly is adjusted, then the conductive composite fiber 104 is wound on the winding mechanism 32, so that the conductive composite fiber 104 is uniformly arranged outside the arrangement base 31, and then the electric telescopic rod 8 is controlled to extend and retract and the L-shaped frame 7 is controlled to rotate, so that the fiber line arrangement assembly is moved into the tank body 2, and the tank body 2 is sealed by the upper cover 3, then the electric heating plate 38 is controlled to work, the conductive composite fiber 104 is heated, the booster pump 10 is controlled to work, the pressure inside the laminated tank 1 is adjusted, and the conductive composite fiber 104 is laminated to make the conductive material 106 and the fiber base material 105 tightly combined.

[0067] In this embodiment, by arranging the fiber line arrangement assembly, the conductive composite fibers 104 to be laminated can be uniformly arranged and arranged outside the arrangement base 31, and the arrangement base 31 is a spindle-shaped structure, so that the conductive composite fibers 104 arranged and arranged on the winding mechanism 32 outside the arrangement base 31 are uniformly staggered, and the adjacent conductive composite fibers 104 wound on the arrangement base 31 will not be in the same horizontal plane, ensuring that the conductive composite fibers 104 remain uniformly distributed during lamination.

[0068] Embodiment 3

[0069] Referring to FIGS. 3-8, the embodiment of the application provides a technical solution: a control system of a heating cell manufacturing device, comprising: the heating cell manufacturing device in embodiment 2 and a control unit, the control unit comprising:

[0070] The data acquisition module acquires historical lamination training data of the conductive composite fibers 104, and the historical lamination training data is acquired under the condition that the conductive composite fibers 104 meet the lamination processing standards. The historical lamination training data includes first historical training data and second historical training data;

[0071] The first historical training data includes the material composition of the conductive composite fibers 104, the heating coefficient of the conductive composite fibers 104, and the heating temperature;

[0072] The second historical training data includes the material composition of the conductive composite fibers 104, the diameter of the conductive composite fibers 104, the heating temperature, and the lamination control parameter;

[0073] The temperature prediction module trains a machine learning model for predicting the heating temperature based on the first historical training data, acquires the material composition of the conductive composite fibers 104 to be laminated and the heating coefficient of the conductive composite fibers 104, and predicts the heating temperature based on the trained machine learning model;

[0074] The parameter prediction module trains a lamination control parameter recommendation model based on the second historical training data, acquires the material composition of the conductive composite fibers 104 to be processed, the diameter of the conductive composite fibers 104, and the heating temperature, inputs them into the trained lamination control parameter recommendation model, obtains a lamination control parameter recommendation set label, and then acquires a lamination control parameter recommendation set corresponding to the lamination control parameter recommendation set label, and controls the work of the lamination tank 1 based on the lamination control parameters in the lamination control parameter recommendation set.

[0075] The parameters affecting the heating coefficient of the conductive composite fibers 104 include the melting point of the conductive material 106, the thermal expansion coefficient of the fiber base material 105, and the diameter of the conductive composite fibers 104;

[0076] The expression of the heating coefficient of the conductive composite fibers 104 is:

[0077] ;

[0078] In the formula, is the heating coefficient of the conductive composite fiber 104, is the melting point of the conductive material 106, is the thermal expansion coefficient of the fiber matrix material 105, is the diameter of the conductive composite fiber 104, and is a weight factor, and are all greater than zero.

[0079] Specifically, the thermal expansion coefficient of the fiber matrix material 105 also affects the selection of the heating temperature, and needs to avoid fiber expansion or warping due to excessive temperature, that is, the greater the thermal expansion coefficient of the fiber matrix material 105, the lower the heating temperature, and vice versa. The higher the melting point of the conductive material 106, the higher the heating temperature, and vice versa. The greater the diameter of the conductive composite fiber 104, the higher the heating temperature, and vice versa. In summary, the greater the heating coefficient of the conductive composite fiber 104, the higher the heating temperature, and vice versa.

[0080] It should be noted that the size of the weight factor is a specific value obtained by quantizing each data for subsequent comparison. The size of the weight factor depends on the number of comprehensive parameters and the corresponding weight factor initially set by the person skilled in the art for each set of comprehensive parameters.

[0081] The method for training the machine learning model for predicting the heating temperature based on the first historical training data comprises:

[0082] Converting the collected first historical training data into a corresponding set of feature vectors;

[0083] Taking each set of feature vectors as the input of the machine learning model, the machine learning model taking the material composition of each set of collected conductive composite fibers 104 and the corresponding heating temperature of the heating coefficient of the conductive composite fiber 104 as the output, taking the material composition of each set of collected conductive composite fibers 104 and the actual corresponding heating temperature of the heating coefficient of the conductive composite fiber 104 as the prediction target, and minimizing the loss function value of the machine learning model as the training target; stop training when the loss function value of the machine learning model is less than or equal to the first target loss value.

[0084] Specifically, the machine learning model is a deep belief network model. It should be noted that in the machine learning model, the calculation formula of the loss function is: , wherein ​​the number of the feature vector, the prediction error, the number of the first group of feature vectors corresponding to the predicted state value, the state value being the heating temperature, the number of the first group of feature vectors corresponding to the actual state value.

[0085] the set of recommended lamination control parameters is , the pressing pressure corresponding to the set label , the pressing time corresponding to the set label ;

[0086] The method for training the recommended lamination control parameter model based on the second historical training data comprises:

[0087] previously setting the corresponding numbers for the set of recommended lamination control parameters;

[0088] converting the second historical training data into a corresponding group of second feature vectors, taking each group of second feature vectors as the input of the recommended lamination control parameter model, taking the group of recommended lamination control parameter set labels corresponding to the material composition, diameter of the conductive composite fiber 104 and heating temperature of the conductive composite fiber 104 as the output of the recommended lamination control parameter model, taking the group of recommended lamination control parameter set labels actually corresponding to the material composition, diameter of the conductive composite fiber 104 and heating temperature of the conductive composite fiber 104 as the prediction target, and taking the minimization of the loss function value of the recommended lamination control parameter model as the training target; and stopping the training when the loss function value of the recommended lamination control parameter model is less than or equal to the preset second target loss value.

[0089] Specifically, the recommended lamination control parameter model is a deep neural network model.

[0090] It should be noted that in the recommended lamination control parameter model, the calculation formula of the prediction error is: , wherein the number of the second feature vector, the prediction error, the number of the first group of second feature vectors corresponding to the predicted state value, the state value being the recommended set label of the control parameter, the number of the first group of second feature vectors corresponding to the actual state value.

[0091] In this embodiment, a control unit is added to collect historical lamination training data of the conductive composite fiber 104. The historical lamination training data includes first historical training data and second historical training data. A machine learning model for predicting the heating temperature is trained based on the first historical training data. Then, by collecting the material composition and heating coefficient of the conductive composite fiber 104 to be laminated, the heating temperature is predicted based on the trained machine learning model. The conductive composite fiber 104 is then heated according to the predicted heating temperature. That is, by comprehensively collecting parameters that affect the heating temperature, the machine learning model is trained, and the heating temperature is predicted based on the trained machine learning model. Then, the heating plate 38 is controlled to work according to the predicted heating temperature, thereby ensuring the softening effect of the conductive material 106 and the fiber matrix material 105, and ensuring the tight bonding of the conductive material 106 and the fiber matrix material 105 after lamination.

[0092] Furthermore, based on the heating temperature predicted by the trained machine learning model, a lamination control parameter recommendation model is trained using second historical training data. This involves comprehensively collecting parameters affecting the lamination control parameters and the predicted heating temperature to train the model. Then, based on the trained model, a set of recommended lamination control parameters is obtained, along with corresponding recommended sets of lamination control parameters. The lamination control parameters within this set are used to control the operation of the lamination tank 1, ensuring a tight bond between the conductive material 106 and the fiber matrix material 105 after lamination. Additionally, the automatic generation of control parameters is achieved, automatically controlling the pressurization pressure and time without requiring manual adjustment based on experience, further guaranteeing the lamination effect of the conductive composite fiber 104.

[0093] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A heating cell manufacturing apparatus for manufacturing a heating cell (101) composed of warp yarns (103) and weft yarns (102) made of conductive composite fibers (104), wherein the warp yarns (103) and weft yarns (102) are woven into a layered fabric by a loom, characterized in that, include: Laminated tank (1), which is composed of tank body (2) and top cover (3); A fiber line arrangement assembly is provided on the upper cover (3). The fiber line arrangement assembly is used to arrange the conductive composite fiber (104) to ensure the stable position of the conductive composite fiber (104). The pressurization assembly includes a pressurization pump (10) and an air guide pipe (9). One end of the air guide pipe (9) is connected to the air outlet of the pressurization pump (10), and the other end of the air guide pipe (9) is connected to the tank (2). The fiber arrangement assembly includes an arrangement substrate (31), which is a spindle-shaped structure. A winding mechanism (32) is provided at equal intervals on the outer wall of the arrangement substrate (31) from bottom to top along its circumference. The winding mechanism (32) includes a strip seat (33), one end of which is inserted into a limiting groove (35) opened in the arrangement base (31). A limiting block (37) is welded to one end of the strip seat (33) located in the limiting groove (35). A spring (36) is provided between the limiting block (37) and the inner wall of the limiting groove (35). A winding roller (34) is rotatably connected to the other end of the strip seat (33).

2. The heating cell manufacturing equipment according to claim 1, characterized in that, A pressure sensor (11) is provided on the top cover (3), an electric heating plate (38) is installed inside the arrangement substrate (31), and a support leg (5) is installed on the outer wall of the laminating tank (1).

3. The heating cell manufacturing equipment according to claim 1, characterized in that, A base (6) is installed on the upper part of the outer wall of the laminated tank (1). An L-shaped frame (7) is rotatably connected to the base (6). An electric telescopic rod (8) is installed on the upper surface of the horizontal end of the L-shaped frame (7). The bottom end of the electric telescopic rod (8) is welded and fixed to the upper cover (3). A driving mechanism is provided on the base (6) for driving the L-shaped frame (7) to rotate axially along its vertical end. The drive mechanism includes a linkage gear (41) fixed to the vertical end of the L-shaped frame (7) and a drive motor (42) embedded in the base (6). A drive gear (43) is fixed on the output shaft of the drive motor (42), and the drive gear (43) meshes with the linkage gear (41).

4. A layered fabric heating cell, manufactured using the heating cell manufacturing equipment as described in any one of claims 1-3, characterized in that, The layered fabric heating element includes warp yarns (103) and weft yarns (102) made of conductive composite fibers (104). The warp yarns (103) and weft yarns (102) are woven into a layered fabric heating element (101) by a weaving machine. The conductive composite fibers (104) are prepared by laminating conductive material (106) and fiber matrix material (105).

5. The layered fabric heating cell according to claim 4, characterized in that, The conductive material (106) is one of carbon nanotubes, graphene, and conductive polymers; The fiber matrix material (105) is one of polypropylene, polyacrylonitrile, PET and polyethylene terephthalate.

6. A control system for heating battery cell manufacturing equipment, characterized in that, include: The heating cell manufacturing equipment and control unit according to any one of claims 1-3, wherein the control unit comprises: The data acquisition module collects historical lamination training data of conductive composite fiber (104). The historical lamination training data is collected when the lamination processing of conductive composite fiber (104) meets the standards. The historical lamination training data includes the first historical training data and the second historical training data. The first historical training data includes the material composition of the conductive composite fiber (104), the heating coefficient of the conductive composite fiber (104), and the heating temperature; The second historical training data includes the material composition of the conductive composite fiber (104), the diameter of the conductive composite fiber (104), the heating temperature, and the lamination control parameters; The temperature prediction module trains a machine learning model to predict the heating temperature based on the first historical training data, collects the material composition and heating coefficient of the conductive composite fiber (104) to be laminated, and predicts the heating temperature based on the trained machine learning model. The parameter prediction module trains a lamination control parameter recommendation model based on the second historical training data, collects the material composition, diameter and heating temperature of the conductive composite fiber (104) to be processed, and inputs them into the trained lamination control parameter recommendation model to obtain the lamination control parameter recommendation set label, and then obtains the lamination control parameter recommendation set corresponding to the lamination control parameter recommendation set label, and controls the lamination tank (1) to work based on the lamination control parameters in the lamination control parameter recommendation set.

7. The control system of the heating cell manufacturing equipment according to claim 6, characterized in that, The parameters affecting the heating coefficient of the conductive composite fiber (104) include the melting point of the conductive material (106), the coefficient of thermal expansion of the fiber matrix material (105), and the diameter of the conductive composite fiber (104). The expression for the heating coefficient of the conductive composite fiber (104) is as follows: ； In the formula, The heating coefficient of the conductive composite fiber (104) is... The melting point of the conductive material (106) is... The coefficient of thermal expansion of the fiber matrix material (105) is given. The diameter of the conductive composite fiber (104) is [missing information]. 、 and As a weighting factor, 、 and All are greater than zero.

8. The control system of the heating cell manufacturing equipment according to claim 6, characterized in that, The method for training a machine learning model to predict heating temperature based on first historical training data includes: The first set of historical training data collected is converted into a corresponding set of feature vectors; Each set of feature vectors is used as input to the machine learning model. The machine learning model outputs the material composition of each set of collected conductive composite fibers (104) and the heating temperature corresponding to the heating coefficient of the conductive composite fibers (104). The material composition of each set of collected conductive composite fibers (104) and the actual heating temperature corresponding to the heating coefficient of the conductive composite fibers (104) are used as prediction targets. The training target is to minimize the loss function value of the machine learning model. Training stops when the loss function value of the machine learning model is less than or equal to the preset first target loss value.

9. The control system of the heating cell manufacturing equipment according to claim 6, characterized in that, The recommended set of lamination control parameters is as follows: , The collection label is The corresponding pressurization pressure at that time The collection label is The corresponding pressurization time; Methods for training a lamination control parameter recommendation model based on second historical training data include: Pre-assign corresponding numbers to the recommended set of lamination control parameters; The second historical training data is converted into a corresponding set of second feature vectors. Each set of second feature vectors is used as the input of the lamination control parameter recommendation model. The lamination control parameter recommendation model outputs a set of lamination control parameter recommendation labels corresponding to the material composition, diameter and heating temperature of the conductive composite fiber (104). The actual set of lamination control parameter recommendation labels corresponding to the material composition, diameter and heating temperature of each set of conductive composite fiber (104) is used as the prediction target. The training target is to minimize the loss function value of the lamination control parameter recommendation model. Training stops when the loss function value of the lamination control parameter recommendation model is less than or equal to the preset second target loss value.

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