WO2023109001A1

WO2023109001A1 - Heat recycling system and method for lithium battery rotary kiln, and medium

Info

Publication number: WO2023109001A1
Application number: PCT/CN2022/092509
Authority: WO
Inventors: 廖显潭; 欧文龙; 张军明; 李金瑞; 傅祥桂
Original assignee: 佛山市天禄智能装备科技有限公司
Priority date: 2021-12-17
Filing date: 2022-05-12
Publication date: 2023-06-22
Also published as: CN114440621A

Abstract

Embodiments of the present application are applicable to the field of lithium battery rotary kilns, and provide a heat recycling system and method for a lithium battery rotary kiln, and a medium. The system comprises: a first temperature measurement module arranged in a rotary kiln and used for measuring the real-time temperature in the kiln; a second temperature measurement module arranged in a heat recycling pipeline system and used for measuring the real-time temperature in the heat recycling pipeline; a main control module controlling the opening degree of each valve assembly in response to temperature data uploaded by the first temperature measurement module and the second temperature measurement module; and valve assemblies disposed in the heat recycling pipeline system and used for controlling the opening degree of the outlet of a heat recycling pipeline in response to a control command of the main control module; and an AI module used for storing the relationship model between the temperature in the kiln and a compensation temperature, wherein the compensation temperature refers to the temperature provided by the heat recycling pipeline to the rotary kiln. According to the present application, the temperature compensation of the heat recycling system can be precisely controlled, and thus the practicability of the heat recycling system is improved.

Description

A heat recovery cycle system, method and medium for a lithium battery rotary kiln

technical field

The application belongs to the field of lithium battery rotary kilns, and in particular relates to a heat recovery circulation system, method and medium of a lithium battery rotary kiln.

Background technique

Rotary kiln In many production industries such as building materials, metallurgy, chemical industry, environmental protection, etc., rotary cylinder equipment is widely used for mechanical, physical or chemical treatment of solid materials. This type of equipment is called rotary kiln. The application of the rotary kiln originated from cement production. In 1824, the British cement worker J Asp invented the earth shaft kiln with intermittent operation; Eransome) invented the rotary kiln, and put it into production after obtaining patents in Britain and the United States, and soon gained considerable economic benefits. The invention of the rotary kiln led to the rapid development of the cement industry, and at the same time promoted people's research on the application of the rotary kiln. Soon the rotary kiln was widely used in many industrial fields, and became more and more important in these productions, becoming the core of the production of corresponding enterprises. equipment.

During the preparation process of lithium batteries, it is necessary to use a rotary kiln to calcinate the positive and negative electrode materials of lithium batteries, as well as to recycle and calcinate waste lithium batteries. The rotary kiln will produce a large amount of heat loss during the working process, that is, the utilization rate of its heat energy is not high. In order to solve this problem, the rotary kiln is usually equipped with a heat recovery cycle system to realize the secondary utilization of heat energy, thereby improving the efficiency of heat energy. Utilization rate, reduce the consumption of heating energy such as coal. However, in the traditional heat recovery cycle system, a device with heat energy recovery is installed at the heat exhaust port or outside the kiln wall, and then the recovered heat energy is returned to the rotary kiln to achieve rough heat energy recovery. However, in practical applications, the rotary kiln itself works within the set temperature range, and there will only be two results when the heat recovered by heat is returned to the rotary kiln. One is that the recovered heat energy is not enough to affect the temperature in the kiln. The actual impact, the second is that the temperature in the kiln with sufficient heat fluctuates greatly, which affects the normal operation of the rotary kiln. It can be seen from this that no matter what kind of heat energy recovery is used, it is of little significance in practical applications, and sometimes even produces a reverse effect. Therefore, there is an urgent need for a reasonable heat recovery cycle system to solve this problem.

Contents of the invention

In view of this, the embodiment of the present application provides a heat recovery circulation system, method and medium of a lithium battery rotary kiln to solve the problem that the heat recovered by the traditional rotary kiln heat recovery circulation system cannot produce actual benefits.

The first aspect of the embodiments of the present application provides a heat recovery cycle system for a lithium battery rotary kiln, including:

The first temperature detection module arranged in the rotary kiln to detect the real-time temperature in the kiln;

A second temperature detection module arranged in the heat recovery pipeline system for detecting the real-time temperature in the heat recovery pipeline;

The main control module responds to the temperature data uploaded by the first temperature detection module and the second temperature detection module and controls the opening degree of the valve assembly;

A valve assembly, arranged in the heat recovery pipeline system, is used to control the outlet opening of the heat recovery pipeline in response to the control command of the main control module;

The AI module is used to store the relationship model between the temperature in the kiln and the compensation temperature, where the compensation temperature refers to the temperature provided by the heat recovery pipeline to the rotary kiln;

The relationship model between the temperature in the storage kiln and the compensation temperature is

Among them, T is the target temperature of the rotary kiln, T ₀ is the current temperature of the rotary kiln, t ₁ is the adjustment temperature of the rotary kiln, t ₂ is the ambient temperature outside the rotary kiln,

is the ambient temperature compensation coefficient outside the rotary kiln, k is the outlet opening of the heat recovery pipeline, λ is the temperature loss parameter of the rotary kiln, and δ is the temperature loss coefficient of the heat recovery pipeline.

In this application, in order to solve the problem that the heat energy recovered by the heat recovery cycle system mentioned above cannot produce actual benefits, this application is based on an actual model, according to the target temperature required by the rotary kiln, and the improvement that the heat recovery cycle system can improve Compensate the temperature and establish a compensation model so that the temperature in the rotary kiln can reach the temperature required for actual production without causing a huge change or large fluctuation in the temperature in the rotary kiln. At the same time, in order to further improve the recycling of recovered heat, this application It is also necessary to reasonably adjust the adjustment temperature of the rotary kiln so that the outlet opening of the heat recovery pipeline is kept at the maximum as much as possible to ensure that the recovered heat can basically be used for temperature compensation in the rotary kiln.

Further, the first temperature detection module is evenly arranged in the rotary kiln, so that it can accurately detect the real-time temperature of any area in the rotary kiln. Partition control can provide more accurate temperature control. In the calcination process of lithium batteries, temperature control is extremely important. Temperature control determines the performance of lithium battery materials. Therefore, the use of partition control strategies can further improve control accuracy.

Further, the second temperature detection module is arranged from the inlet of the heat recovery pipeline to the outlet of the heat recovery pipeline according to a fixed distance or a temperature distribution curve in the heat recovery pipeline. When the recovered heat circulates in the pipeline, it will be lost with time or the pipeline. For example, in a section of heat recovery pipeline, the heat such as the highest temperature at the inlet and outlet (recovery port), and the lowest temperature at the outlet, in the entire pipe There may be a linear or non-linear change in the pipeline (mainly depends on the ambient temperature and the temperature loss coefficient of the pipeline), in order to deal with this problem, this application uses a fixed distance or according to the heat distribution curve in the pipeline for the second temperature The detection module is installed to enhance the accuracy of temperature control.

Further, it also includes a third temperature module for detecting the ambient temperature outside the rotary kiln in real time. It can be seen from the above that the ambient temperature not only has a great influence on the heat in the heat recovery pipeline, but also has an impact on the temperature in the rotary kiln. Taking summer and winter as an example, the difference in ambient temperature has a great influence on the heat and heat in the rotary kiln. The temperature in the recovery pipeline has a great influence, so in order to improve the accuracy of temperature compensation, it is necessary to grasp the influence of the ambient temperature.

Further, based on the deep neural learning network, the AI module continuously adjusts the parameters in the relationship model according to the target temperature and the real-time temperature in the kiln detected by the first temperature detection module, that is, the adjustment temperature, turning The ambient temperature compensation coefficient outside the kiln, the outlet opening of the heat recovery pipeline, the temperature loss parameter of the λ rotary kiln, and δ is the temperature loss coefficient of the heat recovery pipeline.

On the other hand, in order to improve the control accuracy in this application, the relational model is corrected based on the deep neural learning network combined with real-time data, so that the control accuracy can be further improved.

Further, there are at least two valve assemblies, which are arranged at the head end and the end of the heat recovery pipeline.

Further, there are multiple valve assemblies, and the heat recovery pipeline is installed at fixed intervals or at fixed points according to the heat distribution curve in the heat recovery pipeline.

The second aspect of the embodiments of the present application provides a heat recovery cycle method for a lithium battery rotary kiln, which is executed based on the heat recovery cycle system for a lithium battery rotary kiln, which includes:

S101: Collect the temperature inside the rotary kiln, the ambient temperature outside the rotary kiln, and the temperature in the heat recovery pipeline in real time;

S102: Upload the collected temperature data to the main control module (300);

S103: The main control module is based on the relationship model as

Adjusting the compensation temperature of the heat recovery pipeline to the rotary kiln;

S104: the valve assembly performs opening adjustment;

S105: collect the real-time temperature in the kiln again, and judge whether it has reached the target temperature, if not, continue to adjust the opening of the valve assembly until the target temperature is reached;

S106: Correcting the values of various parameters in the relationship model according to the compensation heat difference adjusted twice by the valve assembly;

S107: Return the corrected parameters to the AI module to update the relationship model;

Further, the target temperature T of the rotary kiln can be set by means of system pre-examination or manual adjustment.

A third aspect of the embodiments of the present application provides a medium, the medium stores a computer program, and when the computer program product is run on a terminal device, the system device executes the function described in any one of the above first aspects.

Compared with the prior art, the embodiment of the present application has the following beneficial effects: the present application is based on the deep neural learning network, combined with the relationship module of the established rotary kiln temperature compensation, and continuously optimizes the model, thereby improving the heat recovery cycle system of the rotary kiln. The effective utilization of medium heat reduces the temperature fluctuation caused by the recovered heat to the rotary kiln, and avoids the use of recovered heat to make the rotary kiln work at an abnormal temperature, thereby achieving both the purpose of recovering heat and the effective use of recovered heat The effect is to improve the utilization rate of energy, and it has the technological progress of environmental protection and high efficiency.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the accompanying drawings that need to be used in the descriptions of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings in the following description are only for the present application For some embodiments, those of ordinary skill in the art can also obtain other drawings based on these drawings without paying creative efforts.

Fig. 1 is a schematic structural diagram of a heat recovery circulation system of a lithium battery rotary kiln provided in an embodiment of the present application;

Fig. 2 is a schematic flow chart of a heat recovery cycle method for a lithium battery rotary kiln provided in an embodiment of the present application;

FIG. 3 is a schematic structural diagram of a terminal device provided by an embodiment of the present application.

Detailed ways

In the following description, specific details such as specific system structures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.

In order to illustrate the technical solutions described in this application, specific examples are used below to illustrate.

Referring to Figure 1, it is a schematic structural diagram of the heat recovery cycle system of the lithium battery rotary kiln provided in the embodiment of the present application, including:

A first temperature detection module 100 arranged in the rotary kiln 10 for detecting the real-time temperature in the kiln;

A second temperature detection module 200 arranged in the heat recovery pipeline system 11 for detecting the real-time temperature in the heat recovery pipeline;

The main control module 300 responds to the temperature data uploaded by the first temperature detection module 100 and the second temperature detection module 200 and controls the opening of the valve assembly;

The valve assembly 400 is arranged in the heat recovery pipeline system 11 and is used to control the opening degree of the outlet of the heat recovery pipeline in response to the control command of the main control module 300;

The AI module 500 is used to store the relationship model between the temperature in the kiln and the compensation temperature, wherein the compensation temperature refers to the temperature provided by the heat recovery pipeline to the rotary kiln 10;

Wherein, T is the target temperature of the rotary kiln 10, T ₀ is the current temperature of the rotary kiln 10, t ₁ is the adjustment temperature of the rotary kiln 10, and t ₂ is the ambient temperature outside the rotary kiln 10,

is the ambient temperature compensation coefficient outside the rotary kiln 10, k is the outlet opening of the heat recovery pipeline, λ is the temperature loss parameter of the rotary kiln 10, and δ is the temperature loss coefficient of the heat recovery pipeline.

The rotary kiln 10 in this embodiment can be understood as a rotary kiln 10 dedicated to lithium batteries, or other general-purpose rotary kilns 10 are also applicable to the technical solution provided in this embodiment. That is to say, the traditional rotary kiln equipment can also be the object of the problem solved in this application. The rotary kiln equipment refers to the rotary calcining kiln (commonly known as rotary kiln), which belongs to the building material equipment category. Rotary kiln equipment can be divided into cement kiln, metallurgical chemical kiln and lime kiln according to different processing materials. Rotary kiln equipment can be divided into cement kiln, metallurgical chemical kiln and lime kiln according to different processing materials. Cement kilns are mainly used for calcining cement clinker, which can be divided into two categories: dry production cement kiln and wet production cement kiln. Metallurgical and chemical kilns are mainly used for magnetization roasting of lean iron ore in iron and steel plants in the metallurgical industry; oxidative roasting of chromium and nickel-iron ore; roasting of high-alumina bauxite in refractory plants and clinker and aluminum hydroxide in aluminum plants; roasting of chromium ore in chemical plants And minerals such as chromium ore powder. Lime kiln (i.e. active lime kiln) is used for roasting active lime and lightly burned dolomite used in iron and steel plants and ferroalloy plants.

It is worth noting that the structural components of the rotary kiln equipment in this embodiment generally include:

Kiln body: The kiln body of a zinc oxide rotary kiln is generally welded (or riveted) into a cylinder by 20 mm thick steel plates.

Rolling ring: The rolling ring is not directly set on the kiln body, but is installed on the kiln body through the base plate. Its function is to strengthen the zinc oxide rotary kiln body, and at the same time, it can transfer the weight of the cylinder body to the supporting rollers. The zinc oxide rotary kiln used in the production of refractory materials generally has 5 to 8 rolling rings.

Supporting wheel and supporting wheel shaft: The supporting wheel is installed on the supporting wheel shaft by hot-fitting method, and the supporting wheel shaft is installed in two bearings with bronze bearing bushes. The temperature of the water coming out of the bearings after longitudinal cooling with water should not exceed 25 degrees.

Stopper wheel: The stopper wheel is a limiting device that limits the position of the zinc oxide rotary kiln body on the supporting wheel, but it cannot stop the up and down movement of the nest body.

Transmission device: Zinc oxide rotary kiln generally uses gears to drive the rotation.

Any equipment that meets the above composition can be regarded as the rotary kiln equipment applicable to this application.

Optionally, in some embodiments, the first temperature detection module 100 is evenly arranged in the rotary kiln 10 so that it can accurately detect the real-time temperature of any area in the rotary kiln 10 .

Optionally, in some embodiments, the second temperature detection modules 200 are arranged at fixed intervals from the heat recovery pipeline inlet to the heat recovery pipeline outlet according to a temperature distribution curve in the heat recovery pipeline.

Optionally, in some embodiments, a third temperature module 600 for detecting the ambient temperature outside the rotary kiln 10 in real time is also included.

The first temperature detection module 100, the second temperature detection module 200, and the third temperature module 600 mentioned in this embodiment are essentially the same, and are sensors for detecting temperature. In order to increase the detection temperature, especially in the kiln and A temperature sensor with high temperature resistance is required in the pipeline. Therefore, a non-contact temperature sensor is generally used, and its sensitive element is not in contact with the measured object, also known as a non-contact temperature measuring instrument. This instrument can be used to measure the surface temperature of moving objects, small targets and objects with small heat capacity or rapid temperature changes (transient), and can also be used to measure the temperature distribution of the temperature field. The most commonly used non-contact thermometers are based on the fundamental law of black body radiation and are called radiation thermometers. Radiation thermometry includes brightness method (see optical pyrometer), radiation method (see radiation pyrometer) and colorimetric method (see colorimetric thermometer). All kinds of radiation temperature measurement methods can only measure the corresponding photometric temperature, radiation temperature or colorimetric temperature. Only the temperature measured for a black body (an object that absorbs all radiation and does not reflect light) is the true temperature. If you want to measure the real temperature of the object, you must correct the surface emissivity of the material. However, the surface emissivity of materials depends not only on temperature and wavelength, but also on surface state, coating film and microstructure, so it is difficult to measure accurately. In automatic production, it is often necessary to use radiation thermometry to measure or control the surface temperature of certain objects, such as the steel strip rolling temperature, roll temperature, forging temperature in metallurgy, and the temperature of various molten metals in smelting furnaces or crucibles . In these specific cases, the measurement of the emissivity of an object's surface is quite difficult. For automatic measurement and control of solid surface temperature, an additional reflector can be used to form a black body cavity together with the measured surface. The effect of additional radiation can increase the effective radiation and effective emissivity of the measured surface. Use the effective emissivity coefficient to correct the measured temperature through the instrument, and finally get the real temperature of the measured surface. The most typical additional mirror is a hemispherical mirror. The diffuse radiation of the measured surface near the center of the sphere can be reflected back to the surface by the hemispherical mirror to form additional radiation, thereby increasing the effective emissivity coefficient. In the formula, ε is the surface emissivity of the material, and ρ is the reflectivity of the mirror. As for the radiation measurement of the real temperature of the gas and liquid medium, the method of inserting the heat-resistant material tube to a certain depth to form a black body cavity can be used. The effective emission coefficient of the cylinder cavity after reaching thermal equilibrium with the medium is obtained by calculation. In automatic measurement and control, this value can be used to correct the measured cavity bottom temperature (ie medium temperature) to obtain the true temperature of the medium.

Optionally, in some embodiments, based on the deep neural learning network, the AI module 500 continuously adjusts the parameters in the relational model according to the target temperature and the real-time temperature in the kiln detected by the first temperature detection module 100, that is, the adjustment temperature of The ambient temperature compensation coefficient outside the rotary kiln 10, the outlet opening of the heat recovery pipeline, λ is the temperature loss parameter of the rotary kiln 10, and δ is the temperature loss coefficient of the heat recovery pipeline.

The deep neural learning network in this embodiment adopts a convolutional neural network model or a deep trust network model. Before the advent of unsupervised pre-training, training deep neural networks was often very difficult, and a special case of this was convolutional neural networks. Convolutional neural networks are inspired by the structure of the visual system. The first convolutional neural network computing model is based on local connections between neurons and hierarchically organized image transformations. Neurons with the same parameters are applied to different positions of the previous layer of neural network to obtain a translation-invariant neural network. Network structure form. The deep trust network model, DBN can be interpreted as a Bayesian probability generation model, consisting of multiple layers of random hidden variables, the upper two layers have undirected symmetric connections, and the lower layer gets top-down directed from the upper layer Connected, the state of the bottommost unit is the visible input data vector. DBN is composed of a stack of 2F structural units, and the structural unit is usually RBM (RestIlcted Boltzmann Machine, Restricted Boltzmann Machine). The number of neurons in the visible layer of each RBM unit in the stack is equal to the number of neurons in the hidden layer of the previous RBM unit. According to the deep learning mechanism, the input samples are used to train the first layer of RBM unit, and its output is used to train the second layer of RBM model, and the RBM model is stacked to improve the model performance by adding layers. In the unsupervised pre-training process, after the DBN code is input to the top-layer RBM, the state of the top layer is decoded to the bottom unit to realize the reconstruction of the input. As the structural unit of DBN, RBM shares parameters with each layer of DBN.

Optionally, in some embodiments, there are at least two valve assemblies 400, which are arranged at the head end and the end of the heat recovery pipeline.

Optionally, in some embodiments, there are multiple valve assemblies 400, and the heat recovery pipeline is installed at fixed intervals or at fixed points along the heat distribution curve in the heat recovery pipeline.

Referring to Figure 2, the embodiment of the present application provides a schematic flow chart of a heat recovery cycle method for a lithium battery rotary kiln, which is implemented based on a heat recovery cycle system for a lithium battery rotary kiln, which includes:

S101: Collect the temperature inside the rotary kiln 10, the ambient temperature outside the rotary kiln 10, and the temperature in the heat recovery pipeline in real time;

S102: Upload the collected temperature data to the main control module (300);

S103: The main control module 300 is based on the relationship model as

Adjust the compensation temperature of the heat recovery pipeline to the rotary kiln 10;

S104: the valve assembly 400 performs opening adjustment;

S105: collect the real-time temperature in the kiln again, and judge whether it has reached the target temperature, and if it does not reach the target temperature, continue to adjust the opening of the valve assembly 400 until the target temperature is reached;

S106: Correcting the values of various parameters in the relationship model according to the compensation heat difference adjusted twice by the valve assembly 400;

S107: Return the corrected parameters to the AI module 500 to update the relationship model;

Optionally, in some embodiments, the target temperature T of the rotary kiln 10 can be set by means of system preview or manual adjustment.

An embodiment of the present application provides a medium. The medium is preferably a computer-readable storage medium. The computer-readable storage medium stores a computer program. When the computer program product runs on the terminal device, the system device executes the above-mentioned first aspect. A heat recovery cycle method for any one of the lithium battery rotary kilns. When the computer program is executed by the main control module 300 , various steps of the above-mentioned heat recovery cycle method of the lithium battery rotary kiln are realized.

FIG. 3 is a schematic structural diagram of a terminal device provided by an embodiment of the present application. As shown in FIG. 3 , the terminal device in this embodiment includes: a processor 60 , a memory 61 , and a computer program 62 stored in the memory 61 and operable on the processor 60 . When the processor 60 executes the computer program 62 , the steps in the embodiments of the heat recovery cycle method for the lithium battery rotary kiln mentioned above are realized, such as steps S101 to S107 shown in FIG. 2 . Alternatively, when the processor 60 executes the computer program 62, the functions of the modules/units in the above-mentioned device embodiments are realized.

Exemplarily, the computer program 62 can be divided into one or more modules/units, and the one or more modules/units are stored in the memory 61 and executed by the processor 60 to complete this application. The one or more modules/units may be a series of computer program instruction segments capable of accomplishing specific functions, and the instruction segments are used to describe the execution process of the computer program 62 in the terminal device.

The terminal device may be a computing device such as a desktop computer, a notebook, or a palmtop computer. The terminal device may include, but not limited to, a processor 60 and a memory 61 . Those skilled in the art can understand that FIG. 3 is only an example of a terminal device, and does not constitute a limitation to the terminal device. It may include more or less components than those shown in the figure, or combine certain components, or different components, such as The terminal device may also include an input and output device, a network access device, a bus, and the like.

The so-called processor 60 can be a central processing unit (Central Processing Unit, CPU), and can also be other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), Off-the-shelf programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor, or the processor may be any conventional processor, or the like.

The storage 61 may be an internal storage unit of the terminal device, such as a hard disk or memory of the terminal device. The memory 61 can also be an external storage device of the terminal device, such as a plug-in hard disk equipped on the terminal device, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, Flash card (Flash Card), etc. Further, the memory 61 may also include both an internal storage unit of the terminal device and an external storage device. The memory 61 is used to store the computer program and other programs and data required by the terminal device. The memory 61 can also be used to temporarily store data that has been output or will be output.

Those skilled in the art can clearly understand that for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used for illustration. In practical applications, the above-mentioned functions can be assigned to different functional units, Completion of modules means that the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment may be integrated into one processing unit, or each unit may exist separately physically, or two or more units may be integrated into one unit, and the above-mentioned integrated units may adopt hardware It can also be implemented in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the protection scope of the present application. For the specific working processes of the units and modules in the above system, reference may be made to the corresponding processes in the aforementioned method embodiments, and details will not be repeated here.

In the above-mentioned embodiments, the descriptions of each embodiment have their own emphases, and for parts that are not detailed or recorded in a certain embodiment, refer to the relevant descriptions of other embodiments.

Those skilled in the art can appreciate that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed by hardware or software depends on the specific application and design constraints of the technical solution. Skilled artisans may use different methods to implement the described functions for each specific application, but such implementation should not be regarded as exceeding the scope of the present application.

In the embodiments provided in this application, it should be understood that the disclosed terminal device and method may be implemented in other ways. For example, the terminal device embodiments described above are only illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components May be combined or may be integrated into another system, or some features may be omitted, or not implemented. In another point, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be in electrical, mechanical or other forms.

The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, each unit may exist separately physically, or two or more units may be integrated into one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

If the integrated module/unit is realized in the form of a software function unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments in the present application can also be completed by instructing related hardware through computer programs. The computer programs can be stored in a computer-readable storage medium, and the computer When the program is executed by the processor, the steps in the above-mentioned various method embodiments can be realized. Wherein, the computer program includes computer program code, and the computer program code may be in the form of source code, object code, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a removable hard disk, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM, Read-Only Memory) , Random Access Memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer-readable medium may be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, computer-readable media Excludes electrical carrier signals and telecommunication signals.

The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: it can still implement the foregoing embodiments Modifications to the technical solutions described in the examples, or equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the application, and should be included in the Within the protection scope of this application.

Claims

A heat recovery cycle system for a lithium battery rotary kiln, characterized in that it includes:

The first temperature detection module arranged in the rotary kiln to detect the real-time temperature in the kiln;

A second temperature detection module arranged in the heat recovery pipeline system for detecting the real-time temperature in the heat recovery pipeline;

The main control module responds to the temperature data uploaded by the first temperature detection module and the second temperature detection module and controls the opening degree of the valve assembly;

A valve assembly, arranged in the heat recovery pipeline system, is used to control the outlet opening of the heat recovery pipeline in response to the control command of the main control module;

The AI module is used to store the relationship model between the temperature in the kiln and the compensation temperature, where the compensation temperature refers to the temperature provided by the heat recovery pipeline to the rotary kiln;

The relationship model between the temperature in the storage kiln and the compensation temperature is

Among them, T is the target temperature of the rotary kiln, T 0 is the current temperature of the rotary kiln, t 1 is the adjustment temperature of the rotary kiln, t 2 is the ambient temperature outside the rotary kiln,
is the ambient temperature compensation coefficient outside the rotary kiln, k is the outlet opening of the heat recovery pipeline, λ is the temperature loss parameter of the rotary kiln, and δ is the temperature loss coefficient of the heat recovery pipeline.
The heat recovery cycle system of a lithium battery rotary kiln according to claim 1, wherein the first temperature detection module is evenly arranged in the rotary kiln so that it can accurately detect the temperature of any area in the rotary kiln. real-time temperature.
The heat recovery cycle system of a lithium battery rotary kiln according to claim 1 or 2, characterized in that: the second temperature detection module is arranged at a fixed distance or heat recovery from the heat recovery pipeline inlet to the heat recovery pipeline outlet The temperature distribution curve in the pipeline is arranged.
The heat recovery cycle system of a lithium battery rotary kiln according to claim 1, further comprising a third temperature module for real-time detection of the ambient temperature outside the rotary kiln.
The heat recovery cycle system of a lithium battery rotary kiln according to claim 1, wherein the AI module is based on a deep neural learning network, and according to the target temperature and the real-time The temperature continuously adjusts the parameters in the relationship model, that is, the adjustment temperature, the ambient temperature compensation coefficient outside the rotary kiln, the outlet opening of the heat recovery pipeline, the temperature loss parameter of the λ rotary kiln, and δ is the heat recovery pipeline temperature loss coefficient.
The heat recovery circulation system of a lithium battery rotary kiln according to claim 1, wherein there are at least two valve assemblies, which are arranged at the head end and the end of the heat recovery pipeline.
The heat recovery cycle system of a lithium battery rotary kiln according to claim 6, characterized in that: there are multiple valve assemblies, and the heat recovery pipeline is fixed at a fixed distance or according to the heat distribution curve in the heat recovery pipeline Fixed-point installation.
A heat recovery cycle method for a lithium battery rotary kiln, characterized in that the method is performed based on a heat recovery cycle system for a lithium battery rotary kiln according to any one of claims 1-7, comprising:

S101: Collect the temperature inside the rotary kiln, the ambient temperature outside the rotary kiln, and the temperature in the heat recovery pipeline in real time;

S102: Upload the collected temperature data to the main control module;

S103: The main control module is based on the relationship model as
Adjusting the compensation temperature of the heat recovery pipeline to the rotary kiln;

S104: the valve assembly performs opening adjustment;

S105: collect the real-time temperature in the kiln again, and judge whether it has reached the target temperature, if not, continue to adjust the opening of the valve assembly until the target temperature is reached;

S106: Correcting the values of various parameters in the relationship model according to the compensation heat difference adjusted twice by the valve assembly;

S107: Return the corrected parameters to the AI module to update the relationship model;

Among them, T is the target temperature of the rotary kiln, T 0 is the current temperature of the rotary kiln, t 1 is the adjustment temperature of the rotary kiln, t 2 is the ambient temperature outside the rotary kiln,
is the ambient temperature compensation coefficient outside the rotary kiln, k is the outlet opening of the heat recovery pipeline, λ is the temperature loss parameter of the rotary kiln, and δ is the temperature loss coefficient of the heat recovery pipeline.
The heat recovery cycle method of a lithium battery rotary kiln according to claim 8, wherein the target temperature T of the rotary kiln can be set by means of system pre-examination or manual adjustment.
A medium, the medium is stored with a computer program, characterized in that, when the computer program is executed by the main control module, each step of the heat recovery cycle method of the lithium battery rotary kiln according to any one of claims 8 or 9 is realized .