Intelligent temperature control system, method, equipment, medium and product

Abstract

The invention discloses an intelligent temperature control system, method and device, a medium and a product, and relates to the field of temperature regulation and control, the system comprises a central processing unit, a temperature acquisition unit and an electric energy control unit; the central processing unit is respectively connected with the temperature acquisition unit and the electric energy control unit; the electric energy control unit is respectively connected with the m * n heating units; the temperature acquisition unit is respectively connected with the m temperature sensors; the m temperature sensors are respectively arranged in the m heating areas; one heating area comprises n heating units; the temperature acquisition unit acquires the current temperature of the heating area; the central processing unit determines the control quantity of the next time step according to the current temperature of the heating area and sends the control quantity to the electric energy control unit; the electric energy control unit controls on-off of the heating unit according to the control quantity so as to adjust the temperature of the corresponding heating area. Accurate control over the temperature of the heating area is achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of temperature regulation, and in particular to an intelligent temperature control system, method, device, medium and product. BACKGROUND

[0002] The existing intelligent temperature control module needs the user to manually switch the heating position of the heating device. This feature will bring difficulties to the operation of people who are inconvenient to operate, such as in motion, or people who are inconvenient to move, and even bring the risk of excessive heating.

[0003] The existing intelligent temperature control module cannot regulate energy according to the current temperature. This feature will cause the heating device to be in higher energy consumption, causing unnecessary energy waste. In the use of mobile power banks such as energy supply scenes, it will shorten the support time of the power bank.

[0004] The existing intelligent temperature control module cannot implement fine heating strategies according to the user's use demand. In different scenes, the heating demand of the heating device is different, for example, the state of motion and outdoor post is significantly different, and the demand of warm and cool people is also different. The current technical solution is difficult to accurately regulate the above demand. SUMMARY

[0005] The purpose of the present application is to provide an intelligent temperature control system, method, device, medium and product to improve the accurate regulation of the temperature of the electric heating clothing.

[0006] To achieve the above purpose, the present application provides the following solutions:

[0007] In a first aspect, the present application provides an intelligent temperature control system, comprising: a central processing unit, a temperature acquisition unit and an electric energy control unit; the central processing unit is connected with the temperature acquisition unit and the electric energy control unit respectively; the electric energy control unit is connected with m*n heating units respectively; the temperature acquisition unit is connected with m temperature sensors respectively; m temperature sensors are arranged in m heating areas respectively; one heating area includes n heating units;

[0008] The temperature acquisition unit is used to acquire the current temperature of the heating area;

[0009] The central processing unit is used to determine the control amount of the next time step according to the current temperature of the heating area, and send the control amount to the electric energy control unit;

[0010] The electric energy control unit is used to control the switch of the heating unit according to the control amount, so as to adjust the temperature of the corresponding heating area.

[0011] Optionally, further comprising: a filtering unit; the temperature acquisition unit is connected with the central processing unit through the filtering unit.

[0012] The filtering unit is configured to filter the current temperature of the heating area to obtain a processed current temperature of the heating area.

[0013] Optionally, the central processing unit comprises:

[0014] a feedback correction module configured to determine a temperature deviation according to the current temperature of the heating area and a current target temperature of the heating area;

[0015] a parameter optimization module configured to optimize model parameters of a prediction model at a previous time step according to the temperature deviation by using a least square method or a gradient descent method to obtain model parameters at a current time step;

[0016] a control quantity prediction module configured to determine a control quantity at a next time step by using the prediction model according to the current temperature of the heating area, the model parameters at the current time step and a historical control quantity.

[0017] Optionally, further comprising: a Bluetooth unit; the Bluetooth unit is connected with the central processing unit;

[0018] The Bluetooth unit is configured to communicate with a master control platform, receive an instruction transmitted by a user through the master control platform, and send a state of the intelligent temperature control system to the master control platform; the state comprises a set temperature, a current actual temperature, a working mode and a working time length.

[0019] Optionally, the master control platform is a computer or a mobile phone.

[0020] Optionally, further comprising: a key and display unit; the key and display unit comprises a plurality of keys and a display screen; the keys and the display screen are connected with the central processing unit; the plurality of keys comprise a start key, a stop key, a temperature adjustment key and a mode switching key.

[0021] The display screen is configured to display a state of the intelligent temperature control system; the state comprises a set temperature, a current actual temperature, a working mode and a working time length.

[0022] In a second aspect, the present application provides an intelligent temperature control method, which is applied to the intelligent temperature control system and comprises:

[0023] acquiring a current temperature of a heating area;

[0024] determining a temperature deviation according to the current temperature of the heating area and a current target temperature of the heating area;

[0025] According to the temperature deviation, the model parameters of the prediction model of the previous time step are optimized by using a least square method or a gradient descent method to obtain the model parameters of the current time step;

[0026] According to the current temperature of the heating area, the model parameters of the current time step, and the historical control quantity, a prediction model is used to determine the control quantity of the next time step;

[0027] According to the control quantity, the switch of the heating unit is controlled to adjust the temperature of the corresponding heating area.

[0028] In a third aspect, the present application provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor executes the computer program to implement the intelligent temperature control method according to any one of the above.

[0029] In a fourth aspect, the present application provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the intelligent temperature control method according to any one of the above.

[0030] In a fifth aspect, the present application provides a computer program product, comprising a computer program, and the computer program is executed by a processor to implement the intelligent temperature control method according to any one of the above.

[0031] According to the embodiments provided in the present application, the present application has the following technical effects:

[0032] The present application provides an intelligent temperature control system, method, device, medium and product. The intelligent temperature control system comprises a central processing unit, a temperature acquisition unit and an electric energy control unit. The central processing unit is connected with the temperature acquisition unit and the electric energy control unit respectively. The electric energy control unit is connected with m*n heating units respectively. The temperature acquisition unit is connected with m temperature sensors respectively. The m temperature sensors are arranged in m heating areas respectively. One heating area comprises n heating units. The temperature acquisition unit acquires the current temperature of the heating area. The central processing unit determines the control quantity of the next time step according to the current temperature of the heating area, and sends the control quantity to the electric energy control unit. The electric energy control unit controls the switch of the heating unit according to the control quantity to adjust the temperature of the corresponding heating area. The present application acquires the temperature of the temperature sensor, calculates the temperature state of the current heating area, determines the control quantity of each heating area, and controls the electric energy of the heating unit to realize the accurate control of the temperature of the heating area. BRIEF DESCRIPTION OF DRAWINGS

[0033] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed in the embodiments. Obviously, the drawings described below only constitute some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained from these drawings without creative labor.

[0034] Figure 1 A structural schematic diagram of an intelligent temperature control system according to an embodiment of the present application is provided.

[0035] Figure 2 A working principle diagram of a central processing unit according to an embodiment of the present application is provided.

[0036] Figure 3 A structural schematic diagram of a computer device according to an embodiment of the present application is provided. DETAILED DESCRIPTION

[0037] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments only constitute some embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0038] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application will be further described in detail below with reference to the drawings and specific embodiments.

[0039] In one exemplary embodiment, as shown in Figure 1 , an intelligent temperature control system (i.e., an intelligent temperature control module in Figure 1 ) is provided, comprising: a central processing unit, a temperature acquisition unit and an electric energy control unit; the central processing unit is connected with the temperature acquisition unit and the electric energy control unit respectively; the electric energy control unit is connected with m*n heating units respectively; the temperature acquisition unit is connected with m temperature sensors respectively; the m temperature sensors are arranged in m heating areas respectively; one heating area comprises n heating units.

[0040] In the present embodiment, the intelligent temperature control system of the present application is described by taking an electric heating garment as an example.

[0041] The temperature acquisition unit is used to acquire the current temperature of the heating area. In the present embodiment, the temperature sensors connected with the temperature acquisition unit acquire the temperatures of different areas in the electric heating garment of the wearer, and send the temperatures to the central processing unit.

[0042] The central processing unit is configured to determine a control amount for a next time step according to the current temperature of the heating area, and send the control amount to the electric energy control unit.

[0043] The central processing unit calculates a control amount (amount of current or voltage) that should be given according to the collected temperature, and sends a control instruction (control amount) to the electric energy control unit. The working principle of the central processing unit is as shown in Figure 2 .

[0044] The central processing unit sets up a model predictive control algorithm, which accepts a temperature setting and a mode setting of a user, and generates a heating control amount according to a setting of a control parameter and temperature sampling information fed back by the filtering unit.

[0045] The model predictive control algorithm includes four parts of a prediction model, a rolling optimization module, a feedback correction module, and a parameter optimization module, so as to realize faster, better, more comfortable, and more economical temperature control effect.

[0046] The control amount generation unit is responsible for converting the control amount generated by the model predictive control algorithm into a PWM signal, so as to drive the heating unit to achieve a corresponding temperature target. Meanwhile, in order to ensure the safety of the heating unit in an extreme case, an error-proof safety lock is arranged on the PWM signal path, so as to improve the safety of the overall control system. The temperature collection part is realized by using a temperature sensor.

[0047] As an optional implementation, the central processing unit includes:

[0048] The feedback correction module is configured to determine a temperature deviation according to the current temperature of the heating area and a current target temperature of the heating area (i.e. a temperature prediction value obtained at a previous time step).

[0049] Considering the characteristics of the controlled object (electric heating clothes), the measured temperature T meas (k) needs to be collected and filtered.

[0050] First, the prediction deviation (temperature deviation) is calculated: e(k) = T meas (k) - T'(k|k-1); where T'(k|k-1) is a temperature prediction value of the system at the k time step at the (k-1) time step.

[0051] Then, a Kalman filtering / proportional correction model correction prediction sequence is adopted:

[0052] T'(k+i|k) = T'(k+i|k-1) + K i ·e(k), (i = 1, 2,..., N).

[0053] Wherein, T'(k+i|k) is the temperature prediction value of the (k+i)th time step when the system is at the kth time step; T'(k+i|k-1) is the temperature prediction value of the (k+i)th time step when the system is at the (k-1)th time step; K i is the prediction coefficient of the subsequent i time steps.

[0054] A parameter optimization module is configured to optimize the model parameters of the prediction model of the previous time step by using a least square method or a gradient descent method according to the temperature deviation, so as to obtain the model parameters of the current time step.

[0055] The prediction model is: T(k+1) = a x T(k) + b x u(k-d) + w(k) + J, wherein a and b are system gains, are the model parameters of the prediction model; d is a lag step number; w(k) is a disturbance of the current time step. The current temperature T(k) of the heating area, the historical control amount u(k-d), the rolling optimization model J, the future N-step temperature (N is a prediction time domain), and the basis for optimization are used for prediction.

[0056] In consideration of the performance balance between the temperature tracking accuracy and the control amount smoothness, the following rolling optimization model is adopted:

[0057]

[0058] Wherein: λ i is a temperature tracking weight; T r (k+i) is an actual temperature of the (k+i)th time step; T'(k+i) is a predicted temperature of the (k+i)th time step; μ j is a control increment weight; u(k+j) is an actual control amount of the (k+i)th time step; u(k+j-1) is an actual control amount of the (k+i-1)th time step; M: control time domain width.

[0059] When the prediction deviation e(k) is continuously large, the parameter updating is started. The least square method or the gradient descent method is used to optimize the model parameters θ, so as to realize the online adjustment of the system gains a and b:

[0060]

[0061] Wherein, θ old is the system gain a or b updated at the previous time step; θ new is the system gain a or b updated at the current time step; γ is an optimization acceleration coefficient; θ is the system gain a or b to be optimized.

[0062] A control amount prediction module is configured to determine a control amount of a next time step by using a prediction model according to the current temperature of the heating area, the model parameters of the current time step, and the historical control amount.

[0063] The electric energy control unit is configured to control a switch of the heating unit according to the control quantity to adjust the temperature of the heating area.

[0064] In this embodiment, the electric energy control unit adjusts the temperature of the heating area by controlling the power switch of the heating unit. The temperature of the different heating areas is adjusted by switching control of the temperature strategy and state of the different heating areas.

[0065] As an optional implementation, the system further comprises a filter unit, and the temperature acquisition unit is connected to the central processing unit through the filter unit.

[0066] The filter unit is configured to perform filtering processing on the current temperature of the heating area to obtain a processed current temperature of the heating area.

[0067] As an optional implementation, the system further comprises a Bluetooth unit, and the Bluetooth unit is connected to the central processing unit.

[0068] The Bluetooth unit is configured to communicate with a master control platform, receive an instruction transmitted by a user through the master control platform, and send a state of the intelligent temperature control system to the master control platform. The state includes a set temperature, a current actual temperature, a working mode, and a working time length. The master control platform is a computer or a mobile phone.

[0069] In this embodiment, the Bluetooth unit is configured to communicate with a master control platform such as a computer or a mobile phone, receive an instruction transmitted by a user through the master control platform, and send a state of the intelligent temperature control system to the master control platform.

[0070] As an optional implementation, the system further comprises a key and display unit, and the key and display unit comprises a plurality of keys and a display screen. The keys and the display screen are connected to the central processing unit. The plurality of keys include a start key, a stop key, a temperature adjustment key, and a mode switching key.

[0071] The display screen is configured to display a state of the intelligent temperature control system. The state includes a set temperature, a current actual temperature, a working mode, and a working time length.

[0072] In this embodiment, the keys are configured to receive a key input operation of a user, including starting, stopping, temperature adjustment, mode switching, and the like. The display screen is configured to display a state of the intelligent temperature control system.

[0073] The application collects temperature of temperature sensor, calculates current wearer's body temperature state, and controls electric energy of heating unit, so as to achieve temperature comfort, energy saving and environmental protection. The intelligent temperature control system has Bluetooth function, and a user can set temperature of the intelligent temperature control system by using a mobile phone, a computer and the like. The setting can be setting of temperature control mode, such as strong heating, normal comfort, exercise warming and the like, or can be direct setting of temperature. The intelligent temperature control system controls switching of the heating unit according to the user setting, so as to realize the temperature accurate control target.

[0074] The difference between this method and the existing method is that:

[0075] The temperature sensor has a signal collection function, and the temperature sensor includes a thermistor, a temperature chip and the like, and can be multi-channel collection.

[0076] The central processing function processes the user setting and the signal collected by the temperature sensor, calculates a control amount, and applies a switching control amount to the heating unit to accurately control the temperature.

[0077] The Bluetooth communication function receives the user's temperature setting and gives the user feedback on the current wearing condition including temperature.

[0078] Based on the same inventive concept, the embodiments of the application also provide an intelligent temperature control method applied to the intelligent temperature control system.

[0079] In an exemplary embodiment, the intelligent temperature control method includes:

[0080] Collecting current temperature of the heating area.

[0081] According to the current temperature of the heating area and the current target temperature of the heating area, determining a temperature deviation.

[0082] According to the temperature deviation, using a least square method or a gradient descent method to optimize model parameters of a prediction model of a previous time step, to obtain model parameters of a current time step.

[0083] According to the current temperature of the heating area, the model parameters of the current time step and a historical control amount, using a prediction model, determining a control amount of a next time step.

[0084] According to the control amount, controlling switching of the heating unit to adjust temperature of the corresponding heating area.

[0085] In an exemplary embodiment, a computer device is provided, comprising a memory and a processor, the memory storing a computer program, and the processor implementing the intelligent temperature control method when executing the computer program.

[0086] In an exemplary embodiment, a computer readable storage medium is provided, storing a computer program, and the computer program implementing the intelligent temperature control method when executed by a processor.

[0087] In an exemplary embodiment, a computer program product is provided, comprising a computer program, and the computer program implementing the intelligent temperature control method when executed by a processor.

[0088] In an exemplary embodiment, a computer device is provided, which can be a server or a terminal, and its internal structure diagram can be as shown in Figure 3 The computer device comprises a processor, a memory, an input / output interface (I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device comprises a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operating system and the computer program in the non-volatile storage medium to run. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals through network connection. The computer program is executed by the processor to implement an intelligent temperature control method.

[0089] Those skilled in the art can understand that, Figure 3 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0090] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or authorized by all parties, and the collection, use and processing of related data need to comply with relevant regulations.

[0091] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the processes of the above-mentioned embodiments of the methods can be included. Any reference to memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical storage, high-density embedded non-volatile memory, resistive memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration but not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0092] The database involved in the embodiments provided in the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a blockchain, etc., without being limited thereto. The processor involved in the embodiments provided in the present application can be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., without being limited thereto.

[0093] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, all possible combinations of the technical features in the above embodiments are not described, however, as long as the combinations of the technical features do not exist contradictory, they should be considered as the scope of the present application.

[0094] The principles and implementation modes of the present application are described by applying specific examples in the present application. The above-mentioned embodiments are only used to help understand the method and its core idea of the present application; at the same time, for those skilled in the art, according to the idea of the present application, the specific implementation mode and application range will be changed. In conclusion, the content of the present application should not be understood as a limitation.

Claims

1. An intelligent temperature control system, characterized in that: include: A central processing unit, a temperature acquisition unit, and an electric energy control unit; the central processing unit is connected to the temperature acquisition unit and the electric energy control unit respectively; the electric energy control unit is connected to m×n heating units respectively; the temperature acquisition unit is connected to m temperature sensors respectively; the m temperature sensors are respectively arranged in m heating areas; one heating area includes n heating units; The temperature acquisition unit is used to acquire the current temperature of the heating area; The central processing unit is used to determine the control amount of the next time step according to the current temperature of the heating area, and send the control amount to the power control unit; The power control unit is used to control the switch of the heating unit according to the control amount to adjust the temperature of the corresponding heating area.

2. The intelligent temperature control system according to claim 1, characterized in that: Also includes: Filter unit; the temperature acquisition unit is connected to the central processing unit through the filter unit; The filtering unit is used to perform filtering processing on the current temperature of the heating area to obtain the processed current temperature of the heating area.

3. The intelligent temperature control system according to claim 1, characterized in that: The central processing unit comprises: a feedback correction module, configured to determine a temperature deviation based on a current temperature of the heating area and a current target temperature of the heating area; A parameter optimization module is used to optimize the model parameters of the prediction model of the previous time step using the least square method or the gradient descent method according to the temperature deviation to obtain the model parameters of the current time step; The control quantity prediction module is used to determine the control quantity of the next time step using a prediction model based on the current temperature of the heating area, the model parameters of the current time step and the historical control quantity.

4. The intelligent temperature control system according to claim 1, characterized in that: Also includes: Bluetooth unit; the Bluetooth unit is connected to the central processing unit; The Bluetooth unit is used to communicate with the main control platform, receive instructions transmitted by the user through the main control platform, and send the status of the intelligent temperature control system to the main control platform; the status includes the set temperature, current actual temperature, working mode and working time.

5. The intelligent temperature control system according to claim 4, characterized in that: The main control platform is a computer or a mobile phone.

6. The intelligent temperature control system according to claim 1, characterized in that: Also includes: Button and display unit; the button and display unit includes a plurality of buttons and a display screen; the buttons and the display screen are connected to the central processing unit; the plurality of buttons include a start button, a stop button, a temperature adjustment button and a mode switching button; The display screen is used to display the status of the intelligent temperature control system; the status includes the set temperature, current actual temperature, working mode and working time.

7. An intelligent temperature control method, characterized in that: The intelligent temperature control method is applied to the intelligent temperature control system according to any one of claims 1 to 6, and the intelligent temperature control method includes: Collect the current temperature of the heating area; determining a temperature deviation based on the current temperature of the heating area and the current target temperature of the heating area; According to the temperature deviation, the model parameters of the prediction model of the previous time step are optimized using the least squares method or the gradient descent method to obtain the model parameters of the current time step; Determining the control quantity for the next time step using a prediction model based on the current temperature of the heating area, the model parameters of the current time step, and the historical control quantity; The heating unit is controlled to be switched on and off according to the control amount to adjust the temperature of the corresponding heating area.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the intelligent temperature control method according to claim 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the intelligent temperature control method according to claim 7 is implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the intelligent temperature control method according to claim 7 is implemented.

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