Electromagnetic heating method and system and intelligent electric appliance
By optimizing the frequency and magnetic field strength of electromagnetic heating, the problems of uneven temperature and energy waste in traditional electromagnetic heating equipment have been solved, achieving a more uniform and efficient heating effect.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- NINGBO FOTILE KITCHEN WARE CO LTD
- Filing Date
- 2026-03-02
- Publication Date
- 2026-05-12
AI Technical Summary
Traditional electromagnetic heating equipment results in uneven temperature distribution on the surface of the heated object, making it difficult to adapt to changes in the material, shape, or ambient temperature of the heated object, leading to energy waste.
By acquiring the target temperature field data, initial heating frequency data, and magnetic field strength data of the object to be heated, the frequency and intensity of the magnetic field generating unit are optimized, and the magnetic field generating unit is controlled to generate a magnetic field to achieve uniform heating.
It improves the uniformity and energy efficiency of electromagnetic heating, and reduces the temperature difference on the surface of the object to be heated from ±30°C to ±3°C.
Smart Images
Figure CN122028236A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of intelligent electrical appliance technology, and in particular to an electromagnetic heating method, system, and intelligent electrical appliance. Background Technology
[0002] With the improvement of people's living standards and the promotion and popularization of technologies such as artificial intelligence, more and more traditional lifestyles are gradually changing. The use of home appliances is gradually moving towards intelligence, bringing more convenience to users while diversifying the functions of various home appliances, among which the application of smart air conditioners is increasing. In existing technologies, traditional electromagnetic heating equipment uses a fixed frequency or a single magnetic field distribution, resulting in uneven temperature distribution on the surface of the heated object (such as local overheating or underheating), and it is difficult to adapt to changes in the material, shape, or ambient temperature of the heated object, leading to energy waste. Summary of the Invention
[0003] To address the aforementioned problems in the prior art, this invention discloses an electromagnetic heating method, system, and intelligent appliance, which can improve the uniformity and energy efficiency of electromagnetic heating. The technical solution disclosed in this invention is as follows: According to one aspect of the disclosed embodiments of the present invention, an electromagnetic heating method is provided, the method comprising: Acquire target temperature field data, initial heating frequency data, and initial magnetic field strength data corresponding to the object to be heated; the target temperature field data includes temperature data at each location in the temperature field corresponding to the object to be heated. Based on the initial heating frequency data, the first target heating frequency data is determined according to the first voltage data and the first current data corresponding to the magnetic field generating unit. The location in the temperature field where the temperature data satisfies the first preset condition is determined as the target location; Based on the distance data and angle data between the magnetic field generating unit and the target position, as well as the area data of the magnetic field generating unit, the initial magnetic field strength data is optimized to obtain the first target magnetic field strength data. Based on the first target heating frequency data and the first target magnetic field strength data, the magnetic field generating unit is controlled to generate a magnetic field to heat the object to be heated.
[0004] Optionally, determining the first target heating frequency data based on the first voltage data and the first current data corresponding to the magnetic field generating unit under the initial heating frequency data includes: Based on preset frequency adjustment data, the initial heating frequency data is adjusted to obtain multiple updated heating frequency data. For each updated heating frequency data, each heating power data is determined based on the first voltage data and the first current data corresponding to the magnetic field generating unit; The updated heating frequency data corresponding to the heating power data that meets the second preset condition among multiple heating power data is determined as the first target heating frequency data.
[0005] Optionally, the method further includes: Obtain the initial proportional coefficient and the initial integral coefficient; If the temperature difference data meets the third preset condition, the initial proportional coefficient and the initial integral coefficient are adjusted to obtain the target proportional coefficient and the target integral coefficient; the temperature difference data is the difference data between the target temperature field data and the preset temperature field data. Based on the target proportional coefficient, the target integral coefficient, and the differential temperature data, the compensation magnetic field strength data is determined; Based on the compensated magnetic field strength data, the first target magnetic field strength data is compensated to obtain the second target magnetic field strength data. Accordingly, controlling the magnetic field generating unit to generate a magnetic field based on the first target heating frequency data and the first target magnetic field strength data includes: Based on the first target heating frequency data and the second target magnetic field strength data, the magnetic field generating unit is controlled to generate a magnetic field.
[0006] Optionally, acquiring the target temperature field data, initial heating frequency data, and initial magnetic field strength data corresponding to the object to be heated includes: Obtain the target temperature field data and material data corresponding to the object to be heated; The material data is tested to obtain the resistance data corresponding to the object to be heated; Based on the first preset mapping relationship, the electromagnetic conduction attribute data corresponding to the resistance data is determined; the first preset mapping relationship is used to characterize the correspondence between the resistance data and the electromagnetic conduction attribute data of the object to be heated. Based on the second preset mapping relationship, the initial heating frequency data and the initial magnetic field strength data corresponding to the electromagnetic conduction attribute data are determined; the second preset mapping relationship is used to characterize the correspondence between the electromagnetic conduction attribute data corresponding to the resistance data and the heating frequency data and magnetic field strength data.
[0007] Optionally, obtaining the target temperature field data corresponding to the object to be heated includes: Obtain multimodal temperature data corresponding to the object to be heated, including infrared temperature data, thermocouple temperature data, and temperature image data; The multimodal temperature data is fused to obtain fused temperature data; A temperature field is constructed based on the fused temperature data to obtain the target temperature field data corresponding to the object to be heated.
[0008] Optionally, the step of fusing the multimodal temperature data to obtain fused temperature data includes: Based on a preset filtering algorithm, the infrared temperature data, thermocouple temperature data, and temperature image data are constructed into a state vector, and the multimodal temperature data are fused to obtain the fused temperature data.
[0009] Optionally, controlling the magnetic field generating unit to generate a magnetic field based on the first target heating frequency data and the first target magnetic field strength data includes: Based on the first target heating frequency data and the first target magnetic field strength data, determine the second voltage data and the second current data corresponding to the magnetic field generating unit; Based on the second voltage data and the second current data, the magnetic field generating unit is controlled to generate a magnetic field.
[0010] Optionally, before controlling the magnetic field generating unit to generate a magnetic field based on the first target heating frequency data and the first target magnetic field strength data, the method further includes: Obtain the historical power data corresponding to the object to be heated; Based on the historical power data, the first target heating frequency data and the first target magnetic field strength data are adjusted to obtain the second target heating frequency data and the third target magnetic field strength data. Accordingly, controlling the magnetic field generating unit to generate a magnetic field based on the first target heating frequency data and the first target magnetic field strength data includes: Based on the second target heating frequency data and the third target magnetic field strength data, the magnetic field generating unit is controlled to generate a magnetic field.
[0011] According to another aspect of the embodiments disclosed in this invention, an electromagnetic heating system is provided, which employs the electromagnetic heating method described in any of the preceding claims for heating.
[0012] According to another aspect of the disclosed embodiments of the present invention, a smart appliance is provided, including the electromagnetic heating system as described above.
[0013] The electromagnetic heating method provided by this invention has the following technical effects: The electromagnetic heating method provided by this invention includes acquiring target temperature field data, initial heating frequency data, and initial magnetic field strength data corresponding to the object to be heated; the target temperature field data includes temperature data at each position in the temperature field corresponding to the object to be heated; under the initial heating frequency data, a first target heating frequency data is determined based on the first voltage data and the first current data corresponding to the magnetic field generating unit; the position in the temperature field where the temperature data satisfies a first preset condition is determined as the target position; the initial magnetic field strength data is optimized based on the distance data and angle data between the magnetic field generating unit and the target position, as well as the area data of the magnetic field generating unit, to obtain the first target magnetic field strength data; based on the first target heating frequency data and the first target magnetic field strength data, the magnetic field generating unit is controlled to generate a magnetic field to heat the object to be heated, thereby improving the uniformity of electromagnetic heating and the energy efficiency of electromagnetic heating.
[0014] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description
[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0016] Figure 1 This is a schematic flowchart illustrating an electromagnetic heating method according to an exemplary embodiment; Figure 2 This is a schematic diagram illustrating a process for determining first target heating frequency data according to an exemplary embodiment; Figure 3 This is a schematic diagram illustrating a process for determining the magnetic field strength data of a second target, according to an exemplary embodiment. Detailed Implementation
[0017] To enable those skilled in the art to better understand the technical solutions disclosed in this invention, the technical solutions in the disclosed embodiments will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.
[0018] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention disclosed herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or server that comprises a series of steps or units is not necessarily limited to those explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.
[0019] The following describes an electromagnetic heating method according to this application. Figure 1 This is a flowchart illustrating an electromagnetic heating method according to an exemplary embodiment. This specification provides the operational steps of the method as described in the embodiments or flowcharts, but based on conventional or non-inventive labor, more or fewer operational steps may be included. The order of steps listed in the embodiments is merely one possible execution order among many and does not represent the only possible execution order. In actual system or server products, the methods shown in the embodiments or drawings can be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment). Specifically, as... Figure 1 As shown, the above method may include: S101: Obtain the target temperature field data, initial heating frequency data, and initial magnetic field strength data corresponding to the object to be heated.
[0020] In one specific embodiment, the object to be heated can be any object requiring electromagnetic heating. In a kitchen setting, the object to be heated may include cookware and tableware. The target temperature field data may include the temperature data at each location in the temperature field corresponding to the object to be heated.
[0021] Optionally, obtaining the target temperature field data, initial heating frequency data, and initial magnetic field strength data corresponding to the object to be heated may include: Obtain the target temperature field data and material data corresponding to the object to be heated; The material data is tested to obtain the resistance data of the object to be heated; Based on the first preset mapping relationship, determine the electromagnetic conduction attribute data corresponding to the resistance data; Based on the second preset mapping relationship, the initial heating frequency data and initial magnetic field strength data corresponding to the electromagnetic conduction attribute data are determined.
[0022] In one specific embodiment, the material data of the object to be heated may include materials such as steel, stainless steel, and aluminum; the resistance data corresponding to the object to be heated may include the equivalent resistance and resistance of the object; and the electromagnetic conductivity data may include data such as magnetic permeability and electrical conductivity. A first preset mapping relationship can be used to characterize the correspondence between the resistance data and the electromagnetic conductivity data of the object to be heated; a second preset mapping relationship can be used to characterize the correspondence between the electromagnetic conductivity data corresponding to the resistance data and the heating frequency data and magnetic field strength data.
[0023] In practical applications, an impedance analyzer can be used to detect material data, measure the equivalent resistance and resistance of the object to be heated, and then determine the corresponding permeability and conductivity based on the first preset mapping relationship. After that, based on the second preset mapping relationship, the corresponding initial heating frequency data and initial magnetic field strength data can be determined.
[0024] Optionally, obtaining the target temperature field data corresponding to the object to be heated may include: Obtain multimodal temperature data corresponding to the object to be heated; Multimodal temperature data are fused to obtain fused temperature data; A temperature field is constructed based on the fused temperature data to obtain the target temperature field data corresponding to the object to be heated.
[0025] In one specific embodiment, the multimodal temperature data may include infrared temperature data, thermocouple temperature data, and temperature image data. Specifically, infrared temperature data can be acquired using infrared sensors, and an infrared sensor array can be set up to cover the surface of the object to be heated; thermocouple temperature data can be acquired using distributed thermocouples, with multiple thermocouples arranged radially and axially; and temperature image data can be acquired using a thermal imager.
[0026] In one specific embodiment, a temperature field probability model can be constructed using Gaussian process regression based on the fused temperature data to generate a continuous temperature distribution map, thus obtaining the target temperature field data. Optionally, the spatial resolution of this continuous temperature distribution map can reach 1 mm.
[0027] Optionally, the above-mentioned fusion processing of multimodal temperature data to obtain fused temperature data may include: Based on a preset filtering algorithm, infrared temperature data, thermocouple temperature data, and temperature image data are constructed into a state vector, and multimodal temperature data are fused to obtain fused temperature data.
[0028] In one specific embodiment, the aforementioned preset filtering algorithm can be a Kalman filter algorithm. Specifically, in the Kalman filter algorithm, the state equation can be... The observation equation can be The gain update equation can be ,in, Represents the above state vector, Indicates infrared temperature data. This indicates thermocouple temperature data. Represents temperature image data, Represents the state transition matrix. Indicates process noise. express Target temperature field data at any given time. The observation matrix describes how to extract the observations of interest from the original data or state vector. express Measurement noise at time, Indicates at time step Previously (i.e., based on) The covariance matrix of the state estimation error (information at time) The covariance matrix represents the magnitude and distribution characteristics of random errors in measurements. Specifically, it can be used to detect sensor faults (such as thermocouple open circuits) using the isolated forest algorithm and to dynamically adjust the noise covariance of the Kalman filter. Specifically, the above state equation is used to represent... At any given moment, the state of the system It is based on the current state Through the state transition matrix It was transferred from here, and a process noise was added. .
[0029] Optionally, before data fusion, multimodal data can be mapped to a unified coordinate system through timestamp synchronization and spatial registration (based on perspective transformation matrix).
[0030] S103: Based on the initial heating frequency data, determine the first target heating frequency data according to the first voltage data and the first current data corresponding to the magnetic field generating unit.
[0031] In an optional embodiment, such as Figure 2 As shown, determining the first target heating frequency data based on the first voltage data and the first current data corresponding to the magnetic field generating unit under the initial heating frequency data may include: S201: Based on preset frequency adjustment data, adjust the initial heating frequency data to obtain multiple updated heating frequency data.
[0032] S203: Under each updated heating frequency data, determine each heating power data based on the first voltage data and the first current data corresponding to the magnetic field generating unit.
[0033] S205: Among multiple heating power data, the updated heating frequency data corresponding to the heating power data that meets the second preset condition is determined as the first target heating frequency data.
[0034] In one specific embodiment, the magnetic field generating unit can be a heating coil, and multiple magnetic field generating units can be provided. The heating power data that satisfies the second preset condition can be the largest heating power data among multiple heating power data, and its corresponding updated heating frequency data is the first target heating frequency data. In practical applications, the initial heating frequency data can be used as a reference, and dynamic scanning can be performed within the preset frequency adjustment data range to obtain multiple updated heating frequency data. Then, different updated heating frequencies can be applied, and the corresponding voltage and current can be measured. The frequency data that maximizes the heating power data (i.e., maximizes the energy transfer efficiency) is determined as the first target heating frequency data.
[0035] Specifically, the first target heating frequency data can be calculated using the following formula:
[0036] in, This refers to the heating frequency data of the first target mentioned above. This refers to the aforementioned first voltage data. This represents the first current data mentioned above.
[0037] In the above embodiments, the optimization of the heating frequency can be regarded as the first level of optimization.
[0038] S105: Determine the location in the temperature field where the temperature data meets the first preset condition as the target location.
[0039] In one specific embodiment, the first preset condition may include temperature data greater than a first preset temperature threshold or temperature data less than a second preset temperature threshold, meaning the temperature at the target location is either too high or too low, requiring optimization and adjustment of the temperature at that location to make the temperature field data more uniform. The first and second preset temperature thresholds can be set according to actual application requirements.
[0040] S107: Based on the distance data and angle data between the magnetic field generating unit and the target position, as well as the area data of the magnetic field generating unit, the initial magnetic field strength data is optimized to obtain the first target magnetic field strength data.
[0041] In one specific embodiment, the magnetic field strength data of the first target can be calculated according to the following formula:
[0042] in, The first target magnetic field strength data represents the target location. This represents the current in the nth magnetic field generating unit. This represents the area data of the nth magnetic field generating unit. This represents the angle data between the nth magnetic field generating unit and the target position. This represents the distance between the nth magnetic field generating unit and the target location, where N represents the number of magnetic field generating units. It represents the magnetic permeability.
[0043] In the above embodiments, the optimization of the magnetic field in areas with higher or lower temperatures can be regarded as a second-level optimization, which focuses the local magnetic field.
[0044] S109: Based on the first target heating frequency data and the first target magnetic field strength data, control the magnetic field generation unit to generate a magnetic field to heat the object to be heated.
[0045] Optionally, the above-mentioned control of the magnetic field generating unit to generate a magnetic field based on the first target heating frequency data and the first target magnetic field strength data includes: Based on the heating frequency data and magnetic field strength data of the first target, the second voltage data and second current data corresponding to the magnetic field generating unit are determined. Based on the second voltage data and the second current data, the magnetic field generating unit is controlled to generate a magnetic field.
[0046] In one specific embodiment, the distribution of the generated magnetic field is adjusted by changing the voltage and current of the heating coil, thereby causing a change in the temperature field.
[0047] In an optional embodiment, such as Figure 3 As shown, the above method may further include: S301: Obtain the initial proportional coefficient and initial integral coefficient; S303: If the differential temperature data meets the third preset condition, adjust the initial proportional coefficient and the initial integral coefficient to obtain the target proportional coefficient and the target integral coefficient. S305: Determine the compensation magnetic field strength data based on the target proportional coefficient, target integral coefficient, and differential temperature data; S307: Based on the compensated magnetic field strength data, the first target magnetic field strength data is compensated to obtain the second target magnetic field strength data.
[0048] In one specific embodiment, the difference temperature data can be the difference between the target temperature field data and the preset temperature field data. Specifically, the target temperature field data can include the current temperature data corresponding to each position in the reconstructed temperature field, and the preset temperature field data can be the expected temperature data corresponding to the current temperature data. Based on the difference between the actual current temperature data and the expected temperature data, the compensation magnetic field strength data is determined to compensate for the current magnetic field strength.
[0049] Optionally, upon detecting a disturbance, the magnetic field can be compensated based on the temperature difference data, the target proportional coefficient, and the target integral coefficient. The proportional coefficient can be adjusted according to the disturbance intensity, and the integral coefficient can be adjusted according to the duration of the disturbance. Specifically, if the temperature difference data increases rapidly and the impedance changes, the disturbance can be identified as caused by a sudden change in material properties; if the temperature difference data drifts slowly, the disturbance can be identified as caused by changes in ambient temperature; and if the temperature difference data oscillates violently, the disturbance can be identified as caused by load fluctuations.
[0050] Specifically, the compensation magnetic field strength data can be calculated using the following formula:
[0051] in, This indicates the above-mentioned compensation magnetic field strength data. This represents the target proportionality coefficient mentioned above. This represents the integral coefficient of the above objective. This indicates the temperature difference data mentioned above. This represents the integral term of the differential temperature data, which indicates the time from the time the disturbance occurred ( ) to the current time ( The sum of differential temperature data accumulated over time can reflect the sustained impact and severity of the disturbance.
[0052] In the above embodiments, the process of compensating for the magnetic field can be regarded as the third level of optimization. Through the three-level optimization strategy (global frequency scanning, local magnetic field focusing, and disturbance compensation), the surface temperature difference of the object to be heated is reduced from ±30°C in the traditional system to ±3°C, solving the problem of local overheating or underheating. Through the three-dimensional collaborative innovation of magnetic field, data, and algorithm, the three major pain points of electromagnetic induction heating—uniformity, energy efficiency, and response speed—are solved.
[0053] Accordingly, the above-mentioned control of the magnetic field generation unit to generate a magnetic field based on the first target heating frequency data and the first target magnetic field strength data may include: Based on the heating frequency data of the first target and the magnetic field strength data of the second target, the magnetic field generating unit is controlled to generate a magnetic field.
[0054] In an optional embodiment, before controlling the magnetic field generating unit to generate a magnetic field based on the first target heating frequency data and the first target magnetic field strength data, the method may further include: Obtain historical power data for the object to be heated; Based on historical power data, the heating frequency data and magnetic field strength data of the first target are adjusted to obtain the heating frequency data of the second target and the magnetic field strength data of the third target.
[0055] In one specific embodiment, by analyzing historical power data, the heating demand characteristics of the object to be heated at different heating stages can be identified, so as to adjust the heating frequency, magnetic field strength and compensation strategy, and compare the energy consumption effect under different power settings in historical operation, and select the optimization strategy with the highest energy efficiency.
[0056] Optionally, target temperature field data, historical power data, and material data of the object to be heated can be input into a preset deep learning model to optimize the initial heating frequency data and initial magnetic field strength data, thereby obtaining the first target heating frequency data and the first target magnetic field strength data. During the optimization process, the above three-level strategy can be intelligently fine-tuned and coordinated. For example, in the current state, it can determine which level of strategy to prioritize, adaptively adjust key parameters in the three-level strategy (such as the focusing intensity of the second level and the coefficients of the third level), and fine-tune the heating frequency and magnetic field strength based on the output of the three-level strategy.
[0057] Accordingly, the above-mentioned control of the magnetic field generation unit to generate a magnetic field based on the first target heating frequency data and the first target magnetic field strength data may include: Based on the heating frequency data of the second target and the magnetic field strength data of the third target, the magnetic field generation unit is controlled to generate a magnetic field.
[0058] As can be seen from the technical solutions provided in the embodiments of this specification above, this specification obtains target temperature field data, initial heating frequency data, and initial magnetic field strength data corresponding to the object to be heated; the target temperature field data includes temperature data at each position in the temperature field corresponding to the object to be heated; under the initial heating frequency data, the first target heating frequency data is determined based on the first voltage data and the first current data corresponding to the magnetic field generating unit; the position in the temperature field where the temperature data meets the first preset condition is determined as the target position; the initial magnetic field strength data is optimized based on the distance data and angle data between the magnetic field generating unit and the target position, as well as the area data of the magnetic field generating unit, to obtain the first target magnetic field strength data; based on the first target heating frequency data and the first target magnetic field strength data, the magnetic field generating unit is controlled to generate a magnetic field to heat the object to be heated, thereby improving the uniformity of electromagnetic heating and the energy efficiency of electromagnetic heating.
[0059] The present invention also provides an electromagnetic heating system that uses the above-described electromagnetic heating method for heating.
[0060] The present invention also provides a smart appliance that may include the aforementioned electromagnetic heating system. Specifically, the smart appliance may be any device used for electromagnetic heating.
[0061] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided by this invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.
[0062] Other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles disclosed herein and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of the invention are indicated by the following claims.
[0063] It should be understood that the present invention is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the present invention is limited only by the appended claims.
Claims
1. An electromagnetic heating method, characterized in that, The method includes: Acquire target temperature field data, initial heating frequency data, and initial magnetic field strength data corresponding to the object to be heated; the target temperature field data includes temperature data at each location in the temperature field corresponding to the object to be heated. Based on the initial heating frequency data, the first target heating frequency data is determined according to the first voltage data and the first current data corresponding to the magnetic field generating unit. The location in the temperature field where the temperature data satisfies the first preset condition is determined as the target location; Based on the distance data and angle data between the magnetic field generating unit and the target position, as well as the area data of the magnetic field generating unit, the initial magnetic field strength data is optimized to obtain the first target magnetic field strength data. Based on the first target heating frequency data and the first target magnetic field strength data, the magnetic field generating unit is controlled to generate a magnetic field to heat the object to be heated.
2. The method according to claim 1, characterized in that, The determination of the first target heating frequency data based on the first voltage data and the first current data corresponding to the magnetic field generating unit under the initial heating frequency data includes: Based on preset frequency adjustment data, the initial heating frequency data is adjusted to obtain multiple updated heating frequency data. For each updated heating frequency data, each heating power data is determined based on the first voltage data and the first current data corresponding to the magnetic field generating unit; The updated heating frequency data corresponding to the heating power data that meets the second preset condition among multiple heating power data is determined as the first target heating frequency data.
3. The method according to claim 1, characterized in that, The method further includes: Obtain the initial proportional coefficient and the initial integral coefficient; If the temperature difference data meets the third preset condition, the initial proportional coefficient and the initial integral coefficient are adjusted to obtain the target proportional coefficient and the target integral coefficient; the temperature difference data is the difference data between the target temperature field data and the preset temperature field data. Based on the target proportional coefficient, the target integral coefficient, and the differential temperature data, the compensation magnetic field strength data is determined; Based on the compensated magnetic field strength data, the first target magnetic field strength data is compensated to obtain the second target magnetic field strength data. Accordingly, controlling the magnetic field generating unit to generate a magnetic field based on the first target heating frequency data and the first target magnetic field strength data includes: Based on the first target heating frequency data and the second target magnetic field strength data, the magnetic field generating unit is controlled to generate a magnetic field.
4. The method according to claim 1, characterized in that, The acquisition of the target temperature field data, initial heating frequency data, and initial magnetic field strength data corresponding to the object to be heated includes: Obtain the target temperature field data and material data corresponding to the object to be heated; The material data is tested to obtain the resistance data corresponding to the object to be heated; Based on the first preset mapping relationship, the electromagnetic conduction attribute data corresponding to the resistance data is determined; the first preset mapping relationship is used to characterize the correspondence between the resistance data and the electromagnetic conduction attribute data of the object to be heated. Based on the second preset mapping relationship, the initial heating frequency data and the initial magnetic field strength data corresponding to the electromagnetic conduction attribute data are determined; the second preset mapping relationship is used to characterize the correspondence between the electromagnetic conduction attribute data corresponding to the resistance data and the heating frequency data and magnetic field strength data.
5. The method according to claim 1, characterized in that, The acquisition of the target temperature field data corresponding to the object to be heated includes: Obtain multimodal temperature data corresponding to the object to be heated, including infrared temperature data, thermocouple temperature data, and temperature image data; The multimodal temperature data is fused to obtain fused temperature data; A temperature field is constructed based on the fused temperature data to obtain the target temperature field data corresponding to the object to be heated.
6. The method according to claim 5, characterized in that, The process of fusing the multimodal temperature data to obtain fused temperature data includes: Based on a preset filtering algorithm, the infrared temperature data, thermocouple temperature data, and temperature image data are constructed into a state vector, and the multimodal temperature data are fused to obtain the fused temperature data.
7. The method according to claim 1, characterized in that, The step of controlling the magnetic field generating unit to generate a magnetic field based on the first target heating frequency data and the first target magnetic field strength data includes: Based on the first target heating frequency data and the first target magnetic field strength data, determine the second voltage data and the second current data corresponding to the magnetic field generating unit; Based on the second voltage data and the second current data, the magnetic field generating unit is controlled to generate a magnetic field.
8. The method according to any one of claims 1 to 7, characterized in that, Before controlling the magnetic field generating unit to generate a magnetic field based on the first target heating frequency data and the first target magnetic field strength data, the method further includes: Obtain the historical power data corresponding to the object to be heated; Based on the historical power data, the first target heating frequency data and the first target magnetic field strength data are adjusted to obtain the second target heating frequency data and the third target magnetic field strength data. Accordingly, controlling the magnetic field generating unit to generate a magnetic field based on the first target heating frequency data and the first target magnetic field strength data includes: Based on the second target heating frequency data and the third target magnetic field strength data, the magnetic field generating unit is controlled to generate a magnetic field.
9. An electromagnetic heating system, characterized in that, Heating is performed using the electromagnetic heating method as described in any one of claims 1 to 8.
10. A smart appliance, characterized in that, Including the electromagnetic heating system as described in claim 9.