High-frequency induction heating torch ignition energy consumption optimization system

Abstract

The invention belongs to the technical field of adaptive control, and particularly relates to a high-frequency induction heating torch ignition energy consumption optimization system which comprises a system modeling part, an energy consumption optimization part and a dynamic frequency adaptive control part. The system modeling part is used for performing modeling under skin effect correction on high-frequency impedance during torch heating and calculating total energy consumption; the energy consumption optimization part is used for finding a current peak value, a frequency and a heating time upper limit corresponding to the minimum value of the comprehensive energy consumption optimization objective function according to a high-frequency effect and a skin effect during torch heating; and the dynamic frequency adaptive control part is used for heating the torch according to the current peak value, the frequency and the heating time upper limit corresponding to the minimum value of the comprehensive energy consumption optimization objective function. According to the invention, energy consumption and additional loss can be reduced to the greatest extent.

Description

Technical Field

[0001] The present invention belongs to the technical field of adaptive control, and particularly relates to a high-frequency induction heating torch ignition energy consumption optimization system. Background Art

[0002] With the continuous improvement of industrial automation and intelligent manufacturing levels, high-frequency induction heating technology, as an efficient and energy-saving heating method, has been widely used in fields such as aerospace, metallurgy, and automotive manufacturing. Among them, the torch ignition technology, as a key link in the high-frequency induction heating system, its working efficiency and energy consumption control are directly related to the performance and operating costs of the entire equipment. In the prior art, the torch ignition system is mainly designed based on the traditional low-frequency electromagnetic heating principle, and usually uses a fixed current, a fixed frequency, and a preset heating time to achieve the ignition operation. Although this technical solution can meet the basic ignition requirements to a certain extent, due to the neglect of the dynamic changes of electromagnetic parameters and their nonlinear effects under high-frequency working conditions, there are obvious problems such as energy consumption waste, uneven heating, and slow response in the actual application of the system.

[0003] In the prior art, some researchers have improved the high-frequency induction heating technology and proposed a torch ignition system based on feedback control. The basic idea is to monitor physical quantities such as temperature and power in real time during the torch heating process, and then use a closed-loop control strategy to adjust the input parameters, so as to achieve dynamic control of the ignition process. For example, as mentioned in relevant literature, the heating current is adjusted by using a PID controller or a fuzzy control algorithm. Although this method improves the response speed and stability of the system to a certain extent, its control algorithm is relatively simple and difficult to accurately reflect complex physical phenomena such as electromagnetic field distribution, skin effect and resonance effect in high-frequency induction heating. As a result, there is still a large deviation between the actual energy consumption calculation and the theoretical prediction under high-frequency working conditions. In addition, traditional control methods often only consider a single energy consumption loss index, such as direct thermal energy consumption, while ignoring additional energy losses caused by eddy current losses, non-ideal coupling and other high-frequency effects, thus making the overall energy consumption optimization effect of the system not ideal. In addition, in the prior art, most of the modeling of the high-frequency electromagnetic parameters of the torch heating system uses a low-frequency approximation model, which ignores the current concentration phenomenon caused by the skin effect under high-frequency conditions, resulting in a large difference between the measured resistance and inductance parameters and the actual working state. For example, traditional inductance measurement methods are usually based on the assumption of uniform current distribution, while in a high-frequency environment, due to the current mainly concentrating on the conductor surface, the effective resistance increases significantly and the equivalent inductance also changes, but these factors are often not fully considered in the existing model, resulting in the system being unable to accurately calculate the instantaneous ignition energy consumption and eddy current losses during high-frequency induction heating torch ignition, thus affecting the overall energy consumption optimization strategy. In addition, the current control of high-frequency induction heating torches in the prior art mostly adopts fixed preset values, lacking a real-time dynamic adjustment mechanism and unable to adaptively adjust according to the changes in the actual working state of the torch, which easily leads to excessive current fluctuations or insufficient response during the ignition process, reducing the heating efficiency and ignition stability of the system. Summary of the Invention

[0004] In view of this, the main object of the present invention is to provide a high-frequency induction heating torch ignition energy consumption optimization system, which globally jointly optimizes key parameters such as input current, working frequency and upper limit of heating time during the ignition process by using an objective optimization function, and combines a real-time closed-loop feedback and dynamic adaptive adjustment mechanism to minimize energy consumption and additional losses. By comprehensively depicting the energy transmission, storage and loss processes, the system can effectively cope with problems such as uneven electromagnetic field distribution, non-ideal coupling and environmental interference in a high-frequency environment, thereby greatly improving the ignition efficiency and system stability and reducing the overall operation cost.

[0005] The technical solution adopted by the present invention is as follows: High-frequency induction heating torch ignition energy consumption optimization system, the system includes: a system modeling part, an energy consumption optimization part and a dynamic frequency adaptive control part; the system modeling part is used to model the high-frequency impedance during torch heating with skin effect correction, separate the equivalent resistance and equivalent inductance from the modeled high-frequency impedance, and establish an ignition instantaneous energy consumption and eddy current loss model based on this to calculate the total energy consumption; the energy consumption optimization part is used to establish a comprehensive energy consumption optimization objective function during torch heating according to the high-frequency effect and skin effect during torch heating, combined with the ignition instantaneous energy consumption and eddy current loss model, and find the current peak, frequency and heating time upper limit corresponding to the minimum value of the comprehensive energy consumption optimization objective function; the dynamic frequency adaptive control part is used to heat the torch according to the current peak, frequency and heating time upper limit corresponding to the minimum value of the comprehensive energy consumption optimization objective function, and dynamically adjust the current adaptively.

[0006] Further, the modeled high-frequency impedance is expressed as: ; Where, is the high-frequency impedance at frequency ; is the imaginary symbol; is the phase; is the equivalent inductance at frequency ; is the equivalent resistance at frequency .

[0007] Further, the equivalent resistance at frequency separated from the modeled high-frequency impedance is expressed using the following formula: ; Where, is the reference resistance of the torch; is the conductor thickness of the torch; is the skin depth; is the resistivity of the torch; is the magnetic permeability of the torch; is the weight parameter; is the exponential weight parameter; is the modulation parameter; is the resonant frequency of the torch; is the equivalent capacitance.

[0008] Further, the equivalent inductance at frequency separated from the modeled high-frequency impedance is expressed using the following formula: ; Where, It is a low-frequency inductor.

[0009] Furthermore, the instantaneous ignition energy consumption and eddy current loss model are expressed by the following formula: ; Wherein, is the instantaneous ignition energy consumption and eddy current loss; is the average cross-sectional area of the torch; is the electrical conductivity of the torch material; is time and the current at this time; is the current decay coefficient; is the average radius of the average cross-sectional area of the torch.

[0010] Furthermore, the total energy consumption is calculated by the following formula: ; Wherein, is the upper limit of the heating time; is the energy deviation compensation term caused by non-ideal coupling and high-frequency effects, and is calculated by the following formula: ; Wherein, is the peak current.

[0011] Furthermore, the target optimization function is expressed by the following formula: ; The optimization goal is: ; subject to the following constraints: ; ; ; By solving the current peak of the optimization target optimization function , frequency and the upper limit of the heating time , the torch is heated.

[0012] Furthermore, the current is dynamically and adaptively adjusted by the following formula: ; Wherein, is the initial current; is the set current adaptive adjustment amplitude; is time and the current at this time; is time Current at

[0013] Furthermore, the amplitude of the current adaptive adjustment has a value range of .

[0014] By adopting the above technical solutions, the present invention has the following beneficial effects: By finely modeling the electromagnetic response characteristics of the torch during the heating process, fully considering the energy losses caused by current concentration, skin effect, and resonance phenomenon under high-frequency working conditions, the accurate calculation and optimized control of the energy consumption during the torch ignition process are realized. The system uses advanced modeling technology to organically combine the resistive losses inside the torch with the magnetic energy storage phenomenon, establishing an energy consumption model that reflects the actual heating state, providing a solid data basis for subsequent energy consumption optimization and dynamic adaptive control. The system not only breaks through the limitations of traditional low-frequency heating models theoretically, but also can capture the minute changes in the working state of the torch in real-time during practical applications, thereby dynamically balancing the energy input and output during the ignition process. Due to the adoption of multi-parameter comprehensive optimization design, the system can significantly reduce the overall energy consumption while ensuring that the torch quickly reaches the predetermined heating effect. By finely calculating the energy consumption at the moment of torch ignition and the additional energy consumption caused by the high-frequency effect, the system realizes the comprehensive management of the energy consumption during the heating process, enabling the equipment to make the most of the input energy during operation, thereby reducing the operating cost caused by energy waste. At the same time, the system optimally controls the current and frequency in real-time through an adaptive adjustment mechanism, not only improving the ignition efficiency, but also effectively improving the system instability problem caused by temperature fluctuations and material property changes. This adaptive control strategy enables the torch to maintain an excellent working state under various complex working conditions, thus greatly improving the reliability and durability of the system. In addition, the present invention makes full use of advanced mathematical models and optimization algorithms during the energy consumption optimization process to realize the joint control of multiple key parameters such as heating time, working frequency, and input current. Through closed-loop feedback and real-time data monitoring, the system can dynamically adjust the working state within a short time, enabling each subtle link during the ignition process to be effectively controlled. This not only ensures that the torch can achieve the optimal energy release at the moment of ignition, but also makes the overall energy conversion efficiency of the heating process reach an unprecedented height. Thanks to this control strategy of multi-factor coupling optimization, the total energy consumed during the operation of the equipment is significantly lower than that of traditional heating systems, and at the same time, the ignition response speed and heating uniformity of the torch are also significantly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a schematic structural diagram of a high-frequency induction heating torch ignition energy consumption optimization system provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0016] All features disclosed in this specification, or steps in all methods or processes disclosed, may be combined in any manner, except for mutually exclusive features and / or steps.

[0017] Any feature disclosed in this specification (including any appended claims, abstract) may be replaced by other equivalent or similar-purpose alternative features, unless specifically stated otherwise. That is, unless specifically stated otherwise, each feature is only an example of a series of equivalent or similar features.

[0018] Example 1: Refer to Figure 1 , a high-frequency induction heating torch ignition energy consumption optimization system, the system includes: a system modeling part, an energy consumption optimization part, and a dynamic frequency adaptive control part; the system modeling part is used to model the high-frequency impedance during torch heating with skin effect correction, separate the equivalent resistance and equivalent inductance from the modeled high-frequency impedance, and establish an ignition instantaneous energy consumption and eddy current loss model based on this to calculate the total energy consumption; the energy consumption optimization part is used to establish a comprehensive energy consumption optimization objective function during torch heating according to the high-frequency effect and skin effect during torch heating, in combination with the ignition instantaneous energy consumption and eddy current loss model, and find the current peak, frequency, and upper limit of heating time corresponding to the minimum value of the comprehensive energy consumption optimization objective function; the dynamic frequency adaptive control part is used to heat the torch according to the current peak, frequency, and upper limit of heating time corresponding to the minimum value of the comprehensive energy consumption optimization objective function, and dynamically adjust the current adaptively.

[0019] Specifically, during the high-frequency induction heating of the torch, due to the non-uniform distribution of current density within the conductor, a phenomenon of concentration on the conductor surface layer occurs, namely the skin effect, resulting in significant differences between the impedance parameters in the actual working state and the traditional low-frequency theory. Therefore, in order to accurately describe the electromagnetic characteristics of the torch during heating, the system modeling part first monitors the high-frequency impedance in real time and adopts the skin effect correction method to match the measured original impedance data with the theoretical model. Through mathematical derivation and experimental calibration, a quantitative description of the actual current distribution state inside the torch is achieved. Through the corrected modeling process, two core parameters, the equivalent resistance and the equivalent inductance, are separated from the overall high-frequency impedance. The former mainly reflects the part of the energy dissipated in the form of heat during the torch heating process, while the latter reflects the energy stored due to the magnetic field change during the torch heating process. This process not only takes into account the physical properties such as the inherent resistivity and permeability of the material, but also combines the influence of the actual working frequency on the skin depth, so that the separated equivalent resistance and equivalent inductance can truly reflect the dynamic change law of the torch in the high-frequency working environment. Through this precise parameter extraction, the system modeling part is able to establish a comprehensive energy consumption model for the instantaneous energy consumption and eddy current loss during torch ignition. In practical applications, the calculation of the instantaneous energy consumption during torch ignition is not only affected by the peak value of the input current and the working frequency, but also by the magnetic field distribution inside the torch and its dynamic process of change over time; at the same time, as a secondary energy loss, the eddy current loss is caused by the local current distribution induced by the high-frequency magnetic field in the torch and its surrounding metal components, resulting in the ineffective loss of energy in the form of heat.

[0020] Therefore, when establishing the energy consumption model in the system modeling section, by comprehensively considering the above two parts of energy consumption during the torch heating process, the mathematical descriptions of instantaneous energy consumption and eddy current loss are organically combined to form a set of energy balance equations applicable to the high-frequency induction heating torch ignition process. This equation can theoretically comprehensively depict the complex coupling relationship among energy input, energy storage, and energy loss during torch heating. During the modeling process, not only the parameters such as input current peak value, frequency, and heating time are derived in detail, but also for the change in current density caused by the skin effect in the high-frequency electromagnetic field, an advanced correction algorithm is adopted to incorporate the distribution characteristics of electromagnetic parameters into the energy consumption calculation to ensure the accuracy of the calculation results. At the same time, this system also fully considers factors such as temperature fluctuations that may occur during the torch ignition process, the non-linear influence of material properties changing with temperature, and local magnetic field interference, and an adaptive correction mechanism is introduced into the model, enabling the model to continuously update and correct parameters during actual application, thus ensuring that the torch heating process is always in the optimal working state. By correcting the skin effect of the high-frequency impedance during torch heating, the present invention can isolate the equivalent resistance and equivalent inductance, and the acquisition of these two parameters provides a key basis for subsequent energy consumption optimization. The equivalent resistance is mainly used to describe the thermal energy loss caused by uneven current distribution on the surface of the conductor during the torch heating process, and its value is usually higher than the traditional theoretical value under high-frequency conditions; while the equivalent inductance reflects the ability of the high-frequency magnetic field to store energy inside the torch, and the change in its value directly affects the energy conversion efficiency during the torch ignition process.

[0021] The present invention accurately measures the impedance of the torch in the high-frequency operating state, and uses the skin effect correction theory to correct and process the data, extracting the equivalent resistance and equivalent inductance that reflect the true physical state. This processing method can not only eliminate the deviation caused by the uneven distribution of current, but also provide a reliable physical parameter basis for subsequent energy consumption optimization. Based on this accurate modeling result, the present invention further constructs a mathematical model between the instantaneous energy consumption of the torch ignition and the eddy current loss. This model comprehensively describes the input, storage, and loss of energy during the heating process of the torch in theory. Among them, the instantaneous energy consumption mainly reflects the heat generated by the resistive loss when the current passes through the torch, while the eddy current loss comes from the additional heat generated by the local closed current induced by the high-frequency magnetic field in the torch and the surrounding metal components. Through the quantitative analysis of these two parts of energy consumption, the energy consumption optimization part proposes a comprehensive energy consumption optimization objective function on this basis. This objective function organically combines all the energy loss factors during the heating process of the torch, taking into account both the electromagnetic energy transmission and conversion caused by the high-frequency effect and fully reflecting the influence of the skin effect on the energy consumption distribution in actual operation. Specifically, during the construction of the objective function, the coupling relationship between the current peak value, the operating frequency, and the upper limit of the heating time is mathematically described, so that the contributions of different parameters to the energy consumption loss can be accurately quantified. The establishment of this objective function not only requires a profound understanding of the physical meaning of each parameter, but also must consider the dynamic changes caused by various factors such as the environmental temperature, material properties, and electromagnetic field distribution during the actual heating process of the torch.

[0022] To this end, the present invention adopts advanced numerical simulation techniques and optimization algorithms to globally search for and solve the objective function, and finally determines the peak current, operating frequency, and upper limit of heating time that minimize the value of the objective function, thereby achieving the minimization of overall energy consumption while meeting the requirement that the torch ignition rapidly reaches the required temperature. It should be noted that during this energy consumption optimization process, the system does not simply adjust a single parameter, but comprehensively considers the energy transfer and loss mechanisms during the entire torch heating process, and strives to establish a dynamic feedback mechanism between the theoretical model and the actual operation. In this way, even when the system state changes due to material aging, environmental changes, or other external disturbances during the heating process, the optimization part can recalculate and adjust the objective function through real-time data updates, so as to always keep the system in the optimal working state. This optimization method theoretically breaks through the limitations of traditional single energy consumption control strategies. By introducing the high-frequency effect and skin effect into the energy consumption optimization objective function, the complex physical phenomena of energy transmission during the torch heating process are systematically and comprehensively characterized. At the same time, the construction process of the comprehensive energy consumption optimization objective function reflects the advanced idea of multi-physical field coupling modeling. It not only considers the mutual influence between the electromagnetic field distribution and heat energy conversion, but also introduces a feedback adjustment mechanism into the objective function, realizing the organic combination of the theoretical model and the actual control strategy. By solving the key parameters corresponding to the minimum value of the objective function, the present invention can provide an optimal energy consumption configuration scheme for the high-frequency induction heating torch ignition process, thereby not only ensuring that the torch can rapidly reach the expected heating effect at the moment of ignition, but also effectively reducing the energy waste during the entire heating process, achieving the dual goals of minimizing energy consumption and maximizing heating efficiency.

[0023] Embodiment 2: The high-frequency impedance after modeling is expressed as: ; where is the high-frequency impedance at a frequency of ; is the imaginary symbol; is the phase; is the equivalent inductance at a frequency of ; is the equivalent resistance at a frequency of ;

[0024] Specifically, during the actual operation of the high-frequency induction heating torch, due to the dynamic characteristics of the frequency change involved in the heating process, as a function of time, reflects the real-time regulation of the operating frequency during the torch heating process, and this regulation is closely related to the skin effect. The skin effect causes the current to mainly concentrate on the surface layer of the conductor, thereby making the equivalent resistance is significantly higher than the impedance value in the low-frequency state under high-frequency conditions. At the same time, the magnetic field formed by the high-frequency current inside the conductor will also cause dynamic changes in the equivalent inductance As a result, by introducing this conversion relationship into the formula, not only is a direct response to frequency changes achieved, but also the magnetic field energy storage effect is tightly coupled with frequency, enabling the formula to reflect the electromagnetic characteristics caused by the combined action of the high-frequency effect and the skin effect during the torch ignition process. In other words, the real part and the imaginary part of the complex impedance in the formula respectively describe the two basic phenomena of energy loss in the form of heat and energy storage and periodic release in the form of magnetic energy during the torch heating process. This unified description provides an effective means for the accurate calculation of the energy consumption during torch heating. In addition, the complex impedance modeling method adopted in this embodiment theoretically breaks through the limitation of only using a real number model for heating system analysis in the past. By jointly considering resistive and inductive elements, the model is more in line with the complex electromagnetic phenomena encountered in the actual operation of high-frequency induction heating. A large amount of induced current generated by high-frequency induction at the moment of torch ignition makes the current distribution in the conductor uneven, resulting in a sharp increase in the local temperature. It is difficult to accurately describe this phenomenon only by using the traditional model, while the complex impedance model precisely combines the equivalent parameters and obtained from actual measurement through mathematics, thereby achieving an accurate characterization of the dynamic change characteristics of high-frequency impedance. This characterization not only reveals the internal mechanism of energy conversion during the torch heating process theoretically, but also provides the necessary data support for constructing a comprehensive energy consumption objective function in the energy consumption optimization part, enabling the torch to achieve the optimal utilization of energy instantaneously during ignition.

[0025] At the same time, the application of this formula also has strong self-adaptability. During the torch ignition process of high-frequency induction heating, due to the influence of factors such as ambient temperature, material properties, and heating time, the resistance and inductance parameters in actual operation often show a trend of dynamic change, which requires the system to be able to update its internal model in real time to accurately predict and control the energy consumption of the torch. By introducing as a function of time into the formula, the system can recalculate and The value is such that the numerical expression of the high-frequency impedance always highly coincides with the actual operating conditions. This dynamic adjustment mechanism not only improves the robustness of the system under actual working conditions but also provides real-time feedback data for the dynamic frequency adaptive control part, enabling the entire high-frequency induction heating torch ignition energy consumption optimization system to always maintain the best operating state in a rapidly changing environment. More importantly, the expression form of complex impedance in the formula enables the system, when analyzing the energy consumption during the torch heating process, not to be limited to the energy consumption calculation under simple DC or low-frequency conditions, but to comprehensively consider the complex relationship among current distribution, heat loss, and magnetic energy storage under high-frequency conditions. Through this mathematical description, the system can not only accurately predict the energy consumption distribution during torch heating theoretically but also, in practical applications, effectively adjust the heating parameters by real-time measurement and calculation, reduce the additional energy consumption caused by the skin effect, improve the heating efficiency, and achieve the optimization of energy consumption during the ignition process. It is precisely this modeling method of complex impedance that enables the high-frequency induction heating torch ignition energy consumption optimization system to have higher energy utilization efficiency and control accuracy, and at the same time promotes the application of high-frequency electromagnetic theory in the field of industrial heating.

[0026] Example 3: The equivalent resistance at a frequency of separated from the modeled high-frequency impedance is expressed using the following formula: ; where is the reference resistance of the torch; is the conductor thickness of the torch; is the skin depth; is the resistivity of the torch; is the magnetic permeability of the torch; is the weight parameter; is the exponential weight parameter; is the modulation parameter; is the resonant frequency of the torch; is the equivalent capacitance.

[0027] Specifically, As the reference resistance of the torch, it reflects the inherent resistance value of the torch under low-frequency or ideal conditions. In actual operation, due to the fact that the current inside the conductor is mainly concentrated on the surface under the action of the high-frequency electromagnetic field (i.e., the skin effect), the effective conductive cross-sectional area is greatly reduced, resulting in the actual resistance being much larger than the reference value. The parameter in the formula represents the thickness of the torch conductor, and the ratio between it and the skin depth directly reflects the degree of non-uniformity of the current distribution; the skin depth is given according to , where is the resistivity of the torch material, is the magnetic permeability of the torch material, and reflects the direct influence of the operating frequency on the skin depth. As the frequency increases, decreases, resulting in an increase in the ratio , further amplifying the increase in resistance due to the skin effect. The weight parameter and the exponential parameter in the formula are used to adjust the contribution of this ratio to the equivalent resistance correction part. Its significance lies in reasonably adjusting the influence degree of the high-frequency effect on the resistance change according to the actual measurement data and engineering experience, so that the model can more accurately reflect the current distribution on the conductor surface during the torch heating process and the resulting additional energy consumption; specifically, the exponential parameter reflects the strength of the non-linear effect, while the weight parameter is used to quantify the amplitude of this non-linear correction. At the same time, the modulation parameter and the resonance frequency in the formula further consider the resonance effect of the torch in the high-frequency operating state; during high-frequency induction heating, due to the resonance circuit composed of the equivalent inductance and the equivalent capacitance in the torch, its resonance frequency determines the resonance state of the torch, and the deviation between the torch operating frequency and the resonance frequency directly affects the amplitude and phase distribution of the current, and thus has a significant impact on the energy consumption. By introducing the transcendental function into the formula, the system can smoothly modulate the resistance change caused by the frequency deviation from the resonance point. The non-linear characteristics of the function make the correction effect smaller when the torch operating frequency is closer to the resonance frequency, and when the operating frequency deviates from the resonance state, the resistance correction effect increases rapidly, so that the system can reflect the dynamic characteristics of the electromagnetic parameters changing with the resonance state in real time during the high-frequency heating process.

[0028] Overall, this formula uses the reference resistance The coupling with multiple correction factors fully reveals the dynamic change mechanism of the actual equivalent resistance caused by the skin effect and resonance effect under high-frequency conditions. Its physical significance lies in summarizing the complex energy transmission and loss phenomena in high-frequency electromagnetic induction heating into an adjustable and predictable mathematical model, which provides theoretical support for the accurate calculation of energy consumption during the torch ignition process. Through this expression, the system can dynamically calculate the equivalent resistance according to the actual working state of the torch, thereby providing accurate parameters for subsequent energy consumption optimization, adaptive adjustment and other links, ensuring that the torch reaches the optimal energy utilization state during high-frequency heating. Furthermore, due to the close coupling relationship between the electromagnetic field and heat conduction under high-frequency working conditions, the model not only considers the additional heat energy loss caused by the current concentration on the conductor surface, but also takes into account the influence of magnetic energy storage under resonant conditions on resistance correction, making the overall model more valuable for engineering applications. By continuously adjusting the parameters , as well as The value of, engineers can calibrate and optimize the model according to the actual measurement results, so that the calculated equivalent resistance can accurately match the performance of the torch in actual high-frequency induction heating. This model is not only highly innovative in theory, but also can adaptively update parameters through real-time feedback data in practical applications, so as to realize dynamic monitoring of the electromagnetic characteristics of the torch and real-time optimization of energy consumption. In this way, the system can minimize energy consumption losses and improve overall work efficiency while ensuring rapid ignition and uniform heating. Through the equivalent resistance expression described in this embodiment, the high-frequency induction heating torch ignition energy consumption optimization system can theoretically fully describe the resistive characteristics of the torch during operation and its dynamic changes with frequency, temperature and other factors, thereby providing accurate and real-time parameter input for the adaptive control of the system, ensuring that the torch can always maintain the best working state under actual high-frequency heating conditions.

[0029] Example 4: Separating the frequency from the high-frequency impedance after modeling The equivalent inductance at this time is expressed using the following formula: ; in, For low frequency inductance.

[0030] Specifically, represents the inductance of the torch at low frequency or in an ideal state, which reflects the basic ability of the torch to store magnetic energy without significant skin effect interference; and is the skin depth, and its expression is , which reflects the phenomenon that the effective conductive cross-sectional area decreases due to the current distribution tending to concentrate on the conductor surface under high-frequency working conditions; parameters represents the thickness of the torch conductor, which serves as a scaling parameter to measure the proportional relationship between the actual geometric size of the torch conductor and the skin depth; in this formula, the ratio is a dimensionless parameter, and its numerical value directly reflects the influence degree of the skin effect on the internal electromagnetic distribution of the conductor at the current operating frequency. When the torch operates at a relatively low frequency, due to the relatively large skin depth, has a high value, resulting in the exponential function tending to a relatively small value, so that the correction factor within the brackets approaches 1, that is is close to ; when the operating frequency increases and the skin depth decreases, this dimensionless parameter decreases, causing the exponential term to gradually approach 1. At this time, the subtraction term in the correction factor is close to 0.2, and finally the actually measured equivalent inductance is reduced to . This variation law is of great significance in the high-frequency induction heating torch ignition energy consumption optimization system, because it reveals that in a high-frequency working environment, due to the current mainly distributed along the conductor surface, the energy stored in the torch magnetic field shows an obvious downward trend, resulting in a decrease in the inductance value, which in turn affects the energy consumption and heating efficiency of the system.

[0031] Through this formula, the system can dynamically and real-time calculate the equivalent inductance at the current operating frequency, thus providing accurate parameter inputs for subsequent modules such as energy consumption calculation, objective function construction, and adaptive control. Furthermore, this formula not only reflects the trend of the inductance value changing with frequency, but also effectively incorporates the non-uniformity of the electromagnetic field distribution inside the torch into the calculation by introducing the ratio of the skin depth to the conductor thickness, making the model have higher accuracy and adaptability. Especially in practical applications, during the heating process of the torch, there may be factors such as temperature changes, material aging, and external electromagnetic environment fluctuations, which will all affect the resistivity and permeability of the conductor, thereby indirectly affecting the size of the skin depth. And this formula reflects this change by dynamically updating , so that the calculation result of the equivalent inductance always remains consistent with the actual working conditions. Thus, by comparing with the low-frequency inductance After correction, the formula accurately characterizes the actual energy storage capacity under high-frequency conditions, providing a theoretical basis for the transmission and storage of magnetic energy at the moment of torch ignition and also providing key parameters for system energy consumption optimization. It should be noted that the model adopts the form of an exponential decay function, reflecting the nonlinear characteristics in the physical process. That is, as the ratio of the skin depth to the conductor thickness changes, the correction effect of the inductance value does not change linearly but shows a certain attenuation trend, which is consistent with the situation where the current distribution gradually tends to saturation in the actual high-frequency electromagnetic phenomenon. By continuously calibrating the coefficients in the formula (such as 0.2 and 0.3), the adaptability of the model to different torch materials and geometric sizes can be further improved to ensure accurate prediction of the equivalent inductance of the torch under different working conditions.

[0032] Example 5: The ignition instantaneous energy consumption and eddy current loss model is expressed by the following formula: ; Where is the ignition instantaneous energy consumption and eddy current loss; is the average cross-sectional area of the torch; is the electrical conductivity of the torch material; is time the current at time is the current decay coefficient; is the average radius of the average cross-sectional area of the torch.

[0033] Specifically, in the formula, the first term adopts the form of This part reflects that at the moment of torch ignition, due to the high-frequency current flowing through the equivalent resistance after skin effect correction, the thermal energy dissipation is caused; among them, the square of characterizes the decisive role of the current in the thermal loss, while is accurately extracted through the previous modeling part and can dynamically reflect the actual resistance change of the torch due to uneven electromagnetic field distribution at the working frequency . At the same time, the exponential function form introduced in the denominator plays a role in modulating the smooth attenuation. This function uses the current decay coefficient to control the sensitivity of the energy consumption change when the deviation between the actual ignition time and the moment determined by the resonant frequency of the torch occurs, thus realizing the dynamic regulation of the energy transfer efficiency change near the resonant state of the torch. Its essence is to describe the nonlinear change of energy input during the torch ignition process in a mathematical way, so that the energy consumption at the ignition moment can be corrected accordingly with the change of the actual working state of the system. At the same time, the second term describes the energy consumption caused by the eddy current effect, where The electrical conductivity of the torch material directly determines the material's ability to respond to eddy currents. is the magnetic permeability, which reflects the ability of the torch material to store and release magnetic energy under high-frequency magnetic fields; in addition, The average radius represents the average cross-sectional area of ​​the torch, and its geometric dimensions have a decisive influence on the magnetic field distribution. is the skin depth, and its value is determined by the relationship between the resistivity, magnetic permeability and angular frequency of the material under high-frequency conditions, reflecting the physical property that the current is mainly distributed on the surface of the conductor under high-frequency induction heating conditions; parameter is the average cross-sectional area of ​​the torch, which determines the energy transfer capacity of the torch in the cross-sectional area direction. Therefore, this part of the energy consumption model mathematically adopts the square relationship between magnetic energy density and material parameters, reflecting the secondary coupling effect between energy density in the magnetic field and current and material magnetic parameters. The entire model comprehensively considers the complex coupling relationship between current, impedance, skin effect and eddy current loss during the ignition process of the torch, and considers both the direct heat energy loss generated by the flow of current and the eddy current effect induced by the high-frequency magnetic field in the material, so that the model can accurately reflect the energy consumption characteristics of the torch under the actual high-frequency working state. In practical applications, this model not only provides theoretical support for energy consumption optimization, but also provides real-time data support for the subsequent dynamic frequency adaptive control part, so that the system can dynamically monitor and regulate the input current and related parameters at the moment of ignition to achieve the best balance between energy consumption and heating efficiency. It is worth noting that the exponential function modulation term used in the formula is designed to smoothly transition the current attenuation process. When the torch working state is close to the resonant state, the energy loss changes little, and when it deviates far from the resonant state, it increases rapidly, thereby effectively preventing the instability caused by the drastic fluctuation of system parameters; and the second eddy current loss part quantitatively describes the process of energy loss in the high-frequency magnetic field in a non-ideal form through coupling with the skin depth and cross-sectional area. This dual energy consumption model reflects the present invention's profound understanding of complex electromagnetic effects in the high-frequency induction heating torch ignition energy consumption optimization system. It not only breaks through the limitations of the traditional single energy consumption calculation method, but also fully considers the interaction between current distribution, magnetic field energy storage and heat loss under high-frequency working conditions. Therefore, through in-depth research and optimization of the ignition instantaneous energy consumption and eddy current loss model, the system can ensure that the torch quickly reaches the predetermined heating effect while minimizing energy consumption losses, improving overall heating efficiency and system stability, and thus achieving efficient and energy-saving torch ignition goals.

[0034] Example 6: Calculate the total energy consumption by the following formula: ; in, is the upper limit of the heating time; is the energy deviation compensation term caused by non-ideal coupling and high-frequency effects, and is calculated using the following formula: ; wherein, is the peak current.

[0035] Specifically, when calculating the instantaneous energy consumption, the present invention adopts the basic heat energy loss theory based on the product of the square of the current and the equivalent resistance, and is supplemented by a modulation factor to smoothly describe the sensitivity of the energy consumption change of the torch when approaching the resonant state. This modulation effect can quickly reflect the reduction of the energy transmission efficiency when there is a large deviation between the operating frequency of the torch and its resonant frequency During this period, the system can accurately count the cumulative energy consumption from the start of heating to time and dynamically reflect the time-varying characteristics of the energy consumption of the torch during the entire ignition process through continuous integration, thereby providing a reliable data basis for the overall energy consumption optimization. However, in practical applications, due to the complex non-ideal coupling phenomenon involved in the high-frequency induction heating process and the problem of uneven local electromagnetic fields caused by high-frequency effects, there is often a certain deviation between the theoretically calculated instantaneous energy consumption and the actual energy consumption. To overcome this deficiency, this embodiment introduces a compensation term , whose main purpose is to correct the energy loss caused by non-ideal coupling and high-frequency effects. The design of the compensation term fully considers the important influence of the peak current during the torch ignition process, and at the same time introduces the deviation degree between the operating frequency and the resonant frequency. The deviation amount is non-linearly amplified through an exponential decay function, so as to automatically increase the compensation amplitude when the operating frequency of the torch is far from the resonant frequency, and make the compensation effect tend to be smaller when the frequency is close to the resonant state. This design concept not only ensures that the compensation term can reflect the difference between the actual energy consumption and the theoretical value in real time under different operating conditions, but also provides an effective correction mechanism for the local energy waste caused by high-frequency effects during the torch ignition process, so that the calculation result of the total energy consumption is closer to the actual operating conditions.

[0036] In the entire energy consumption calculation model, the integral term and the compensation term cooperate with each other to form a closed-loop feedback mechanism, ensuring that while the system dynamically accumulates the instantaneous energy consumption, it can also automatically correct the energy deviation caused by external disturbances, material parameter changes, frequency fluctuations, and other high-frequency effects. Through this method, the system not only realizes the comprehensive monitoring of energy transfer and loss during the torch ignition process, but also can maintain the accuracy and stability of the overall energy consumption calculation through the real-time adjustment of the compensation term when encountering internal nonlinear fluctuations or external environmental changes in the system. It can be said that this method theoretically breaks through the deficiencies of the traditional single integration method in high-frequency energy consumption calculation, enabling energy consumption assessment not to be limited to the simple superposition of instantaneous data, but to comprehensively consider the additional energy consumption caused by complex electromagnetic phenomena, thus achieving the goal of optimizing the energy consumption control during the torch ignition process. Furthermore, the total energy consumption calculation formula proposed in this embodiment has extremely high adaptability and practicality in engineering practice. Since the torch is often affected by various factors such as temperature changes, material aging, and electromagnetic environment fluctuations during actual operation, its high-frequency electromagnetic characteristics change subtly over time, and the combination of integral operation and compensation mechanism is designed specifically for this dynamic characteristic. By continuously integrating the instantaneous energy consumption data at each moment during the heating process, the system can capture the subtle differences in energy consumption at the initial, middle, and final stages of the torch ignition; while the compensation term automatically adjusts the system energy compensation amount by real-time feedback of the relationship between the working frequency and the resonant frequency of the torch, thereby achieving the dynamic balance and control of the overall energy consumption.

[0037] Embodiment 7: Target Optimization Function It is expressed by the following formula: ; The optimization goal is: ; subject to the following constraints: ; ; ; By solving the optimization goal of the optimization function The peak current under the optimization goal and constraints , frequency and the upper limit of the heating time , the torch is heated.

[0038] Specifically, the construction of this target optimization function fully considers that during the high-frequency induction heating process of the torch, due to the current in the conductor being mainly distributed on the surface under the influence of the skin effect, the actual effective current flowing through is significantly different from that under low-frequency conditions. Therefore, an equivalent resistance corrected by the skin effect is introduced into the model, and its expression contains the reference resistance and a correction factor determined by a weight parameter , an exponential parameter and a modulation parameter . The correction factor smooths the deviation between the torch operating frequency and the resonance frequency through a transcendental function , such that when the torch operating frequency approaches the resonance state, the resistance correction effect is weak, and when it deviates from the resonance state, the correction effect rapidly increases, thus truly reflecting the energy loss characteristics of the torch under high-frequency heating conditions. At the same time, a second part describing eddy current loss is also introduced into the objective function. This part characterizes the energy loss phenomenon generated by eddy currents in a high-frequency magnetic field in a quadratic coupling form through parameters such as the conductivity , permeability of the torch material, the cross-sectional area of the torch, and the average radius . Combining with the parameter of the skin depth , it reflects the energy dissipation induced by the magnetic field under high-frequency conditions. In order to fully embody the dynamic characteristics of the instantaneous energy consumption and eddy current loss during the torch ignition process, the objective optimization function adopts an integral method to accumulate the energy consumption from the initial moment to the heating time upper limit within the entire heating cycle, and simultaneously considers the non-uniformity of the instantaneous energy consumption varying with time in the integral expression. By continuously summing the integral expression, the system can obtain a theoretical value representing the total energy consumption within the entire heating cycle.

[0039] However, due to the influence of non-ideal coupling and high-frequency effects during the actual heating process, there is a deviation between the theoretical model and the actual energy consumption. Therefore, a compensation term is additionally set in the objective function. This compensation term is closely related to the peak current , the operating frequency and the degree of deviation between the torch and the resonance state. Its design idea is to non-linearly amplify and correct the energy consumption error caused by non-ideal factors using an exponential decay function, such that when the torch operating frequency is far from the resonance frequency, the compensation term rapidly increases to make up for the additional energy loss caused by high-frequency effects; while when the operating frequency approaches the resonance state, the influence of the compensation term weakens accordingly, ensuring that the system energy consumption calculation is more in line with the actual operating conditions. Therefore, this objective optimization function not only organically integrates the theoretical calculations of instantaneous energy consumption and eddy current loss, but also corrects the energy consumption deviation caused by system non-ideality through a compensation mechanism, making the overall model theoretically more accurate and adaptable. In this optimization model, the optimization objective of the system is to minimize , that is, by solving To determine the optimal parameter combination, the specific implementation process is to take the partial derivatives of the objective function with respect to the peak current , the operating frequency , and the upper limit of the heating time , and set the partial derivatives equal to zero, thereby obtaining the parameter solutions that satisfy the optimization conditions. This method embodies the extreme value principle and the optimal control theory in mathematics, and dynamically adjusts each key parameter through the continuous feedback of the actual system data to achieve closed-loop adaptive control. In fact, due to the time-varying and non-linear characteristics of the electromagnetic parameters exhibited by the torch during high-frequency induction heating, the system not only needs to theoretically construct a rigorous energy consumption optimization model, but also must be able to obtain the dynamic data of the torch working state in real time, and use sensors and feedback mechanisms to update the model parameters to ensure that the optimal parameters obtained can truly reflect the current working conditions of the torch. Through this global optimization method, the torch can obtain the optimal combination of current, frequency, and upper limit of heating time at the moment of ignition, so as to meet the requirements of rapid ignition heating while minimizing the overall energy consumption and reducing the energy loss caused by the high-frequency effect. Further, each parameter in the objective optimization function not only has a clear physical meaning in mathematical expression, but also has been verified by a large amount of experimental data in engineering applications. The fitting accuracy of the model can be further improved by adjusting the weight parameters and modulation coefficients, so that the system can maintain excellent energy consumption control effects under different working conditions. Especially in the actual application environment, due to the influence of external temperature, material aging, and other uncertain factors, the working state of the torch may change slightly. The objective function can quickly respond to these changes through the dynamic integration of instantaneous energy consumption and eddy current loss and the real-time correction of the compensation term, and then achieve adaptive control through feedback regulation. This energy consumption optimization method based on the optimization objective function not only theoretically describes all energy consumption factors in the high-frequency induction heating torch ignition process, but also significantly improves the ignition efficiency and reduces energy consumption waste through the joint optimization of key parameters in the actual control strategy, thus realizing the improvement of the overall performance of the system.

[0040] Example 8: Dynamically and adaptively adjust the current through the following formula: ; where is the initial current; is the set current adaptive adjustment amplitude; is the time when the current is; is the time when the current is.

[0041] Specifically, in the formula, is adjusted not only by the current operating frequency, but also in combination with the historical time points and the current change trend to ensure that the current regulation process will not cause system instability due to mutations. Specifically, this item ensures that the current regulation can be synchronized with the current operating frequency of the torch, thus reducing the electromagnetic field mismatch problem caused by frequency drift, while this item corrects the current change amplitude in a non-linear manner by performing a logarithmic transformation on the change rate of the historical current difference, so that when the current change rate is small, the adjustment amplitude tends to be gentle, and when the current change rate is large, the system can respond in a timely manner, thus ensuring the smoothness and optimization of the energy input during the ignition process. The key role of this mechanism lies in introducing dynamic feedback of current change, enabling the system to make adaptive adjustments according to the actual working conditions and improving the stability and energy efficiency of the entire torch ignition process. The theoretical basis of this method stems from the current distribution characteristics in the conductor during the high-frequency induction heating process and the non-linear dynamic response of the electromagnetic induction system. Under high-frequency working conditions, the current in the torch conductor is affected by the skin effect, causing it to be mainly concentrated on the surface of the conductor. This phenomenon makes the current density show significant dynamic changes in time and space. If the current control strategy only adopts a fixed amplitude or linear adjustment method, it is difficult to adapt to the complex electromagnetic environment during the torch ignition process, which may lead to local overheating or a decrease in energy utilization efficiency. Therefore, the present invention proposes a dynamic adaptive adjustment method based on the historical current change rate. The unique feature of this method is that it uses the data of the previous two time steps as inputs, calculates the current change trend, and performs non-linear correction on its influence through logarithmic transformation, making the current adjustment process of the system smoother and having an adaptive characteristic.

[0042] Especially in practical applications, the working state of the torch may be affected by factors such as changes in material properties, environmental temperature fluctuations, and system electromagnetic field interference. The adaptive adjustment strategy adopted by this method can maintain the stability and optimality of the current input under these changing external conditions. For example, when the torch enters the high-frequency resonance state, the current change rate of the system is relatively stable. At this time the value of is small, weakening the influence of the adjustment item and making the current adjustment tend to be stable, thus ensuring that no additional energy fluctuations will occur when the system is operating efficiently. When the torch frequency shifts, or when the electromagnetic field distribution of the system changes due to a sudden change in the current input, this method can respond quickly by increasing The influence weight of the item enhances the current adjustment amplitude accordingly, thereby promptly correcting the energy input state of the system and enabling the torch to quickly return to the optimal working state. In addition, the mathematical structure of this method fully considers the non-linear characteristics in the high-frequency induction heating process. Especially by introducing the logarithmic correction term, the change rate of the current adjustment is not a simple linear relationship, but dynamically adjusted according to the magnitude of the historical change rate of the current. This mechanism ensures that the system can maintain a strong adaptive ability under different working conditions and at the same time avoids the system oscillation problem that may be caused by too fast adjustment rate. In fact, the application of this method in engineering practice shows that compared with the traditional fixed current control or simple linear adjustment method, the adaptive current adjustment method proposed by the present invention can effectively reduce the energy loss during the ignition process and improve the stability of the system, enabling the torch to complete the ignition process under the optimal energy consumption conditions, improving the overall heating efficiency and extending the equipment life. Further, the advantage of this method is also reflected in its high compatibility with the high-frequency induction heating torch ignition energy consumption optimization system. Since the energy consumption optimization objective function of the system has been solved based on the coupling relationship of current, frequency and time, and the proposed adaptive adjustment method is to make the actual input of the current consistent with the optimized calculation result on the basis of ensuring the energy consumption optimization, avoiding the deviation caused by the change of the external environment or the internal system state. In other words, this method not only realizes the dynamic adjustment of the current input, but also constructs a real-time control mechanism that matches the overall energy consumption optimization framework, making the energy management of the torch ignition process more accurate and ensuring that the system always operates on the optimal control curve.

[0043] Example 9: Adaptive adjustment amplitude of current The value range of is

[0044] Specifically, choosing this range first reflects the requirement for extremely high-precision control of the torch current input. It is neither allowed to make the adjustment amplitude too large, resulting in too fast current change and causing system oscillation or energy waste, nor to make the adjustment amplitude too small, unable to respond promptly to the instantaneous deviation caused by external environment or internal parameter fluctuations, thus unable to achieve the real-time optimization of energy consumption and heat distribution under high-frequency electromagnetic field conditions. During the torch ignition process, the current generated by high-frequency electromagnetic induction is mainly concentrated on the surface layer of the conductor due to the skin effect, resulting in a local amplification phenomenon in the actual effective current distribution. And this phenomenon is summarized as parameters such as the corrected equivalent resistance and equivalent inductance in the instantaneous energy consumption calculation. By finely measuring these parameters and calibrating the model, the accurate current response curve of the torch under different working conditions can be obtained. Therefore, the lower limit of ΔI is set as , in fact, it is to ensure that within an extremely small range of changes, the system can capture the weak signals of current fluctuations, so as to make a detailed adjustment to the electromagnetic field distribution and local heat conduction; and the upper limit is limited to is to prevent unstable phenomena caused by over-large current adjustments. For example, too rapid current fluctuations may cause a sharp rise in the temperature inside the torch, leading to problems such as local overheating or a decrease in material properties. It is this scientific setting of the upper and lower limit ranges that enables the entire system to maintain a high dynamic response speed when facing actual complex working conditions, and at the same time ensures the smoothness and continuity of energy consumption changes during the ignition process, thus achieving the optimal control of global energy consumption.

[0045] Although the specific implementation manners of the present invention are described above, those skilled in the art should understand that these specific implementation manners are only examples. Without departing from the principle and essence of the present invention, those skilled in the art can make various omissions, substitutions and changes to the details of the above methods and systems. For example, combining the above method steps, thus performing substantially the same functions in a substantially the same way to achieve substantially the same results belongs to the scope of the present invention. Therefore, the scope of the present invention is only defined by the appended claims.

Claims

1. High-frequency induction heating torch ignition energy consumption optimization system, characterized in that, The system includes: a system modeling part, an energy consumption optimization part, and a dynamic frequency adaptive control part; the system modeling part is used to perform modeling on the high-frequency impedance during torch heating with skin effect correction, separate the equivalent resistance and equivalent inductance from the modeled high-frequency impedance, and establish an ignition instantaneous energy consumption and eddy current loss model based on this to calculate the total energy consumption; the energy consumption optimization part is used to establish a comprehensive energy consumption optimization objective function during torch heating according to the high-frequency effect and skin effect during torch heating, combined with the ignition instantaneous energy consumption and eddy current loss model, and find the current peak, frequency, and upper limit of heating time corresponding to the minimum value of the comprehensive energy consumption optimization objective function; the dynamic frequency adaptive control part is used to heat the torch according to the current peak, frequency, and upper limit of heating time corresponding to the minimum value of the comprehensive energy consumption optimization objective function, and perform dynamic adaptive adjustment on the current.

2. The high-frequency induction heating torch ignition energy consumption optimization system according to claim 1, characterized in that, The modeled high-frequency impedance is expressed as: ； Among them, is the high-frequency impedance at a frequency of . is the imaginary symbol; is the phase; is the equivalent inductance at a frequency of . is the equivalent resistance at a frequency of .

3. The high-frequency induction heating torch ignition energy consumption optimization system according to claim 2, wherein, The equivalent resistance at a frequency of separated from the modeled high-frequency impedance is expressed using the following formula: ； Among them, is the reference resistance of the torch; is the conductor thickness of the torch; is the skin depth; is the resistivity of the torch; is the magnetic permeability of the torch; is the weight parameter; is the exponential weight parameter; is the modulation parameter; is the resonance frequency of the torch; is the equivalent capacitance.

4. The high-frequency induction heating torch ignition energy consumption optimization system according to claim 3, characterized in that The equivalent inductance at a frequency of separated from the modeled high-frequency impedance is expressed by the following formula: ； Among them, is a low-frequency inductor.

5. The high-frequency induction heating torch ignition energy consumption optimization system according to claim 4, characterized in that The ignition instantaneous energy consumption and eddy current loss model is expressed using the following formula: ； Among them, is the instantaneous ignition energy consumption and eddy current loss; is the average cross-sectional area of the torch; is the electrical conductivity of the torch material; is time is the current at that time; is the current decay coefficient; is the average radius of the average cross-sectional area of the torch.

6. The high-frequency induction heating torch ignition energy consumption optimization system according to claim 5, characterized in that The total energy consumption is calculated through the following formula: ； Among them, is the upper limit of the heating time; is the energy deviation compensation term caused by non-ideal coupling and high-frequency effects, and is calculated using the following formula: ； Among them, is the peak current.

7. The high-frequency induction heating torch ignition energy consumption optimization system according to claim 6, wherein, Objective optimization function It is represented by the following formula: ； The optimization objective is: ; and the following constraint conditions are satisfied: ； ； ； Optimizing the objective function of the optimization goal The peak current under the optimization goal and constraints , frequency and the upper limit of the heating time , to heat the torch.

8. The high-frequency induction heating torch ignition energy consumption optimization system according to claim 7, wherein The current is dynamically and adaptively adjusted through the following formula: ； Among them, is the initial current; is the set current self - adaptive adjustment amplitude; is time the current at time is time the current at time 9. The high-frequency induction heating torch ignition energy consumption optimization system according to claim 8, wherein Current self - adaptive adjustment amplitude The value range is .

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