Control system and control method of LLC resonant induction heating power supply

Abstract

The application provides a control system and a control method of an LLC resonant induction heating power supply. The LLC resonant induction heating power supply heats a load through a half-bridge inverter circuit. The control system comprises a modulation unit and an odd harmonic control unit. The modulation unit is used to determine a target modulation index and a fundamental frequency, and to realize an output frequency adjustable high-frequency alternating square wave by controlling the switching of each power device of the half-bridge inverter circuit. The waveform of the high-frequency alternating square wave has a half-wave symmetric structure with a fundamental period as a cycle. The odd harmonic control unit is used to predict an optimal switching angle combination of each power device under the condition of meeting an odd harmonic suppression target. The modulation unit generates a modulation signal for controlling the switching of each power device based on the optimal switching angle combination. The application can significantly improve the harmonic suppression effect of a high-frequency induction heating power supply under a dynamic load.

Description

Technical Field

[0001] This application belongs to the field of induction heating power supply technology, specifically providing a control system and control method for an LLC resonant induction heating power supply. Background Technology

[0002] Induction heating power supplies serve as core components in industrial heat treatment systems, widely used in heating and metal processing. Their performance directly impacts the efficiency and quality of the heating process. Traditional induction heating power supply systems typically rely on high-frequency resonant circuits for energy conversion. However, in actual operation, due to nonlinear load characteristics and dynamically changing operating conditions, power supply systems often experience power quality degradation. In particular, the accumulation of harmonic components in the voltage and current waveforms severely affects system energy efficiency and may lead to electromagnetic compatibility issues, thereby interfering with surrounding electronic equipment.

[0003] Furthermore, key components in resonant circuits, such as capacitors and inductors, age during temperature fluctuations and long-term use, causing their parameters to shift. This shift can lead to resonant point mismatch, resulting in unstable power output and potentially causing abnormally high current, which can damage power switching devices. Existing protection systems typically rely on static threshold judgment methods, lacking adaptability to dynamic changes, failing to accurately capture fault characteristics, and exhibiting slow response times, making timely protection difficult and increasing the risk of equipment damage.

[0004] Existing technologies have limitations in addressing the aforementioned problems. While passive filtering methods can reduce harmonics through multi-stage filtering networks, their effectiveness is limited and they struggle to adapt to rapid changes under complex operating conditions. On the other hand, active control methods based on resonant feature point detection, although capable of identifying resonant mismatches, are susceptible to operating condition interference, leading to reduced detection accuracy and the risk of misjudgment. In summary, existing technologies fail to effectively resolve the contradiction between harmonic elimination and maintaining resonant stability. Therefore, a new method is needed to improve system stability and efficiency, reduce harmonic impact, and ensure the reliability of the power supply system. Summary of the Invention

[0005] To address the problems existing in the prior art and to achieve precise control of the LLC resonant induction heating power supply, this application provides a control system for the LLC resonant induction heating power supply through an embodiment. The LLC resonant induction heating power supply heats the load through a half-bridge inverter circuit. The control system includes a modulation unit, which is used to determine the target modulation index and the fundamental frequency, and to achieve an adjustable frequency high-frequency AC square wave output by controlling the switching of each power device in the half-bridge inverter circuit. The waveform of the high-frequency AC square wave is periodic with the fundamental duration and has a half-wave symmetrical structure.

[0006] The control system further includes an odd harmonic control unit, which predicts the optimal switching angle combination of each power device under the odd harmonic suppression target. The modulation unit generates a modulation signal for controlling the switching of each power device based on the optimal switching angle combination.

[0007] Preferably, the target for odd-order harmonic suppression is:

[0008]

[0009] Where M is the target modulation index, M min M max Let M be the lower and upper bounds, respectively. i∈[1,4] represents the optimal switching angle combination, 2n+1 represents the order expression of the odd harmonics to be suppressed, and N is the upper limit of n.

[0010] Preferably, the odd harmonic control unit uses a trained artificial neural network to predict and output the optimal switching angle combination with the target modulation index as input, wherein the training set for training the artificial neural network is obtained by searching an enhanced particle swarm optimization algorithm based on switching angle sorting constraints and modulation index constraints.

[0011] Preferably, the enhanced particle swarm optimization algorithm employs a main-subgroup hierarchical search strategy. The search objectives for the main-subgroup fitness function and the subgroup fitness function are respectively satisfied as preset search objectives for the main-iterative search process and the sub-iterative search process. The algorithm iteratively searches for the optimal switching angle combination corresponding to each modulation index in the switching angle search space. Specifically, the main-subgroup hierarchical search strategy involves: in each main-iterative search process, firstly, controlling all search particles to execute the main-subgroup search strategy to search with the modulation index as the objective; then, controlling each search particle to execute the subgroup search strategy at least once in the sub-iterative search process to search with the objective of suppressing odd harmonics and satisfying the switching angle sorting constraint and the modulation index constraint.

[0012] Preferably, the primary group fitness function FF0 is:

[0013]

[0014] The subgroup fitness function FF h for:

[0015]

[0016] Among them, V1 * V1 represents the target fundamental frequency amplitude determined based on the target modulation index, and V2 represents the actual fundamental frequency amplitude. hLet w0 be the amplitude of the h-th harmonic, and w be the amplitude of the h-th harmonic. h λ1 and λ2 are the weighting coefficients corresponding to the fundamental amplitude error and the amplitude errors of each odd harmonic, respectively; λ1 and λ2 are the penalty factors for violating the angle constraint and modulation index constraint, respectively; P violation Penalty item for incorrect switching angle sequence; P M This is a penalty term for the modulation index M exceeding the legal range.

[0017] Preferably, during each iteration of the search process, each search particle also performs a perturbation update action, the magnitude of which is determined based on the sinusoidal perturbation model shown below:

[0018] Δθ i =A·sin(2πf) i ×k+φ i ), i∈[1,4],

[0019] Where, Δθ i Let f be the angular disturbance of the i-th switching angle, A be the disturbance amplitude, and f be the angular disturbance. i φ i denoted as the perturbation frequency and initial phase of the i-th switching angle, respectively, and k is the current search iteration number.

[0020] Preferably, the control system further includes: an anomaly detection unit, which performs real-time monitoring of the degree of resonant frequency drift of the LLC resonant induction heating power supply based on the measured values ​​of the secondary side current peak and the load capacity.

[0021] Furthermore, the real-time monitoring operation monitors the degree of resonant frequency drift by determining whether the measured values ​​of the secondary current peak and the load capacity exceed the normal operating range. The normal operating range is located between the load capacity-secondary current peak slope corresponding to the ideal resonant frequency and the load capacity-secondary current peak slope corresponding to the upper limit of resonant frequency drift.

[0022] Furthermore, the slope of the load capacity-secondary current peak slope corresponding to the upper limit of the resonant frequency drift is K. a The slope of the curve representing the load capacity minus the peak value of the secondary current corresponding to the ideal resonant frequency is K. b And K a With K b The ratio is the reciprocal of the ratio of the secondary current duration 'a' corresponding to the upper limit of the resonant frequency drift and the secondary current duration 'b' corresponding to the ideal resonant frequency under the same load capacity.

[0023] This application also provides a control method for an LLC resonant induction heating power supply through embodiments. This control method uses the aforementioned control system of the LLC resonant induction heating power supply to control the LLC resonant induction heating power supply to heat the load.

[0024] The embodiments of this application provide a control system and control method for an LLC resonant induction heating power supply. First, even harmonics are eliminated by reasonably constructing the modulation signal waveform. Then, by introducing a trained neural network model to search for the optimal switching angle corresponding to the modulation index, real-time suppression of odd harmonics other than the fundamental wave is achieved, which greatly reduces the real-time calculation burden and significantly improves the harmonic suppression effect of the high-frequency induction heating power supply under dynamic load.

[0025] Secondly, the training data for the neural network model for suppressing odd harmonics is generated using an enhanced particle swarm optimization algorithm. During the search for the optimal switching angle combination corresponding to each modulation index, a hierarchical search strategy with a "main group-auxiliary group" structure is employed, taking into account the specific requirements of the high-frequency induction heating power supply regarding real-time control, switching angle feasibility, and the periodic structure of the angle, to effectively improve the coverage and efficiency of multi-objective optimization. Furthermore, a sorting constraint mechanism and modulation index constraint are introduced to avoid illegal or physically unrealizable switching angle combinations. Penalties are imposed for behaviors such as failure to achieve harmonic suppression targets, overlapping opening angles, and exceeding modulation index limits, thereby strengthening the convergence guidance capability of the optimization algorithm within the valid solution space. In addition, a sinusoidal perturbation function suitable for the periodic structure of the angle space is adopted to enhance the periodic matching and jump rationality of the search direction, further improving the search efficiency and convergence quality of the algorithm in the switching angle optimization task.

[0026] Furthermore, the control system and control method provided in this application accurately identify resonance detuning problems caused by load mutations, coil aging, or capacitor parameter drift by real-time monitoring of the dynamic relationship between the peak resonant current and the load capacity. This effectively improves the safety detection sensitivity of the LLC resonant induction heating power supply, reduces energy loss and equipment downtime risks caused by detuning, and extends the life of key components. Attached Figure Description

[0027] Figure 1 This is a circuit schematic diagram of an LLC resonant induction heating power supply.

[0028] Figure 2 This is a schematic diagram of the architecture of a control system for an LLC resonant induction heating power supply provided according to some embodiments of this application;

[0029] Figure 3 This is a schematic diagram illustrating an implementation of an odd harmonic control unit according to some embodiments of this application;

[0030] Figure 4 A flowchart of an enhanced particle swarm optimization algorithm provided according to some embodiments of this application;

[0031] Figure 5This is a schematic diagram of the secondary voltage waveforms before and after suppressing odd harmonics in a specific simulation example;

[0032] Figure 6A This is a schematic diagram showing the measured induced voltage of a high-frequency LLC resonant induction heating power supply before harmonic suppression in a specific embodiment.

[0033] Figure 6B This is a schematic diagram illustrating the measured induced voltage of a high-frequency LLC resonant induction heating power supply after harmonic suppression using the control system provided in this application, in a specific embodiment.

[0034] Figure 7 This is a schematic diagram of the architecture of a control system for an LLC resonant induction heating power supply provided according to some other embodiments of this application;

[0035] Figure 8 A schematic diagram of the secondary current waveform after the rated resonant frequency and the resonant frequency shift.

[0036] Figure 9 This is a schematic diagram of the normal operating region of an LLC resonant heating power supply provided according to an embodiment of this application. Detailed Implementation

[0037] The present application will now be further described based on preferred embodiments and with reference to the accompanying drawings.

[0038] In the description of the embodiments of this application, it should be noted that if terms such as "upper," "lower," "inner," or "outer" are used to indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product of this application is in use, they are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on this application. In addition, in the description of this application, in order to distinguish different units, the terms "first," "second," etc. are used in this specification, but these are not limited by the manufacturing order, nor should they be construed as indicating or implying relative importance. Their names may differ in the detailed description and claims of this application.

[0039] The vocabulary used in this specification is for illustrative purposes and is not intended to limit the scope of this application. It should also be noted that, unless otherwise expressly specified and limited, the terms "set," "connected," and "linked" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection, a direct connection, or an indirect connection via an intermediate medium; or they can refer to the internal communication between two components. Those skilled in the art will understand the specific meaning of these terms in this application.

[0040] Figure 1 Here is a circuit diagram of an existing LLC resonant induction heating power supply, such as... Figure 1 As shown, this LLC resonant induction heating circuit mainly consists of a rectifier section, a half-bridge inverter circuit section, and a load section. The rectifier section is connected to the three-phase AC power grid of the industrial grid, and the AC power is rectified into DC bus voltage Vdc through a three-phase uncontrolled rectifier bridge. The half-bridge inverter circuit consists of two power devices (such as IGBT switching transistors) S1 and S2, and two voltage divider capacitors C1 and C2 of equal capacity. By sending frequency modulation signals with a duty cycle of approximately 50% to the gates of S1 and S2 respectively, the switching of S1 and S2 can be controlled, thereby generating a high-frequency square wave with adjustable frequency (in order to achieve effective heating of the workpiece, the frequency can reach tens of kHz in some high-frequency induction heating circuits).

[0041] The high-frequency square wave is coupled to the secondary coil through the primary coil to achieve voltage transformation and electrical isolation before being output to the load section. The load section adopts an LLC resonant topology, including a series resonant inductor Ls, a parallel resonant capacitor Cr, as well as a load equivalent inductance Lr and a load equivalent resistance R. The resonant network can generate a high-frequency current close to a sine wave, ultimately achieving effective induction heating of the workpiece.

[0042] The working process of this LLC resonant induction heating power supply is as follows:

[0043] 1) Initial state: At the initial moment, assume that S1 and S2 are both in the off state, and C1 and C2 are charged through the load, so that the voltage across them is half of the power supply voltage, that is, Vc1=Vc2=Vdc / 2.

[0044] 2) S1 is on, S2 is off: When the control signal turns on S1, C1 discharges through S1 and its voltage gradually decreases. At the same time, because S1 is on, the power supply voltage Vdc charges C2 through S1, causing the voltage across C2 to gradually increase. During this process, the voltage on the load is part of the positive half-cycle waveform. The specific voltage value depends on the charging and discharging state of C1 and C2.

[0045] 3) Both S1 and S2 are off: When the control signal of S1 disappears, S1 changes from the on state to the off state. At this time, due to the presence of inductance (usually the primary winding of a transformer or other inductive load), the current in the load cannot immediately become zero, but gradually decreases. During this process, the current in the load continues to flow, but in the opposite direction to before, causing C1 to be charged and C2 to be discharged. Finally, when the current in the load drops to zero, the voltage across C1 returns to Vdc / 2, and the voltage across C2 also returns to Vdc / 2, and the system returns to the initial state.

[0046] 4) S2 is on, S1 is off: When the control signal turns on S2, the process is similar to the above, but in the opposite direction. C2 discharges through S2, and its voltage gradually decreases. At the same time, the power supply voltage Vdc charges C1 through S2, causing the voltage across C1 to gradually increase. During this process, the voltage on the load is part of the negative half-cycle waveform.

[0047] During the heating process of the workpiece, the above four states are repeatedly cycled, resulting in an alternating voltage on the load, thereby realizing power output. The frequency and amplitude of the alternating voltage applied to the load can be adjusted by changing the modulation signals of S1 and S2. In order to characterize the modulation signal of the power device, in the embodiments of this application, the angle (i.e., phase) corresponding to the opening or closing of each power device in a complete cycle is defined as the switching angle θ. In the process of modulating and controlling the half-bridge inverter circuit, in order to avoid the two power devices from conducting at the same time, it is generally necessary to set a dead time so that the modulation signals of the two power devices are offset to a certain extent on the basis of mutual complementarity. Therefore, the control parameters of each power device need to be characterized by two switching angles, and the switching angles of the two power devices need to satisfy a specific order and are not completely complementary. Therefore, the power output state of the half-bridge inverter circuit can be described by a set of four switching angles θ1 to θ4.

[0048] In addition to the fundamental current that can heat the workpiece, the current output by the aforementioned half-bridge inverter circuit often includes various high-order harmonic currents. Harmonic currents increase the power loss of the equipment, causing overheating of components such as transformers and inductors, and also increase reactive power, thereby reducing power efficiency. Therefore, it is necessary to optimize the switching angle combination θ1~θ4 to suppress each harmonic, so that the waveform loaded onto the load reaches the desired target.

[0049] To effectively suppress harmonic currents, some embodiments of this application provide a control system for an LLC resonant induction heating power supply, see reference. Figure 2 The control system includes a modulation unit and an odd harmonic control unit.

[0050] The modulation unit is used to determine the target modulation index M and the fundamental frequency, and to achieve an adjustable high-frequency AC square wave output by controlling the switching of the power devices S1 and S2 in the half-bridge inverter circuit. In the embodiments of this application, the waveform of the high-frequency AC square wave has a half-wave symmetry structure with the fundamental duration as the period. That is, within a complete control cycle of 0 to 2π, the switching angles of S1 and S2 are defined in the 0 to π region, and the switching angles in the π to 2π region are generated by reverse mirroring, so that the output waveform within the complete cycle satisfies the half-wave symmetry condition. Since when a periodic signal has half-wave symmetry, all even harmonics (including the 2nd, 4th, 6th, 8th, etc.) in its spectrum will be automatically eliminated and will no longer appear in the output voltage. Therefore, through this modulation signal waveform control method, it is not necessary to consider suppressing even harmonics, but only to selectively suppress odd harmonics such as the 3rd, 5th, 7th, and 9th harmonics, thereby significantly reducing the complexity of system control while achieving harmonic suppression.

[0051] In the embodiments of this application, the odd harmonic control unit is used to predict the optimal switching angle combination of each power device while satisfying the odd harmonic suppression target. i∈[1,4], the predicted optimal switching angle combination is output to the modulation unit. The modulation unit then generates the modulation signal output to the gates of power devices S1 and S2 based on the optimal switching angle combination, combined with the odd harmonic frequency and the half-wave symmetry characteristic that the high-frequency AC square wave should have.

[0052] Fourier analysis can be used to calculate the relationship between each harmonic component and the output signal. Fourier analysis decomposes a periodic signal into multiple harmonics of different frequencies. Through Fourier series expansion, the amplitude and phase of each harmonic can be clearly obtained. Therefore, the output voltage of a half-bridge inverter circuit can be characterized and calculated using Fourier analysis, thus providing a quantitative basis for selective harmonic cancellation.

[0053] The high-frequency AC square wave output by the half-bridge inverter circuit can be expanded using Fourier series. When its waveform has a half-wave symmetrical structure and the DC component is 0, its fundamental wave and each odd harmonic can be expressed as equations (1) and (2):

[0054]

[0055]

[0056] Here, 2n+1 represents the order expression of the odd harmonics that need to be suppressed, and N represents the upper limit of n. For example, when N equals 4, the value of n is 1, 2, 3, 4, which means that the 3rd, 5th, 7th, and 9th harmonics need to be suppressed.

[0057] Obviously, the ideal output waveform for heating the workpiece should ensure that V1 and each odd harmonic V3...V 2N+1 The higher the ratio, the better; that is, the optimal switching angle combination. i∈[1,4] should satisfy the odd harmonic suppression target as shown in equation (3):

[0058]

[0059] Equation (3) indicates that when the four switching angles of the modulation signal are in the optimal switching angle combination, these four switching angles... The sum of the cosine functions of the four switching angles is a non-zero value M, and the sum of the cosine functions of each odd multiple of the four switching angles is zero.

[0060] Equation (3) not only gives the conditions that each switching angle needs to satisfy under the condition that each odd harmonic is suppressed, but also gives the amplitude characteristics of the fundamental wave when these conditions are satisfied, i.e. In this application, M is defined as the target modulation index.

[0061] The target modulation index M characterizes the ratio between the fundamental amplitude and the DC bus voltage under the premise that all harmonics are well suppressed. Therefore, it can be used to evaluate the utilization rate of input power while ensuring harmonic suppression. Generally, increasing the value of M can effectively improve the heating efficiency of the workpiece. However, in high-frequency induction heating, an excessively high M may have adverse effects: First, an excessively large M will cause severe distortion of the output waveform, increase the unsuppressed higher-order harmonic components, and weaken the harmonic suppression effect; second, an excessively high fundamental amplitude may cause overvoltage in the inverter circuit devices, increasing the risk of device damage; third, in the selective harmonic elimination process, when M approaches or even reaches 1, there may be no feasible solution for the switching angle combination or extreme switching angle configurations may be required, making optimization difficult and control unstable. Therefore, in some preferred embodiments of this application, the target modulation index needs to be at the lower limit M. min and upper limit M max Between, that is, M∈[M min M max To balance power control accuracy, harmonic optimization effect, and system operational reliability, M min Preferably not less than 0.35, M max Preferably, it should not exceed 0.7.

[0062] Figure 3 This diagram illustrates, in some specific embodiments, the modulation unit and the odd harmonic control unit collaboratively controlling the half-bridge inverter circuit, with reference to... Figure 3The modulation unit can estimate the required load power capacity based on the specific heating requirements of the workpiece, and then determine the appropriate fundamental frequency and amplitude. Combined with the DC bus voltage, it determines the target modulation index M. Upon receiving the target modulation index M, the odd-order harmonic control unit uses it as input to predict and output the optimal switching angle combination. i∈[1,4], and then feed it back to the modulation unit, which generates a modulation signal with the optimal switching angle combination and half-wave symmetry, and uses the generated modulation signal to control power devices S1 and S2.

[0063] As analyzed above, the target modulation index M is determined based on the workpiece heating requirements and the input voltage, within the range [M]. min M max Since the switching angle combination is a continuously varying quantity within the target modulation index, searching for the optimal switching angle combination based on the target modulation index needs to meet both speed and accuracy requirements. Although a lookup table method can quickly search for the optimal switching angle combination, it can only perform fast searches based on discrete M values. For M values ​​not in the table, due to the nonlinear characteristics of the switching angle combination, prediction based on interpolation may not yield an ideal switching angle combination. Therefore, in a preferred embodiment of this application, such as... Figure 3 As shown, the odd harmonic control unit uses a trained artificial neural network to predict the optimal combination of switching angles.

[0064] Artificial neural networks can be implemented using various neural network models known to those skilled in the art, such as feedforward neural networks and deep learning networks. In some specific embodiments, an artificial neural network may include an input layer (modulation index M), a hidden layer (4 neurons, Tanh activation), and an output layer (4 neurons, corresponding to switching angles). The artificial neural network can be trained using multiple pre-generated sets (M ~ optimal switching angle combination). The training process takes the ability of each output switching angle to achieve the desired fundamental amplitude and harmonic amplitude as the optimization objective. Through training with a large number of samples, the ability to predict the optimal switching angle combination based on the input modulation index M is obtained.

[0065] Since the input to the artificial neural network is the target modulation index M, whose value has a clear physical meaning, the data used to train the artificial neural network needs to meet specific physical constraints. Therefore, in the preferred embodiment of this application, each training data in the training set is obtained by searching using an enhanced particle swarm optimization algorithm based on switching angle sorting constraints and modulation index constraints.

[0066] Specifically, this enhanced particle swarm optimization algorithm employs a master-subgroup hierarchical search strategy. Satisfying the preset master-subgroup fitness function and subgroup fitness function are the search objectives for the master-subgroup iterative search and sub-subgroup iterative search processes, respectively. It iteratively searches for the optimal switching angle combination corresponding to each modulation index in the switching angle search space. Specifically, the master-subgroup hierarchical search strategy works as follows: In each master-subgroup iterative search process, all search particles first execute the master-subgroup search strategy to search for the modulation index. Then, each search particle executes the subgroup search strategy at least once in the sub-subgroup iterative search process to suppress odd harmonics and satisfy the switching angle ordering constraint and modulation index constraint.

[0067] Figure 4 This illustrates a process for determining training data using the reinforced particle swarm optimization algorithm, see reference. Figure 4 In each main iteration search process, all search particles are first controlled to move towards the target modulation index with the main group fitness function as the objective, and the main group search strategy is executed. The main group search strategy is used to drive each search particle to move from its current position towards the target modulation index, so as to ensure that the searched switching angle combination can meet the requirements for heating the workpiece as much as possible. Then, after updating the optimal switching angle combination, the sub-iteration search process is entered. In each sub-iteration search, the sub-group search strategy with the sub-group fitness function as the objective is executed. The sub-group search strategy comprehensively considers the requirements for odd harmonic suppression near the current modulation index value as well as the constraints on the switching angle sequence and modulation index exceeding the limit, so as to ensure that the search results meet the constraints on the switching physical conditions of the power device while achieving the modulation index and harmonic suppression targets.

[0068] In some specific embodiments, the main group fitness function FF0 and the subgroup fitness function FF1 are shown in equations (4) and (5), respectively:

[0069]

[0070]

[0071] Among them, V1 * V1 represents the target fundamental frequency amplitude determined based on the target modulation index, and V2 represents the actual fundamental frequency amplitude. h Let w0 be the amplitude of the h-th harmonic, and w be the amplitude of the h-th harmonic. h λ1 and λ2 are the weighting coefficients corresponding to the fundamental amplitude error and the amplitude errors of each odd harmonic, respectively; λ1 and λ2 are the penalty factors for violating the angle constraint and modulation index constraint, respectively; P violation Penalty item for incorrect switching angle sequence; P M This is a penalty term for the modulation index M exceeding the legal range.

[0072] In some alternative embodiments, P MAs shown in equation (6):

[0073]

[0074] Penalty is a preset constant used to penalize illegal M-value search results.

[0075] In some preferred embodiments, during each iteration of the search process, each search particle also performs a perturbation update action, the magnitude of which is determined by the sinusoidal perturbation model shown in equation (7):

[0076] Δθ i =A·sin(2πf) i ×k+φ i ), i∈[1,4] (7),

[0077] Where, Δθ i Let f be the angular disturbance of the i-th switching angle, A be the disturbance amplitude, and f be the angular disturbance. i φ i denoted as the perturbation frequency and initial phase of the i-th switching angle, respectively, and k is the current search iteration number.

[0078] It should be noted that the above perturbation update action can be performed in each main iteration search process or in each sub-iteration search process. That is, k can represent the number of iterations of the main iteration search or the number of iterations of the sub-iteration search.

[0079] Figure 5 To illustrate the voltage waveform output by the induction heating power supply under the control of the aforementioned control system in a specific simulation example, the figure also shows the transformer waveform without odd-order harmonic suppression. To highlight the waveform distortion trend and harmonic content changes, the vertical axis uses normalized voltage representation, that is, the voltage values ​​at each point are standardized according to the fundamental amplitude. This is used to highlight the changing trends of waveform distortion and harmonic components, limiting the waveform values ​​to between -1 and +1. Figure 5 Simulation results show that without odd harmonic optimization, the output voltage has obvious low-order odd harmonics (such as the 3rd and 5th harmonics). However, after applying the odd harmonic control unit to suppress odd harmonics, the waveform distortion is significantly reduced, verifying the effectiveness of the present invention in harmonic suppression and waveform quality improvement.

[0080] Figure 6A In a specific embodiment, the measured voltage waveform of an LLC resonant induction heating power supply before harmonic suppression is shown. This heating power supply is a high-frequency resonant type. In the figure, the yellow channel represents the half-bridge drive signal applied to the power device, and the blue channel represents the output induced voltage waveform. Figure 6BThe measured waveform results are shown for harmonic suppression of the LLC resonant induction heating power supply using the control system provided in this application, where the value of M is 0.6.

[0081] Compare Figure 6A , Figure 6B As can be seen, after the harmonic suppression is performed by the control system provided in this application, the output signal exhibits a relatively regular sinusoidal shape, and the main resonant frequency is stabilized at 35.87kHz. This indicates that the harmonic control strategy can effectively suppress harmonics in actual high-frequency induction heating power supplies and has good dynamic stability.

[0082] LLC resonant induction heating circuits generally operate in the high-frequency range. Key components in the resonant circuit, such as capacitors and inductors, will age during temperature fluctuations and long-term use, causing their parameters to shift. This shift will lead to resonant point mismatch (generally, the resonant frequency will drift towards higher frequencies), which in turn will cause unstable power output, and may even lead to abnormal current increase and damage to power devices.

[0083] Existing LLC resonant induction heating circuit protection systems typically rely on static threshold determination methods, which lack adaptability to dynamic changes, cannot accurately capture fault characteristics, and have a slow response speed, making it difficult to achieve timely protection, thereby increasing the risk of equipment damage.

[0084] To address the aforementioned problems, in some preferred embodiments of the control system provided in this application, such as... Figure 7 As shown, an anomaly detection unit has also been added. The anomaly detection unit can monitor the degree of resonant frequency drift in the LLC resonant induction heating power supply in real time based on the measured values ​​of the peak secondary current of the half-bridge inverter circuit and the load capacity of the load section.

[0085] refer to Figure 7 The anomaly detection unit can receive the real-time measurement results of the voltage detection device and the current detection device set on the secondary side of the half-bridge inverter circuit. Based on the measurement results, it obtains the load capacity of the load section (generally, it can be expressed as average power) and the peak value of the secondary side current. By judging whether the measured value of the peak value of the secondary side current and the load capacity exceed the normal operating range, it evaluates the degree of resonant frequency drift of the LLC resonant network.

[0086] In the embodiments of this application, the normal operating region is located between the load capacity-secondary current peak slope corresponding to the ideal resonant frequency and the load capacity-secondary current peak slope corresponding to the upper limit of resonant frequency drift.

[0087] The following, in conjunction with the attached diagram, explains how to determine the load capacity-secondary current peak slope and the normal operating range.

[0088] Figure 8 The diagram shows the transformer secondary current waveforms before and after component aging in a circuit with the same load capacity (correspondingly, the switching cycles of the power devices need to be the same).

[0089] Without loss of generality, a wide and low waveform represents the secondary current waveform corresponding to the ideal resonant frequency achievable by the circuit when the power devices switch at a set period, assuming the components in the circuit have not aged. This waveform represents the theoretically "should" output current of the induction heating power supply under normal operating conditions. A narrow and high waveform represents the secondary current waveform output by the heating power supply after the resonant frequency point has drifted upward due to component aging (generally, component aging will cause the resonant frequency point to shift upward compared to the ideal resonant frequency). Considering the half-wave symmetry of the current, only the upper half can be analyzed, such as... Figure 8 As shown, the area enclosed by the two waveforms can be expressed by equations (8) and (9), respectively:

[0090]

[0091] Where h2 and h1 represent the peak values ​​of the secondary current at the ideal resonant frequency and after the resonant frequency has drifted upwards, respectively, under the same load capacity; b and a represent the corresponding durations of the secondary current. When the load capacity is the same, and ignoring secondary effects such as the control dead zone, it can be assumed that the area of ​​the arch formed by the two different current waveforms in the figure should be consistent, that is:

[0092]

[0093] As can be seen from equation (10), after the resonant frequency is shifted upward, the ratio of the peak current on the secondary side to the ratio of the current duration is inversely proportional to the ideal resonant frequency.

[0094] Using the above relationships, the ideal secondary peak current corresponding to each load capacity can be calculated. Then, by connecting the points, the desired secondary peak current can be obtained. Figure 9 The expression for the slash B in the equation is shown in equation (11):

[0095]

[0096] Then, according to equation (11), the upward drift of the resonant frequency relative to the ideal resonant frequency can be directly obtained (the ratio is...). The slope K of the slope corresponding to (times) a ,and When K is adjusted according to the upper limit of the allowable upward drift at the resonant frequency... aWhen setting the parameters (for example, by setting the upper limit of the resonant frequency drift to 120% of the ideal resonant frequency according to the component specifications of the resonant capacitor), the following can be obtained: Figure 9 The upper limit of the mid-resonance frequency drift corresponds to the load capacity - peak secondary current sloping line A. Clearly, the normal operating range of the induction heating power supply lies between sloping line B and sloping line A.

[0097] In some specific embodiments, the anomaly detection unit continuously collects data on the load capacity and the secondary side peak current, and then detects when the secondary side peak current exceeds... Figure 9 When the device is in its normal operating range, a warning message is sent to the modulation unit. The modulation unit stops sending drive signals to the phase power devices for a period of time and cuts off the input and output. Furthermore, if the modulation unit receives more than a limited number of warning messages within a set time interval, it sends a serious fault signal to the host computer or other devices, and the host computer or other devices or manual operation completely cut off the power supply.

[0098] Compared with traditional spectrum analysis methods, the above-mentioned anomaly detection methods are simpler, more efficient and accurate in calculation and analysis. They have the advantages of adapting to complex working conditions, high sensitivity and low computational complexity, making them easy to implement in embedded systems in real time. They also have good adaptability to resonant frequency drift and can provide early warning in the early stages of a fault, thereby improving the reliability and safety of the system.

[0099] In some specific embodiments, the modulation unit, odd harmonic control unit, and anomaly detection unit can all be implemented by devices such as digital signal processors (DSPs), microcontroller units (MCUs), field-programmable gate arrays (FPGAs), or embedded systems based on Linux or RTOS that have been programmed with corresponding functions or can execute corresponding algorithms. In addition, the above devices also communicate with a host computer, which can be a desktop computer, laptop computer, tablet computer, mobile phone, or other devices equipped with an interactive interface that can perform operations such as setting and adjusting control parameters, as well as real-time acquisition and processing of anomaly information.

[0100] Some embodiments of this application also provide a control method for an LLC resonant induction heating power supply. This control method uses the aforementioned control system of the LLC resonant induction heating power supply to control the LLC resonant induction heating power supply to heat the load. The specific implementation of the above method has been described in detail in the description of the control system above, and will not be repeated here.

[0101] The specific embodiments of this application have been described in detail above. For those skilled in the art, several improvements and modifications can be made to this application without departing from the principle of this application, and these improvements and modifications also fall within the protection scope of the claims of this application.

Claims

1. A control system for an LLC resonant induction heating power supply, wherein the LLC resonant induction heating power supply heats a load through a half-bridge inverter circuit, comprising a modulation unit, the modulation unit being used to determine a target modulation index and a fundamental frequency, and to achieve an output frequency-adjustable high-frequency AC square wave by controlling the switching of various power devices in the half-bridge inverter circuit, characterized in that, The waveform of the high-frequency AC square wave is periodic with the fundamental wave duration and has a half-wave symmetrical structure. The control system further includes an odd harmonic control unit, which is used to predict the optimal switching angle combination of each power device under the odd harmonic suppression target. The modulation unit generates a modulation signal for controlling the switching of each power device based on the optimal switching angle combination. The target for odd harmonic suppression is: ， in, The target modulation index, , They are respectively The lower and upper limits, The optimal combination of switching angles, Here is the expression for the order of the odd harmonics that need to be suppressed. for The upper limit; The odd harmonic control unit uses a trained artificial neural network to predict and output the optimal switching angle combination with the target modulation index as input. The training set for training the artificial neural network is obtained by searching an enhanced particle swarm optimization algorithm based on switching angle sorting constraints and modulation index constraints. The enhanced particle swarm optimization algorithm employs a master-subgroup hierarchical search strategy. Satisfying the preset master-subgroup fitness function and subgroup fitness function are the search objectives for the master-subgroup iterative search process and the sub-iterative search process, respectively. It iteratively searches for the optimal switching angle combination corresponding to each modulation index in the switching angle search space. Specifically, the master-subgroup hierarchical search strategy is as follows: In each main iteration search process, firstly, all search particles are controlled to execute the main group search strategy to search with the modulation index as the goal. Then, each search particle is controlled to execute the subgroup search strategy at least once in the sub-iteration search process to search with the goal of suppressing each odd harmonic and satisfying the switching angle ordering constraint and the modulation index constraint. The main group fitness function for: ， The subgroup fitness function for: ， in, The target fundamental amplitude is determined based on the target modulation index. This represents the actual fundamental frequency amplitude. For the first h The amplitude of the second harmonic. , These are the weighting coefficients corresponding to the fundamental amplitude error and the amplitude errors of each odd harmonic, respectively. and These are the penalty factors for violating the angle constraint and the modulation index constraint, respectively. Penalty item for incorrect switching angle sequence; Modulation index M Penalties for items exceeding the legal range.

2. The control system for the LLC resonant induction heating power supply according to claim 1, characterized in that, During each iteration of the search process, each search particle also performs a perturbation update action, the magnitude of which is determined based on the sinusoidal perturbation model shown below: ， in, For the first The angular disturbance of the switching angle For the disturbance amplitude, , The first The disturbance frequency and initial phase of each switching angle, This represents the number of iterations in the current search.

3. The control system for the LLC resonant induction heating power supply according to claim 1, characterized in that, Also includes: The anomaly detection unit monitors the degree of resonant frequency drift of the LLC resonant induction heating power supply in real time based on the measured values ​​of the secondary side current peak and load capacity.

4. The control system of the LLC resonant induction heating power supply according to claim 3, characterized in that, The real-time monitoring operation monitors the degree of resonant frequency drift by determining whether the measured values ​​of the secondary current peak and the load capacity exceed the normal operating range. The normal operating range is located between the load capacity-secondary current peak slope corresponding to the ideal resonant frequency and the load capacity-secondary current peak slope corresponding to the upper limit of resonant frequency drift.

5. The control system of the LLC resonant induction heating power supply according to claim 4, characterized in that, The slope of the load capacity-secondary current peak slope corresponding to the upper limit of the resonant frequency drift is... The slope of the load capacity-secondary current peak slope corresponding to the ideal resonant frequency is... ,and and The ratio represents the secondary current duration corresponding to the upper limit of the resonant frequency drift under the same load capacity. Secondary current duration corresponding to the ideal resonant frequency The reciprocal of the ratio.

6. A control method for an LLC resonant induction heating power supply, characterized in that, The control system of the LLC resonant induction heating power supply according to claim 1 is used to control the LLC resonant induction heating power supply to heat the load.

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