Full-condition soft switching control method and device, computer device and storage medium

Abstract

The application discloses a full-condition soft switching control method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring real-time working condition data including at least real-time current; obtaining a failure probability of the soft switching based on the real-time current; identifying the working condition based on the real-time working condition data to obtain current operation information; determining a current modulation strategy from a coarse adjustment mode or a fine adjustment mode based on the failure probability and the current operation information; and modulating in a load transient boundary area based on the current modulation strategy and iteratively adjusting based on current modulation feedback until the current modulation feedback meets a preset modulation cutoff condition. By using current as a front feedback, active modulation control based on predicted current with feedforward properties can quickly adapt to load changes, avoid soft switching failure, and adapt to full working conditions. A full-condition soft switching control scheme that can be stable in the range from light load to heavy load is provided to reduce hard switching loss and EMI spikes.

Description

Technical Field

[0001] This application relates to the field of power electronics technology, and in particular to soft-switching control methods, devices, computer equipment and storage media for all operating conditions. Background Technology

[0002] In existing technologies, soft-switching control is prone to failure under light load conditions, leading to increased hard-switching losses in switching devices, electromagnetic interference spikes in the system, and decreased efficiency under light load. Traditional solutions mainly include fixed-frequency modulation, phase compensation, or simple feedback control, but these methods often cannot cover a wide load range or respond quickly to load changes, lacking adaptability to all operating conditions.

[0003] Existing similar studies have proposed switching to pulse width modulation (PFM) frequency mode via digital control logic under light loads and using current sampling for dead-time compensation, but these methods cannot actively adjust the phase, making them prone to soft-switching failures under light loads. Other studies have introduced multiple phase dimensions for control, but these typically rely on static lookup tables or proportional-integral (PI) control, resulting in limited response speed and control accuracy. Therefore, the current technology lacks a stable, full-condition soft-switching control scheme that can effectively reduce hard-switching losses and EMI spikes across the entire operating range from light to heavy loads. Summary of the Invention

[0004] This application provides a soft-switching control method, apparatus, computer equipment, and storage medium for all operating conditions, which can solve the problem of the lack of a stable soft-switching control scheme for all operating conditions in the prior art, so as to reduce hard switching losses and EMI spikes.

[0005] In a first aspect, embodiments of this application provide a soft-switching control method for all operating conditions, including: In response to soft-switching control commands, acquire real-time operating condition data, including at least the real-time current. The current of the next cycle is predicted based on the real-time current using Lagrange interpolation or a variable step size prediction model to obtain the predicted current; the safe dead time between the turn-on and turn-off of the switching device is calculated based on the current peak and zero-crossing point of the predicted current; and the failure probability of the soft switch is determined based on the safe dead time, the predicted current, and the current threshold of the switching device. Based on the real-time current, voltage, temperature, and switching losses, the operating condition type is identified to obtain the current operating condition type; the load nature and power direction are determined; the current operating condition type, the load nature, and the power direction are packaged to obtain the current operating information; Based on the failure probability and the current operating information, the current modulation strategy is determined from either the coarse adjustment mode or the fine adjustment mode. Modulation is performed in the load transient boundary region based on the current modulation strategy, and iterative adjustments are made based on the current modulation feedback until the current modulation feedback meets the preset modulation cutoff condition.

[0006] In some embodiments, determining the current modulation strategy from either the coarse-tuning mode or the fine-tuning mode based on the failure probability and the current operating information includes: Based on the failure probability, current operating condition type, load characteristics, and power direction, the current modulation mode is determined, wherein the current modulation mode includes a coarse modulation mode or a fine modulation mode; The offset for frequency modulation of the main resonance is determined based on the current modulation mode, and the additional phase shift angle for phase modulation is determined, wherein the additional phase shift angle is the phase shift angle required to remove capacitor charge; The current modulation strategy is determined based on the current modulation mode, the offset of the frequency modulation, and the additional phase shift angle of the phase modulation.

[0007] In some embodiments, determining the current modulation mode based on the failure probability, the current operating condition type, the load characteristics, and the power direction includes: If, based on the failure probability, current operating condition type, load characteristics, and power direction, it is determined that the current state is in a transient transition from heavy load to light load, then the current adjustment mode is determined to be a coarse modulation mode for phase modulation and a fine modulation mode for frequency modulation. If it is determined that the current state is a transient transition from light load to heavy load, then the current modulation mode is determined to be coarse modulation mode for frequency modulation and fine modulation mode for phase modulation.

[0008] In some embodiments, determining the offset for frequency modulation of the main resonance and the additional phase shift angle for phase modulation based on the current modulation mode includes: The difference between the real-time current and the predicted current is used to obtain the current deviation; Based on the current deviation, a first proportional coefficient for the mapped switching frequency fine-tuning amount is determined according to the current modulation mode; Multiplying the current deviation by the first proportional coefficient yields the offset for frequency modulation of the main resonance. Based on the current deviation, a second proportional coefficient for the mapped phase compensation fine-tuning amount is determined according to the current modulation mode; Multiplying the current deviation by the second proportional coefficient yields the additional phase shift angle for phase modulation.

[0009] In some embodiments, modulation is performed in the load transient boundary region based on the current modulation strategy, and iterative adjustments are made based on the current modulation feedback until the current modulation feedback meets a preset modulation cutoff condition, including: If it is determined that the load has entered the transient boundary region, frequency modulation of the main resonance is performed based on the offset indicated by the current modulation strategy, and phase modulation is performed based on the additional phase shift angle indicated by the current modulation strategy. The influence on the phase angle is eliminated by decoupling the frequency conversion process. The frequency modulation result and the phase modulation result are respectively used to generate a pulse width modulation signal and a phase modulation drive signal, which are then input into a preset power switch driver to output the output current. If the difference between the output current and the predicted current exceeds a preset threshold, the output current is used as the real-time current, and the frequency and phase are iteratively adjusted again until the difference does not exceed the preset threshold.

[0010] Secondly, embodiments of this application also provide a soft-switching control device for all operating conditions, comprising: The acquisition module is used to acquire real-time operating condition data, including at least the real-time current, in response to soft-switching control commands. The current prediction module is used to predict the current of the next cycle based on the real-time current using Lagrange interpolation or a variable step size prediction model, and obtain the predicted current; based on the current peak and zero crossover point of the predicted current, the safe dead time between the turn-on and turn-off of the switching device is calculated; based on the safe dead time, the predicted current, and the current threshold of the switching device, the failure probability of the soft switch is determined. The operating condition identification module is used to identify the operating condition type based on the real-time current, voltage, temperature, and switching losses to obtain the current operating condition type; determine the load nature and power direction; and package the current operating condition type, the load nature, and the power direction to obtain the current operating information. The modulation strategy determination module is used to determine the current modulation strategy from either the coarse modulation mode or the fine modulation mode based on the failure probability and the current operating information. The modulation module is used to perform modulation in the load transient boundary region based on the current modulation strategy, and to perform iterative adjustments based on the current modulation feedback until the current modulation feedback meets the preset modulation cutoff condition.

[0011] Thirdly, embodiments of this application also provide a soft-switching control computer device for all operating conditions, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0012] Fourthly, embodiments of this application also provide a computer-readable storage medium storing a computer program, the computer program including program instructions that, when executed by a processor, can implement the above-described method.

[0013] This application provides a soft-switching control method, apparatus, computer device, and storage medium for all operating conditions. In response to a soft-switching control command, real-time operating condition data, including at least the real-time current, is acquired. The current for the next cycle is predicted using Lagrange interpolation or a variable step-size prediction model, resulting in a predicted current. Based on the current peak and zero-crossing point of the predicted current, the safe dead time between the switching device's turn-on and turn-off is calculated. Based on the safe dead time, the predicted current, and the current threshold of the switching device, the failure probability of the soft switch is determined. Operating condition type is identified based on the real-time current, voltage, temperature, and switching losses to obtain the current operating condition type. The load characteristics and power direction are determined. The current operating condition type, load characteristics, and power direction are packaged to obtain current operating information. Based on the failure probability and the current operating information, a current modulation strategy is determined from either a coarse-tuning mode or a fine-tuning mode. Modulation is performed in the load transient boundary region based on the current modulation strategy, and iterative adjustments are made based on the current modulation feedback until the current modulation feedback meets a preset modulation cutoff condition. In this application, by using current as the forward feedback and employing predictive current active modulation control with feedforward properties, it is possible to quickly adapt to load changes, avoid soft-switching failures, and adapt to all operating conditions. A stable full-condition soft-switching control scheme is provided that can operate within a light to heavy load range, thereby reducing hard-switching losses and EMI spikes. Attached Figure Description

[0014] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 A flowchart illustrating the soft-switching control method for all operating conditions provided in this application embodiment; Figure 2 A schematic block diagram of a soft-switching control device for all operating conditions provided in an embodiment of this application; Figure 3 A schematic block diagram of a computer device provided in an embodiment of this application. Detailed Implementation

[0016] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0017] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the stated features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0018] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the application. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0019] It should also be further understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0020] In existing technologies, soft-switching control is prone to failure under light load conditions, leading to increased hard-switching losses in switching devices, electromagnetic interference spikes in the system, and decreased efficiency under light load. Traditional solutions mainly include fixed-frequency modulation, phase compensation, or simple feedback control, but these methods often cannot cover a wide load range or respond quickly to load changes, lacking adaptability to all operating conditions.

[0021] Existing similar studies have proposed switching to pulse width modulation (PFM) frequency mode via digital control logic under light loads and using current sampling for dead-time compensation, but these methods cannot actively adjust the phase, making them prone to soft-switching failures under light loads. Other studies have introduced multiple phase dimensions for control, but these typically rely on static lookup tables or proportional-integral (PI) control, resulting in limited response speed and control accuracy. Therefore, the current technology lacks a stable, full-condition soft-switching control scheme that can effectively reduce hard-switching losses and EMI spikes across the entire operating range from light to heavy loads.

[0022] This application provides a soft-switching control method, device, computer equipment, and storage medium for all operating conditions, aiming to provide a stable soft-switching control scheme for all operating conditions from light load to heavy load, so as to reduce hard switching losses and EMI spikes.

[0023] This application is based on a full-condition soft-switching control method that combines current prediction with coarse and fine modulation to achieve stable soft switching in the light to heavy load range, thereby reducing hard switching losses and EMI spikes.

[0024] Figure 1 This is a flowchart illustrating the soft-switching control method for all operating conditions provided in an embodiment of this application. For example... Figure 1 As shown, the method includes the following steps S110-S150:

[0025] S110, in response to a soft-switching control command, acquires real-time operating condition data including at least the real-time current;

[0026] Soft switching and hard switching are two ways of describing the operating state of power switching transistors in the field of power electronics. Power switching transistors include MOSFETs and IGBTs. The core difference between soft switching and hard switching lies in whether voltage and current exist simultaneously on the switching device when the switching action occurs.

[0027] Hard switching is the most traditional and simplest switching method. The switching transistor is forced to turn on or off while under voltage or current flow. At the moment of turn-on, when there is still a relatively high voltage across the transistor, a drive signal turns it on, causing the current to rise rapidly and the voltage to gradually decrease. During this period of current rise and voltage drop, there is an overlap between the voltage and current. At the moment of turn-off, when there is still a large current in the transistor, a drive signal turns it off, causing the voltage to rise rapidly and the current to gradually decrease. In this overlapping region of voltage rise and current drop, losses are generated again. Hard switching has high switching losses; the area of ​​the overlapping region, calculated by multiplying the voltage by the current at the moment of switching, is the loss. The higher the switching frequency, the more switching occurs per second, resulting in greater total losses and severe heat generation. The rapid changes in voltage and current at the moment of switching generate abundant harmonics, interfering with other circuits.

[0028] Soft switching creates zero-voltage or zero-current switching conditions by adding a small amount of resonant components such as inductors, capacitors, and diodes. Soft switching is divided into two categories: zero-voltage switching and zero-current switching. Zero-voltage switching turns on the transistor only after the voltage across it drops to zero. Zero-current switching turns off the transistor only after the current flowing through it drops to zero.

[0029] Soft switching utilizes a newly added resonant circuit to actively change the voltage or current flowing through the main switch before it operates, bringing them to zero before the main switch operates. This seemingly extra step actually eliminates the overlap between voltage and current.

[0030] Soft switching theoretically has extremely low switching losses, approaching zero. Because of these very low losses, the switching frequency can be made very high, thereby significantly reducing the size of components such as transformers and capacitors, and achieving power supply miniaturization.

[0031] Real-time operating data includes voltage, current, temperature, switching losses, and other data. Among these, the current in the real-time operating data refers to the real-time current.

[0032] The system collects data such as voltage, current, temperature, and switching losses from the power module output. The accurate, real-time signals provide a foundation for subsequent prediction and control, ensuring a reliable data source for the control logic under light load conditions, thereby preventing soft-switching failures.

[0033] As an example, a high-speed ADC is used to sample the power module arm current, where the sampling frequency is greater than or equal to 10 times the switching frequency. Temperature signals are acquired via thermistors or thermocouples and input to the DSP / MCU. The signals are then filtered to eliminate high-frequency noise and normalized to form standardized data packets.

[0034] In each control cycle, for example, 1 / 10 of the switching cycle, or 10 µs, corresponding to a 100 kHz switching frequency, the controller reads the following real-time data: real-time current, temperature, and switching losses.

[0035] The primary bridge arm current or resonant inductor current is acquired by a high-frequency Hall sensor or a precision shunt resistor, and after anti-aliasing filtering, the real-time current is obtained by sampling and quantization by a high-speed ADC.

[0036] As an example, switching losses can be obtained in real time through a pre-calibrated loss model, such as a lookup function based on voltage, current and junction temperature, or by integrating high-frequency waveforms.

[0037] S120. Based on the real-time current, predict the current of the next cycle using Lagrange interpolation or a variable step size prediction model to obtain the predicted current; calculate the safe dead time between the turn-on and turn-off of the switching device based on the current peak and zero-crossing point of the predicted current; determine the failure probability of the soft switch based on the safe dead time, the predicted current, and the current threshold of the switching device. The predicted current is obtained by predicting the current of the next cycle based on the real-time current using Lagrange interpolation or a variable step size prediction model. The collected current data were fitted using Lagrange interpolation or a variable step size prediction model.

[0038] By using Lagrange interpolation or variable step size prediction algorithms, the possibility of soft-switching failure in the next cycle can be predicted. By predicting potential soft-switching failures in advance, the system can take measures in advance during light-load transients to avoid hard-switching losses and EMI spikes (electromagnetic interference).

[0039] Lagrange interpolation assumes that the change of current over time can be described by a polynomial function, and this polynomial must pass precisely through all known sampling points. Using several known current values ​​and their corresponding times, a polynomial with its highest power one order less than the number of known points can be uniquely determined. This polynomial is then extended into the future, substituting the time of the next sampling period to calculate the predicted current value at that moment. This method performs reasonably well in short-term predictions for situations where the current change is very smooth and noise is extremely low, such as steady-state sine waves or linear ramps.

[0040] As an example, the prediction process using Lagrange interpolation is as follows: First, current values ​​are collected at a fixed sampling period, and the time and current values ​​of the most recent sampling points, such as 3 or 4, are saved. Then, an interpolation polynomial is constructed using these known points, following the Lagrange interpolation method. This polynomial is exactly equal to the current value collected at each known time, while at other times it smoothly changes according to the polynomial's pattern. Finally, the next period is extrapolated by substituting the time of the next sampling period into this polynomial; the calculated value is the predicted current for the next period.

[0041] Variable step size prediction models belong to adaptive prediction methods. They do not assume that the current follows a fixed polynomial, but rather that the current can be approximated by a linear combination of several past current values; this is an autoregressive model. The weights in the model are not fixed in advance but are continuously adjusted during operation. This adjustment uses a dynamically changing step size factor. When the prediction error is large, the step size automatically increases, allowing the weights to catch up with the changes more quickly; when the error is small, the step size automatically decreases, stabilizing the weights near their optimal values. This characteristic of the step size changing with the error is the origin of the name "variable step size."

[0042] As an example, the prediction process using a variable step size prediction model is as follows: Set an order, for example, taking the four most recent historical current values, and initialize all weights to 0, while also setting an initial step size. After obtaining a new current sample, cache several recent historical current values. Calculate the current prediction value by multiplying the current weights by the corresponding historical currents and summing the results. Subtract the predicted value from the actual current current to obtain an error signal, which is then used to calculate the prediction error. Based on the magnitude of the error, and following a preset rule (e.g., a larger error means a larger step size), calculate a new step size. Using the current error, historical currents, and the new step size, adjust each weight using an adaptive algorithm such as the least mean square algorithm to make the next prediction more accurate. Combine the latest weights with the most recent historical currents to calculate the current prediction value for the next sampling period. Repeat the above steps; the model will automatically adjust based on the actual error in each period, thus adapting to the changing trend of the current.

[0043] The variable step size prediction model is highly adaptable to noise, load abrupt changes, and current waveform variations. During startup or when there are sudden current changes, large errors trigger large step sizes, leading to rapid convergence; in steady state, small errors trigger small step sizes, resulting in smooth and accurate predictions.

[0044] Based on the current peak and zero-crossing point of the predicted current, the safe dead time between the switching device's turn-on and turn-off is calculated. In soft switching, especially zero-voltage switching (ZVS), dead time is the waiting time between the turn-on of the upper and lower bridge arm switches. Its purpose is to allow the circuit enough time to resonate after one switch is turned off, reducing the voltage across the other switch to zero or near zero before giving it a turn-on signal.

[0045] If the dead time is too short, the diode will be forcibly turned on before the voltage drops to zero, resulting in losses. If the dead time is too long, the current may flow in reverse through the body diode for too long, increasing conduction losses and even affecting ZVS maintenance. Therefore, a safe dead time needs to be dynamically calculated based on the current state.

[0046] In LLC or other resonant converters, the key quantities that determine the dead time requirement are the amount of charge that needs to be drawn from the junction capacitance of the switch that is about to be turned on, and the amount of current available to draw that charge.

[0047] The current peak reflects the peak value of the resonant energy. The higher the peak value, the stronger the available pumping capacity and the shorter the required dead time.

[0048] The zero-crossing point represents the moment when the current direction changes. ZVS requires the current to maintain the same direction during the dead time, therefore the dead time must end before the current crosses zero.

[0049] By predicting the current waveform, such as obtaining the sine / triangular wave shape of the next cycle, the zero-crossing time tzero of the predicted current and the peak Ipeak of the predicted current can be found. Based on these two, the safe dead time between the turn-on and turn-off of the switching device can be determined.

[0050] The failure probability of the soft switch is determined based on the safe dead time, the predicted current, and the current threshold of the switching device.

[0051] Even after calculating the safe dead time, actual operating conditions such as light load, differences in device parameters, and temperature variations may still prevent the ZVS condition from being met. Determining the failure probability of the soft switch allows for a quantitative assessment of the likelihood of soft switch failure, which can be used for system early warning or control mode switching.

[0052] The essence of soft-switching failure is that the resonant current fails to discharge the voltage of the junction capacitance to zero during the dead time.

[0053] Define a safety margin M, where M is the ratio of the available charge to the required charge. If M is greater than or equal to 1, it means the task is theoretically feasible; if M is less than 1, it means failure.

[0054] M is a random variable, which can be modeled as a probability distribution. Then, the probability P-fail, where M < 1, is calculated. If Pfail is greater than the set failure probability threshold Pset, then a frequency modulation or phase compensation mode switch is triggered.

[0055] S130. Based on the real-time current, voltage, temperature, and switching losses, identify the operating condition type to obtain the current operating condition type; determine the load nature and power direction; package the current operating condition type, the load nature, and the power direction to obtain the current operating information; By comprehensively analyzing real-time collected current, voltage, temperature, and switching loss data, the current operating status of the power system is identified and classified, generating structured operating information for use in current prediction, mode selection, and coordinated control.

[0056] Based on the real-time current, voltage, temperature, and switching losses, the operating condition type is identified to obtain the current operating condition type; The controller reads real-time current, voltage, temperature, and switching losses at each control cycle, for example, 1 / 10 of the switching cycle, or 10 µs, corresponding to a 100 kHz switching frequency.

[0057] The operating conditions include light load, heavy load, overload, steady-state, no-load, and dynamic transition conditions.

[0058] Among them, the judgment combination for light load conditions is that the effective value of the primary current is less than the light load threshold, such as 5% of the rated current and the switching loss increases abnormally, indicating that the soft switch has started to fail. At this time, the resonant energy is insufficient and zero voltage turn-on is easily lost. The combination for judging heavy load conditions is that the effective value of the primary current is greater than the heavy load threshold, such as 80% of the rated current and the junction temperature is lower than the maximum value. At this time, the resonant energy is sufficient and zero voltage turn-on is easy to achieve. The overload condition judgment combination is that the effective value of the primary current exceeds the overload threshold, such as 120% of the rated current and continues to exceed the protection delay. In this case, current limiting or frequency protection needs to be triggered. The no-load condition is determined when the output current is less than the no-load threshold, such as 0.5% of the rated current, which is considered an extremely light load and requires entering the burst mode. The dynamic transition condition judgment combination is that the current change rate exceeds a set threshold, which is used to identify the rapid load change process; The steady-state condition is determined when the current, voltage, and temperature fluctuate less than the threshold within a preset window, which falls within the normal operating range.

[0059] The controller incorporates a finite state machine, combining the aforementioned criteria with a threshold comparator. As an example, in a new energy vehicle charging module embodiment, when a sudden drop from 30A to 1.8A is detected and the calculated switching loss exceeds twice the normal light-load loss, the current operating condition is determined to be a light-load condition, indicating a high risk of soft-switching failure.

[0060] Determine the load characteristics and power direction; By analyzing the phase relationship between the primary current and the midpoint voltage of the bridge arm or the primary voltage of the transformer, the nature of the load—inductive, capacitive, or resistive—can be determined. In an inductive load, the current lags behind the voltage, meaning the current zero-crossing point occurs after the voltage zero-crossing point. In a capacitive load, the current leads the voltage. If the current zero-crossing point precedes the voltage zero-crossing point, it indicates that the system has entered the capacitive region, at which point the soft switch will completely fail, potentially even damaging the switching transistor. In a resistive load, the current and voltage are essentially in phase.

[0061] Using a zero-crossing detection circuit or digital comparator, capture the zero-crossing moments of the rising edge of the voltage and the rising edge of the current, and calculate the phase difference. Based on the sign and absolute value of the phase difference, determine the load type: if the current lags, the load type is inductive; if the current leads, the load type is capacitive; if the current leads by less than 5 degrees, the load type is resistive.

[0062] The current operating condition type, the load characteristics, and the power direction are packaged together to obtain the current operating information.

[0063] Power direction indicates the direction of energy flow, either forward from the input to the output or backward from the output back to the input. As an example, the instantaneous input power is calculated and low-pass filtered to obtain the average power Pavg. If the average power is greater than a forward threshold, it is considered forward power; otherwise, it is considered near-zero power. The controller combines the obtained operating condition type, load characteristics, and power direction into a compact data structure called the current operating information.

[0064] S140. Based on the failure probability and the current operating information, determine the current modulation strategy from either the coarse adjustment mode or the fine adjustment mode. Based on the previously calculated soft-switching failure probability and the current operating information obtained through operating condition identification, the system autonomously determines whether to adopt the coarse frequency adjustment mode, the fine phase adjustment mode, or a combination of both, and calculates the specific frequency adjustment amount and phase compensation amount. Finally, a complete and executable control strategy is formed to drive the switching transistor and ensure that soft switching can be achieved or approximated under various operating conditions.

[0065] S140. Based on the failure probability and the current operating information, determine the current modulation strategy from either the coarse adjustment mode or the fine adjustment mode. Based on the previously calculated soft-switching failure probability and the current operating information obtained through operating condition identification, the system autonomously determines whether to adopt the coarse frequency adjustment mode, the fine phase adjustment mode, or a combination of both, and calculates the specific frequency adjustment amount and phase compensation amount. Finally, a complete and executable control strategy is formed to drive the switching transistor and ensure that soft switching can be achieved or approximated under various operating conditions.

[0066] S140 includes S1401-S1403: S1401. Based on the failure probability, current operating condition type, load characteristics, and power direction, determine the current modulation mode, wherein the current modulation mode includes a coarse modulation mode or a fine modulation mode; The controller first reads two key inputs: one is the soft switch failure probability, which ranges from 0 to 1, with a higher value indicating a higher risk of soft switch failure; the other is the current operating information, which includes key information such as the current operating condition type (e.g., light load, heavy load, dynamic transition), the load nature (inductive, resistive, or capacitive), and the power direction (positive, reverse, or near zero).

[0067] The controller decides which modulation mode to use based on the following logic: If the soft-switching failure probability exceeds a preset threshold, such as 0.8, and the current operating condition is light load or dynamic transition, then a coarse modulation mode is selected. This involves significantly adjusting the characteristics of the resonant network by changing the switching frequency, thereby quickly restoring the zero-voltage switching condition. This is because when the failure risk is high, a stronger control action is needed to pull the system back to the ZVS region.

[0068] If the soft-switching failure probability does not exceed the threshold, but the load characteristics have deviated from inductive, such as approaching resistive or even capacitive, resulting in insufficient phase margin for zero-voltage switching, then fine modulation mode is selected. This involves precisely adjusting the position of the current zero-crossing point through minute phase shift compensation, while keeping the switching frequency essentially constant. This situation occurs under light loads but before triggering a high failure probability critical region.

[0069] If the current state is under heavy load or steady state and the probability of soft switching failure is very low, for example, less than 0.5, it means that the system is already in a good soft switching state, so no modulation is triggered and the current control strategy remains unchanged.

[0070] If the power direction is reversed, such as in the case of regenerative braking of an energy-regenerative motor, and the load is inductive, then a combination of coarse and fine adjustment is used simultaneously. This is because the resonant characteristics are different when working in reverse, and frequency and phase need to be adjusted in tandem to maintain bidirectional soft switching.

[0071] In some embodiments, S1401 includes steps A1-A2: By proactively addressing transient transitions from heavy load to light load or vice versa, soft switching failures and hard switching loss spikes are prevented. Current prediction is used as a trigger condition for phase compensation and frequency switching.

[0072] A1. If it is determined based on the failure probability, current operating condition type, load characteristics, and power direction that the current state is in a transient transition from heavy load to light load, then the current adjustment mode is determined to be a coarse modulation mode for phase modulation and a fine modulation mode for frequency modulation. During the transient transition from heavy load to light load, coarse modulation mode is used for phase modulation and fine modulation mode for frequency modulation. At this time, the system rapidly decreases from a high current, high power state to a low current, low power state. The coarse adjustment control strategy uses the phase angle as the main adjustment method with large steps, while the fine adjustment of the switching frequency only makes small and fine adjustments.

[0073] Because the current drops rapidly during the transient transition from heavy load to light load, the resonant energy decreases sharply. If the frequency is still coarsely increased, it may cause excessive frequency jumps, leading to output voltage fluctuations or transformer core saturation. The phase shift angle has a very sensitive and direct effect on power transmission adjustment.

[0074] During the transient transition from heavy load to light load, rapidly reducing the phase shift angle can quickly reduce the transmission power and prevent output voltage overshoot; at the same time, the phase change also has a significant impact on the phase of the resonant current, which can quickly compensate for the loss of ZVS margin caused by the load decrease.

[0075] Once the load has decreased to a newer operating point, the resonant impedance is fine-tuned using a small frequency shift to optimize the ZVS condition. The frequency change is small and will not cause large transient shocks.

[0076] During the transient transition from heavy load to light load, the phase angle is quickly adjusted to avoid hard switching and EMI spikes.

[0077] A2. If it is determined that the current state is in a transient transition from light load to heavy load, then the current modulation mode is determined to be coarse modulation mode for frequency modulation and fine modulation mode for phase modulation.

[0078] During the transient transition from light load to heavy load, coarse modulation mode is used for frequency modulation, and fine modulation mode is used for phase modulation. The system rapidly rises from a low current, low power state to a high power state. The coarse adjustment control strategy uses the switching frequency as the main, large-step adjustment means, while the fine adjustment phase angle only makes small, fine adjustments.

[0079] Because a significant increase in transmission power is required when transitioning from a light load to a heavy load, reducing the switching frequency can rapidly increase the resonant current and gain, making it the most effective coarse adjustment method. Coarse frequency adjustment offers a fast response, meeting the transient power demands of heavy loads.

[0080] After the frequency is adjusted to a roughly suitable new operating point, the current phase may shift slightly due to increased load. Fine-tuning the phase shift angle can compensate for the current direction deviation within the dead zone, ensuring that ZVS is maintained. Conversely, using coarse phase adjustment to increase power might require a large phase shift angle change, easily leading to current overshoot or hard switching; coarse frequency adjustment is more natural.

[0081] S1402. Determine the offset for frequency modulation of the main resonance based on the current modulation mode, and determine the additional phase shift angle for phase modulation, wherein the additional phase shift angle is the phase shift angle required to remove capacitor charge. The frequency modulation offset of the main resonance refers to the amount of change made relative to the nominal switching frequency of the system. By actively adjusting the switching frequency, the equivalent impedance of the resonant network is changed, thereby adjusting the amplitude and phase of the resonant current, so that the switching transistor can re-enter the zero-voltage turn-on (ZVS) or zero-current turn-off (ZCS) operating region.

[0082] The additional phase shift angle of phase modulation refers to a small angle adjustment added to the existing driving phase relationship, such as the phase shift angle between the primary and secondary sides, or the duty cycle center offset of the upper and lower bridge arms. It is used to accurately compensate for the timing deviation of the current zero crossing point and ensure that the junction capacitance voltage has been discharged to zero before the switch is turned on.

[0083] S1402, including steps B1-B5: B1. Calculate the difference between the real-time current and the predicted current to obtain the current deviation; Within each control cycle, the controller reads the currently acquired current value, such as the primary resonant current or the bridge arm current, and simultaneously reads the predicted current for the next cycle provided by the prediction unit. The difference between the two values ​​yields the current deviation ΔI. If ΔI > 0, the actual current is greater than the predicted value; if ΔI < 0, the actual current is less than the predicted value. This deviation directly reflects the degree of deviation between the system's current operating point and the control target.

[0084] B2. Based on the current deviation, determine the first proportional coefficient of the mapped switching frequency fine-tuning amount according to the current modulation mode; The controller performs coarse or fine adjustment based on the determined current modulation mode, selecting the corresponding first proportional coefficient from the parameter table. This coefficient converts the current deviation into a frequency adjustment amount, measured in Hz / A. If the current mode is coarse frequency adjustment, a larger value is used for the first proportional coefficient, allowing for rapid frequency response to current deviations and significant adjustments. If the current mode is fine frequency adjustment, a smaller value is used for the first proportional coefficient, allowing only minor frequency changes and avoiding transient overshoot. The first proportional coefficient can be obtained through offline experimental calibration or online adaptive adjustment.

[0085] B3. Multiply the current deviation by the first proportional coefficient to obtain the offset for frequency modulation of the main resonance; The frequency offset is calculated by multiplying the current deviation by the first proportional coefficient. When the actual current is greater than the predicted current, the frequency offset is positive, indicating that the switching frequency needs to be increased, which is usually used to reduce gain or lower current. When the actual current is less than the predicted current, the frequency offset is negative, indicating that the switching frequency needs to be decreased, the gain increased, and the current raised.

[0086] B4. Based on the current deviation, determine the second proportional coefficient of the mapped phase compensation fine-tuning amount according to the current modulation mode; Similarly, the controller selects a second proportional coefficient based on the current modulation mode. If the current modulation mode is coarse phase adjustment, a larger value is used for the second proportional coefficient, enabling rapid phase response to current deviations and quickly changing the transmitted power and current phase. If the current mode is fine phase adjustment, a smaller value is used for the second proportional coefficient, performing only minor phase compensation to maintain the ZVS phase margin.

[0087] B5. Multiply the current deviation by the second proportional coefficient to obtain the additional phase shift angle for phase modulation.

[0088] The additional phase shift angle for phase modulation is the product of the current deviation and the second proportional coefficient.

[0089] S1403. Based on the current modulation mode, the offset of the frequency modulation, and the additional phase shift angle of the phase modulation, the current modulation strategy is determined.

[0090] S150. Modulate in the load transient boundary region based on the current modulation strategy, and iteratively adjust based on the current modulation feedback until the current modulation feedback meets the preset modulation cutoff condition.

[0091] S150 includes S1501-S1503: S1501. If it is determined that the load is currently entering the transient boundary region, frequency modulation of the main resonance is performed based on the offset indicated by the current modulation strategy, and phase modulation is performed based on the additional phase shift angle indicated by the current modulation strategy, wherein the influence on the phase angle is eliminated by decoupling the frequency conversion process. Frequency conversion affects the phase angle. When the frequency is increased to coarsely adjust soft switching, even if the commanded phase shift angle remains unchanged, the actual current zero-crossing point will drift relative to the drive signal. This is because a higher frequency shortens half a switching cycle, resulting in a larger electrical angle for the same delay. The inductive or capacitive characteristics of the resonant network change with frequency, causing a natural current phase shift. Consequently, frequency adjustments contaminate the set phase shift angle, reducing ZVS accuracy and sometimes requiring repeated iterations to converge.

[0092] Decoupling is achieved by decoupling the frequency conversion process to eliminate its impact on the phase angle. The core purpose is to prevent frequency changes from interfering with the pre-set phase shift angle when the system is simultaneously performing coarse frequency modulation and fine phase modulation adjustments, ensuring that both can be adjusted independently and stably.

[0093] As an example, the coarse-tuning process is as follows: the switching frequency fsw,new is adjusted based on the predicted current change ΔIpred. fsw,new = fsw,nom + kfΔIpred, where fsw,new is the coarse-tuned switching frequency, fsw,nom is the nominal switching frequency, which is the reference PWM switching frequency set during system design (maintaining optimal soft-switching under standard load; fsw,nom serves as the reference frequency for coarse-tuning, and all frequency modulation offsets are calculated based on this value), and kf is the adjustment coefficient. The controller simultaneously outputs frequency and phase commands through a cooperative algorithm to update the power drive signal.

[0094] S1502. The frequency modulation result and the phase modulation result are respectively used to generate a pulse width modulation signal and a phase modulation drive signal, and input to the preset power switch driver to output the output current. First, the digital pulse width modulation (PWM) module configures its period register according to the final determined switching frequency, and simultaneously generates a set of complementary pulse width modulation signals according to a preset duty cycle. This set of signals directly controls the on and off times of the power switches, determining the converter's operating frequency. Second, for topologies requiring phase-shift control, the controller, based on the final determined phase shift angle, delays or advances the rising edge of the secondary-side drive signal to generate a phase-modulated drive signal with a precise phase difference, building upon the primary-side drive signal. These two types of drive signals—the frequency-modulated pulse width signal and the phase-modulated phase-shift signal—are synchronously output to the isolation driver chip.

[0095] The isolated driver chip amplifies the low-voltage logic level to a level sufficient to drive the gate voltage of the power switch and applies these signals to the control electrode of the switch. The switch operates according to the timing of the drive signals, chopping the DC bus voltage into a high-frequency AC square wave. After transformer coupling and rectification filtering, a stable load current is finally output. Simultaneously, the output current is fed back to the controller in real time through a sampling circuit to calculate the current deviation for the next cycle, thereby achieving closed-loop control.

[0096] S1503. If the difference between the output current and the predicted current exceeds a preset threshold, the output current is used as the real-time current, and the frequency and phase are iteratively adjusted again until the difference does not exceed the preset threshold.

[0097] After the system output current is established, the controller compares the real-time sampled output current with the previously predicted current and calculates the difference between the two. If the absolute value of this difference exceeds a preset threshold, it indicates that there is a significant deviation between the actual current and the predicted current, and the soft-switching conditions may not have reached their optimal state. In this case, the system does not directly accept the current control effect but instead enters an iterative adjustment process.

[0098] The output current obtained from this sampling is used as the new real-time current value, replacing the original real-time current data. The current deviation calculation, frequency offset and phase compensation calculation, and decoupling processing are then re-executed. Based on the updated current deviation, the controller readjusts the switching frequency and phase shift angle, generates a new round of pulse width modulation signal and phase modulation drive signal, and drives the power switch again to output a new current.

[0099] This iterative process repeats every control cycle or every few switching cycles until the difference between the output current and the predicted current narrows to within a preset threshold. At this point, the system considers the actual current to be essentially in line with the predicted value, and the phase and frequency conditions required for soft switching are met. It then exits the iteration and continues operating with the current modulation strategy, or enters steady-state monitoring mode. This closed-loop feedback mechanism ensures consistency between predictive control and actual operating conditions, automatically correcting for load changes, parameter drift, or prediction errors, maintaining soft-switching stability and high efficiency across all operating conditions.

[0100] This application provides a method, apparatus, computer device, and storage medium for soft-switching control under all operating conditions. The method includes: in response to a soft-switching control command, acquiring real-time operating condition data, including at least real-time current; predicting the current of the next cycle based on the real-time current using Lagrange interpolation or a variable step-size prediction model to obtain a predicted current; calculating the safe dead time between the turn-on and turn-off of the switching device based on the current peak and zero-crossing point of the predicted current; determining the failure probability of the soft switch based on the safe dead time, the predicted current, and the current threshold of the switching device; identifying the current operating condition type based on the real-time current, voltage, temperature, and switching losses to obtain the current operating condition type; determining the load characteristics and power direction; packaging the current operating condition type, the load characteristics, and the power direction to obtain current operating information; determining a current modulation strategy from either a coarse-tuning mode or a fine-tuning mode based on the failure probability and the current operating information; performing modulation in the transient boundary region of the load based on the current modulation strategy, and iteratively adjusting based on the current modulation feedback until the current modulation feedback meets a preset modulation cutoff condition. In this application, by using current as the forward feedback and employing predictive current active modulation control with feedforward properties, it is possible to quickly adapt to load changes, avoid soft-switching failures, and adapt to all operating conditions. A stable full-condition soft-switching control scheme is provided that can operate within a light to heavy load range, thereby reducing hard-switching losses and EMI spikes.

[0101] Figure 2 This is a schematic block diagram of a soft-switching control device for all operating conditions provided in an embodiment of this application. Figure 2 As shown, corresponding to the above-described soft-switching control method for all operating conditions, this application also provides a soft-switching control device for all operating conditions. This soft-switching control device includes a module for executing the above-described soft-switching control method for all operating conditions. Specifically, please refer to... Figure 2 The full-condition soft-switching control device includes an acquisition module, a current prediction module, a condition identification module, a modulation strategy determination module, and a modulation module, wherein: The acquisition module is used to acquire real-time operating condition data, including at least the real-time current, in response to soft-switching control commands. The current prediction module is used to predict the current of the next cycle based on the real-time current using Lagrange interpolation or a variable step size prediction model, and obtain the predicted current; based on the current peak and zero crossover point of the predicted current, the safe dead time between the turn-on and turn-off of the switching device is calculated; based on the safe dead time, the predicted current, and the current threshold of the switching device, the failure probability of the soft switch is determined. The operating condition identification module is used to identify the operating condition type based on the real-time current, voltage, temperature, and switching losses to obtain the current operating condition type; determine the load nature and power direction; and package the current operating condition type, the load nature, and the power direction to obtain the current operating information. The modulation strategy determination module is used to determine the current modulation strategy from either the coarse modulation mode or the fine modulation mode based on the failure probability and the current operating information. The modulation module is used to perform modulation in the load transient boundary region based on the current modulation strategy, and to perform iterative adjustments based on the current modulation feedback until the current modulation feedback meets the preset modulation cutoff condition.

[0102] In some embodiments, the modulation strategy determination module determines the current modulation strategy from either a coarse-tuning mode or a fine-tuning mode based on the failure probability and the current operating information, specifically for: Based on the failure probability, current operating condition type, load characteristics, and power direction, the current modulation mode is determined, wherein the current modulation mode includes a coarse modulation mode or a fine modulation mode; The offset for frequency modulation of the main resonance is determined based on the current modulation mode, and the additional phase shift angle for phase modulation is determined, wherein the additional phase shift angle is the phase shift angle required to remove capacitor charge; The current modulation strategy is determined based on the current modulation mode, the offset of the frequency modulation, and the additional phase shift angle of the phase modulation.

[0103] In some embodiments, the modulation strategy determination module determines the current modulation mode based on the failure probability, current operating condition type, load characteristics, and power direction, specifically for: If, based on the failure probability, current operating condition type, load characteristics, and power direction, it is determined that the current state is in a transient transition from heavy load to light load, then the current adjustment mode is determined to be a coarse modulation mode for phase modulation and a fine modulation mode for frequency modulation. If it is determined that the current state is a transient transition from light load to heavy load, then the current modulation mode is determined to be coarse modulation mode for frequency modulation and fine modulation mode for phase modulation.

[0104] In some embodiments, the modulation strategy determination module, when performing the determination of the offset for frequency modulation of the main resonance based on the current modulation mode, and the determination of the additional phase shift angle for phase modulation, is specifically used for: The difference between the real-time current and the predicted current is used to obtain the current deviation; Based on the current deviation, a first proportional coefficient for the mapped switching frequency fine-tuning amount is determined according to the current modulation mode; Multiplying the current deviation by the first proportional coefficient yields the offset for frequency modulation of the main resonance. Based on the current deviation, a second proportional coefficient for the mapped phase compensation fine-tuning amount is determined according to the current modulation mode; Multiplying the current deviation by the second proportional coefficient yields the additional phase shift angle for phase modulation.

[0105] In some embodiments, the modulation module performs modulation in the load transient boundary region based on the current modulation strategy and iteratively adjusts based on the current modulation feedback until the current modulation feedback meets a preset modulation cutoff condition, specifically for: If it is determined that the load has entered the transient boundary region, frequency modulation of the main resonance is performed based on the offset indicated by the current modulation strategy, and phase modulation is performed based on the additional phase shift angle indicated by the current modulation strategy. The influence on the phase angle is eliminated by decoupling the frequency conversion process. The frequency modulation result and the phase modulation result are respectively used to generate a pulse width modulation signal and a phase modulation drive signal, which are then input into a preset power switch driver to output the output current. If the difference between the output current and the predicted current exceeds a preset threshold, the output current is used as the real-time current, and the frequency and phase are iteratively adjusted again until the difference does not exceed the preset threshold.

[0106] In summary, the full-condition soft-switching control device in this application embodiment acquires real-time operating condition data, including at least real-time current, in response to soft-switching control commands; predicts the current of the next cycle based on the real-time current using Lagrange interpolation or a variable step-size prediction model to obtain the predicted current; calculates the safe dead time between the switching device's turn-on and turn-off based on the current peak and zero-crossing point of the predicted current; determines the failure probability of the soft switch based on the safe dead time, the predicted current, and the current threshold of the switching device; identifies the operating condition type based on the real-time current, voltage, temperature, and switching losses to obtain the current operating condition type; determines the load nature and power direction; packages the current operating condition type, the load nature, and the power direction to obtain the current operating information; determines the current modulation strategy from either a coarse-tuning mode or a fine-tuning mode based on the failure probability and the current operating information; modulates the load in the transient boundary region based on the current modulation strategy and iteratively adjusts it based on the current modulation feedback until the current modulation feedback meets the preset modulation cutoff condition. In this application, by using current as the forward feedback and employing predictive current active modulation control with feedforward properties, it is possible to quickly adapt to load changes, avoid soft-switching failures, and adapt to all operating conditions. A stable full-condition soft-switching control scheme is provided that can operate within a light to heavy load range, thereby reducing hard-switching losses and EMI spikes.

[0107] It should be noted that those skilled in the art can clearly understand that the specific implementation process of the above-mentioned full-condition soft-switching control device and each unit can be referred to the corresponding descriptions in the foregoing method embodiments. For the sake of convenience and brevity, these descriptions will not be repeated here.

[0108] The aforementioned full-condition soft-switching control device can be implemented as a computer program, which can be used in, for example... Figure 3 It runs on the computer device shown.

[0109] Please see Figure 3 , Figure 3 This is a schematic block diagram of a computer device 700 provided in an embodiment of this application. The computer device 700 can be a terminal or a server. The terminal can be an electronic device with communication functions, such as a smartphone, tablet, laptop, desktop computer, personal digital assistant, or wearable device. The server can be a standalone server or a server cluster composed of multiple servers.

[0110] See Figure 3 The computer device 700 includes a processor 702, a memory, and a network interface 705 connected via a system bus 701. The memory may include a non-volatile storage medium 703 and internal memory 704.

[0111] The non-volatile storage medium 703 may store an operating system 7031 and a computer program 7032. The computer program 7032 includes program instructions that, when executed, cause the processor 702 to perform a soft-switching control method across all operating conditions.

[0112] The processor 702 provides computing and control capabilities to support the operation of the entire computer device 700.

[0113] The internal memory 704 provides an environment for the execution of the computer program 7032 in the non-volatile storage medium 703. When the computer program 7032 is executed by the processor 702, the processor 702 can execute a soft-switching control method for all operating conditions.

[0114] This network interface 705 is used for network communication with other devices. Those skilled in the art will understand that... Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device 700 to which the present application is applied. The specific computer device 700 may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0115] The processor 702 is used to run the computer program 7032 stored in the memory to perform the following steps: In response to soft-switching control commands, acquire real-time operating condition data, including at least the real-time current. The current of the next cycle is predicted based on the real-time current using Lagrange interpolation or a variable step size prediction model to obtain the predicted current; the safe dead time between the turn-on and turn-off of the switching device is calculated based on the current peak and zero-crossing point of the predicted current; and the failure probability of the soft switch is determined based on the safe dead time, the predicted current, and the current threshold of the switching device. Based on the real-time current, voltage, temperature, and switching losses, the operating condition type is identified to obtain the current operating condition type; the load nature and power direction are determined; the current operating condition type, the load nature, and the power direction are packaged to obtain the current operating information; Based on the failure probability and the current operating information, the current modulation strategy is determined from either the coarse adjustment mode or the fine adjustment mode. Modulation is performed in the load transient boundary region based on the current modulation strategy, and iterative adjustments are made based on the current modulation feedback until the current modulation feedback meets the preset modulation cutoff condition.

[0116] It should be understood that in the embodiments of this application, the processor 702 may be a central processing unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0117] It will be understood by those skilled in the art that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program includes program instructions and can be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the process steps of the embodiments of the above methods.

[0118] The storage medium can be any computer-readable storage medium that can store program code, such as a USB flash drive, external hard drive, read-only memory (ROM), magnetic disk, or optical disk.

[0119] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of each example have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0120] In the embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For example, the division of each unit is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0121] The steps in the methods of this application embodiment can be adjusted, merged, or deleted according to actual needs. The units in the system of this application embodiment can be merged, divided, or deleted according to actual needs. Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0122] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a terminal, or a network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application.

[0123] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A soft-switching control method for all operating conditions, characterized in that, The method includes: In response to soft-switching control commands, acquire real-time operating condition data, including at least the real-time current. The current of the next cycle is predicted based on the real-time current using Lagrange interpolation or a variable step size prediction model to obtain the predicted current; the safe dead time between the turn-on and turn-off of the switching device is calculated based on the current peak and zero-crossing point of the predicted current; and the failure probability of the soft switch is determined based on the safe dead time, the predicted current, and the current threshold of the switching device. Based on the real-time current, voltage, temperature, and switching losses, the operating condition type is identified to obtain the current operating condition type; the load nature and power direction are determined; the current operating condition type, the load nature, and the power direction are packaged to obtain the current operating information; Based on the failure probability and the current operating information, the current modulation strategy is determined from either the coarse adjustment mode or the fine adjustment mode. Modulation is performed in the load transient boundary region based on the current modulation strategy, and iterative adjustments are made based on the current modulation feedback until the current modulation feedback meets the preset modulation cutoff condition.

2. The method according to claim 1, characterized in that, Based on the failure probability and the current operating information, the current modulation strategy is determined from either the coarse-tuning mode or the fine-tuning mode, including: Based on the failure probability, current operating condition type, load characteristics, and power direction, the current modulation mode is determined, wherein the current modulation mode includes a coarse modulation mode or a fine modulation mode; The offset for frequency modulation of the main resonance is determined based on the current modulation mode, and the additional phase shift angle for phase modulation is determined, wherein the additional phase shift angle is the phase shift angle required to remove capacitor charge; The current modulation strategy is determined based on the current modulation mode, the offset of the frequency modulation, and the additional phase shift angle of the phase modulation.

3. The method according to claim 2, characterized in that, Based on the failure probability, current operating condition type, load characteristics, and power direction, the current modulation mode is determined, including: If, based on the failure probability, current operating condition type, load characteristics, and power direction, it is determined that the current state is in a transient transition from heavy load to light load, then the current adjustment mode is determined to be a coarse modulation mode for phase modulation and a fine modulation mode for frequency modulation. If it is determined that the current state is a transient transition from light load to heavy load, then the current modulation mode is determined to be coarse modulation mode for frequency modulation and fine modulation mode for phase modulation.

4. The method according to claim 2, characterized in that, Based on the current modulation mode, the offset for frequency modulation of the main resonance and the additional phase shift angle for phase modulation are determined, including: The difference between the real-time current and the predicted current is used to obtain the current deviation; Based on the current deviation, a first proportional coefficient for the mapped switching frequency fine-tuning amount is determined according to the current modulation mode; Multiplying the current deviation by the first proportional coefficient yields the offset for frequency modulation of the main resonance. Based on the current deviation, a second proportional coefficient for the mapped phase compensation fine-tuning amount is determined according to the current modulation mode; Multiplying the current deviation by the second proportional coefficient yields the additional phase shift angle for phase modulation.

5. The method according to claim 2, characterized in that, Modulation is performed in the load transient boundary region based on the current modulation strategy, and iterative adjustments are made based on the current modulation feedback until the current modulation feedback meets the preset modulation cutoff condition, including: If it is determined that the load has entered the transient boundary region, frequency modulation of the main resonance is performed based on the offset indicated by the current modulation strategy, and phase modulation is performed based on the additional phase shift angle indicated by the current modulation strategy. The influence on the phase angle is eliminated by decoupling the frequency conversion process. The frequency modulation result and the phase modulation result are respectively used to generate a pulse width modulation signal and a phase modulation drive signal, which are then input into a preset power switch driver to output the output current. If the difference between the output current and the predicted current exceeds a preset threshold, the output current is used as the real-time current, and the frequency and phase are iteratively adjusted again until the difference does not exceed the preset threshold.

6. A soft-switching control device for all operating conditions, characterized in that, The device includes: The acquisition module is used to acquire real-time operating condition data, including at least the real-time current, in response to soft-switching control commands. The current prediction module is used to predict the current of the next cycle based on the real-time current using Lagrange interpolation or a variable step size prediction model, and obtain the predicted current; based on the current peak and zero crossover point of the predicted current, the safe dead time between the turn-on and turn-off of the switching device is calculated; based on the safe dead time, the predicted current, and the current threshold of the switching device, the failure probability of the soft switch is determined. The operating condition identification module is used to identify the operating condition type based on the real-time current, voltage, temperature, and switching losses to obtain the current operating condition type; determine the load nature and power direction; and package the current operating condition type, the load nature, and the power direction to obtain the current operating information. The modulation strategy determination module is used to determine the current modulation strategy from either the coarse modulation mode or the fine modulation mode based on the failure probability and the current operating information. The modulation module is used to perform modulation in the load transient boundary region based on the current modulation strategy, and to perform iterative adjustments based on the current modulation feedback until the current modulation feedback meets the preset modulation cutoff condition.

7. A soft-switching control computer device for all operating conditions, characterized in that, The method includes a memory, a processor, and a full-condition soft-switching control program stored in the memory and executable on the processor. The processor executes the full-condition soft-switching control program to implement the steps of the full-condition soft-switching control method according to any one of claims 1 to 5.

8. A storage medium, characterized in that, The storage medium stores a program for implementing a soft-switching control method for all operating conditions, and the program for implementing the soft-switching control method for all operating conditions is executed by a processor to implement the steps of the soft-switching control method for all operating conditions as described in any one of claims 1 to 5.

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