Dual active bridge converter control method and system based on double-layer weighted active disturbance rejection

Abstract

The application discloses a double active bridge converter control method and system based on double-layer weighted active disturbance rejection, and relates to the technical field of power electronics. The method comprises the following steps: constructing an input-output voltage dynamic model according to the characteristics of a double active bridge converter system, and converting the input-output voltage dynamic model into a linear state space equation; constructing an energy function dynamic equation based on a transmission power balance relationship according to the linear state space equation; constructing the energy function dynamic equation into an extended state space equation of a standard type according to the active disturbance rejection theory, and designing a double-layer observer according to the extended state space equation; constructing a control law based on a state space model and an energy function according to the double-layer observer structure, and solving the output voltage of the double active bridge converter by using the control law. The application can guarantee the fast response and high efficiency of the output voltage of the DAB converter under the coupling of noise and lumped interference.

Description

Technical Field

[0001] This invention relates to the field of power electronics technology, and in particular to a control method and system for a dual active bridge converter based on double-layer weighted active disturbance rejection. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] Dual active bridge converters (DABs) play a crucial role in key energy transfer processes between DC buses and power batteries / energy storage systems due to their advantages such as large power transfer capacity and small filter size. However, practical applications of DABs face challenges such as large estimation errors caused by high-frequency noise and external interference, and output voltage fluctuations caused by power fluctuations and load abrupt changes, threatening the stability of system operation.

[0004] While existing control methods have made progress in improving the dynamic performance of DAB converters, their ability to address the coupling of high-frequency noise and disturbances remains significantly limited. Classical linear control methods (such as PI and LQR) struggle to balance noise amplification and disturbance suppression due to their fixed-gain design. Nonlinear methods (such as predictive control, sliding mode control, and fuzzy control), while improving transient response, are limited by model sensitivity, computational complexity, or empirical dependence. These shortcomings lead to increased output voltage fluctuations and decreased stability, highlighting the urgent need to develop disturbance observers with high noise immunity.

[0005] Active disturbance rejection control (ADRC) has received widespread attention in recent years due to its ability to handle external disturbances and internal uncertainties without relying on an accurate mathematical model of the controlled object. The core component of ADRC is the extended state observer (ESO). The ESO can not only estimate the system state in real time but also simultaneously estimate external disturbances and unknown dynamics. However, the high gain of the ESO amplifies measurement noise and transmits it to the control signal calculated based on the observer's state vector.

[0006] Therefore, how to design a reasonable and effective active disturbance rejection control scheme to ensure stable operation of the DAB control system under conditions of high noise and lumped disturbance coupling has become a pressing technical research problem that needs to be solved. Summary of the Invention

[0007] To address the shortcomings of existing technologies, the purpose of this invention is to provide a dual active bridge converter control method and system based on dual-layer weighted active disturbance rejection, which can still ensure the fast response and high efficiency of the DAB converter output voltage under noise and lumped interference coupling.

[0008] To achieve the above objectives, the present invention is implemented through the following technical solution:

[0009] The first aspect of this invention provides a control method for a dual active bridge converter based on a two-layer weighted active disturbance rejection system, comprising the following steps:

[0010] Based on the characteristics of the dual active bridge converter system, an input-output voltage dynamic model is constructed, and the input-output voltage dynamic model is converted into a linear state-space equation;

[0011] Based on the linear state-space equations and the transmission power balance relationship, an energy function dynamic equation is constructed.

[0012] Based on the active disturbance rejection theory, the energy function dynamic equation is constructed into a standard extended state-space equation, and a two-layer observer is designed based on the extended state-space equation.

[0013] Based on the dual-layer observer structure, a control law is constructed based on the extended state-space equation and the energy function dynamics equation, and the output voltage of the phase-shift tracking dual active bridge converter is solved using the control law.

[0014] A second aspect of the present invention provides a dual active bridge converter control system based on a two-layer weighted active disturbance rejection system, comprising:

[0015] The voltage dynamics model building module is configured to construct an input-output voltage dynamics model based on the characteristics of the dual active bridge converter system, and to convert the input-output voltage dynamics model into a linear state-space equation.

[0016] The energy dynamics model building module is configured to construct energy function dynamics equations based on the transmission power balance relationship according to the linear state-space equations.

[0017] The observer design module is configured to construct the energy function dynamic equation into a standard extended state-space equation based on the active disturbance rejection theory, and to design a two-layer observer based on the extended state-space equation.

[0018] The observer control module is configured to construct a control law based on the state-space model and energy function according to the two-layer observer structure, and use the control law to solve for the output voltage of the shift-ratio tracking dual active bridge converter.

[0019] A third aspect of the present invention provides a medium having a program stored thereon, which, when executed by a processor, implements the steps of the dual active bridge converter control method based on dual-layer weighted active disturbance rejection as described in the first aspect of the present invention.

[0020] A fourth aspect of the present invention provides an apparatus including a memory, a processor, and a program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the dual active bridge converter control method based on dual-layer weighted active disturbance rejection as described in the first aspect of the present invention.

[0021] The above one or more technical solutions have the following beneficial effects:

[0022] To effectively suppress noise and compensate for lumped disturbances, thereby achieving accurate tracking of the DAB output voltage, this invention discloses a dual active bridge converter control method and system based on dual-layer weighted active disturbance rejection. Combining a dual-layer observer system and a weighted active disturbance rejection control method, noise and disturbances are effectively separated through weighting factors and fusion factors. Noise is filtered through a first-level subsystem and lumped disturbances are smoothed through a second-level subsystem. This effectively suppresses the impact of noise on converter data and compensates for estimation errors caused by lumped disturbances, achieving asymptotic stability of the DAB converter output voltage under noise and disturbance coupling conditions.

[0023] This invention designs a two-layer observer incorporating weighting and fusion factors to compensate for disturbances. By combining the optimized control method with the two-layer observer, asymptotic stability of the DAB under coupled conditions is achieved. Even under varying operating conditions and disturbances, stable output voltage control is maintained, demonstrating broad application prospects and significant practical value.

[0024] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0025] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0026] Figure 1 This is a topology diagram of a dual active bridge converter according to an embodiment of the present invention;

[0027] Figure 2 This is a simplified structural diagram of the dual active bridge converter according to an embodiment of the present invention;

[0028] Figure 3 This is a topology diagram of the two-layer observer system according to Embodiment 1 of the present invention;

[0029] Figure 4 This is a closed-loop feedback control structure diagram of the control method for a dual active bridge converter according to an embodiment of the present invention;

[0030] Figure 5 This is a simulation waveform of the output voltage of the dual-layer weighted active disturbance rejection control in Embodiment 1 of the present invention during a sudden change in output voltage.

[0031] Figure 6 This is a waveform diagram of relevant parameters of the DAB converter under the dual-layer weighted active disturbance rejection control in Embodiment 1 of the present invention when the output voltage changes abruptly;

[0032] Figure 7 This is a comparison of the simulated output voltage waveforms of dual-layer weighted active disturbance rejection control (ADRC), PI control, and traditional ADRC under load abrupt changes in Embodiment 1 of the present invention.

[0033] Figure 8 The waveform diagram of relevant parameters of the DAB converter under the double-layer weighted active disturbance rejection control in Embodiment 1 of the present invention during load change is shown. Detailed Implementation

[0034] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0035] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0036] Example 1:

[0037] Embodiment 1 of the present invention provides a control method for a dual active bridge converter based on a two-layer weighted active disturbance rejection system, comprising the following steps:

[0038] Step 1: Construct an input-output voltage dynamic model based on the characteristics of the dual active bridge converter system, and convert the input-output voltage dynamic model into a linear state-space equation.

[0039] Step 1.1: Construct a dynamic model of input and output voltages based on the characteristics of the dual active bridge converter system.

[0040] Step 1.1.1: Obtain the topology of the dual active bridge converter.

[0041] In one specific implementation, this embodiment is applied to a dual active bridge converter topology, and a single phase-shift modulation strategy is used for square wave control, that is, the duty cycle between the two AC square wave voltages is fixed at 50%, and the phase shift ratio between the two H bridges is changed.

[0042] Figure 1 This demonstrates a typical circuit topology for a DAB converter. The dual active bridge converter consists of primary and secondary H-arms, power transfer inductors, and... (External auxiliary inductor or leakage inductance of high-frequency transformer can be used) and high-frequency transformer Input side DC power supply and output side load (load The voltage on both sides is the output voltage. ), and capacitors and Composition, including switching devices The primary H-arm of the bridge is composed of The secondary H-arm of the bridge forms an energy transfer inductor. and high frequency transformer The magnetic network forms a connection between the AC ports of the two bridge arms. It is the turns ratio of the transformer (i.e., the ratio of the number of turns in the primary winding to the number of turns in the secondary winding of the DAB). and These are the AC side voltages of the primary and secondary bridge arms, respectively. Inductor voltage, This represents the inductor current.

[0043] Step 1.1.2: Analyze the dynamic relationship between input and output voltages based on the topology of the dual active bridge converter, and construct the dynamic model of input and output voltages.

[0044] In one specific implementation, this model is constructed based on the coupling relationship between input-side and output-side capacitor voltage changes and power transmission, derived from the principle of capacitor charge balance.

[0045] The power transfer of a DAB is determined by the shift ratio and voltage amplitude, and its steady-state power formula is:

[0046]

[0047] in, For steady-state power, For switching frequency, It is the system inductor, which can be connected to an external auxiliary inductor or use the leakage inductance of a high-frequency transformer. It is the turns ratio of the transformer. and These are the capacitances of the input and output capacitors, respectively. This represents the input voltage of the DAB. This represents the voltage across the output capacitor. It is the shift ratio between two AC square wave voltages.

[0048] The dynamics of the input / output capacitors are determined by the power balance:

[0049]

[0050]

[0051] in, and These are the rates of change of the input voltage and the output voltage, respectively. The load equivalent resistance, It is the internal resistance on the DC voltage side. This indicates the voltage of the DC voltage source.

[0052] Step 1.2: Convert the input and output voltage dynamics model into a linear state-space equation.

[0053] In one specific implementation, to facilitate intuitive analysis of the input-output voltage dynamics of the DAB converter, its equivalent circuit is simplified, resulting in a simplified topology diagram of the dual active bridge converter, as shown below. Figure 2 As shown in the diagram. The DAB will regulate the charging / discharging of energy storage devices such as power batteries and supercapacitors to ensure that user load demands are met normally.

[0054] The dynamic model of the physical characteristics of the DAB converter is transformed into the linear state-space equations of the system. The linear state-space equations of the DAB system are established and simplified. Based on the simplified topology of the DAB, the linear state-space equations of the DAB system can be obtained by Kirchhoff's Voltage Law (KVL) as follows:

[0055] (1).

[0056] in, For switching frequency, It is the system inductor, which can be connected to an external auxiliary inductor or use the leakage inductance of a high-frequency transformer. It is the turns ratio of the transformer. and These are the capacitances of the input and output capacitors, respectively. The load equivalent resistance, It is the internal resistance on the DC voltage side. Indicates the DC voltage source voltage. This represents the input voltage of the DAB. This represents the voltage across the output capacitor. and These are the rates of change of the input voltage and the output voltage, respectively. It is the shift ratio between two AC square wave voltages.

[0057] Step 2: Construct the energy function dynamic equation based on the transmission power balance relationship according to the linear state-space equation.

[0058] In one specific implementation, the total energy storage function of the system is defined as follows: The energy expression is derived from the power difference. Define the energy change rate function as The energy dynamics equations are obtained as follows:

[0059] (2).

[0060] Based on the results of the above feedback linearization (1), define For the instantaneous energy stored in the capacitors of the converter, the power balance relationship is: the rate of change of energy within the converter equals the difference between the input power and the output power, which has a clear physical meaning. Therefore, the total energy storage function of the DAB system is:

[0061] (3).

[0062] Choose the energy change rate function as:

[0063] (4).

[0064] Taking its derivative and performing a coordinate transformation, we obtain the energy dynamics equation as follows:

[0065] (5).

[0066] Step 3: Based on the active disturbance rejection theory, the energy function dynamic equation is constructed into a standard extended state-space equation, and a two-layer observer is designed based on the extended state-space equation to suppress measurement noise during the sampling process and compensate for lumped disturbances during the operation of the DAB system.

[0067] Step 3.1: Based on the active disturbance rejection theory, the energy function dynamic equation is transformed into the standard form extended state-space equation through coordinate transformation.

[0068] In one specific implementation, with As the principal state variables, To be the control variable, and to define the generalized total disturbance as... The derivative of the perturbation is defined as By replacing To eliminate the influence of different operating points. The characteristics of the DAB energy function are described using active disturbance rejection theory as follows:

[0069] (6).

[0070] in, The second-order time derivative of the total energy storage function of the DAB system is derived from the basic definition of ADRC, which elevates the energy dynamics equation to a second-order system for use in the design of higher-order controllers. Representing the input gain, it can be further obtained , Represents a preset working point. This represents a mismatch perturbation. It is a matching perturbation.

[0071] The generalized total disturbance that needs to be estimated Treating this as a new state, the extended state-space equations of the controllable canonical form are as follows:

[0072] (7).

[0073] in, Let be the instantaneous converter energy function stored in the capacitor. Let be the rate of change of energy. For the total disturbance, They represent The derivative, To control the quantity, Represents a preset working point. This indicates normal measurement output. Let be the rate of change of the disturbance.

[0074] Written in compact form as

[0075] (8).

[0076] in, For the expanded state variables, , and This represents the system matrix, input matrix, and perturbation input matrix of the extended state-space equations. Indicates sensor noise, This indicates a measurement output with noise. This indicates the control quantity.

[0077] In order to estimate the total disturbance in real time online, the corresponding linear extended state observer (LESO) is designed based on (7) as follows:

[0078] (9).

[0079] in, It is an extended state variable The estimated term, This is the ESO feedback error gain matrix that needs to be designed. According to the bandwidth parameterization method, all observer poles should be placed in the same location, i.e. The observer gain can be set to... .

[0080] Step 3.2: Design a two-layer observer based on the extended state-space equations.

[0081] like Figure 3 As shown, Figure 3 middle, The output current of the DAB, This represents the output voltage of the DAB. Based on the extended state-space equations, the observer structure is improved. To accurately estimate the total disturbance in real time and effectively suppress noise, unlike the existing single-layer ESO structure, this embodiment proposes a weighted two-layer fusion estimator (WDO) based on a hybrid structure of a two-layer third-order ESO and a second-order ESO, which is closely related to the performance of HWADRC.

[0082] Step 3.21: To suppress the impact of output measurement noise on estimation performance and compensate for some disturbances, construct the first-level subsystem dynamic model (WDO-1).

[0083] The dynamic model of the first-stage subsystem of the two-layer observer system is as follows:

[0084] (10).

[0085] in, This is the dynamic model of the first-level subsystem. They represent The first derivative, They are respectively for The final estimate, This is the WDO-1 unknown lumped disturbance prediction value. and measurement noise The estimated value of the combination, It is a constant, the observer gain. Represents the gain of the extended state observer. This represents an adjustable parameter used to determine the bandwidth of the extended state observer.

[0086] The main function of WDO-1 is to suppress the impact of output measurement noise on estimation performance and to compensate for some disturbances. Then the remaining perturbations The second-level subsystem will be built using WDO-2, and the data will be filtered using the UDE approach to improve the accuracy of the total disturbance estimation.

[0087] Step 3.22: Construct a second-level subsystem dynamic model to compensate for residual disturbances.

[0088] The signal will be used as the sole input signal to enter the second-stage subsystem WDO-2. The dynamic model of WDO-2 is as follows:

[0089] (11).

[0090] in, This is a dynamic model of the second-level subsystem. They represent The first derivative, These are the remaining disturbances and rate of change of disturbance The estimate, It is a configurable bandwidth observer gain used to smooth and compensate for disturbances.

[0091] Step 4: Based on the dual-layer observer structure, construct the control law based on the extended state-space equation and the energy function dynamics equation, and use the control law to solve for the output voltage of the shift-ratio tracking dual active bridge converter.

[0092] Step 4.1: Based on the observer structure, construct the control law using the state-space model and energy function.

[0093] Based on the filtering estimation effect of WDO, feedback control law It can be designed as:

[0094] (12).

[0095] in , This is a reference value for the internal energy of the converter. and These are the reference input and reference output voltages under steady-state conditions. They represent The estimated value. These are the magnification factors for proportional and differential equations, respectively. For controller bandwidth, It is a weighting factor. Because the dynamics of the disturbance and the characteristics of the noise are different, a weighting factor is introduced. To dynamically adjust the sensitivity of WDO to measurement noise and disturbance signals.

[0096] In this embodiment, the weighting factor α is typically a preset constant. The weighting factor α is mainly used to balance the estimation weights of the two-layer observer for disturbances and noise, allowing the observer to exhibit different characteristics in its roles of noise suppression and disturbance compensation, without requiring a strong real-time response. This embodiment uses the weighting factor α to suppress the influence of high-frequency noise and external disturbances on the output voltage. Its effect is on the observer's estimation accuracy of disturbances and noise, indirectly affecting the generation of the shift ratio.

[0097] By substituting (12) into the energy function, the dynamic characteristics of the DAB energy function with WDO are re-expressed as:

[0098] (13).

[0099] The system disturbance will be compensated after convergence. , Represents the fusion factor.

[0100] Through the ADRC structure, especially the disturbance estimation and compensation of ESO, the higher-order dynamics and disturbances of the system are effectively canceled, making the system's output response approximately directly determined by the control input u0. Therefore, the dynamic characteristic expression formula designed in this embodiment simplifies the controller design, eliminating the need to handle the complex nonlinear terms of the original system. It reduces the dependence on the precise mathematical model, and parameter adjustment only requires nominal gain, weighting factor, and observer bandwidth.

[0101] Step 4.2: Using the control law, solve for the updated shift ratio based on the relationship between the control input and the shift ratio.

[0102] In one specific implementation, the control input is obtained based on the control law; the value of the shift ratio is calculated using the relationship between the control input and the shift ratio; when the load changes abruptly, the shift ratio D can be quickly adjusted by tracking the reference voltage to compensate for the power gap and prevent voltage drop or overshoot. The solved shift ratio value can be applied in the dual active bridge converter to effectively track the output voltage reference value.

[0103] Specifically, in order to control the DAB converter, the control signal should be modulated to shift outwards compared to... Its generation method can be calculated based on existing single-phase-shift modulation strategies, according to the relationship between control input and phase shift. The solution for the shift ratio has the following expression:

[0104] (14).

[0105] Based on characteristics, in Around, the transmission power of DAB is compared to that of mobile. The relationship between the absolute values ​​of the characteristics is symmetrical. According to (15), The solution is also The output should be symmetrical. Furthermore, to prevent damage to the DAB converter, the following constraints should be applied to the output of the shift ratio to limit the output range:

[0106] (15).

[0107] In DAB conversion, the most important power transfer is determined by both the phase difference and the voltage amplitude. The converter controls the direction and magnitude of power transfer by adjusting the phase shift, thereby tracking the voltage reference value. This is achieved by using the solved phase shift... Substitute into the output power of DAB Specifically, this also involves the following aspects of the model:

[0108] (16)

[0109] The first item on the right is the power input for phase shift control, and the second item is the load power consumption. This is achieved through closed-loop regulation. And then adjust through power balance This allows it to converge to the reference output voltage value in a steady state. .

[0110] The active disturbance rejection optimization control method for dual active bridge converters in this embodiment is applicable to various phase shifting modes of DABs, such as single phase shift, extended phase shift, and dual phase shift. It can adapt to different phase shifting modes, exhibiting strong adaptability. Taking the simplest single phase shift control as an example, the control flowchart for controlling the dual active bridge converter using the two-layer weighted active disturbance rejection control method described in this embodiment is as follows: Figure 4 As shown, this embodiment uses MATLAB R2023b software to verify the control method in this embodiment.

[0111] The specific simulation parameters are set as follows: Switching frequency System inductance The turns ratio of the transformer The input and output capacitors are respectively and Load equivalent resistance DC voltage side internal resistance DC voltage source voltage The noise source uses Gaussian white noise and follows... in principle.

[0112] like Figure 5 As shown, this embodiment provides a two-layer weighted active disturbance rejection control at reference voltage abrupt changes (voltage changes from...). Mutation The output voltage simulation waveform is shown below. It can be seen that when the operating conditions of the DAB converter change, the model exhibits fast convergence speed and good steady-state and dynamic tracking performance, with a transient recovery time of 17.3ms. Furthermore, it is completely unaffected by changes or inaccuracies in the converter parameters, significantly improving the system's robustness. Figure 6 As shown in the figure, the waveform diagrams of the relevant parameters of the DAB converter under the dual-layer weighted active disturbance rejection control provided in this embodiment are extracted from the waveform outputs before and after the load change. It can be seen that the waveform output is normal under the control of the present invention.

[0113] like Figure 7 As shown, this embodiment provides a two-layer weighted active disturbance rejection control and PID control, and a traditional active disturbance rejection control in the case of load mutation (output load changes from...). Mutation The output voltage simulation waveforms are compared. It can be seen that during dynamic adjustment, the voltage stabilization time in this embodiment is approximately 4.991ms and the voltage overshoot is 5.78V when the load changes abruptly, demonstrating the fast dynamic characteristics of predictive control. While PID control can stabilize relatively quickly, its amplitude fluctuations are large, with a voltage overshoot and a relative error of 14.65V. The transient recovery time of the traditional active disturbance rejection control strategy is 20.087ms, and the voltage overshoot is 26.92V, proving the superiority of the method in this invention. Under the controller provided in this embodiment, the output voltage tracking error is approximately 1.23V.

[0114] like Figure 8 As shown in the figure, the waveform diagrams of the relevant parameters of the DAB converter under the dual-layer weighted active disturbance rejection control provided in this embodiment are extracted from the waveform outputs before and after the load change. It can be seen that the waveform output is normal under the control of this embodiment.

[0115] Example 2:

[0116] Embodiment 2 of the present invention provides a dual active bridge converter control system based on dual-layer weighted active disturbance rejection, comprising:

[0117] The voltage dynamics model building module is configured to construct an input-output voltage dynamics model based on the characteristics of the dual active bridge converter system, and to convert the input-output voltage dynamics model into a linear state-space equation.

[0118] The energy dynamics model building module is configured to construct energy function dynamics equations based on the transmission power balance relationship according to the linear state-space equations.

[0119] The observer design module is configured to construct the energy function dynamic equation into a standard extended state-space equation based on the active disturbance rejection theory, and to design a two-layer observer based on the extended state-space equation.

[0120] The observer control module is configured to construct a control law based on the state-space model and energy function according to the two-layer observer structure, and use the control law to solve for the output voltage of the shift-ratio tracking dual active bridge converter.

[0121] Example 3:

[0122] Embodiment 3 of the present invention provides a medium on which a program is stored. When the program is executed by a processor, it implements the steps in the dual active bridge converter control method based on dual-layer weighted active disturbance rejection as described in Embodiment 1 of the present invention.

[0123] Example 4:

[0124] Embodiment 4 of the present invention provides a device including a memory, a processor, and a program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps in the dual active bridge converter control method based on dual-layer weighted active disturbance rejection as described in Embodiment 1 of the present invention.

[0125] The steps and methods involved in Examples 2, 3 and 4 above correspond to those in Example 1. For specific implementation details, please refer to the relevant description section of Example 1.

[0126] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computer devices. Optionally, they can be implemented using computer-executable program code, thereby allowing them to be stored in a storage device for execution by a computer device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. The present invention is not limited to any particular combination of hardware and software.

[0127] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A control method for a dual active bridge converter based on dual-layer weighted active disturbance rejection, characterized in that, Includes the following steps: Based on the characteristics of the dual active bridge converter system, an input-output voltage dynamic model is constructed, and the input-output voltage dynamic model is converted into a linear state-space equation; Based on the linear state-space equations and the transmission power balance relationship, an energy function dynamic equation is constructed. Based on the active disturbance rejection theory, the energy function dynamic equation is constructed into a standard form extended state-space equation. A two-layer observer is then designed based on this extended state-space equation. The standard form extended state-space equation is as follows: ， in, Let be the instantaneous converter energy function stored in the capacitor. Let be the rate of change of energy. For the total disturbance, They represent The derivative, To control the quantity, Represents a preset working point. This indicates normal measurement output. The rate of change of the disturbance; The specific steps for designing a two-layer observer based on the extended state-space equations are as follows: To suppress the impact of output measurement noise on estimation performance and compensate for some disturbances, a dynamic model of the first-level subsystem is constructed. A second-level subsystem dynamic model is constructed to compensate for residual disturbances; The two-layer observer includes: First-level subsystem dynamics model: ， in, This is the dynamic model of the first-level subsystem. They represent The first derivative, They are respectively for The final estimate, It is the predicted value of the unknown lumped disturbance in the dynamic model of the first-level subsystem. and measurement noise The estimated value of the combination, It is a constant, the observer gain. Represents the gain of the extended state observer. This represents an adjustable parameter used to determine the bandwidth of the extended state observer; Second-level subsystem dynamics model: ， in, This is the dynamic model of the second-level subsystem. They represent The first derivative, These are the remaining disturbances and rate of change of disturbance The estimate, It is the bandwidth observer gain, used to smooth and compensate for disturbances; Based on the dual-layer observer structure, a control law is constructed based on the state-space model and energy function, and the output voltage of the shift-ratio tracking dual active bridge converter is solved using the control law. The control law is: ， in, For control laws, , This is a reference value for the internal energy of the converter. and These are the reference input and reference output voltages in a steady state. They represent The estimated value, These are the magnification factors for proportional and differential equations, respectively. For controller bandwidth, It is a weighting factor. and These are the capacitance values ​​of the input and output capacitors, respectively.

2. The control method for a dual active bridge converter based on dual-layer weighted active disturbance rejection as described in claim 1, characterized in that, The specific steps for constructing the input and output voltage dynamics model based on the characteristics of a dual active bridge converter system are as follows: Obtain the topology of the dual active bridge converter; Based on the analysis of the input-output voltage dynamics relationship of the dual active bridge converter topology, an input-output voltage dynamics model is constructed.

3. The control method for a dual active bridge converter based on dual-layer weighted active disturbance rejection as described in claim 1, characterized in that, The specific steps for solving the output voltage of the phase-shift tracking dual active bridge converter using the control law are as follows: The control input obtained from the control law; The value of the shift ratio is calculated using the relationship between the control input and the shift ratio. The solved shift ratio value is applied in a dual active bridge converter to track the output voltage reference value.

4. A control system for the dual active bridge converter control method based on double-layer weighted active disturbance rejection as described in any one of claims 1-3, characterized in that, include: The voltage dynamics model building module is configured to construct an input-output voltage dynamics model based on the characteristics of the dual active bridge converter system, and to convert the input-output voltage dynamics model into a linear state-space equation. The energy dynamics model building module is configured to construct energy function dynamics equations based on the transmission power balance relationship according to the linear state-space equations. The observer design module is configured to construct the energy function dynamic equation into a standard extended state-space equation based on the active disturbance rejection theory, and to design a two-layer observer based on the extended state-space equation. The observer control module is configured to construct a control law based on the state-space model and energy function according to the two-layer observer structure, and use the control law to solve for the output voltage of the shift-ratio tracking dual active bridge converter.

5. A computer-readable storage medium, characterized in that, It stores multiple instructions, which are adapted to be loaded and executed by the processor of the terminal device. The dual active bridge converter control method based on double-layer weighted active disturbance rejection as described in any one of claims 1-3.

6. A terminal device, characterized in that, The invention includes a processor and a computer-readable storage medium, wherein the processor is used to implement various instructions; and the computer-readable storage medium is used to store multiple instructions adapted to be loaded by the processor and executed by the processor for the dual active bridge converter control method based on double-layer weighted active disturbance rejection as described in any one of claims 1-3.

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