Power transmission line mc-wpt system based on model-free adaptive control and control method thereof

Abstract

The application relates to the technical field of magnetic coupling wireless power transmission, and particularly discloses a power transmission line MC-WPT system based on model-free adaptive control and a control method thereof. A model-free adaptive controller is adopted to calculate a phase-shifting angle at the next moment according to a sampling voltage at the current moment and a sampling voltage at the previous moment, and a phase-shifting angle at the current moment and a phase-shifting angle at the previous moment of the high-frequency inverter unit, and to send the phase-shifting angle at the next moment to the high-frequency inverter unit, so as to realize closed-loop control until the voltage of an online monitoring device reaches a desired voltage. The application combines model-free adaptive control with a multi-relay coil wireless power transmission system, is not subject to a complex mathematical model of the multi-relay wireless power transmission system, simplifies a design and analysis link of the whole system, and adjusts control parameters according to parameter perturbation and load change in the system, improves the overall robustness of the system, and guarantees transmission distance and transmission stability of the wireless power transmission system.

Description

Technical Field

[0001] This invention relates to the field of magnetically coupled wireless power transfer (MC-WPT) technology, and in particular to a transmission line MC-WPT system and control method based on model-free adaptive control. Background Technology

[0002] With the continuous development of the economy, society, and smart grids, large-capacity, long-distance power transmission is an important means to address the mismatch between China's energy resource distribution and electricity demand. Online monitoring equipment for transmission lines has been widely used, but the reliability of its power supply has become a significant factor restricting the development of online monitoring technology. Currently, the main power supplies for online monitoring equipment include battery power, solar power, wind power, microwave power, and voltage transformers. However, these all suffer from insufficient reliability, high implementation difficulty, and high application costs in terms of safety, practicality, and cost. Therefore, to solve the power supply problem for online monitoring equipment, many scholars both domestically and internationally have been researching how to combine current transformer (CT) energy harvesting devices installed on high-voltage transmission lines with wireless power transfer (WPT) technology. This would allow the energy harvested from the line to power the online monitoring equipment installed on the transmission towers, ensuring the safe and stable operation of high-voltage transmission lines.

[0003] In high-voltage transmission lines with voltage levels greater than or equal to 110kV, the safe insulation distance is more than 1m. Currently, the effective transmission distance of commonly used resonant wireless power transmission systems is often less than this safe insulation distance, and the supplied energy cannot meet the power requirements of the load. To improve the effective transmission distance of the system, a common approach is to add multiple relay coils in the middle of the traditional dual-coil structure.

[0004] However, current multi-relay coil wireless power transmission systems for high-voltage power transmission applications all have some shortcomings:

[0005] 1. Multi-relay wireless power transmission systems are characterized by high-order and complex cross-coupling. Based on the commonly used analysis methods, a large number of system parameters need to be processed during the modeling and analysis process, making it difficult to directly solve the system energy efficiency equation and achieve power control for different loads.

[0006] 2. Poor system robustness: Most multi-relay wireless power transmission systems use open-loop or traditional PID control methods, which have poor anti-interference capabilities and are not conducive to the safe and stable operation of online monitoring equipment. Summary of the Invention

[0007] This invention provides a transmission line MC-WPT system and its control method based on model-free adaptive control. The technical problem it solves is: how to achieve constant voltage output control of the transmission line MC-WPT system with a new control method and improve the robustness of the MC-WPT system.

[0008] To address the above technical problems, this invention provides a model-free adaptive control-based MC-WPT system for transmission lines, comprising a primary-side power conversion device, a magnetic coupling mechanism, a secondary-side power conversion device, and online monitoring equipment. The primary-side power conversion device includes a high-voltage energy extraction and conversion unit, a high-frequency inverter unit, and a primary-level compensation network. The secondary-side power conversion device includes a secondary compensation network and a full-bridge rectifier module. The key features are:

[0009] The system also includes a voltage sampling module and a model-free adaptive controller;

[0010] The voltage sampling module is used to sample the voltage of the online monitoring device and send it to the model-free adaptive controller;

[0011] The model-free adaptive controller calculates the phase shift angle for the next moment based on the sampled voltage at the current moment and the sampled voltage at the previous moment, as well as the phase shift angle of the high-frequency inverter unit at the current moment and the previous moment, and sends it to the high-frequency inverter unit to achieve closed-loop control until the voltage of the online monitoring device reaches its expected voltage.

[0012] Preferably, the specific process by which the model-free adaptive controller calculates the latest phase shift angle is as follows:

[0013] according to Calculate the theoretical voltage value at the next moment. ,in This represents the difference in phase angle between the current moment and the previous moment. This is the estimated value of the system's pseudo-Jacobi matrix at the current moment. The sampled voltage at the current moment, superscript Indicates matrix transpose;

[0014] according to Calculate the phase shift angle at the next moment. , This is an estimate of the system's pseudo-Jacobi matrix at the next time step. For the first step of the long factor, It is the first weighting factor. The desired voltage of the online monitoring device.

[0015] Preferably, the estimated value of the system pseudo-Jacobi matrix at the next time step. Iterate according to the following formula:

[0016] ,

[0017] in, It is the second step length factor. It is the second weighting factor. This represents the difference between the sampled voltage at the current moment and the previous moment.

[0018] Preferably, the magnetic coupling mechanism includes a transmitting coil, One relay coil and one receiving coil.

[0019] Preferably, the relay coil is connected to a relay compensation capacitor.

[0020] Preferably, the primary compensation network adopts an LCC compensation network, and the secondary compensation network adopts an LCC compensation network.

[0021] Preferred, , , , .

[0022] This invention also provides a control method for a transmission line MC-WPT system based on model-free adaptive control, the key of which includes the following steps:

[0023] S1. The model-free adaptive controller controls the high-frequency inverter unit with an initial phase shift angle;

[0024] S2. The voltage sampling module samples the voltage of the online monitoring device and sends it to the model-free adaptive controller;

[0025] S3. The model-free adaptive controller calculates the phase shift angle of the next moment based on the sampled voltage at the current moment and the sampled voltage at the previous moment, as well as the phase shift angle of the high-frequency inverter unit at the current moment and the previous moment, and sends it to the high-frequency inverter unit to achieve closed-loop control until the voltage of the online monitoring device reaches its expected voltage.

[0026] Furthermore, step S3 specifically includes the following steps:

[0027] S31, according to Calculate the theoretical voltage value at the next moment. ,in This represents the difference in phase angle between the current moment and the previous moment. The superscript represents the estimated value of the system's pseudo-Jacobi matrix at the current moment. Indicates matrix transpose. The sampled voltage at the current moment;

[0028] S32, according to Calculate the phase shift angle at the next moment. , This is an estimate of the system's pseudo-Jacobi matrix at the next time step. For the first step of the long factor, It is the first weighting factor. This is the expected voltage for the online monitoring device.

[0029] Furthermore, in step S32, the estimated value of the system pseudo-Jacobi matrix at the next time step... Iterate according to the following formula:

[0030] ,

[0031] in, It is the second step length factor. It is the second weighting factor. This represents the difference between the sampled voltage at the current moment and the previous moment.

[0032] This invention provides a model-free adaptive control-based MC-WPT (Multi-mode Transmission Line) system and its control method. The model-free adaptive controller calculates the phase shift angle for the next moment based on the current and previous sampled voltages, as well as the phase shift angles of the high-frequency inverter unit at both times, and sends this calculation to the high-frequency inverter unit. This achieves closed-loop control until the voltage of the online monitoring equipment reaches its desired value. This invention combines model-free adaptive control with a multi-relay wireless power transmission system, eliminating the need for complex mathematical models and simplifying the design and analysis of the entire system. Furthermore, it automatically adjusts control parameters based on parameter perturbations and load changes within the system, improving overall system robustness and ensuring the transmission distance and stability of the wireless power transmission system. Compared to traditional adaptive control methods, the model-free adaptive control method has the following advantages:

[0033] 1. It relies solely on real-time measured data from the controlled system, without depending on any mathematical model information of the controlled system;

[0034] 2. No external test signals or training processes are required, which are necessary for neural network-based nonlinear adaptive control methods; therefore, the control cost is low.

[0035] 3. The method is simple, computationally inexpensive, easy to implement, and robust.

[0036] 4. It can guarantee the monotonic convergence of the tracking error of the closed-loop system and the stability of bounded-input bounded-output (BIBO), which is an important feature that distinguishes it from other data-driven control methods. Attached Figure Description

[0037] Figure 1 This is a module structure diagram of the MC-WPT system for transmission lines based on model-free adaptive control provided in an embodiment of the present invention;

[0038] Figure 2 This is a hierarchical diagram of the magnetic coupling mechanism provided in an embodiment of the present invention;

[0039] Figure 3 This is a diagram showing the magnetic field distribution between coils of the magnetic coupling mechanism provided in an embodiment of the present invention;

[0040] Figure 4 This is a flowchart of model-free adaptive control provided in an embodiment of the present invention;

[0041] Figure 5 This is a schematic diagram of the input and output of a model-free adaptive controller in simulation provided by an embodiment of the present invention. Detailed Implementation

[0042] The embodiments of the present invention are described in detail below with reference to the accompanying drawings. The embodiments are given for illustrative purposes only and should not be construed as limiting the present invention. The accompanying drawings are for reference and illustration only and do not constitute a limitation on the scope of patent protection of the present invention, because many changes can be made to the present invention without departing from the spirit and scope of the present invention.

[0043] The wireless power transmission system designed in this invention is used as an online monitoring device in high-voltage transmission lines. Regarding the design of the coupling mechanism, since single-transmitter, single-receiver coupling mechanisms are sensitive to system parameters, have short transmission distances, and poor output power stability, the design of the magnetic coupling mechanism should focus on increasing the number of relay units and designing model-free adaptive controller parameters.

[0044] The energy harvested by CT energy harvesting technology from the alternating electromagnetic field around high-voltage transmission lines can meet the power supply needs of most online monitoring equipment, such as... Figure 1 As shown, the MC-WPT system for transmission lines based on model-free adaptive control provided in this embodiment of the invention includes a primary-side power conversion device, a magnetic coupling mechanism, a secondary-side power conversion device, and an online monitoring device. The primary-side power conversion device includes a high-voltage energy harvesting and conversion unit, a high-frequency inverter unit, and a primary compensation network. The secondary-side power conversion device includes a secondary compensation network and a full-bridge rectifier module. The system also includes a voltage sampling module and a model-free adaptive controller (fcn).

[0045] The voltage sampling module is used to sample the voltage of the online monitoring device and send it to the model-free adaptive controller;

[0046] The model-free adaptive controller calculates the phase shift angle for the next moment based on the sampled voltage at the current moment and the sampled voltage at the previous moment, as well as the phase shift angle of the high-frequency inverter unit at the current moment and the previous moment, and sends it to the high-frequency inverter unit to achieve closed-loop control until the voltage of the online monitoring device reaches its expected voltage.

[0047] The entire system operates as follows: First, energy is obtained from the high-voltage transmission line via the CT power extraction device. Then, the primary-side power conversion device converts the power frequency energy into high-frequency energy. Finally, the energy is transmitted to the secondary-side power conversion device via a magnetic coupling mechanism consisting of a transmitting coil, multiple relay coils, and a receiving coil. The magnetic coupling mechanism includes multiple coils (the transmitting coil, relay coil, and receiving coil). The relay coil and receiving coil generate magnetic coupling under the action of a high-frequency alternating magnetic field. The receiving coil captures part of the high-frequency alternating magnetic field and generates a high-frequency induced voltage. The secondary power conversion device rectifies the high-frequency induced voltage to generate DC power and collects the output DC voltage as a control quantity. The phase shift angle of the inverter is obtained through a model-free adaptive controller and sent to the high-frequency inverter unit of the primary power conversion device for phase shift control. Finally, a reliable and stable low-voltage DC power supply is provided to the online monitoring equipment of the high-voltage transmission line.

[0048] The embodiments of the present invention employ, as follows Figure 2 The transmitting coil-dual repeater coil-receiving coil structure is shown, and the magnetic field distribution between the coils is as follows. Figure 3 As shown, by Figure 3 It can be seen that the coupling effect between the power transmitting and receiving coils is good, the magnetic field is mainly distributed in the space between the coils, and the magnetic field radiated to the external space is small and negligible, indicating that the magnetic core material plays a good magnetic shielding role.

[0049] To achieve a relatively stable constant voltage output, the primary compensation network adopts an LCC compensation network, the secondary compensation network adopts an LCC compensation network, and each relay coil is also connected to a relay compensation network.

[0050] Specifically, such as Figure 4 As shown in the flowchart, the voltage sampling module samples the voltage of each online monitoring device and sends it to the model-free adaptive controller. The model-free adaptive controller calculates the latest phase shift angle. .

[0051] The model-free adaptive controller calculates the latest phase shift angle. The specific process is as follows:

[0052] First according to Calculate the theoretical voltage value at the next moment. ,in This represents the difference in phase angle between the current moment and the previous moment. This is the estimated value of the system's pseudo-Jacobi matrix at the current moment. The sampled voltage at the current moment, superscript Indicates matrix transpose;

[0053] Then according to Calculate the phase shift angle at the next moment. , This is an estimate of the system's pseudo-Jacobi matrix at the next time step. For the first step of the long factor, It is the first weighting factor. This refers to the desired voltage for this online monitoring device.

[0054] ,if ,

[0055]

[0056] It is the estimated value of the pseudo-Jacobi matrix of the system at the current moment; yes The initial value of the system pseudo-Jacobi matrix at the next time step. Iterate according to the following formula:

[0057]

[0058] in, It is the second step length factor. It is the second weighting factor. This represents the difference between the sampled voltage at the current moment and the previous moment.

[0059] This invention establishes a SIMULINK simulation model, employing an inverter to convert DC power to 85kHz high-frequency AC power, and using an LCC-SS-LCC resonant network for compensation. The current transformer (CT) of the high-voltage transmission line provides a stable DC power supply to the primary-side high-frequency inverter. The transmitting coil then transmits the power wirelessly to the secondary-side receiving coil via two independent repeater coils. The DC power obtained after full-bridge rectification and final filtering is supplied to the load. Voltage sampling is performed at the load end, and the sampled voltage is sent back as follows: Figure 5 In the model-free adaptive controller shown, the latest phase shift angle theta_next is obtained through iterative calculation and sent back to the high-frequency inverter unit on the primary side for phase shifting operation, ultimately achieving closed-loop control with constant voltage across the DC load.

[0060] After establishing the SIMULINK model, assuming the DC output voltage across the load is to be controlled to 50V (i.e., ref = 50V), DC voltage is sampled at a frequency of 200kHz across the load. The sampled values ​​are as follows: Figure 5 In the model-free adaptive controller shown, U is used as the input variable. After a delay of 1 / Z, U_1 input to the controller represents the DC voltage input in the previous sampling period. theta is the phase shift angle of the inverter unit at the current moment, which is the input of the controller output. After a delay of 1 / Z, theta_1 input is the phase shift angle of the inverter at the previous moment. fai is the parameter of the estimator at the current moment. Theta_next output is the phase shift angle output to the inverter, and is also used as a new input to theta for a new round of iterative calculation. The fai_next output is the new estimator parameter output, which is used as a new input to fai at the next moment. First, the weighting factors are determined. Step size factor Weighting factors Step size factor .

[0061] First, calculate:

[0062] ,

[0063] ,

[0064] According to the formula It can be calculated And then according to The theta_next value is calculated and input into the inverter unit.

[0065] And according to the formula calculate Used for the next iteration.

[0066] The calculated theta_next is output to the phase-shift register of the DSP28335 controller. The DSP28335's EPWM module drives the inverter's PWM wave. EPWM1A and EPWM1B drive two MOSFETs on the same bridge arm 1 of the inverter; these are two completely inverted PWM waves. EPWM2A and EPWM2B drive two MOSFETs on the other bridge arm 2 of the inverter; these are also two completely inverted PWM waves. The effect of this phase shift angle is that, with bridge arm 1 stationary, bridge arm 2 is phase-shifted. This creates a small conduction angle between bridge arm 1 and bridge arm 2, reducing the PWM duty cycle of the entire full-bridge inverter output, thus reducing the voltage. Similarly, theta2_next is used as the phase shift angle for EPWM3 and EPWM4. After voltage adjustment, it is compared with the preset ref, and then the new estimator parameters and theta phase shift angle are recalculated for further phase shift adjustment until the DC voltage U and ref are completely equal.

[0067] This invention also provides a control method for a transmission line MC-WPT system based on model-free adaptive control, see reference. Figure 4 The flowchart includes the following steps:

[0068] Including the following steps:

[0069] S1. The model-free adaptive controller controls the high-frequency inverter unit with an initial phase shift angle;

[0070] S2. The voltage sampling module samples the voltage of the online monitoring device and sends it to the model-free adaptive controller;

[0071] S3. The model-free adaptive controller calculates the phase shift angle of the next moment based on the sampled voltage at the current moment and the sampled voltage at the previous moment, as well as the phase shift angle of the high-frequency inverter unit at the current moment and the previous moment, and sends it to the high-frequency inverter unit to achieve closed-loop control until the voltage of the online monitoring device reaches its expected voltage.

[0072] Step S3 specifically includes the following steps:

[0073] S31, according to Calculate the theoretical voltage value at the next moment. ,in This represents the difference in phase angle between the current moment and the previous moment. This is the estimated value of the system's pseudo-Jacobi matrix at the current moment, with the superscript T indicating matrix transpose. The sampled voltage at the current moment;

[0074] S32, according to Calculate the phase shift angle at the next moment. , This is an estimate of the system's pseudo-Jacobi matrix at the next time step. For the first step of the long factor, It is the first weighting factor. This is the expected voltage for the online monitoring device.

[0075] In step S32, the estimated value of the system pseudo-Jacobi matrix at the next time step. Iterate according to the following formula:

[0076]

[0077] in, It is the second step length factor. It is the second weighting factor. This represents the difference between the sampled voltage at the current moment and the previous moment.

[0078] In summary, the MC-WPT transmission line system and its control method based on model-free adaptive control provided in this invention employ a model-free adaptive controller to calculate the phase shift angle for the next moment based on the sampled voltage at the current moment and the sampled voltage at the previous moment, as well as the phase shift angle of the high-frequency inverter unit at the current moment and the previous moment, and sends this calculation to the high-frequency inverter unit. This achieves closed-loop control until the voltage of the online monitoring equipment reaches its desired voltage. This invention combines model-free adaptive control with a multi-relay wireless power transmission system, avoiding the constraints of the complex mathematical model of the multi-relay wireless power transmission system, simplifying the design and analysis of the entire system. Furthermore, it automatically adjusts the control parameters according to parameter perturbations and load changes within the system, improving the overall robustness of the system and ensuring the transmission distance and stability of the wireless power transmission system. Compared with traditional adaptive control methods, the model-free adaptive control method has the following advantages:

[0079] 1. It relies solely on real-time measured data from the controlled system, without depending on any mathematical model information of the controlled system;

[0080] 2. No external test signals or training processes are required, which are necessary for neural network-based nonlinear adaptive control methods; therefore, the control cost is low.

[0081] 3. The method is simple, computationally inexpensive, easy to implement, and robust.

[0082] 4. It can guarantee the monotonic convergence of the tracking error of the closed-loop system and the stability of bounded-input bounded-output (BIBO), which is an important feature that distinguishes it from other data-driven control methods.

[0083] The above embodiments are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above embodiments. Any changes, modifications, substitutions, combinations, or simplifications made without departing from the spirit and principle of the present invention shall be considered equivalent substitutions and shall be included within the protection scope of the present invention.

Claims

1. A transmission line MC-WPT system based on model-free adaptive control, comprising a primary-side power conversion device, a magnetic coupling mechanism, a secondary-side power conversion device, and online monitoring equipment, wherein the primary-side power conversion device comprises a high-voltage energy harvesting and conversion unit, a high-frequency inverter unit, and a primary-level compensation network, and the secondary-side power conversion device comprises a secondary-level compensation network and a full-bridge rectifier module, characterized in that: The system also includes a voltage sampling module and a model-free adaptive controller; The voltage sampling module is used to sample the voltage of the online monitoring device and send it to the model-free adaptive controller; The model-free adaptive controller calculates the phase shift angle of the next moment based on the sampled voltage at the current moment and the sampled voltage at the previous moment, as well as the phase shift angle of the high-frequency inverter unit at the current moment and the previous moment, and sends it to the high-frequency inverter unit to achieve closed-loop control until the voltage of the online monitoring device reaches its expected voltage. The specific process by which the model-free adaptive controller calculates the latest phase shift angle is as follows: according to Calculate the theoretical voltage value at the next moment. ,in This represents the difference in phase angle between the current moment and the previous moment. This is the estimated value of the system's pseudo-Jacobi matrix at the current moment. The sampled voltage at the current moment, superscript Indicates matrix transpose; according to Calculate the phase shift angle at the next moment. , This is an estimate of the system's pseudo-Jacobi matrix at the next time step. For the first step of the long factor, It is the first weighting factor. The desired voltage of the online monitoring device; The estimated value of the system pseudo-Jacobi matrix at the next time step Iterate according to the following formula: ， in, It is the second step length factor. It is the second weighting factor. This represents the difference between the sampled voltage at the current moment and the previous moment. The magnetic coupling mechanism includes a transmitting coil, One relay coil and one receiving coil.

2. The MC-WPT system for transmission lines based on model-free adaptive control according to claim 1, characterized in that: The relay coil is connected to a relay compensation capacitor.

3. The MC-WPT system for transmission lines based on model-free adaptive control according to claim 2, characterized in that, The primary compensation network adopts an LCC compensation network, and the secondary compensation network adopts an LCC compensation network.

4. The MC-WPT system for transmission lines based on model-free adaptive control according to claim 1, characterized in that: ， ， ， 。 5. A control method for a transmission line MC-WPT system based on model-free adaptive control, applied to the transmission line MC-WPT system based on model-free adaptive control as described in any one of claims 1 to 4, characterized in that, Including the following steps: S1. The model-free adaptive controller controls the high-frequency inverter unit with an initial phase shift angle; S2. The voltage sampling module samples the voltage of the online monitoring device and sends it to the model-free adaptive controller; S3. The model-free adaptive controller calculates the phase shift angle of the next moment based on the sampled voltage at the current moment and the sampled voltage at the previous moment, as well as the phase shift angle of the high-frequency inverter unit at the current moment and the previous moment, and sends it to the high-frequency inverter unit to achieve closed-loop control until the voltage of the online monitoring device reaches its expected voltage. Step S3 specifically includes the following steps: S31, according to Calculate the theoretical voltage value at the next moment. ,in This represents the difference in phase angle between the current moment and the previous moment. The superscript represents the estimated value of the system's pseudo-Jacobi matrix at the current moment. Indicates matrix transpose. The sampled voltage at the current moment; S32, according to Calculate the phase shift angle at the next moment. , This is an estimate of the system's pseudo-Jacobi matrix at the next time step. For the first step of the long factor, It is the first weighting factor. This is the expected voltage of the online monitoring device; In step S32, the estimated value of the system pseudo-Jacobi matrix at the next time step. Iterate according to the following formula: ， in, It is the second step length factor. It is the second weighting factor. This represents the difference between the sampled voltage at the current moment and the previous moment.

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