ZPA frequency tracking method and system of tight coupling wireless power transmission mechanism

Abstract

The invention provides a ZPA frequency tracking method and system of a tight coupling wireless power transmission mechanism, and aims to solve the technical problems that an existing ZPA frequency tracking system is complex in structure and the tracking method is weak in anti-interference capability. The method comprises the following steps: constructing a fundamental wave approximation model of a primary side current i1, forming a vector theta by model parameters of the fundamental wave approximation model, and setting an initial vector; and reading a primary side current sampling value at the current moment, constructing a least square objective function of a vector theta, iteratively updating parameters in the vector theta by using a recursive Gaussian-Newton GN algorithm by taking the primary side current sampling value as input, and generating a driving signal according to the updated parameters. According to the method, the amplitude, the frequency and the phase information of the current fundamental wave only need to be sampled at the primary side, the ZPA frequency drift caused by the coil position deviation and the parameter change of the square coupling mechanism is effectively solved, the influence of the frequency bifurcation problem under the tight coupling condition is avoided, and the initial value of the algorithm can be adjusted to approach the high and low frequency bifurcation point.

Description

Technical Field

[0001] This invention relates to the field of wireless power transmission, and in particular to a ZPA frequency tracking method and system for a tightly coupled wireless power transmission mechanism. Background Technology

[0002] Magnetic-coupled wireless power transfer (MC-WPT) utilizes the near-field region of non-radiative electromagnetic fields to transmit power, offering advantages such as long transmission distance, high efficiency, and high security. It is applied in numerous fields, including wireless charging of electric vehicles and power supply for portable electronic devices. However, WPT systems under tight coupling conditions can experience frequency bifurcation, resulting in multiple zero-phase-angle (ZPA) resonant points. This causes the operating frequency to deviate from the inverter's switching frequency, significantly reducing transmission efficiency. Therefore, accurately detecting the system's ZPA frequency and adjusting the inverter's switching frequency is crucial for resolving the detuning problem.

[0003] Currently, zero-crossing detection and phase-locked loop (PLL) automatic frequency locking technology are commonly used to achieve ZPA frequency tracking. This is achieved by detecting the zero-crossing point of the sampled current at the inverter bridge port and performing phase detection adjustment to ensure that the primary side current and voltage are in phase. However, in high-power applications, the zero-crossing detection circuit is susceptible to noise. In addition, traditional PLL technology generally requires the use of related analog chips, which increases the complexity of hardware design and application costs. Summary of the Invention

[0004] The purpose of this invention is to provide a ZPA frequency tracking method and system with a tightly coupled wireless power transmission mechanism. This addresses the technical problems of existing ZPA frequency tracking systems having complex structures and weak anti-interference capabilities.

[0005] A ZPA frequency tracking method for a tightly coupled wireless power transfer mechanism, comprising the following steps:

[0006] S1: Construct a fundamental approximation model for the primary current i1. The model parameters of the fundamental approximation model constitute a vector θ. Set the initial vector. ;

[0007] S2: Read the primary current sample value at the current moment, construct the least squares objective function of vector θ, and use the primary current sample value as input to iteratively update the parameters using the recursive Gauss-Newton (GN) algorithm, and generate the driving signal based on the updated parameters.

[0008] Optionally, the fundamental approximation model of the primary current i1 constructed in step S1 is as follows:

[0009]

[0010] In the formula, a1 is the amplitude of the fundamental current, b1 is the initial phase of the fundamental current, and ω is the frequency of the fundamental current. Let the vector formed by these components be θ = [a1, b1, ω].T and set the initial vector .

[0011] Optionally, the least-squares objective function for constructing vector θ in step S2 is:

[0012] ;

[0013] In the formula, * represents the sampling data identifier. Represents the length of the data. θ represents the estimated value of the vector θ, and k represents the sampling time.

[0014] Optionally, the specific steps in step S2, which involve iteratively updating the parameters using the recursive Gauss-Newton (GN) algorithm and generating the driving signal based on the updated parameters, are as follows:

[0015] S2.1: Read the current sample value at the current moment, with k=1 at the initial moment;

[0016] S2.2: Using the primary current value at time k as input, the parameters in the vector θ are iteratively updated using the recursive Gauss-Newton GN algorithm, and the estimated current value at time k+1 is predicted.

[0017] S2.3: Generate a driving signal by iteratively updating the parameters in the vector θ, and return to step S2.1 with k=k+1, and repeat steps S2.1-S2.3.

[0018] Optionally, the estimated current value in step S2.2 is:

[0019] ;

[0020] In the formula , Represents the sampling length The algorithm estimates the amplitude at time step. Sampling length The algorithm estimates the frequency at time step. Sampling length The time of moment, Sampling length The algorithm estimates the phase at each time step.

[0021] A ZPA frequency tracking system for a tightly coupled wireless power transmission mechanism is provided to implement the ZPA frequency tracking method for the aforementioned tightly coupled wireless power transmission mechanism, comprising a transmitter and a receiver coupled together for power transmission.

[0022] It also includes a current sampling circuit for acquiring the primary current of the transmitter, a DSP controller for solving the optimal parameters of the fundamental approximation model based on the primary current, and a drive circuit for generating drive signals based on the optimal parameters.

[0023] Optionally, the transmitting end includes a DC power supply V connected in sequence. in Inverter, primary-side compensation circuit and transmitting coil L1;

[0024] The receiving end includes a receiving coil L2, a secondary compensation circuit, a rectifier filter, and a load R connected in sequence. o .

[0025] Optionally, the primary-side compensation circuit and the secondary-side compensation circuit are in an SS-type topology.

[0026] Because of the adoption of the above technical solution, the present invention has the following advantages:

[0027] 1. The ZPA frequency tracking method proposed in this application only requires the amplitude, frequency and phase information of the fundamental current of the primary side sampling, which effectively solves the ZPA frequency drift caused by the coil position offset and parameter change of the square coupling mechanism. It is not affected by the frequency bifurcation problem under tight coupling, and can adjust the initial value of the algorithm to make it approach the high and low frequency bifurcation points respectively.

[0028] 2. This application samples the primary current data, avoiding the delay and interference problems caused by primary and secondary communication, and does not require a substantial zero-crossing detection circuit, thus having strong anti-noise interference capability.

[0029] 3. This application provides digital tracking of ZPA frequency, which is flexible, convenient, real-time, and enables online tracking.

[0030] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0031] The accompanying drawings of this invention are described below.

[0032] Figure 1 This is a schematic diagram of the ZPA frequency tracking system of the present invention.

[0033] Figure 2 This is a schematic diagram of frequency bifurcation when the coupling coefficient is greater than the critical value according to the present invention.

[0034] Figure 3 This is a flowchart of the ZPA frequency tracking method of the present invention.

[0035] Figure 4 This is a schematic diagram of the fundamental wave approximation algorithm of the present invention.

[0036] Figure 5 This is a schematic diagram illustrating the zero-crossing prediction of the present invention.

[0037] Figure 6 This is a schematic diagram illustrating the principle of driving signal generation in this invention.

[0038] Figure 7 This is a schematic diagram of the primary current and voltage during the oscillation process in the simulation of this invention.

[0039] Figure 8 This is a schematic diagram of the primary side current and voltage during the operation of the low-frequency branch ZPA in the simulation of this invention.

[0040] Figure 9 This is a schematic diagram of the primary side current and voltage during the operation of the high-frequency branch ZPA in the simulation of this invention. Detailed Implementation

[0041] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0042] Example 1:

[0043] like Figure 1 The ZPA frequency tracking system with a tightly coupled wireless power transfer mechanism shown includes a transmitter and a receiver. The transmitter includes a DC power supply V connected in sequence. in The inverter, primary-side compensation circuit, and transmitting coil L1 are included. The receiving end includes receiving coil L2, secondary-side compensation circuit, rectifier filter, and load R connected in sequence. o ;

[0044] In this embodiment, the primary-side compensation circuit includes a primary-side compensation capacitor C1, the secondary-side compensation circuit includes a secondary-side compensation capacitor C2, the inverter is a full-bridge inverter including four power MOSFETs S1-S4, and the rectifier filter includes four diodes D1-D4 and a filter capacitor C. f .

[0045] In this embodiment, the transmitting coil L1 and the receiving coil L2 form a square coupling mechanism. This square coupling mechanism utilizes a magnetic core to concentrate and guide the magnetic field, improving the magnetic coupling efficiency between the transmitting and receiving coils, thereby increasing the efficiency of power transmission. Furthermore, a shielding aluminum plate is added to reduce magnetic field leakage. The coil, magnetic core, and shielding aluminum plate are stacked sequentially, and a grooved acrylic plate is provided on the outside of the stacked structure for winding the Litz energy coil.

[0046] like Figure 1As shown, the wireless power transmission system also includes a current sampling circuit, a DSP controller, and a drive circuit. The current sampling circuit is used for the primary-side current i1. The DSP controller is used to generate a ZPA frequency tracking control signal based on the collected primary-side current i1. The drive circuit is used to generate a drive signal to drive the inverter based on the ZPA frequency tracking control signal. The primary-side current i1 is the inverter output current of the primary-side full-bridge inverter.

[0047] In this embodiment, the parameters of the primary coil L1 and the secondary coil L2 are the same. When the high-frequency DC power supply V... in When ω is the operating frequency, the equivalent impedance Z1 of the transmitter and the equivalent impedance Z2 of the receiver can be expressed as:

[0048]

[0049] Where R1 and R2 represent the internal resistances of L1 and L2, respectively. Typically, the internal resistance of the coil is small and can be ignored for simplified analysis. The natural resonant frequency can then be obtained:

[0050]

[0051] The system's input resistance can be expressed as:

[0052]

[0053] In the formula, R eq This represents the equivalent load resistance of the full-bridge rectifier, with a value of 8R. o / π 2 , The conjugate of the equivalent impedance Z2 at the receiving end is represented by the coefficient λ, which takes the following values:

[0054]

[0055] Setting the imaginary part of the input impedance to 0, we can find the resonant frequency at the bifurcation point and substitute it into the coupling coefficient. Thus, we obtain the equation:

[0056]

[0057] Let the high and low bifurcation angular frequencies be ω H With ω L The solution is:

[0058]

[0059] It is easy to see that when the coupling coefficient k is greater than the critical value k critical Frequency bifurcation occurs, and the frequency difference between the two bifurcated branches increases with increasing k. Figure 2 Schematic diagram of frequency bifurcation ( ).

[0060] Example 2:

[0061] like Figure 3 The ZPA frequency tracking method for a tightly coupled wireless power transfer mechanism shown herein comprises the following steps:

[0062] S1: Construct a fundamental approximation model for the primary current i1. The model parameters of the fundamental approximation model constitute a vector θ. Set the initial vector. ;

[0063] In this embodiment, performing a Fourier expansion on the primary current i1 yields the form of the sum of harmonics of the primary current i1 as follows:

[0064]

[0065] In the formula, a n and b n Let represent the amplitude and initial phase of the nth current harmonic, respectively, ω represent the fundamental angular frequency, and t represent time. Since the wireless power transmission system is essentially a frequency-selective resonant converter, the primary current i1 can be approximated by its fundamental form as:

[0066]

[0067] Since the amplitude a1, initial phase b1, and frequency ω of the fundamental current all depend on the operating conditions and their specific values ​​are usually unknown, they are estimated by sampling current data. Let the vector formed by these parameters be θ = [a1, b1, ω]. T and set the initial vector .

[0068] S2: Read the primary current sample value at the current moment, construct the least squares objective function of vector θ, and use the primary current sample value as input to iteratively update the parameters using the recursive Gauss-Newton (GN) algorithm, and generate the driving signal based on the updated parameters.

[0069] In this embodiment, the least squares objective function for constructing vector θ is:

[0070]

[0071] In the formula, * represents the sampling data identifier. Represents the length of the data. θ represents the estimated value of the vector θ, and k represents the sampling time.

[0072] In this embodiment, the specific steps for iteratively updating parameters using the recursive Gauss-Newton (GN) algorithm and generating driving signals based on the updated parameters are as follows:

[0073] S2.1: Read the current sample value at the current moment, with k=1 at the initial moment;

[0074] S2.2: Using the primary current value at time k as input, the parameters in the vector θ are iteratively updated using the recursive Gauss-Newton GN algorithm, and the estimated current value at time k+1 is predicted.

[0075] In this embodiment, the recursive Gaussian-Newton (GN) algorithm is used to solve for the value of θ. The optimal solution is approximated through gradual updates, avoiding excessively large update steps and eliminating the need to store historical data, thus ensuring the algorithm's online real-time performance. The vector θ is then set to the 6th... The estimated value of each sampling length is defined as Its partial derivative vector is defined as The covariance matrix is ​​expressed as Then we have:

[0076]

[0077]

[0078] gradient and Hessian matrix The definition is as follows:

[0079]

[0080]

[0081] Will exist Performing a second-order Taylor expansion at the given point, we have:

[0082]

[0083] seek θ at the minimum value k Let the value be zero, and we can solve for:

[0084]

[0085] However, the obtained solution is in batch form, which will generate a large data burden during computation. Therefore, the covariance matrix set above is introduced:

[0086]

[0087] In the formula, .

[0088] Using the matrix lemma, we can obtain:

[0089]

[0090] Then the expression Introduced in China The matrix is ​​used to derive the recursive GN algorithm, which introduces a diagonal matrix Q to balance the convergence speed and accuracy of the algorithm. The algorithm details are as follows.

[0091]

[0092] In this embodiment, the estimated current value is:

[0093]

[0094] In the formula , Represents the sampling length The algorithm estimates the amplitude at time step. Sampling length The algorithm estimates the frequency at time step. Sampling length The time of moment, Sampling length The algorithm estimates the phase at each time step.

[0095] S2.3: Generate a driving signal by iteratively updating the parameters in the vector θ, and return to step S2.1 with k=k+1, and repeat steps S2.1-S2.3.

[0096] In this embodiment, after each sampling, a recursive GN calculation is performed to update the values ​​of the three parameters: amplitude a1, initial phase b1, and frequency ω. The current value at the next moment is then predicted. The estimated current and the actual current waveform are illustrated below. Figure 4 As shown, after a series of sampling and parameter updates, the estimated current waveform finally coincides with the actual current, and the algorithm achieves convergence.

[0097] When the estimated current waveform perfectly matches the actual current waveform, the zero-crossing time predicted by the algorithm is the true zero-crossing time of the actual waveform. At this time, the MOSFET switching actions are prepared in advance to achieve the zero-phase state of the actual current and voltage, that is, to realize the ZPA state operation of the system. The zero-crossing prediction is illustrated as follows. Figure 5 As shown, the dashed line represents the predicted waveform, and the solid line represents the actual waveform.

[0098] In this embodiment, the generation of the driving signal mainly depends on the frequency of the fundamental wave. With phase estimate The clock cycle value is denoted as T. clk Assuming the initial value of the time base counter CNT is 0, the value period register PRD, For load value, The algorithm estimates the load value, and the load values ​​of registers A and B are compared as shown in the following formulas, where floor represents the floor operation. Figure 6 The schematic diagram for generating drive signals S1 and S2 is shown. Similarly, drive signals S3 and S4 are generated according to the same logic.

[0099]

[0100]

[0101]

[0102] By configuring the initial frequency value of the algorithm, the circuit can be controlled to eventually converge to different ZPA steady-state solution branches, that is, when the initial frequency is set... The system operating frequency tends to converge to a higher frequency; conversely, when the initial frequency is set... Then it tends to converge to low frequencies.

[0103] Simulation verification:

[0104] Simulations were performed using MATLAB / Simulink, with the original resonant frequency of the WPT system set to 55 kHz, under a tightly coupled scenario and a coupling coefficient of 0.71. The oscillation of the self-excited system originates from a small fluctuation in the current after power-on, at which point the algorithm begins execution. The oscillation process is illustrated below. Figure 7 As shown.

[0105] When the algorithm converges, the system is in a stable phase, with the primary current and voltage in the same direction, thus achieving ZPA operation. Figure 8 The system converges to a low-frequency bifurcation point, approximately 38 kHz. Figure 9 The system converges to a high-frequency bifurcation point, approximately 93 kHz.

[0106] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A ZPA frequency tracking method for a tightly coupled wireless power transfer mechanism, characterized in that, The specific steps are: S1: construct a fundamental approximation model of the primary current i1, the model parameters of the fundamental approximation model constitute a vector θ, set an initial vector ; S2: read the primary side current sampling value at the current time, construct the least square objective function of vector θ, and use the recursive Gauss-Newton GN algorithm to iteratively update the parameters in vector θ with the primary side current sampling value as input, and generate the driving signal according to the updated parameters.

2. The ZPA frequency tracking method of a tightly coupled wireless power transfer mechanism according to claim 1, wherein, The step S1 constructs the fundamental approximation model of the primary side current i1 as:

3. In the formula, a1 is the amplitude of the fundamental current, b1 is the initial phase of the fundamental current, ω is the frequency of the fundamental current, and let the vector composed of them be θ = [a1, b1, ω] T , and set the initial vector .

4. The ZPA frequency tracking method of a tightly coupled wireless power transfer mechanism according to claim 1, wherein, The step S2 constructs the least square objective function of vector θ as: ； In the formula, * is the sampling data identification, represent the data length, represent the estimated value of the vector θ, and k represents the sampling time.

5. The method of claim 1, wherein, The specific steps of using the recursive Gauss-Newton GN algorithm to iteratively update the parameters and generating the driving signal according to the updated parameters in step S2 are: S2.1: read the current sampling value at the current time, and initialize k=1; S2.2: use the recursive Gauss-Newton GN algorithm to iteratively update the parameters in vector θ with the primary side current value at time k as input, and predict the estimated current value at time k+1; S2.3: generate the driving signal by iteratively updating the parameters in vector θ, and return to step S2.1 with k=k+1, and repeat steps S2.1-S2.

3.

6. The ZPA frequency tracking method of a tightly coupled wireless power transfer mechanism according to claim 4, wherein, The estimated current value in step S2.2 is: ； In the formula , Represents the sampling length The algorithm estimates the amplitude at time step. Sampling length The algorithm estimates the frequency at time step. Sampling length The time of moment, Sampling length The algorithm estimates the phase at each time step.

7. A ZPA frequency tracking system for a tightly coupled wireless power transfer mechanism, characterized in that, A ZPA frequency tracking method for implementing the tightly coupled wireless power transmission mechanism of any one of claims 1-5, comprising a transmitting end and a receiving end coupled for power transmission; It also includes a current sampling circuit for collecting the primary side current of the transmitting end, a DSP controller for solving the optimal parameters of the fundamental approximation model according to the primary side current, and a driving circuit for generating a driving signal according to the optimal parameters.

8. The ZPA frequency tracking system of a tightly coupled wireless power transfer mechanism of claim 6, wherein, The transmitting end comprises a direct current power supply V in , an inverter, a primary side compensation circuit and a transmitting coil L1; The receiving end comprises a receiving coil L2, a secondary side compensation circuit, a rectifier filter and a load R connected in sequence o .

9. The ZPA frequency tracking system of a tightly coupled wireless power transfer mechanism of claim 7, wherein, The primary side compensation circuit and the secondary side compensation circuit are S-S type topology.

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