Wireless charging receiving system supporting multiple protocols

Abstract

The invention discloses a wireless charging receiving system supporting multiple protocols, and relates to the technical field of wireless charging, the wireless charging receiving system comprises a signal acquisition module, a protocol detection module, an impedance adjustment module and a rectification control module, the signal acquisition module acquires an alternating magnetic field signal and generates a fundamental frequency I signal and a fundamental frequency Q signal through orthogonal transformation; the protocol detection module adopts a multi-scale decomposition method to analyze the fundamental frequency I signal and the fundamental frequency Q signal, and outputs a charging protocol type; the impedance adjusting module adjusts the variable impedance network according to the charging protocol type to generate an optimal matching parameter; and the rectification control module controls the switching time sequence of the full-bridge rectification circuit based on the optimal matching parameter, and outputs stable charging power. Through cooperation of the signal acquisition module, the protocol detection module, the impedance adjustment module and the rectification control module, a receiving system supporting various wireless charging standards is constructed, and compatibility and reliability of wireless charging are improved.

Description

Technical Field

[0001] The present invention relates to the field of wireless charging technology, and in particular to a wireless charging receiving system supporting multiple protocols. Background Art

[0002] Existing wireless charging systems face protocol compatibility challenges. There are currently multiple wireless charging standards on the market, such as Qi, AirFuel, PMA, etc. Each standard uses different communication protocols and matching mechanisms, resulting in the inability to achieve universal charging for electronic devices of different brands and models. This protocol fragmentation not only increases the complexity of device interoperability, but also significantly increases user usage costs, limiting the promotion and application of wireless charging technology.

[0003] The impedance matching technology of traditional wireless charging receiving systems has defects. Existing solutions generally use static or simple impedance adjustment methods, which cannot accurately adapt to the dynamic charging requirements of different charging protocols and devices. Due to the lack of intelligent impedance matching algorithms, it is difficult for the system to optimize charging parameters in real time, resulting in low charging efficiency, large energy conversion losses, and significant power fluctuations during charging, which seriously affects user experience and battery life. Summary of the invention

[0004] In view of the problems of poor protocol compatibility and low impedance matching efficiency of the existing wireless charging system, the present invention is proposed.

[0005] Therefore, the problem to be solved by the present invention is how to design an intelligent and efficient multi-protocol wireless charging receiving system to improve the compatibility and reliability of wireless charging.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: In the first aspect, an embodiment of the present invention provides a wireless charging receiving system supporting multiple protocols, which includes a signal acquisition module, a protocol detection module, an impedance adjustment module and a rectification control module, wherein: the signal acquisition module acquires an alternating magnetic field signal and generates a baseband I signal and a baseband Q signal through an orthogonal transformation; the protocol detection module uses a multi-scale decomposition method to analyze the baseband I signal and the baseband Q signal, and outputs a charging protocol type; the impedance adjustment module adjusts a variable impedance network according to the charging protocol type to generate optimal matching parameters, wherein the variable impedance network includes a switch capacitor array and a switch inductor array; the rectification control module controls the switching timing of the full-bridge rectifier circuit based on the optimal matching parameters, and outputs a stable charging power.

[0007] As a preferred solution of the wireless charging receiving system supporting multiple protocols described in the present invention, the signal acquisition module is provided with an oscillation unit, a first orthogonal unit, a second orthogonal unit, a first filtering unit, a second filtering unit, a first gain unit and a second gain unit, wherein the oscillation unit generates a first local oscillation signal and a second local oscillation signal with a phase difference of 90 degrees; the first orthogonal unit multiplies the alternating magnetic field signal with the first local oscillation signal, and the second orthogonal unit multiplies the alternating magnetic field signal with the second local oscillation signal; the first filtering unit performs band-pass filtering on the output of the first orthogonal unit, and the second filtering unit performs band-pass filtering on the output of the second orthogonal unit; the first gain unit amplifies the output of the first filtering unit to obtain a baseband I signal, and the second gain unit amplifies the output of the second filtering unit to obtain a baseband Q signal.

[0008] As a preferred solution of the wireless charging receiving system supporting multiple protocols described in the present invention, the processing flow of the protocol detection module is as follows: the baseband I signal and the baseband Q signal are decomposed by wavelet transform to obtain frequency domain eigenvalues; a spectrum distribution diagram is established according to the frequency domain eigenvalues ​​to extract a feature point sequence; the feature point sequence is input into a convolutional neural network to obtain a protocol matching probability; and the charging protocol type is determined by a threshold judgment according to the protocol matching probability.

[0009] As a preferred solution of the wireless charging receiving system supporting multiple protocols described in the present invention, the convolutional neural network includes: the input layer arranges the feature point sequence into a feature matrix; the convolution layer performs a two-dimensional convolution operation on the feature matrix to extract local features; the pooling layer performs maximum sampling on the local features; the fully connected layer outputs the probability distribution of each charging protocol; and the decision layer selects the charging protocol corresponding to the maximum probability as the charging protocol type.

[0010] As a preferred solution of the wireless charging receiving system supporting multiple protocols described in the present invention, the impedance adjustment module includes: determining the target impedance range according to the charging protocol type; configuring the initial switching state of the switch capacitor array and the switch inductor array; sampling the input voltage and input current, and calculating the current input impedance value; comparing the current input impedance value with the target impedance range, and calculating the required impedance adjustment amount; adjusting the switch states of the switch capacitor array and the switch inductor array in turn based on the preset step value and the adjustment amount; determining the switch state combination when the impedance is optimally matched through an iterative optimization algorithm, and calculating the corresponding equivalent capacitance value and equivalent inductance value; substituting the equivalent capacitance and equivalent inductance values ​​into the impedance matching model to obtain the optimal matching parameters.

[0011] As a preferred solution of the wireless charging receiving system supporting multiple protocols described in the present invention, the rectifier control module includes: connecting a storage capacitor in parallel at the output end of the full-bridge rectifier circuit to construct a voltage-doubling rectifier structure; detecting the output voltage of the voltage-doubling rectifier structure; determining the optimal conduction angle of the rectifier switch based on the optimal matching parameters, and generating a gate drive signal corresponding to the conduction angle; judging the deviation value between the output voltage and the reference voltage through a comparator; dynamically adjusting the duty cycle of the gate drive signal through a PI control algorithm according to the deviation value; using the adjusted gate drive signal to control the rectifier switch and output a stable charging power.

[0012] As a preferred solution of the wireless charging receiving system supporting multiple protocols described in the present invention, the optimal matching parameters include resonant frequency, quality factor, coupling coefficient and rectification angle.

[0013] The beneficial effects of the present invention are as follows: the present invention uses orthogonal transformation to convert high-frequency alternating magnetic field signals into baseband I / Q signal pairs containing complete amplitude and phase information, providing a reliable data basis for protocol identification; combines multi-scale wavelet decomposition and a convolutional neural network based on a VGG structure for protocol identification, and designs a probability evaluation module with a cache mechanism to conduct a comprehensive analysis of multiple consecutive judgment results, thereby improving the accuracy and anti-interference ability of protocol identification; uses a binary-weighted switched capacitor array and a switched inductor array to construct a variable impedance network, and achieves precise impedance adjustment through a binary search strategy based on a target impedance range; uses a voltage-doubling rectification structure with energy storage capacitors in parallel, combined with conduction angle control based on optimal matching parameters and dynamic duty cycle adjustment of a PI algorithm, to achieve stable charging power output. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0015] Figure 1 The system architecture diagram of a wireless charging receiving system that supports multiple protocols.

[0016] Figure 2 The signal acquisition module flow chart of the wireless charging receiving system that supports multiple protocols.

[0017] Figure 3 The impedance adjustment module flow chart of the wireless charging receiving system supporting multiple protocols.

[0018] Figure 4 The figure is a flow chart of the rectifier control module of a wireless charging receiving system that supports multiple protocols. DETAILED DESCRIPTION

[0019] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0020] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0021] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0022] Example 1, reference Figure 1~Figure 4 , which is the first embodiment of the present invention, and this embodiment provides a wireless charging receiving system supporting multiple protocols, and the system architecture diagram is as follows Figure 1 As shown, it includes a signal acquisition module, a protocol detection module, an impedance adjustment module and a rectification control module. The specific structure and working process of each module are described in detail below.

[0023] The signal acquisition module process is as follows Figure 2 As shown, the signal acquisition module collects the alternating magnetic field signal and generates the baseband I signal and the baseband Q signal through orthogonal transformation. The alternating magnetic field signal is induced by the receiving coil, which adopts a rectangular flattened structure design and is wound with enameled copper wire. The receiving coil converts the alternating magnetic field generated by the transmitter into an alternating voltage signal. The amplitude range of the signal is 0.5V~5V, and the frequency is the same as the operating frequency of the transmitter, which is 100~200kHz.

[0024] Specifically, the signal acquisition module is provided with an oscillation unit, a first orthogonal unit, a second orthogonal unit, a first filtering unit, a second filtering unit, a first gain unit and a second gain unit. The oscillation unit generates a first local oscillation signal and a second local oscillation signal with a phase difference of 90 degrees. Among them, the oscillation unit adopts a phase-locked loop circuit based on a quartz crystal, and outputs a reference clock with a frequency of 200kHz. The reference clock signal is passed through a frequency division circuit composed of a D flip-flop to obtain two orthogonal signals, and the phase difference error is controlled within ±3 degrees. The amplitude of the output signal is 3.3V, which has high frequency stability.

[0025] The first orthogonal unit multiplies the alternating magnetic field signal with the first local oscillator signal, and the second orthogonal unit multiplies the alternating magnetic field signal with the second local oscillator signal. Specifically, the first orthogonal unit multiplies the alternating magnetic field signal with the first local oscillator signal to generate a sum frequency component and a difference frequency component, the sum frequency component frequency is about 200~400kHz, and the difference frequency component frequency is in the range of 0~50kHz; the second orthogonal unit multiplies the alternating magnetic field signal with the second local oscillator signal to also generate a sum frequency component and a difference frequency component. Since the two local oscillator signals have a phase difference of 90 degrees, the difference frequency components output by the two orthogonal units also have a phase difference of 90 degrees, forming an orthogonal relationship.

[0026] The first filter unit performs bandpass filtering on the output of the first orthogonal unit, and the second filter unit performs bandpass filtering on the output of the second orthogonal unit. Specifically, the first filter unit and the second filter unit use a second-order Butterworth active bandpass filter to suppress high-frequency sum frequency components and retain difference frequency components. The two signals after filtering still maintain a 90-degree phase difference, and the amplitude is smoother after being shaped by the filter.

[0027] The first gain unit amplifies the output of the first filter unit to obtain a baseband I signal, and the second gain unit amplifies the output of the second filter unit to obtain a baseband Q signal. Specifically, the first gain unit amplifies the difference frequency I component output by the first filter unit, and the gain adjustable range is 5 to 20 times. After amplification and level adjustment, a baseband I signal with a peak value of 3V is obtained; the second gain unit amplifies the difference frequency Q component output by the second filter unit with the same gain to obtain a baseband Q signal orthogonal to the I signal. These two baseband signals carry the amplitude and phase information of the original alternating magnetic field signal, which can be used for subsequent protocol feature extraction.

[0028] Through the processing of the above signal acquisition module, the high-frequency alternating magnetic field signal is converted into a baseband I / Q signal pair containing complete amplitude and phase information through orthogonal transformation, where the I signal reflects the in-phase component of the original signal, and the Q signal reflects the orthogonal component of the original signal, and the two together constitute a complex representation describing the original signal. This orthogonal transformation processing method not only reduces the bandwidth requirements for subsequent processing, but also retains all the characteristic information of the signal, providing a reliable data basis for protocol identification.

[0029] The protocol detection module uses a multi-scale decomposition method to analyze the baseband I signal and the baseband Q signal, and outputs the charging protocol type. The baseband I signal and Q signal are sampled by a 16-bit ADC, and the sampling rate is set to 500kHz to ensure that the Nyquist sampling theorem requirements are met. The sampling time window is 10ms, and 5000 sampling points are obtained in each time window.

[0030] Specifically, the processing flow of the protocol detection module includes: first, the baseband I signal and the baseband Q signal are decomposed by wavelet transform to obtain the frequency domain eigenvalues. Specifically, the db4 wavelet basis function is used to perform three-layer wavelet decomposition, and three detail coefficient sequences and one approximate coefficient sequence are obtained after decomposition. For each layer of decomposition results, statistics such as energy characteristics, standard deviation, and mean are calculated to form preliminary eigenvalues. At the same time, the maximum value, minimum value, and position of occurrence of the wavelet coefficients are extracted as supplementary eigenvalues. These eigenvalues ​​(preliminary eigenvalues ​​and supplementary eigenvalues) together constitute a 64-dimensional frequency domain eigenvector.

[0031] Secondly, a spectrum distribution diagram is established based on the frequency domain eigenvalues ​​to extract the feature point sequence. The 64-dimensional frequency domain feature vector is rearranged in the form of 8×8 to construct a two-dimensional spectrum distribution matrix. In this matrix, key feature points are extracted by calculating features such as local extreme points, energy concentration areas, and spectrum transition bands. The specific extraction process includes: detecting the location points where the energy density exceeds the preset threshold, recording their coordinates and amplitude; calculating the center of mass position of the spectrum; marking the boundary points of the spectrum bandwidth. Finally, a 32×32 feature point sequence matrix is ​​obtained.

[0032] Next, the feature point sequence is input into the convolutional neural network to obtain the protocol matching probability. The convolutional neural network adopts the typical VGG structure, but is optimized for the wireless charging protocol features: first, the 32×32 feature point sequence matrix is ​​used as the network input; then, features are extracted through 3 convolution blocks, each of which contains 2 3×3 convolution layers and 1 2×2 maximum pooling layer; finally, classification is completed through 2 fully connected layers. Among them, the first convolution block uses 16 convolution kernels, the second uses 32, and the third uses 64. The convolution layer uses the ReLU activation function, and the pooling layer uses the maximum pooling strategy.

[0033] Finally, according to the protocol matching probability, the charging protocol type is determined through threshold judgment. The protocol matching probability threshold is set to 0.75. When the matching probability of a certain protocol type exceeds the threshold, a comprehensive judgment is made based on the consistency of three consecutive judgment results to improve the recognition reliability. If the matching probability of all protocol types is lower than the threshold, the secondary judgment mechanism is started: the ratio of the highest probability value to the second highest probability value is calculated. When the ratio exceeds 1.5, the protocol type corresponding to the highest probability is selected; otherwise, the signal is marked as an unknown protocol type, triggering the resampling analysis process.

[0034] Among them, the convolutional neural network is specifically implemented as follows: the input layer arranges the feature point sequence into a feature matrix; the convolution layer performs a two-dimensional convolution operation on the feature matrix to extract local features; the pooling layer performs maximum sampling on the local features to reduce the data dimension; the fully connected layer outputs the probability distribution of each charging protocol; the decision layer selects the charging protocol corresponding to the maximum probability as the charging protocol type. Among them, the decision layer implements a probability evaluation module with a caching mechanism to conduct a comprehensive analysis of the results of five consecutive decisions. When the same protocol type appears in the cache more than three times and the average probability value exceeds 0.85, it is finally confirmed as the protocol type. This mechanism effectively improves the reliability of the decision and reduces the misjudgment caused by instantaneous interference.

[0035] Through the processing of the above-mentioned protocol detection module, the baseband I / Q signal is analyzed in time and frequency based on multi-scale wavelet decomposition, and rich feature information is extracted. This module uses the db4 wavelet basis function for three-layer decomposition to obtain multi-dimensional feature vectors such as energy features and statistical features, and effectively characterizes the frequency domain characteristics of the signal through a two-dimensional spectrum distribution matrix. The convolutional neural network based on the VGG structure is innovatively introduced, and the deep extraction and classification of protocol features are realized through three-layer convolution blocks and two-layer fully connected layers. At the same time, a probability evaluation module with a cache mechanism is designed to conduct a comprehensive analysis of multiple consecutive judgment results and establish a reliable protocol identification mechanism. This processing solution combining multi-scale analysis and deep learning not only improves the accuracy of protocol identification, but also enhances the robustness of the system to interference, laying the foundation for the compatibility of multi-protocol wireless charging.

[0036] The impedance adjustment module flow chart is as follows: Figure 3 As shown, the impedance adjustment module adjusts the variable impedance network according to the charging protocol type to generate optimal matching parameters, wherein the variable impedance network includes a switched capacitor array and a switched inductor array.

[0037] Specifically, the working process of the impedance adjustment module includes: first, according to the charging protocol type, determine the target impedance range. Specifically, by looking up the pre-stored protocol parameter table, obtain the standard impedance range corresponding to the protocol, and for unknown protocols, obtain the corresponding impedance range through feature database matching. Secondly, configure the initial switching state of the switch capacitor array and the switch inductor array. The switch capacitor array is composed of multiple binary-weighted capacitor units, and the switch inductor array is composed of multiple binary-weighted inductor units. In the initial state, all switches are set to the off state.

[0038] Then, the input voltage and input current are sampled to calculate the current input impedance value. A high-precision ADC is used to synchronously sample the input voltage and current. After the sampled data is averaged and filtered, the amplitude and phase of the current impedance are obtained through complex operations. Next, the current input impedance value is compared with the target impedance range to calculate the required impedance adjustment amount. The adjustment direction is determined based on the relationship between the impedance amplitude and the target range, and the type of network to be adjusted is determined based on the impedance phase angle. When the phase angle is positive, the capacitor array is adjusted first, and when it is negative, the inductor array is adjusted first.

[0039] Subsequently, based on the preset step value and adjustment amount, the switch states of the switch capacitor array and the switch inductor array are adjusted in turn. A binary search strategy is adopted, and each attempt is made starting from the highest switch. After each adjustment, the impedance is measured after the system is stabilized. The final state of the current switch is determined by comparing the impedance change trend before and after the adjustment. Then, the switch state combination for optimal impedance matching is determined through an iterative optimization algorithm, and the corresponding equivalent capacitance value and equivalent inductance value are calculated. The error between the impedance amplitude and the target value is used as the optimization target, the switch state combination that meets the accuracy requirements is recorded, and the equivalent parameters of the network are calculated based on the switch state.

[0040] Finally, the equivalent capacitance and equivalent inductance values ​​are substituted into the impedance matching model to obtain the optimal matching parameters, where the optimal matching parameters include resonant frequency, quality factor, coupling coefficient and rectification angle.

[0041] In actual applications, to ensure the stability of the charging process, the response time of the impedance adjustment process is controlled within 50ms. The system achieves fast impedance adjustment through parallel processing algorithm optimization and key path acceleration to meet the needs of dynamic charging scenarios.

[0042] In addition, the construction process of the impedance matching model is as follows: Based on the principle of resonant circuit, the receiving end forms a series resonant network through a switched capacitor array, a switched inductor array and a load resistor, where the load resistor represents the effective load characteristics of the wireless charging receiving end. The resonant network is modeled using the complex domain analysis method, and the equivalent capacitor, equivalent inductor and load resistor form an impedance link. The passband characteristics of the received signal are determined by the impedance characteristics of the resonant network. According to Kirchhoff's law of the circuit, the voltage relationship of the resonant network is written, the complex transfer function of the network is derived, the frequency response characteristics of the network are analyzed, and the mapping relationship between frequency and network impedance is established. Based on the principle of minimum reflection coefficient, the matching problem of load impedance and source impedance is transformed into an optimization problem, and an impedance matching model with reflection coefficient as the optimization target is established. The quality factor correction term is introduced to consider the loss effect of the resonant network and improve the impedance matching model. This model can be used to calculate the matching parameters under given equivalent capacitance and equivalent inductance values.

[0043] By using binary weighted switched capacitor arrays and switched inductor arrays to construct a variable impedance network, combined with a binary search strategy based on the target impedance range and an iterative optimization algorithm, the impedance can be precisely and controllably adjusted. The module obtains the current impedance value by synchronously sampling the input voltage and current through a high-precision ADC, and intelligently selects the type of adjustment network based on the impedance phase angle. At the same time, a quality factor-corrected impedance matching model is introduced to deal with the influence of resonant network loss, and finally the optimal matching parameters are output, providing an efficient and accurate impedance matching solution for multi-protocol wireless charging systems.

[0044] The rectifier control module flow chart is as follows: Figure 4 As shown, the rectifier control module controls the switching timing of the full-bridge rectifier circuit based on the optimal matching parameters to output stable charging power.

[0045] Specifically, the working process of the rectifier control module includes: first, a storage capacitor is connected in parallel to the output end of the full-bridge rectifier circuit to construct a voltage doubler rectifier structure. The energy storage capacitor uses a capacitor with low equivalent series resistance. The voltage doubler rectifier structure includes four power switch tubes of the full-bridge rectifier circuit and a parallel storage capacitor, which is used to rectify and boost the input AC voltage to a DC voltage. Secondly, the output voltage of the voltage doubler rectifier structure is detected. The voltage divider detection circuit is used to collect the output voltage signal in real time. The voltage divider signal is input into the analog-to-digital conversion unit of the controller after signal conditioning to obtain the actual output voltage value.

[0046] Then, based on the optimal matching parameters, the optimal conduction angle of the rectifier switch is determined, and a gate drive signal corresponding to the conduction angle is generated. The switching period is calculated according to the resonant frequency, and the optimal conduction time is determined by combining the quality factor and the coupling coefficient. Four complementary gate drive signals are generated through the phase shift link. Next, the deviation value between the output voltage and the reference voltage is determined by the comparator. The reference voltage is selected according to the charging protocol type, and the comparator outputs a deviation signal to characterize the charging state. When the deviation exceeds the preset range, the control parameter adjustment is triggered.

[0047] Subsequently, the duty cycle of the gate drive signal is dynamically adjusted according to the deviation value through the PI control algorithm. The PI controller calculates the control amount according to the deviation value, the proportional coefficient determines the adjustment speed, the integral coefficient is used to eliminate the steady-state error, and the control amount is mapped to the duty cycle adjustment signal. At the same time, based on the charging protocol type and load change characteristics, the system adopts an adaptive parameter adjustment strategy to dynamically optimize the proportional coefficient and integral coefficient of the PI controller to improve the system's adaptability to different charging scenarios.

[0048] Finally, the regulated gate drive signal is used to control the rectifier switch and output stable charging power. The gate drive signal modulated by duty cycle controls the conduction timing of the power switch tube to adjust the output power and stabilize the output voltage within the target value range.

[0049] By adopting a voltage-doubling rectifier structure with energy storage capacitors in parallel, combined with conduction angle control based on optimal matching parameters and dynamic duty cycle adjustment of the PI algorithm, the output power is precisely controlled. The module determines the optimal conduction time based on the resonant frequency, quality factor and coupling coefficient, generates a complementary drive signal through the phase shift link, and adjusts the duty cycle in real time based on the output voltage deviation, ultimately achieving stable charging power output, providing an efficient and accurate rectification control solution for multi-protocol wireless charging systems.

[0050] In summary, the present invention uses orthogonal transformation to convert high-frequency alternating magnetic field signals into baseband I / Q signal pairs containing complete amplitude and phase information, providing a reliable data basis for protocol identification; combines multi-scale wavelet decomposition and a convolutional neural network based on a VGG structure for protocol identification, and designs a probability evaluation module with a cache mechanism to conduct a comprehensive analysis of multiple consecutive judgment results, thereby improving the accuracy and anti-interference ability of protocol identification; uses a binary-weighted switched capacitor array and a switched inductor array to construct a variable impedance network, and achieves precise impedance adjustment through a binary search strategy based on a target impedance range; uses a voltage-doubling rectifier structure with energy storage capacitors in parallel, combined with conduction angle control based on optimal matching parameters and dynamic duty cycle adjustment of the PI algorithm, to achieve stable charging power output.

[0051] Example 2, reference Figure 1~Figure 4 , which is the second embodiment of the present invention, and this embodiment provides a wireless charging receiving system that supports multiple protocols. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0052] In order to verify the feasibility and performance of the technical solution of the present invention, a complete simulation experimental platform is built, which consists of a transmitting test system and a receiving test system.

[0053] In the signal acquisition module test, the receiving coil adopts a 45μH flat structure design, with an inner diameter of 45mm, an outer diameter of 68mm, and 22 turns of coil. After testing, within the coupling distance of 540mm, the induced voltage amplitude of the receiving coil is 0.8V~4.2V. The baseband I / Q signal pair output by the signal acquisition module is observed by an oscilloscope, and the signal amplitude is stable at 2.8V~3.1V, and the phase difference of the two signals is controlled in the range of 87°~92°, which meets the requirements of subsequent processing.

[0054] The performance test of the protocol detection module uses test signals of three mainstream protocols, Qi, PMA and A4WP, and each protocol contains 1,000 test samples. The test results show that under normal working conditions (coupling coefficient greater than 0.3), the system's recognition accuracy for the three protocols reaches 98.2%, 97.5% and 96.8%, respectively. When there is a ±20% amplitude fluctuation or a ±10° phase deviation, the recognition accuracy can still be maintained above 93%. The system response time is 42ms on average and no more than 65ms at most. In order to illustrate the advantages of the present invention in terms of performance indicators, a comparative analysis is conducted with the prior art solutions, and the comparison results are shown in Table 1.

[0055] Table 1 Performance comparison between the method of the present invention and the traditional pattern matching algorithm From the comparison data in Table 1, it can be seen that the protocol recognition scheme of the present invention, which adopts a multi-scale decomposition method combined with a convolutional neural network, has obvious advantages over the traditional pattern matching algorithm in key indicators such as protocol recognition accuracy, system response time, and impedance adjustment accuracy. In particular, while maintaining a high power efficiency, a faster response speed and more accurate impedance matching are achieved.

[0056] The impedance adjustment module uses an 8-bit binary weighted switched capacitor array and switched inductor array. The capacitance adjustment range is 1pF~256pF, with a step value of 1pF; the inductance adjustment range is 0.1μH~25.6μH, with a step value of 0.1μH. In actual tests, the system can complete the impedance matching process within 45ms, and the matching accuracy is better than ±2.5%. When the load impedance changes by ±30%, the system can re-reach the optimal matching state within one control cycle.

[0057] The rectifier control module uses IR power MOSFET to build a full-bridge rectifier circuit with an on-resistance of 20mΩ and a switching frequency synchronized with the transmitter. The energy storage capacitor uses a 150μF / 35V low-ESR electrolytic capacitor. At a nominal output power of 5W, the system output voltage is stable within the range of 5V±0.1V, and the ripple factor is less than 1%. The duty cycle is dynamically adjusted through the PI control algorithm. The system's adjustment time for a sudden increase / decrease of 50% load does not exceed 2ms, and the overshoot is controlled within 5%.

[0058] The overall performance test of the system was conducted in the power range of 0.5W~15W, with an ambient temperature of 25℃ and a relative humidity of 65%. The results showed that under rated working conditions, the overall power conversion efficiency of the system reached 86.5%, including 89.3% rectification efficiency and 96.8% modulation efficiency. The system has good compatibility with the three mainstream protocols, can automatically identify the protocol type and complete parameter optimization, and the entire process from detection to stable charging takes an average of 125ms.

[0059] The long-term stability test lasted for 1000 hours, during which the system worked at a rated power of 10W and the performance parameters were recorded every hour. The test results showed that the fluctuation range of various performance indicators of the system was controlled within ±3%, and there was no significant performance degradation or failure, which verified the reliability and stability of the system design.

[0060] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A wireless charging receiving system supporting multiple protocols, characterized in that: It includes a signal acquisition module, a protocol detection module, an impedance adjustment module and a rectification control module, wherein: The signal acquisition module acquires the alternating magnetic field signal and generates a baseband I signal and a baseband Q signal through orthogonal transformation; The protocol detection module analyzes the baseband I signal and the baseband Q signal, and outputs a charging protocol type; The impedance adjustment module adjusts the variable impedance network according to the charging protocol type to generate optimal matching parameters, wherein the variable impedance network includes a switched capacitor array and a switched inductor array; The rectifier control module controls the switching timing of the full-bridge rectifier circuit based on the optimal matching parameters to output stable charging power.

2. The wireless charging receiving system supporting multiple protocols as claimed in claim 1, characterized in that: The signal acquisition module is provided with an oscillation unit, a first orthogonal unit, a second orthogonal unit, a first filtering unit, a second filtering unit, a first gain unit and a second gain unit, wherein: The oscillation unit generates a first local oscillation signal and a second local oscillation signal with a phase difference of 90 degrees; The first orthogonal unit multiplies the alternating magnetic field signal with the first local oscillator signal, and the second orthogonal unit multiplies the alternating magnetic field signal with the second local oscillator signal; The first filtering unit performs bandpass filtering on the output of the first orthogonal unit, and the second filtering unit performs bandpass filtering on the output of the second orthogonal unit; The first gain unit amplifies the output of the first filtering unit to obtain the baseband I signal, and the second gain unit amplifies the output of the second filtering unit to obtain the baseband Q signal.

3. The wireless charging receiving system supporting multiple protocols as claimed in claim 1, characterized in that: The processing flow of the protocol detection module is as follows: Decomposing the baseband I signal and the baseband Q signal by wavelet transform to obtain frequency domain eigenvalues; Establish a frequency spectrum distribution diagram according to the frequency domain characteristic values ​​and extract a characteristic point sequence; Inputting the feature point sequence into a convolutional neural network to obtain a protocol matching probability; According to the protocol matching probability, the charging protocol type is determined through threshold judgment.

4. The wireless charging receiving system supporting multiple protocols as claimed in claim 3, characterized in that: The convolutional neural network comprises: The input layer arranges the feature point sequence into a feature matrix; The convolution layer performs a two-dimensional convolution operation on the feature matrix to extract local features; The pooling layer performs maximum sampling on the local features; The fully connected layer outputs the probability distribution of each charging protocol; The decision layer selects the charging protocol corresponding to the maximum probability as the charging protocol type.

5. The wireless charging receiving system supporting multiple protocols as claimed in claim 1, characterized in that: The impedance adjustment module comprises: Determining a target impedance range according to the charging protocol type; configuring the initial switching states of the switched capacitor array and the switched inductor array; Sample the input voltage and input current, and calculate the current input impedance value; Compare the current input impedance value with the target impedance range to calculate the required impedance adjustment amount; Based on the preset step value and the adjustment amount, sequentially adjusting the switch states of the switch capacitor array and the switch inductor array; The switch state combination for optimal impedance matching is determined through an iterative optimization algorithm, and the corresponding equivalent capacitance and equivalent inductance values ​​are calculated; Substituting the equivalent capacitance and equivalent inductance values ​​into the impedance matching model, the optimal matching parameters are obtained.

6. The wireless charging receiving system supporting multiple protocols as claimed in claim 1, characterized in that: The rectifier control module comprises: Connecting an energy storage capacitor in parallel to the output end of the full-bridge rectifier circuit to construct a voltage doubling rectifier structure; Detecting the output voltage of the voltage doubler rectifier structure; Based on the optimal matching parameters, determining the optimal conduction angle of the rectifier switch, and generating a gate drive signal corresponding to the conduction angle; Determining a deviation value between the output voltage and a reference voltage by a comparator; According to the deviation value, dynamically adjusting the duty cycle of the gate drive signal through a PI control algorithm; The regulated gate drive signal is used to control the rectifier switch and output stable charging power.

7. The wireless charging receiving system supporting multiple protocols as claimed in claim 5, characterized in that: The optimal matching parameters include resonance frequency, quality factor, coupling coefficient and rectification angle.

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