Real-time decoding method and system for wireless charging communication data packets for smart tires
By performing high-frequency sampling and nonlinear filtering at the wireless charging transmitter inside the smart tire, a dynamic decision threshold is generated, solving the problem of real-time decoding of communication packets in complex media environments and achieving stable communication monitoring and fault location.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- ANHUI AGRICULTURAL UNIVERSITY
- Filing Date
- 2026-05-11
- Publication Date
- 2026-06-05
AI Technical Summary
Existing technologies struggle to achieve real-time monitoring and reliable decoding of wireless charging communication packets within smart tires, especially in complex environments. Issues such as deep modulation attenuation of communication signals, enhanced baseline drift, and increased noise and transient disturbances significantly increase the difficulty of capturing and decoding communication packets.
By performing high-frequency sampling of the differential voltage across the transmitting coil of the wireless charging transmitter, extracting the peak point and performing nonlinear filtering, a dynamic decision threshold is generated. This threshold is then combined with the duration of the level reversal point to make bit decisions, thereby enabling real-time decoding of communication data packets.
Real-time monitoring and reliable decoding of wireless charging communication packets were achieved in complex media environments, reducing data volume and real-time processing pressure, adapting to coupling and load changes, providing stable level decision and error suppression, and supporting stability assessment and fault location of in-tire wireless charging systems.
Smart Images
Figure CN122160211A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of wireless power supply and charging monitoring technology for smart tire in-tire units, and in particular to a method and system for real-time decoding of wireless charging communication data packets for smart tires. Background Technology
[0002] Intelligent tire in-tire units need to operate stably for extended periods throughout the tire's lifespan. Given the difficulty of replacing batteries in in-tire units and the limitations of space and sealing for energy replenishment, using wireless charging to continuously recharge in-tire units has significant engineering value.
[0003] The working conditions inside the tire are significantly different from those in a conventional open environment: the tire medium between the coils is more complex and thicker, which leads to a significant reduction in the coupling between the coils at the transmitting and receiving ends; in order to maintain the output power of the receiving end, the transmitting end often needs to raise the voltage at the transmitting coil end and dynamically adjust the output, which makes the Amplitude Shift Keying (ASK) of the load modulation communication signal from the receiving end to the transmitting end more prone to problems such as modulation depth attenuation, increased baseline drift, and increased noise and transient disturbances, resulting in a significant increase in the difficulty of capturing and decoding communication packets.
[0004] In existing technologies, communication analysis of Qi-class wireless charging systems typically relies on offline sampling of the transmitting coil voltage / current using an oscilloscope or general data acquisition equipment, followed by manual or script-based post-processing. Qi-class is a protocol introduced by the Wireless Power Consortium (WPC). This approach has the following shortcomings under in-tire conditions: 1) Difficult to monitor online for extended periods: Offline sampling and manual analysis are inefficient and make it difficult to support stability assessments for continuous operation; 2) Large data volume and poor real-time performance: If the complete carrier waveform is directly acquired, a high sampling rate is required to preserve modulation details, resulting in high data throughput and storage pressure, which is not conducive to real-time processing; 3) Insufficient resistance to changes in operating conditions: Voltage baseline drift and amplitude changes caused by changes in in-tire coupling can easily lead to the failure of fixed threshold decision. 4) The problem of range adaptation is prominent: Under the working conditions inside the tire, the peak voltage of the transmitting coil may increase significantly, exceeding the input range of the data acquisition module, resulting in clipping distortion, which makes the communication modulation characteristics unrecognizable and decoding failure.
[0005] Therefore, there is an urgent need for a system and method that is designed for the tire medium environment and can realize real-time monitoring and reliable decoding of wireless charging communication packets at the transmitting end, in order to support the evaluation of the working stability of the in-tire wireless charging system, parameter optimization and fault location. Summary of the Invention
[0006] The purpose of this application is to provide a method and system for real-time decoding of wireless charging communication data packets for smart tires, which can realize real-time monitoring and reliable decoding of communication packets at the transmitting end.
[0007] To achieve the above objectives, this application provides the following solution.
[0008] In a first aspect, this application provides a real-time decoding method for wireless charging communication data packets for smart tires, applied to wireless charging scenarios where the medium between the transceiver coils is complex and the coupling between the transceiver ends changes with attitude. The wireless charging scenario includes a wireless power supply scenario for the in-tire unit of a smart tire, and includes the following steps.
[0009] The differential voltage across the transmitting coil of the wireless charging transmitter is sampled at high frequency to obtain the original sampling sequence.
[0010] Based on the original sampling sequence, peak points are extracted according to the carrier period to obtain peak sequences and time information that correspond one-to-one with the carrier period.
[0011] The peak sequence is subjected to nonlinear filtering to obtain a filtered peak sequence.
[0012] The filtered peak sequence is segmented into time windows. For each time window, the maximum and minimum values are calculated, and the dynamic decision threshold for the corresponding time window is generated from the maximum and minimum values.
[0013] The filtered peak sequence is compared with the dynamic decision threshold of the corresponding time window to generate a high-level sequence and a low-level sequence, and the level inversion point of the high-level sequence and the low-level sequence is detected.
[0014] Bit decision is made based on the duration between adjacent level transition points: when the detected duration falls within the first preset duration range, it is determined to be logic bit 0; when two consecutive durations fall within the second preset duration range, it is determined to be logic bit 1.
[0015] When the detected duration does not meet any bit decision condition of the first preset duration range and the second preset duration range, an abnormal reset is performed, discarding the currently unparsed bits, bytes or data packets, and re-searching for the synchronization sequence to restore synchronization.
[0016] In the bit stream obtained from the bit decision, preamble synchronization and parsing of the header and information fields according to the asynchronous serial byte structure are performed, and verification is performed to obtain the real-time decoding result of the wireless charging communication data packet.
[0017] Secondly, this application provides a real-time decoding system for wireless charging communication data packets for smart tires, including the following modules.
[0018] The differential attenuation circuit is connected to the data acquisition module and the two ends of the wireless charging transmitter coil to symmetrically attenuate the differential voltage across the transmitter coil.
[0019] The data acquisition module is used to perform high-frequency sampling of the differential voltage across the transmitting coil after differential attenuation and output the original sampling sequence.
[0020] The peak extraction module is used to extract peak points based on the original sampling sequence according to the carrier period, so as to obtain the peak sequence and time information corresponding one-to-one with the carrier period.
[0021] The real-time decoding processing module is used to perform nonlinear filtering on the peak sequence, generate dynamic decision thresholds, complete level decision and level duration fault tolerance decision, and perform abnormal reset and resynchronization, complete the parsing and verification of communication data packets, and obtain the real-time decoding result of wireless charging communication data packets; the real-time decoding processing module is configured to execute the above-mentioned real-time decoding method for wireless charging communication data packets for smart tires.
[0022] The results output module is used to display, store, and upload the real-time decoding results of wireless charging communication data packets.
[0023] According to the specific embodiments provided in this application, this application has the following technical effects.
[0024] This application significantly reduces the data volume by extracting peak values based on carrier cycle peaks, compared to directly processing the complete carrier waveform, thus alleviating real-time processing and storage pressure and making it suitable for continuous online monitoring. The combination of "nonlinear filtering + dynamic decision threshold" maintains stable level decision even under voltage baseline drift caused by coupling and load changes. Bit decision is performed based on the duration between adjacent level reversal points, and an abnormal reset is set to suppress error propagation and reduce packet loss risk. Without modifying the transceiver circuitry or the Qi communication protocol, real-time monitoring and recording of wireless charging communication data packets during the Ping, identification and configuration, and power transmission phases can be achieved at the transmitting end, providing a reliable means for stability assessment, parameter optimization, and fault location of in-tire wireless charging systems. Attached Figure Description
[0025] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0026] Figure 1This is a schematic flowchart illustrating a real-time decoding method for wireless charging communication data packets in smart tires, provided as an embodiment of this application.
[0027] Figure 2 This is a block diagram of the overall structure of a real-time decoding system for wireless charging communication data packets for smart tires, provided as an embodiment of this application.
[0028] Figure 3 This is a schematic diagram of the differential voltage sampling and peak extraction process of the transmitting coil provided in an embodiment of this application.
[0029] Figure 4 This is a schematic diagram of peak sequence nonlinear filtering and dynamic decision threshold generation provided in an embodiment of this application; wherein, Figure 4 (a) in the diagram is a schematic diagram of the nonlinear filtering process. Figure 4 (b) in the diagram is a schematic diagram of the dynamic decision threshold.
[0030] Figure 5 This is a schematic diagram illustrating level reversal point extraction and duration fault-tolerant decision-making according to an embodiment of this application; wherein, Figure 5 (a) in the diagram is a schematic diagram of the communication packet frame parsing process, including preamble synchronization, byte parsing, and verification. Figure 5 (b) in the diagram is a schematic diagram of the high-level sequence and low-level sequence after binarization.
[0031] Figure 6 This is a schematic diagram of a communication packet frame parsing process provided in an embodiment of this application.
[0032] Figure 7 This is a schematic diagram of a symmetrical differential π-type attenuation network circuit structure provided in an embodiment of this application. Detailed Implementation
[0033] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0034] To make the objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.
[0035] Example 1 like Figure 1As shown, this application provides a real-time decoding method for wireless charging communication data packets for smart tires, applied to wireless charging scenarios where the medium between the transceiver coils is complex and the coupling between the transceiver ends changes with attitude. The wireless charging scenario includes a wireless power supply scenario for the in-tire unit of a smart tire, and includes the following steps.
[0036] S1: High-frequency sampling is performed on the differential voltage across the transmitting coil of the wireless charging transmitter to obtain the original sampling sequence.
[0037] S2: Based on the original sampling sequence, extract the peak points according to the carrier period to obtain the peak sequence and time information corresponding to the carrier period.
[0038] S3: Perform nonlinear filtering on the peak sequence to obtain a filtered peak sequence, so as to suppress impulse noise and preserve level transition edges.
[0039] S4: Divide the filtered peak sequence into time windows, calculate the maximum and minimum values for each time window, and generate a dynamic decision threshold for the corresponding time window based on the maximum and minimum values to adaptively track voltage baseline drift caused by load and coupling changes.
[0040] S5: Compare the filtered peak sequence with the dynamic decision threshold of the corresponding time window to generate a high-level sequence and a low-level sequence, and detect the level reversal point of the high-level sequence and the low-level sequence.
[0041] S6: Bit decision is made based on the duration between adjacent level transition points: when the detected duration falls within the first preset duration range, it is determined as logic bit 0; when two consecutive durations fall within the second preset duration range, it is determined as logic bit 1. The first preset duration range is 400μs~600μs; the second preset duration range is 200μs~300μs.
[0042] S7: When the detected duration does not meet any bit judgment condition of the first preset duration range and the second preset duration range, perform an abnormal reset, discard the currently unparsed bits, bytes or data packets, and re-search the synchronization sequence to restore synchronization.
[0043] S8: Perform preamble synchronization and parsing of the header and information fields according to the asynchronous serial byte structure in the bit stream obtained in the bit decision, and perform verification to obtain the real-time decoding result of the wireless charging communication data packet.
[0044] This application addresses the application requirements of smart tire in-tire units that need long-term continuous power replenishment. It provides an online transmitter-side communication monitoring method to address communication difficulties caused by the harsh environment inside the tire, such as weak coupling between the transceiver coils, increased operating voltage at the transmitter, exacerbated baseline drift, deep attenuation of ASK load modulation, and enhanced noise and transient disturbances. This method is used to analyze and record the communication data packets between the receiver and transmitter during the in-tire wireless charging process in real time, thereby providing a reliable basis for evaluating the operational stability, optimizing parameters, and locating faults in the in-tire wireless charging system.
[0045] In one exemplary embodiment, the wireless charging communication data packet is used for online monitoring and parameter recording of the continuous energy replenishment process of the smart tire in-tire unit.
[0046] The wireless charging communication data packet follows the Qi protocol, and the carrier frequency of the differential voltage across the transmitting coil is in the range of 110 kHz to 205 kHz.
[0047] The sampling frequency of the high-frequency sampling is not less than 5 times the carrier frequency, and preferably 1 MS / s.
[0048] In an exemplary embodiment, peak points are extracted based on the original sampling sequence according to the carrier period to obtain peak sequences and time information corresponding one-to-one with the carrier period, specifically including: The maximum value within each carrier cycle is selected as a peak point, and the original sampling sequence is reduced in dimensionality to a peak sequence corresponding to the carrier cycle, resulting in a peak sequence and time information that correspond one-to-one with the carrier cycle. This peak sequence is used for subsequent communication modulation feature extraction and decoding.
[0049] In an exemplary embodiment, the nonlinear filtering is median filtering, and the window length of the median filtering is an odd number of points, preferably 3 points or more.
[0050] In an exemplary embodiment, the dynamic decision threshold for the corresponding time window is generated from the maximum and minimum window values, specifically including: The average of the maximum and minimum values of each time window is used as the dynamic decision threshold of the time window; the length of the time window is 0.5ms to 2ms, and the number of peak points corresponding to a carrier frequency of about 130 kHz is 50 to 300, preferably about 130.
[0051] In an exemplary embodiment, before comparing the filtered peak sequence with a dynamic decision threshold corresponding to the time window to generate a high-level sequence and a low-level sequence, the method further includes: Calculate the modulation depth for each time window, where the modulation depth is the difference between the maximum and minimum values of the corresponding time window.
[0052] When the modulation depth is less than the preset minimum modulation depth threshold, the time window is determined to be an ineffective modulation window, and the level decision of the corresponding time window is skipped; the preset minimum modulation depth threshold is 0.2V.
[0053] In an exemplary embodiment, detecting the level transition point between the high-level sequence and the low-level sequence specifically includes: The high-level sequence is mapped to a first discrete integer value, the low-level sequence is mapped to a second discrete integer value, and the level inversion point is detected by differential operation.
[0054] In one exemplary embodiment, the verification process includes at least one or more of the following: stop bit verification, parity verification, and verification methods that involve performing an XOR operation on the header and information fields to obtain a checksum and comparing it with the received checksum.
[0055] Example 2 like Figure 2 As shown, this application provides a real-time decoding system for wireless charging communication data packets in smart tires, applied to the tire medium environment. The receiving end replenishes the energy storage element in the tire's internal unit, and the receiving end uses load modulation (ASK) to change the voltage of the transmitting coil. The transmitting end includes a transmitting coil, and coil terminals A and B generate a differential voltage ΔV. coil ,include: 1. Differential attenuation circuit: Connected to the data acquisition module and the two ends of the wireless charging transmitter coil, it is used to symmetrically attenuate the differential voltage across the two ends of the transmitter coil (i.e., coil end A and coil end B) to obtain the attenuated voltage ΔV. adc This ensures that the differential peak voltage entering the data acquisition module is lower than the upper limit of the acquisition range; the differential attenuation circuit is preferably a symmetrical differential π-type attenuation network, and the specific structure is shown in Example 6.
[0056] 2. Data Acquisition Module: This module performs high-frequency sampling of the differential voltage across the transmitting coil after differential attenuation, outputting the original sampling sequence x[n]. The data acquisition module can be composed of an FPGA, DSP, MCU, or a DAQ with real-time sampling capability; the sampling frequency should be no less than 5 times the carrier frequency, preferably about 1 MS / s, to ensure that the carrier and modulation details can be reliably reconstructed in the peak sequence.
[0057] 3. Peak Extraction Module: This module extracts peak points based on the original sampled sequence according to the carrier period, outputting a peak sequence p[i] and its time information t[i] that corresponds one-to-one with the carrier period. The peak extraction module can be implemented on the acquisition side or the real-time processing side, and its output satisfies the serialized expression of "one peak point for one carrier period".
[0058] 4. Real-time Decoding Processing Module: This module performs nonlinear filtering, dynamic decision threshold generation, level decision, inversion point detection, duration fault tolerance decision, and performs exception reset and resynchronization on the peak sequence. It completes the parsing and verification of communication data packets, obtaining the real-time decoding result of the wireless charging communication data packets (i.e., decoded communication packets). The real-time decoding processing module can be integrated with the data acquisition module or deployed separately.
[0059] 5. Result Output Module: Used to display, store, and upload the real-time decoding results of wireless charging communication data packets, including but not limited to: packet type, field content, timestamp, verification results, statistical information, etc.; used to provide online monitoring basis for wireless charging systems in tire medium environments.
[0060] This application performs high-frequency differential sampling of the voltage across the transmitting coil and performs peak extraction in real time to form a peak sequence; median filtering is applied to the peak sequence to suppress impulse noise and maintain the level transition edge; a dynamic threshold is constructed using the maximum / minimum values of a segmented window to adaptively track the voltage baseline drift under in-tire conditions and complete high / low level decision; differential dual-phase 0 / 1 bit decoding is implemented based on level duration-based fault-tolerant decision, and communication frame parsing is completed by combining preamble synchronization, asynchronous serial byte structure, odd parity / stop bit verification, and XOR checksum verification; when the peak voltage of the transmitting coil exceeds the acquisition range, the input voltage is limited to the range and the loading on the resonant circuit is reduced through a symmetrical differential attenuation network, thereby ensuring that the communication modulation characteristics are distinguishable and data packets are not lost in real-time decoding under in-tire conditions.
[0061] This application enables real-time monitoring and storage of all stages of wireless charging communication packets at the transmitting end without modifying the Qi protocol development board circuit and protocol. It provides a reusable wireless charging communication monitoring tool for complex working conditions inside smart tires, improves system debugging efficiency, and supports the optimization and verification of key designs such as transmission distance, coil size, and power control parameters.
[0062] Example 3 In this embodiment, the two ends of the transmitting coil are selected as observation points to obtain the voltage amplitude change caused by the load modulation at the receiving end on the primary side. The specific processing flow is as follows: Figure 3 As shown in (a) above, the peak sequence is as follows: Figure 3 As shown in (b) of the diagram, the steps are as follows.
[0063] S101: Based on a differential attenuation circuit, the differential voltage across the transmitting coil is symmetrically attenuated, ensuring that the peak differential voltage entering the data acquisition module is below the upper limit of the acquisition range; ΔV adc (t) = k × ΔV coil (t), where ΔV coil(t) represents the differential voltage across the transmitting coil (i.e., coil terminals A and B) at time t; ΔV adc (t) is the voltage value input to the data acquisition module after voltage division at time t; k is the differential attenuation coefficient, in this embodiment, k=0.33.
[0064] S102: High-frequency sampling is performed on the differential voltage across the transmitting coil to form the original sampling sequence x[n]. F s ≥5×F c , of which F s F is the sampling frequency. c For the carrier voltage frequency, in the embodiment, F s =1MS / s, F c =130kHz.
[0065] S103: Extract peak values from the original sampling sequence x[n] according to the carrier period. Select one peak value as the peak point in each carrier period to form a peak sequence and record the time stamp information of the peak points.
[0066] S104: Output the peak sequence p[i] and time information t[i].
[0067] Through the above peak serialization process, the high-frequency carrier waveform is "compressed" into a peak envelope sequence that varies with time. This not only preserves the amplitude information required for ASK modulation, but also significantly reduces the data size for subsequent processing, which is beneficial for achieving online decoding under conditions of limited real-time hardware resources.
[0068] Example 4 In the presence of the tire or in complex media, peak sequences may contain local spikes and high-frequency disturbances. To suppress noise without disrupting the level transition moments, this embodiment employs nonlinear filtering, preferably median filtering. The nonlinear filtering process is as follows: Figure 4 As shown in (a) above, the dynamic decision threshold is as follows: Figure 4 As shown in (b) of the diagram.
[0069] S201: Perform median filtering on the peak sequence to obtain the filtered peak sequence pf[i] and its corresponding time information tf[i]; the median filtering window length is an odd number of points, preferably 3 points or more, to balance noise reduction capability and edge preservation capability.
[0070] S202: Divide the filtered peak sequence into time windows with a window length of (0.5 ~ 2) ms (corresponding to 50 to 300 peak points when the carrier is about 130 kHz, preferably about 130 points).
[0071] S203: Calculate the maximum window value V for each window. max With the minimum value of the window V minThe average of the two is used as the dynamic decision threshold V. th V th =(V max +V min ) / 2. The aforementioned dynamic decision threshold can be updated with the window to track voltage baseline drift caused by coupling changes and load changes, thereby avoiding misjudgments caused by fixed thresholds under in-tire conditions.
[0072] In practical applications, to eliminate steady-state regions where no effective modulation has occurred, the system can calculate the modulation depth and compare it with a minimum modulation depth threshold; where the modulation depth A m = V max - V min ,; when A m When the voltage is less than a threshold (e.g., 0.2V), the window can be determined to be an ineffective modulation window and the level decision can be skipped to reduce false triggering.
[0073] Example 5 The communication packet frame parsing process, including preamble synchronization, byte parsing, and verification, is as follows: Figure 5 As shown in (a) above, the binarized high-level sequence and low-level sequence are as follows: Figure 5 As shown in (b) of the diagram.
[0074] S301: Compare the filtered peak sequence with the dynamic decision threshold of its window: if it is higher than the threshold, it is judged as high level, and if it is lower than the threshold, it is judged as low level, thus obtaining the high level sequence and the low level sequence.
[0075] S302: In order to reduce the complexity of flip point detection, the level sequence is binarized, and the high level sequence is mapped to a first discrete integer value and the low level sequence is mapped to a second discrete integer value. In this embodiment, the first discrete integer value is 9 and the second discrete integer value is 6.
[0076] S303: Perform differential or state scanning on high-level and low-level sequences to detect level transition points; calculate the duration Δ between adjacent transition points. t .
[0077] S304: Fault tolerance decision based on bit duration characteristics of differential dual-phase modulation: When Δ t If the value falls within (400 ~ 600) μs, it is determined to be a logic bit 0.
[0078] When two segments Δ are detected consecutively t If all values fall within (200 ~ 300) μs, they are determined to be logic bit 1.
[0079] S305: When the detected Δt does not meet any of the above decision windows, perform an abnormal reset: discard the currently unparsed bits / bytes / data packets and return to the synchronous search process to prevent the entire packet decoding from failing due to error propagation caused by noise or local distortion.
[0080] Example 6 After obtaining the bitstream, this embodiment performs frame structure parsing on the communication packets, such as... Figure 6 As shown. The parsing process includes: S401: Search for a preamble in the bitstream to achieve synchronization.
[0081] S402: Determine if synchronization was successful. If yes, execute S403; otherwise, execute S406.
[0082] S403: Based on the start bit after the preamble, the header and information fields are parsed sequentially according to the asynchronous serial byte structure. In practical applications, the header and information start bit + information bit + check bit + stop bit are parsed in 11-bit byte format.
[0083] S404: Perform verification on the parsed bytes. Verification methods include, but are not limited to, stop bit verification, parity verification, and performing an XOR operation on the header and information fields to obtain a checksum and comparing it with the received checksum.
[0084] S405: Determine if the verification was successful. If yes, proceed to S407; otherwise, proceed to S408.
[0085] S406: Discard and search for the preamble again, returning to S401.
[0086] S407: Output the contents of a valid communication packet.
[0087] S408: Discard and search for the preamble again, returning S404.
[0088] In a preferred embodiment of this application, the protocol is Qi 1.1, the preamble can be a series of consecutive logic 1s (e.g., 11-25 bits), the byte structure can include a start bit, data bits, parity bit, and stop bit, and the checksum can be the XOR result of the header and the information field. It should be noted that the above-mentioned Qi 1.1 field rules are a preferred implementation; the system-level innovation lies in the reliable extraction, decision-making, and real-time decoding framework for communication modulation characteristics in a tire-based media environment.
[0089] Example 7 To address the issue of elevated peak voltage in the transmitting coil under tire-medium conditions leading to data acquisition module range exceeding limits, clipping distortion, and ultimately decoding failure, this embodiment incorporates a differential attenuation circuit as an essential system module.
[0090] like Figure 7 As shown, the symmetrical differential π-type attenuation network includes a first resistor R1, a second resistor R2, and a third resistor R3, wherein: R1 and R3 are connected in series across the two ends of the transmitting coil (i.e.) Figure 7 The middle part represents the transmitting coil end A and the transmitting coil end B, and R1=R3 is satisfied to ensure differential symmetry.
[0091] R2 is connected between the positive (+) and negative (-) terminals of the differential input. Figure 7 AI+ and AI- are the positive and negative terminals of the differential input of the data acquisition module connected when acquiring voltage; suppressing the conversion of common-mode interference to differential-mode noise.
[0092] The attenuation coefficient k satisfies: Wherein, R1 is the first resistance value, R2 is the second resistance value, R3 is the third resistance value, and k is preferably in the range of 0.2 to 0.5, and more preferably about 0.33, so as to achieve a balance between range adaptation and signal-to-noise ratio.
[0093] In addition, to reduce the impact of loading on the resonant circuit at the transmitting end, the equivalent differential input impedance presented by the attenuation network at the transmitting coil end should be much greater than the equivalent impedance of the transmitting coil, so as to minimize the change in the operating point of the wireless charging system and preserve the ASK modulation depth.
[0094] When the differential input range of the data acquisition module is ±10 V, the attenuation circuit can limit the differential peak voltage of the coil under tire medium conditions to within ±10 V, thus avoiding clipping distortion.
[0095] Example 8 This application can be deployed as an online monitoring tool for intelligent tire in-tire wireless power supply systems: without changing the receiver's protocol stack, it achieves online analysis and recording of key stages of the wireless charging process (such as Ping, identification and configuration, and power transmission) by acquiring the differential voltage across the transmitting coil and decoding the receiver's communication packets in real time. This real-time decoding system for wireless charging communication data packets in intelligent tires can be used for: Monitor whether the power contract establishment process is stable and whether there are frequent retries.
[0096] Monitor the timing and content of control data packets to help determine adjustment behavior under changes in coupling or load.
[0097] When charging abnormalities or efficiency degradation occur, the problem can be located by combining the communication packet and coil voltage peak sequence (e.g., synchronization loss, insufficient modulation depth, range clipping, etc.).
[0098] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0099] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.
Claims
1. A method for real-time decoding of wireless charging communication data packets for smart tires, characterized in that, This technology is applied to wireless charging scenarios where the dielectric between the transceiver coils is complex and the coupling between the transceiver ends changes with attitude. These scenarios include wireless power supply from an intelligent tire in-tire unit, comprising: The differential voltage across the transmitting coil of the wireless charging transmitter is sampled at high frequency to obtain the original sampling sequence; Based on the original sampling sequence, peak points are extracted according to the carrier period to obtain peak sequences and time information that correspond one-to-one with the carrier period. The peak sequence is subjected to nonlinear filtering to obtain a filtered peak sequence; The filtered peak sequence is segmented into time windows. For each time window, the maximum and minimum values are calculated, and the dynamic decision threshold for the corresponding time window is generated from the maximum and minimum values. The filtered peak sequence is compared with the dynamic decision threshold of the corresponding time window to generate a high-level sequence and a low-level sequence, and the level inversion point of the high-level sequence and the low-level sequence is detected. Bit decision is made based on the duration between adjacent level transition points: when the detected duration falls within the first preset duration range, it is determined to be logic bit 0; when two consecutive durations fall within the second preset duration range, it is determined to be logic bit 1. When the detected duration does not meet any bit decision condition of the first preset duration range and the second preset duration range, an abnormal reset is performed, discarding the currently unparsed bits, bytes or data packets, and re-searching the synchronization sequence to restore synchronization; In the bit stream obtained from the bit decision, preamble synchronization and parsing of the header and information fields according to the asynchronous serial byte structure are performed, and verification is performed to obtain the real-time decoding result of the wireless charging communication data packet.
2. The real-time decoding method for wireless charging communication data packets for smart tires according to claim 1, characterized in that, The wireless charging communication data packet is used for online monitoring and parameter recording of the continuous energy replenishment process of the smart tire in-tire unit; The wireless charging communication data packet follows the Qi protocol, and the carrier frequency of the differential voltage across the transmitting coil is in the range of 110kHz to 205kHz. The sampling frequency of the high-frequency sampling is not less than 5 times the carrier frequency.
3. The real-time decoding method for wireless charging communication data packets for smart tires according to claim 1, characterized in that, Based on the original sampling sequence, peak points are extracted according to the carrier period to obtain peak sequences and time information corresponding one-to-one with the carrier period, specifically including: The maximum value within each carrier cycle is selected as a peak point, and the original sampling sequence is reduced in dimensionality to a peak sequence corresponding to the carrier cycle, thus obtaining a peak sequence and time information that correspond one-to-one with the carrier cycle.
4. The real-time decoding method for wireless charging communication data packets for smart tires according to claim 1, characterized in that, The nonlinear filter is a median filter, and the window length of the median filter is an odd number of points.
5. The real-time decoding method for wireless charging communication data packets for smart tires according to claim 1, characterized in that, The dynamic decision threshold for the corresponding time window is generated from the maximum and minimum values of the window, specifically including: The average of the maximum and minimum values of each time window is used as the dynamic decision threshold for the time window; the length of the time window is from 0.5ms to 2ms.
6. The real-time decoding method for wireless charging communication data packets for smart tires according to claim 1, characterized in that, Before comparing the filtered peak sequence with the dynamic decision threshold of the corresponding time window to generate the high-level sequence and the low-level sequence, the process further includes: Calculate the modulation depth for each time window, where the modulation depth is the difference between the maximum and minimum values of the corresponding time window. When the modulation depth is less than the preset minimum modulation depth threshold, the time window is determined to be an ineffective modulation window, and the level decision of the corresponding time window is skipped; the preset minimum modulation depth threshold is 0.2V.
7. The real-time decoding method for wireless charging communication data packets for smart tires according to claim 1, characterized in that, Detecting the level transition points of the high-level sequence and the low-level sequence specifically includes: The high-level sequence is mapped to a first discrete integer value, the low-level sequence is mapped to a second discrete integer value, and the level inversion point is detected by differential operation.
8. A real-time decoding system for wireless charging communication data packets for smart tires, characterized in that, include: The differential attenuation circuit is connected to the data acquisition module and the two ends of the wireless charging transmitter coil to symmetrically attenuate the differential voltage across the transmitter coil. The data acquisition module is used to perform high-frequency sampling of the differential voltage across the transmitting coil after differential attenuation and output the original sampling sequence. The peak extraction module is used to extract peak points based on the original sampling sequence according to the carrier period, so as to obtain the peak sequence and time information corresponding one-to-one with the carrier period; The real-time decoding processing module is used to perform nonlinear filtering on the peak sequence, generate dynamic decision thresholds, complete level decision and level duration fault tolerance decision, and perform abnormal reset and resynchronization, complete the parsing and verification of communication data packets, and obtain the real-time decoding result of wireless charging communication data packets; the real-time decoding processing module is configured to execute the real-time decoding method for wireless charging communication data packets for smart tires according to any one of claims 1-7. The results output module is used to display, store, and upload the real-time decoding results of wireless charging communication data packets.
9. The real-time decoding system for wireless charging communication data packets for smart tires according to claim 8, characterized in that, The differential attenuation circuit is a symmetrical differential π-type attenuation network, which includes a first resistor, a second resistor, and a third resistor. The first resistor is connected in series between the first end of the transmitting coil and the differential input positive terminal of the data acquisition module; the third resistor is connected in series between the second end of the transmitting coil and the differential input negative terminal of the data acquisition module; and the second resistor is connected across the differential input positive terminal and differential input negative terminal of the data acquisition module. The resistance values of the first resistor and the third resistor are equal; The differential attenuation coefficient k of the symmetric differential π-type attenuation network satisfies: Where R1 is the first resistance value, R2 is the second resistance value, and R3 is the third resistance value; The equivalent differential input impedance presented by the differential attenuation circuit at both ends of the transmitting coil is much greater than the equivalent impedance of the transmitting coil.
10. The real-time decoding system for wireless charging communication data packets for smart tires according to any one of claims 9, characterized in that, The real-time decoding system for wireless charging communication data packets used in smart tires is used to monitor and record wireless charging communication data packets during the Ping, identification and configuration, and power transmission phases of the in-tire unit wireless charging process.