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CN-122008743-A - TPMS tire phase detection method based on DFT and least square method

CN122008743ACN 122008743 ACN122008743 ACN 122008743ACN-122008743-A

Abstract

The invention discloses a tire phase detection method based on DFT and least square method, which comprises the steps of S1, representing Q sampling point data through a sinusoidal signal model, S2, calculating an average value of each sampling point, calculating a corresponding time stamp based on a sampling period, S3, converting to obtain each frequency domain signal, obtaining an amplitude spectrum and a phase spectrum, S4, finding out a frequency index corresponding to the maximum value from the amplitude spectrum, obtaining a corresponding decimal index, calculating a main frequency, extracting a corresponding initial amplitude and an initial phase angle, S5, carrying out disassembly, fitting and least square method solving on the sinusoidal signal model, S6, selecting a sampling point m for calculating the phase, and calculating the phase of the sampling point m. The invention solves the problems of insufficient precision and weak anti-interference in TPMS parameter detection of the traditional DFT method, can accurately extract parameters such as the tire initial phase angle, the specific sampling point phase and the like, and provides reliable data support for TPMS to judge the tire state and the movement position.

Inventors

  • ZHANG XIAOQIANG
  • XI WENHUI
  • PU XIAOFEI

Assignees

  • 琻捷电子科技(江苏)股份有限公司

Dates

Publication Date
20260512
Application Date
20260311

Claims (9)

  1. 1. The TPMS tire phase detection method based on the DFT and the least square method is characterized by comprising the following steps of: S1, acquiring sampling point data of Q time domains through TPMS and recording a sampling period T, wherein each sampling point data passes through a sinusoidal signal model Wherein A is signal amplitude, f main is main frequency, phi 0 is initial phase angle, and t is time; s2, calculating an average value C of each sampling point, and correcting the data of each sampling point into Calculating a time stamp T [ n ] corresponding to each sampling point data based on a sampling period T, wherein T [0] =0, T [ n ] =t [ n-1] +f s ,f s =1000/T is a sampling frequency, and n=1, 2, & gt, Q-1; S3, for each corrected part Performing DFT conversion to obtain corresponding frequency domain signals The method comprises the steps of acquiring a magnitude spectrum and a phase spectrum; k=0, 1,..q-1; S4, finding out the frequency index k max corresponding to the maximum value from the amplitude spectrum and obtaining the corresponding decimal index k max_interp , calculating the main frequency f main based on the sampling frequency f s and the decimal index k max_interp and extracting the initial amplitude corresponding to the main frequency And an initial phase angle phi 0 , the phase angle phi is equal to the initial phase angle phi, ; S5, based on a main frequency f main , sequentially carrying out disassembly, fitting and least square method solving on the sinusoidal signal model; and S6, continuously selecting a sampling point m for calculating the phase based on the solving result in the step S5, and calculating the phase of the selected point m.
  2. 2. The TPMS tire phase detection method based on DFT and least squares method according to claim 1, wherein in step S1, Q sampling point data covers at least three half sampling periods.
  3. 3. The method for detecting tire phase of TPMS based on DFT and least squares methods as recited in claim 1, wherein in step S3, The phase spectrum formula is , Is that Is used to determine the imaginary part of (c), Is that Is a real part of (c).
  4. 4. The method for detecting tire phase of TPMS based on DFT and least squares as recited in claim 1, wherein after finding out the frequency index k max in step S4, the left and right adjacent indexes k max-1 and k max+1 are continuously selected, and then the decimal index k max_interp is obtained by interpolation.
  5. 5. The method for detecting tire phase of TPMS based on DFT and least squares as recited in claim 4, wherein the interpolation method uses first order linear interpolation.
  6. 6. The TPMS tire phase detection method based on DFT and least squares method according to claim 1, wherein when the disassembly is performed in step S5, the sinusoidal signal model is disassembled into , wherein, a=cos Φ 0 ,b=sinφ 0 .
  7. 7. The method for detecting tire phase of TPMS based on DFT and least squares as recited in claim 6, wherein the intermediate parameters used in fitting include Solving the expression of a and b by the least square method to be 。
  8. 8. The method for detecting the tire phase of the TPMS based on the DFT and least square method as recited in claim 1, wherein the step S6 is performed with phase normalization after calculating the phase of the selected point m, and the step includes converting the phase of the sampling point m into an angle of 0-360 degrees or a standard radian of 0-2 pi.
  9. 9. The method for detecting the tire phase of the TPMS based on the DFT and least square methods as recited in claim 1, wherein the TPMS is an acceleration sensor with a Z axis, and the Z axis is perpendicular to the tangential direction of the hub.

Description

TPMS tire phase detection method based on DFT and least square method Technical Field The invention relates to the technical field of automobile electronics, in particular to a tire phase detection method of a TPMS (tire pressure monitor System) based on DFT and a least square method, which is particularly suitable for a method for acquiring data through a tire acceleration sensor, extracting parameters related to tire rotation with high precision, assisting a tire four-wheel automatic positioning technology and carrying out specific sampling point phase. Background Tire Pressure Monitoring System (TPMS) is one of the core electronic systems for guaranteeing the driving safety of automobiles, and the TPMS acquires time domain sampling data in the tire movement process through an acceleration sensor arranged in the tire, so that key information such as the rotation state and pressure change of the tire is analyzed. The tire rotation frequency (corresponding to the main frequency of the signal), the sensitivity (corresponding to the amplitude of the signal) of the acceleration sensor, the initial phase shift (initial phase angle) of the signal and the phase of a specific sampling point (such as the 11 th point phase) are core parameters reflecting the working state of the tire, and the detection accuracy directly influences the judgment accuracy of the TPMS on the abnormal state of the tire. In the prior art, since the TPMS approximates a periodic sinusoidal signal to a data signal collected by a tire, a Discrete Fourier Transform (DFT) is generally used to perform frequency domain conversion on the time-sampled data to extract the core parameters, so as to know the running state of the tire. However, at present, when extracting tire data by DFT, there are at least the following drawbacks: 1) The direct current component contained in the sampling data can interfere with the frequency domain analysis result, so that parameter extraction deviation is caused; 2) DFT conversion is easily affected by frequency spectrum leakage, and especially when the signal frequency and the sampling frequency do not meet the integer multiple relation, the primary frequency identification precision is low, so that the calculation error of amplitude and phase parameters is larger; 3) The phase parameters extracted directly through DFT are not optimized and corrected, so that the high-precision requirements of TPMS on parameter detection cannot be met, the tire state can be misjudged, and the driving safety is affected. Therefore, a TPMS tire phase and key parameter detection method capable of overcoming the problems of direct current component interference and spectrum leakage and improving the parameter detection accuracy is needed. Disclosure of Invention Aiming at the problems, the invention aims to provide a tire phase detection method of a tire based on a DFT and least square method, which realizes the efficient processing of the acquired data of a tire acceleration sensor by removing direct current components, DFT conversion, first-order linear interpolation, least square fitting sinusoidal signal model and the like, accurately extracts the main frequency, amplitude, initial phase angle and selected point phase of the signal, ensures the accuracy of the tire state judgment and the movement position of the tire, and solves the problems of insufficient precision and weak anti-interference capability of the traditional DFT method in the parameter detection of the tire. The method is realized by the following technical scheme: a TPMS tire phase detection method based on DFT and least square method comprises the following steps: S1, acquiring sampling point data of Q time domains through TPMS and recording a sampling period T, wherein each sampling point data passes through a sinusoidal signal model Wherein A is signal amplitude, f main is main frequency, phi 0 is initial phase angle, and t is time; s2, calculating an average value C of each sampling point, and correcting the data of each sampling point into Calculating a time stamp T [ n ] corresponding to each sampling point data based on a sampling period T, wherein T [0] =0, T [ n ] =t [ n-1] +f s,fs =1000/T is a sampling frequency, and n=1, 2, & gt, Q-1; S3, for each corrected part Performing DFT conversion to obtain corresponding frequency domain signalsThe method comprises the steps of acquiring a magnitude spectrum and a phase spectrum; k=0, 1,..q-1; S4, finding out the frequency index k max corresponding to the maximum value from the amplitude spectrum and obtaining the corresponding decimal index k max_interp, calculating the main frequency f main based on the sampling frequency f s and the decimal index k max_interp and extracting the initial amplitude corresponding to the main frequency And an initial phase angle phi 0, the phase angle phi is equal to the initial phase angle phi,; S5, based on a main frequency f main, sequentially carrying out disassembly, fitting and