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CN-122017381-A - Electric traction magnetic interference detection method and system for charging interface of electric automobile

CN122017381ACN 122017381 ACN122017381 ACN 122017381ACN-122017381-A

Abstract

The invention relates to the technical field of electric automobile charging safety detection, and discloses an electric automobile charging interface electric traction magnetic interference detection method and system, wherein vibration speed data, internal temperature data and working current data of a charging interface shell are obtained; the method comprises the steps of utilizing a multichannel band-pass filter bank and empirical mode decomposition to extract dual-source sound wave components of an engine and a motor, utilizing a beam forming algorithm to reconstruct a sound wave space propagation mode to generate a dual-source sound interference pattern matrix, calculating a temperature-corrected magnetostriction constitutive parameter matrix based on temperature data, inverting a dual-source magnetic field based on the temperature-corrected parameter matrix, separating contribution components of a magnetic source of the engine and a magnetic source of the motor, and outputting a dual-source cooperative interference detection result. The invention solves the technical problems that the double-source in-phase resonance state cannot be identified, the transient strong magnetic pulse of power switching cannot be detected, and the magnetic field inversion accuracy is low under the condition of uneven temperature.

Inventors

  • HE ZENGSHAN
  • ZHANG NENG
  • ZHU JIE
  • QIU CHENG
  • Yao bao
  • WU SHENG
  • YAO JIEYI
  • GAO ANXIN

Assignees

  • 武汉科正技术服务有限公司

Dates

Publication Date
20260512
Application Date
20251114

Claims (10)

  1. 1. The electric traction magnetic interference detection method for the charging interface of the electric automobile is characterized by comprising the following steps of: acquiring vibration speed time sequence data acquired by a laser Doppler vibration meter distributed at multiple points on a charging interface shell, temperature data acquired by a distributed optical fiber temperature sensor in the charging interface and working current data of a vehicle power system, and performing timestamp alignment processing to generate a vibration-temperature-current synchronous combined data set; Frequency domain separation is carried out on vibration speed time series data by utilizing a multichannel band-pass filter bank, a first sound wave component corresponding to engine characteristic frequency and harmonic wave thereof and a second sound wave component corresponding to motor characteristic frequency and harmonic wave thereof are extracted, empirical mode decomposition is carried out on each sound wave component, an intrinsic mode function is extracted, and a double-source multi-scale sound vibration signal set is generated; calculating the sound wave amplitude and the phase of each sensor position in the double-source multi-scale sound vibration signal set, reconstructing the space propagation mode of sound waves by using a beam forming algorithm, identifying the wave crest and wave trough space distribution of sound wave interference fringes, and generating a double-source sound interference pattern matrix; A finite difference solver of a heat conduction equation is utilized, the internal heat source distribution of the charging interface is inverted based on temperature data, a heat source power density diagram of spatial distribution is calculated, a temperature-dependent magnetostriction coefficient field of spatial distribution is calculated based on a temperature dependence function of magnetostriction coefficients, and a temperature-corrected magnetostriction constitutive parameter matrix is generated by combining the heat source power density diagram; Based on a magnetostriction constitutive parameter matrix corrected by temperature, a coupling function of magnetic field intensity and strain is established, a double-source acoustic interference pattern matrix and a vibration signal are input as boundary conditions by using a finite element inverse analysis method, internal magnetic field distribution meeting a magnetic field equation and an elastic wave equation is solved iteratively, contribution components of an engine magnetic source and a motor magnetic source are separated in an inversion mode, and a temperature-compensated double-source magnetic field decomposition result is generated; And performing cross-correlation calculation on a temperature-compensated dual-source magnetic field decomposition result and a traction system typical working magnetic field template, generating interference characteristic similarity indexes of each magnetic source, evaluating the relation between the superimposed magnetic field intensity and a damage threshold of a communication module, and outputting a dual-source cooperative interference detection result, an interference intensity level, a contact resistance abnormality alarm and a suggested load scheduling strategy.
  2. 2. The method for detecting electric traction magnetic interference of an electric vehicle charging interface according to claim 1, wherein reconstructing a spatial propagation mode of an acoustic wave using a beam forming algorithm comprises: performing Hilbert transformation on each inherent mode function in the double-source multi-scale sound vibration signal set to obtain instantaneous amplitude and instantaneous phase of each sensor position; Calculating the space propagation direction of the sound wave by using a delay and sum beam forming algorithm, and calculating the beam output as the weighted sum of the sensor signals for the space searching direction, wherein the weighted coefficient of each sensor performs phase compensation according to the wave vector corresponding to the position and the searching direction, the modulus value of the wave vector is determined by the ratio of the sound wave frequency to the sound velocity multiplied by twice the circumference ratio, and the direction is along the searching direction; calculating the amplitude distribution of beam output on the space grid points, identifying the respective propagation modes of the first acoustic wave component and the second acoustic wave component, and calculating the phase difference of the first acoustic wave component and the second acoustic wave component at each point in space; According to the spatial distribution of the phase difference, identifying an area with the phase difference approaching zero or twice and integer times of the peripheral rate as a constructive interference peak, identifying an area with the phase difference approaching odd times of the peripheral rate as a destructive interference trough, and generating a double-source acoustic interference pattern matrix containing the spatial coordinates of the peak and the trough; Wherein, the criterion for judging that the difference between the phase difference and the double integer multiple of the circumference ratio is smaller than one sixth of the circumference ratio is near zero or the criterion for judging that the difference between the phase difference and the double integer multiple of the circumference ratio is near the odd multiple of the circumference ratio is smaller than one sixth of the circumference ratio.
  3. 3. The method for detecting electric traction magnetic interference of an electric vehicle charging interface according to claim 1, wherein the generating a temperature-corrected magnetostrictive constitutive parameter matrix comprises: Establishing a three-dimensional heat conduction equation of a charging interface, wherein the change rate of the description temperature along with time is equal to the product of the material density and the specific heat capacity multiplied by the heat conductivity and the divergence of the temperature gradient plus the heat source power density; Performing space dispersion on the heat conduction equation by using a finite difference method, dividing the internal space of the charging interface into uniform grids, approximating the space derivative of the temperature to a differential form on each grid node, and generating a discretized linear equation set; taking the measured temperature data as boundary conditions and known node values, inverting the heat source power density of each grid node by solving a discretization linear equation set, and generating a heat source power density map of spatial distribution; inputting temperature values of grid nodes from a magnetostriction coefficient temperature dependent function obtained by pre-calibration, calculating corresponding magnetostriction coefficients, and generating a spatially distributed temperature-variable magnetostriction coefficient field; Combining the temperature-variable magnetostriction coefficient field with mechanical parameters such as elastic modulus, poisson ratio and the like of each component material of the charging interface, constructing a magnetostriction constitutive relation matrix of each grid node, and collecting constitutive relation matrices of all grid nodes to generate a temperature-corrected magnetostriction constitutive parameter matrix; The temperature dependence function of the magnetostriction coefficient is obtained by applying magnetic fields with known intensities to ferromagnetic materials of a charging interface under different temperature conditions, measuring strain response of the materials, and fitting the magnetic field to obtain a functional relation between the magnetostriction coefficient and the temperature, wherein the functional form is that the magnetostriction coefficient at a reference temperature is multiplied by a polynomial correction term comprising a temperature difference and a square of the temperature difference.
  4. 4. The method for detecting electric vehicle charging interface electric traction magnetic interference according to claim 1, wherein the inverting and separating contribution components of each of the engine magnetic source and the motor magnetic source comprises: establishing a multi-physical field coupling equation set in the charging interface, wherein the multi-physical field coupling equation set comprises a magnetic field equation, an elastic wave equation and a magnetostriction coupling relation, the magnetic field equation describes that the rotation of the magnetic field intensity is equal to the current density and the divergence of the magnetic induction intensity is zero, the elastic wave equation describes that the second-order time derivative of displacement is equal to the inverse of the material density multiplied by the divergence of the stress tensor plus the magnetostriction physical force, and the magnetostriction coupling relation describes that the strain is equal to the product of the magnetostriction constitutive parameter matrix and the magnetic field intensity; dispersing the coupling equation set by using a finite element method, taking the internal magnetic field strength of the charging interface as an unknown variable to be solved, and representing the unknown variable as a combination of node values; Converting the measured vibration speed data into surface displacement boundary conditions, and taking the interference peak and trough positions provided by the dual-source acoustic interference pattern matrix as constraint conditions of magnetic field space distribution; An iteration solving method is adopted, an initial guess value of the magnetic field distribution is initially set, strain and vibration generated by magnetostrictive coupling of the magnetic field distribution corresponding to the initial guess value are calculated, the calculated vibration is compared with actual measurement vibration, the magnetic field distribution is adjusted according to the difference, and iteration is repeated until the difference is smaller than a convergence threshold value; The iteration solving method adopts a conjugate gradient method to carry out iteration optimization, an objective function is defined as weighted residual error square sum of normalized actual measurement vibration and calculated vibration, a regularization term is added, wherein the actual measurement vibration speed and the calculated vibration speed are normalized to scale a vibration speed value to be within a range from zero to one, the weighted residual error square sum is calculated by multiplying a weight coefficient by a difference square between the normalized actual measurement vibration speed and the normalized calculated vibration speed of each measuring point, and the regularization term adopts a square volume integral form of a magnetic field gradient to restrict the spatial smoothness of a solution; The weight coefficient is set according to the signal-to-noise ratio of the measuring points, a larger weight is set for the measuring points with high signal-to-noise ratio, and the weight coefficient is calculated as the signal-to-noise ratio of each measuring point divided by the sum of the signal-to-noise ratios of all the measuring points; Integrating, for the time series data, the vibration velocity residuals at each time instant over a selected time window, the objective function comprising a time integral of a weighted sum of squares of residuals at each time instant over the time window, wherein the time window is set to comprise at least five periods of magnetic field oscillation to ensure that a complete time-varying feature is captured; In the converged magnetic field distribution, separating a first magnetic field component corresponding to the characteristic frequency of the engine and a second magnetic field component corresponding to the characteristic frequency of the motor according to the spatial frequency characteristic, wherein the first magnetic field component and the second magnetic field component respectively represent the contributions of the magnetic source of the engine and the magnetic source of the motor, and generating a temperature compensated double-source magnetic field decomposition result; the initial guess value utilizes magnetic field data measured by a magnetic field sensor array around the charging interface, an initial magnetic field distribution inside the charging interface is generated by adopting a three-dimensional interpolation method, and the convergence threshold value is that the root mean square error relative variation of the vibration speed calculated by two continuous iterations is smaller than 1%.
  5. 5. The method for detecting electric traction magnetic interference of an electric vehicle charging interface according to claim 1, wherein the outputting the double-source cooperative interference detection result includes: obtaining an engine magnetic field template and a motor magnetic field template from a prestored traction system typical working magnetic field template library; Calculating normalized cross correlation coefficients of the first magnetic field component and the engine magnetic field template in the temperature compensated double-source magnetic field decomposition result, and normalizing by summing the inner products of the first magnetic field component and the engine magnetic field template at each spatial position and dividing the products by the square root of the square sum of the respective amplitude values; the cross correlation coefficient of the second magnetic field component and the motor magnetic field template is calculated in a similar way, and an interference characteristic similarity index is generated; calculating the total intensity of the double-source superimposed magnetic field, aiming at the position of the charging interface communication module, taking the root mean square value of the magnetic field intensity of the position in a detection time window as an evaluation index, and comparing the root mean square value with a preset communication module damage threshold; The grading judgment is carried out according to the comparison result, namely, when the total intensity is smaller than half of the damage threshold value, a normal interference intensity level is output, when the total intensity is larger than or equal to half of the damage threshold value and smaller than the damage threshold value, a warning interference intensity level is output, and when the total intensity is larger than or equal to the damage threshold value, a dangerous interference intensity level is output; Calculating the power loss of each contact of the charging interface based on the heat source power density map, inversely calculating the contact resistance value, and generating an abnormal contact resistance alarm when the contact resistance exceeds three times of a normal value; when the interference intensity level is 'warning' or 'danger', a load scheduling strategy suggestion is generated according to the phase relation of the double-source magnetic field.
  6. 6. The method of claim 1, further comprising the step of detecting transient ferromagnetic pulses at a power switching instant: Acquiring magnetic induction intensity data acquired by a magnetic field sensor array around a charging interface, calculating magnetic vector potential field distribution by using a poisson equation solver under a coulomb standardization condition, performing complex representation conversion, detecting phase singular points, labeling topological charge symbols of the singular points by using a topological charge calculation algorithm, and generating a singular point set with topological charge labels; Calculating the conservation of topological charges among the singular point sets at successive moments, detecting the mutation of the total sum of the topological charges to identify a singular point annihilation event and a regeneration event, generating a topological event density field by using a nuclear density estimation algorithm, and extracting a density field peak value region to identify a power switching candidate moment; In a time window of the power switching candidate moment, calculating a phase difference time sequence and a magnetic field energy time derivative of two sources in a temperature compensated double-source magnetic field decomposition result, detecting the moment that the phase difference is close to zero degree and the energy abrupt change peak value exceeds a threshold value, and generating transient in-phase interference characteristic parameters; When the detection result of the double-source cooperative interference is output, combining transient in-phase interference characteristic parameters, and when the transient in-phase interference moment is detected and the energy mutation exceeds the damage threshold of the communication module, adding a transient strong magnetic pulse alarm mark in the output.
  7. 7. The method for detecting electric traction magnetic interference of an electric vehicle charging interface according to claim 6, wherein the generating a singular point set with a topological charge label comprises: the method comprises the steps of obtaining three-dimensional magnetic induction intensity measured by a magnetic field sensor array, solving a poisson equation to obtain a magnetic vector potential field based on the coulomb specification condition that the divergence of the magnetic vector potential is zero, wherein the poisson equation describes that the Laplace operator of the magnetic vector potential is equal to negative magnetic permeability multiplied by current density; selecting a certain component of the magnetic vector potential field, performing complex representation conversion, and constructing an analytic signal through Hilbert transformation to extract phase distribution; Calculating the gradient of phase distribution, identifying phase singular points at the positions where the gradient diverges or is discontinuous, and recording the space coordinates of each singular point; For each phase singular point, calculating the total amount of phase change divided by twice the circumference ratio along a closed loop around the phase singular point to obtain a topology charge value, wherein the topology charge value is positive and the phase counter-clockwise rotation is represented, the topology charge value is negative and the phase counter-clockwise rotation is represented, the topology charge sign of each singular point is marked, and a singular point set with topology charge mark is generated; the closed loop is selected as a circular path taking the phase singular point as a center and the radius as the nearest neighbor distance of the singular point.
  8. 8. The method for detecting electric traction magnetic interference of an electric vehicle charging interface according to claim 6, wherein the identifying a power switching candidate time includes: respectively calculating topological load sum for two singular point sets at the moment and the next moment; When the absolute value of the difference value of the topological charge sum is greater than or equal to two, identifying the topological charge sum as a topological event, judging the topological charge sum as a singular point annihilation event if the topological charge sum at the next moment is smaller than the topological charge sum at the current moment, and judging the topological charge sum as a singular point regeneration event if the topological charge sum at the next moment is greater than the topological charge sum at the current moment; Counting the occurrence frequency of the topological event at each moment in a time window, and calculating a topological event density function by utilizing a Gaussian kernel density estimation algorithm, wherein the density function generates a topological event density field by carrying out weighted summation on the Gaussian kernel function applied to each event moment and dividing the weighted summation by the total number of the events and bandwidth parameter calculation; Extracting local maximum points of a topological event density field, and identifying the moment when the density value exceeds the mean value by two times of standard deviation as a power switching candidate moment; wherein the bandwidth parameter is set according to a schiff criterion that considers standard deviation and quartile range of event moments, enabling a balance between smoothing noise and maintaining peak characteristics.
  9. 9. The method for detecting electric vehicle charging interface electric traction magnetic interference according to claim 6, wherein the generating transient in-phase interference characteristic parameters comprises: Extracting a first magnetic field component and a second magnetic field component from a temperature-compensated double-source magnetic field decomposition result in a time window of plus or minus one hundred milliseconds before and after each power switching candidate moment, and calculating a phase difference time sequence of the first magnetic field component and the second magnetic field component; Calculating a time derivative of the total energy of the magnetic field, wherein the energy is defined as a volume fraction of the square of the magnetic induction in the charging interface solving area divided by twice the magnetic permeability; detecting the moment when the first condition is met, wherein the absolute value of the phase difference is smaller than fifteen degrees, the second condition is met, the absolute value of the peak value of the energy time derivative is larger than the energy threshold value, and the moment when the condition is met is judged to be the transient in-phase interference moment; recording a phase difference value, an energy mutation amplitude value and a duration time of transient in-phase interference moment, and generating a transient in-phase interference characteristic parameter; The fifteen-degree phase difference threshold corresponds to that when the phase difference of the two sources is smaller than the angle, the vector synthesized amplitude of the double-source magnetic field exceeds one-fifth of the single-source amplitude, and the energy threshold is set to be the average value of the time derivative of the magnetic field energy in the normal working state plus three times of standard deviation.
  10. 10. An electric vehicle charging interface electric traction magnetic interference detection system for executing the electric vehicle charging interface electric traction magnetic interference detection method according to any one of claims 1 to 9, characterized by comprising: The laser Doppler vibration instrument is arranged at multiple points of the charging interface shell and is used for collecting vibration speed time sequence data; the distributed optical fiber temperature sensor is arranged in the charging interface and is used for collecting temperature data; The magnetic field sensor array is arranged around the charging interface and is used for collecting magnetic induction intensity data; And the data processing unit is used for executing the steps of the electric traction magnetic interference detection method of the charging interface of the electric automobile and generating a double-source cooperative interference detection result.

Description

Electric traction magnetic interference detection method and system for charging interface of electric automobile Technical Field The invention relates to the technical field of electric vehicle charging safety detection, in particular to an electric vehicle charging interface electric traction magnetic interference detection method and system. Background When the plug-in hybrid electric vehicle is charged quickly at a charging station, in order to maintain the operation of a high-power air conditioner and a thermal management system, an engine-driven generator and a rear wheel-driven traction motor work simultaneously, and each generates a time-varying magnetic field. The relative phase relationship of the dual magnetic sources determines the interference field intensity distribution at the charging interface, creating constructive interference when the phases are synchronized, the interference being increased by a factor of 1.8 for the single source. Meanwhile, the contact resistance of the internal contact of the charging interface is increased due to long-term heavy current operation, the local temperature rise reaches 75 ℃ when heavy current passes, and the magnetostriction coefficient of the ferromagnetic material in the high-temperature region shifts in temperature, so that the magnetic field-acoustic wave conversion efficiency shows space non-uniformity. In the prior art, a magnetic field sensor is used for measuring a magnetic field around a charging interface, and vibration signals of a charging interface shell are converted into magnetic field intensity information through a magnetostriction principle to indirectly detect. However, the prior art has the following defects that the traditional magnetic field sensor can only measure the superposition result of the double-source magnetic field, cannot distinguish the respective contribution quantity of the engine magnetic source and the motor magnetic source, so that whether the magnetic field sensor is in the most dangerous in-phase interference state cannot be judged, at the moment of switching the power source, the phase singular points of the two source magnetic fields are subjected to topological annihilation and regeneration, so that the spatial distribution of the magnetic field is severely reconstructed, the transient strong magnetic pulse possibly damages a communication module, the transient process cannot be detected in the prior art, the internal space of a charging interface is narrow and the temperature distribution is uneven, and when the magnetic field inversion is carried out by using the normal-temperature fixed magnetostriction coupling coefficient, the system error generated in a high-temperature area reaches 35%, so that the real risk of the double-source cooperative interference cannot be accurately estimated. The defects cause the technical problems that the double-source in-phase resonance state cannot be accurately identified in the charging process of the hybrid electric vehicle, the transient strong magnetic pulse of power switching cannot be detected, and the magnetic field inversion accuracy is low under the condition of uneven temperature. Disclosure of Invention The invention provides an electric traction magnetic interference detection method and system for an electric vehicle charging interface, which solve the technical problems that a double-source in-phase resonance state of a hybrid vehicle cannot be identified, a transient strong magnetic pulse for power switching cannot be detected, and magnetic field inversion accuracy is low under the condition of uneven temperature in the related art. The invention provides an electric traction magnetic interference detection method of an electric automobile charging interface, which comprises the following steps: acquiring vibration speed time sequence data acquired by a laser Doppler vibration meter distributed at multiple points on a charging interface shell, temperature data acquired by a distributed optical fiber temperature sensor in the charging interface and working current data of a vehicle power system, and performing timestamp alignment processing to generate a vibration-temperature-current synchronous combined data set; Frequency domain separation is carried out on vibration speed time series data by utilizing a multichannel band-pass filter bank, a first sound wave component corresponding to engine characteristic frequency and harmonic wave thereof and a second sound wave component corresponding to motor characteristic frequency and harmonic wave thereof are extracted, empirical mode decomposition is carried out on each sound wave component, an intrinsic mode function is extracted, and a double-source multi-scale sound vibration signal set is generated; calculating the sound wave amplitude and the phase of each sensor position in the double-source multi-scale sound vibration signal set, reconstructing the space propagation mode of sound waves by using a beam form