CN113625353B - Electric vehicle wireless charging foreign matter detection method and device - Google Patents

Electric vehicle wireless charging foreign matter detection method and device Download PDF

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CN113625353B
CN113625353B CN202110948230.0A CN202110948230A CN113625353B CN 113625353 B CN113625353 B CN 113625353B CN 202110948230 A CN202110948230 A CN 202110948230A CN 113625353 B CN113625353 B CN 113625353B
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foreign matter
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CN113625353A (en
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张文彪
颜鹏旭
莫清清
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North China Electric Power University
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V3/00—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation
    • G01V3/38—Processing data, e.g. for analysis, for interpretation, for correction
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/10—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles characterised by the energy transfer between the charging station and the vehicle
    • B60L53/12—Inductive energy transfer
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/60—Monitoring or controlling charging stations
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B7/00—Measuring arrangements characterised by the use of electric or magnetic techniques
    • G01B7/003—Measuring arrangements characterised by the use of electric or magnetic techniques for measuring position, not involving coordinate determination
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B7/00—Measuring arrangements characterised by the use of electric or magnetic techniques
    • G01B7/28—Measuring arrangements characterised by the use of electric or magnetic techniques for measuring contours or curvatures
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M1/00—Testing static or dynamic balance of machines or structures
    • G01M1/12—Static balancing; Determining position of centre of gravity
    • G01M1/122—Determining position of centre of gravity
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V3/00—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation
    • G01V3/08—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation operating with magnetic or electric fields produced or modified by objects or geological structures or by detecting devices
    • G01V3/083—Controlled source electromagnetic [CSEM] surveying
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V3/00—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation
    • G01V3/08—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation operating with magnetic or electric fields produced or modified by objects or geological structures or by detecting devices
    • G01V3/10—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation operating with magnetic or electric fields produced or modified by objects or geological structures or by detecting devices using induction coils
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J50/00—Circuit arrangements or systems for wireless supply or distribution of electric power
    • H02J50/10—Circuit arrangements or systems for wireless supply or distribution of electric power using inductive coupling
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J50/00—Circuit arrangements or systems for wireless supply or distribution of electric power
    • H02J50/60—Circuit arrangements or systems for wireless supply or distribution of electric power responsive to the presence of foreign objects, e.g. detection of living beings
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V3/00—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation
    • G01V3/08—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation operating with magnetic or electric fields produced or modified by objects or geological structures or by detecting devices
    • G01V3/083—Controlled source electromagnetic [CSEM] surveying
    • G01V2003/084—Sources
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V3/00—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation
    • G01V3/08—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation operating with magnetic or electric fields produced or modified by objects or geological structures or by detecting devices
    • G01V3/083—Controlled source electromagnetic [CSEM] surveying
    • G01V2003/085—Receivers
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/70—Energy storage systems for electromobility, e.g. batteries
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/7072—Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02T90/10—Technologies relating to charging of electric vehicles
    • Y02T90/12—Electric charging stations
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02T90/10—Technologies relating to charging of electric vehicles
    • Y02T90/14—Plug-in electric vehicles

Abstract

The invention discloses a method and a device for detecting wireless charging foreign matters of an electric vehicle. The method comprises the following steps: acquiring a first induction voltage obtained by respectively exciting each coil in the detection coil array by using a low-frequency excitation signal and a second induction voltage obtained by respectively exciting each coil by using a high-frequency excitation signal; reconstructing an imaging region image under a low-frequency excitation signal and an imaging region image under a high-frequency excitation signal by adopting an electromagnetic tomography method according to the first induction voltage and the second induction voltage; the imaging area image is a conductivity distribution image of the imaging area; and setting a threshold value according to the conductivity, analyzing the imaging area images to determine whether foreign matters exist, and comparing the two imaging area images when the foreign matters exist to determine whether the foreign matters are metal foreign matters or living foreign matters. The invention can simultaneously detect the metal foreign matters and the living foreign matters, thereby ensuring the safety of wireless charging.

Description

Electric vehicle wireless charging foreign matter detection method and device
Technical Field
The invention relates to the field of charging foreign matter detection, in particular to a wireless charging foreign matter detection method and device for an electric vehicle.
Background
The electric automobile is favored by people as a clean energy vehicle, and the research and development of the electric automobile are very rapid and the electric automobile is widely popularized and applied in recent years. The wireless charging has the characteristics of non-contact, convenience, flexibility, safety, reliability and the like, and solves a plurality of defects existing in the traditional wired charging mode.
However, in the alternating magnetic field, due to the eddy current effect, the metal foreign matter may reduce the mutual inductance and the coupling coefficient between the transmitting coil and the receiving coil of the wireless charging system, thereby reducing the power transmission efficiency, and meanwhile, the metal surface may generate heat, which may cause a fire if contacting with combustible materials such as paper, petroleum and the like in the charging process. The living body foreign matter may cause a safety hazard due to its own movement. The driver cannot see whether or not a foreign object is present in the vehicle. Therefore, the wireless charging foreign matter detection method for the electric vehicle has very important significance. At present, a detection method capable of simultaneously detecting a metal foreign object and a living body foreign object is urgently needed to ensure the safety of wireless charging.
Disclosure of Invention
Based on the above, the embodiment of the invention provides a method and a device for detecting a wireless charging foreign object of an electric vehicle, so as to simultaneously detect a metal foreign object and a living foreign object, thereby ensuring the safety of wireless charging.
In order to achieve the purpose, the invention provides the following scheme:
a wireless charging foreign matter detection method for an electric vehicle comprises the following steps:
acquiring a first induction voltage and a second induction voltage; the first induction voltage is obtained by respectively exciting each coil in the detection coil array by adopting a low-frequency excitation signal; the second induction voltage is obtained by respectively exciting each coil by adopting a high-frequency excitation signal; the detection coil array is arranged above a transmitting coil of the wireless charging system;
according to the first induced voltage, reconstructing an imaging region image under a low-frequency excitation signal by adopting an electromagnetic tomography method, and according to the second induced voltage, reconstructing an imaging region image under a high-frequency excitation signal by adopting the electromagnetic tomography method; the imaging area image is a conductivity distribution image of the imaging area;
and respectively analyzing an imaging area image under the low-frequency excitation signal and an imaging area image under the high-frequency excitation signal according to a conductivity set threshold value, determining whether foreign matters exist in a charging area above the detection coil array, and comparing the imaging area image under the low-frequency excitation signal with the imaging area image under the high-frequency excitation signal when the foreign matters exist, so as to determine whether the foreign matters are metal foreign matters or living foreign matters.
Optionally, the obtaining the first induced voltage and the second induced voltage specifically includes:
sequentially exciting the coils by adopting a low-frequency excitation signal to obtain low-frequency mutual induction voltage of each coil; the first induction voltage comprises low-frequency mutual induction voltages of all coils; the low-frequency mutual induction voltage of the nth coil is the induction voltage of each coil except the nth coil in the detection coil array when the nth coil is excited by a low-frequency excitation signal;
sequentially exciting the coils by adopting a high-frequency excitation signal to obtain high-frequency mutual induction voltage of each coil; the second induction voltage comprises high-frequency mutual induction voltages of all coils; wherein, the high-frequency mutual induction voltage of the nth coil is the induction voltage of each coil except the nth coil in the detection coil array when the nth coil is excited by a high-frequency excitation signal.
Optionally, reconstructing an imaging region image under a low-frequency excitation signal by using an electromagnetic tomography method according to the first induced voltage specifically includes:
calculating a low-frequency induction voltage matrix according to the first induction voltage and the induction voltage of the detection coil array under the condition of a null field;
calculating a first electric field intensity when the low-frequency excitation signal is adopted to excite each coil respectively; the first electric field intensity is the electric field intensity of each pixel point in an imaging area corresponding to the detection coil array during each low-frequency excitation;
calculating the low-frequency sensitivity distribution of every two coils in the detection coil array according to the first electric field intensity under all low-frequency excitation;
determining a low-frequency sensitivity matrix from all the low-frequency sensitivity profiles;
and reconstructing an imaging region image under a low-frequency excitation signal by taking the minimum error between a reconstructed image and a real image as a target based on the low-frequency sensitivity matrix and the low-frequency induced voltage matrix.
Optionally, reconstructing an imaging region image under a high-frequency excitation signal by using the electromagnetic tomography method according to the second induced voltage specifically includes:
calculating a high-frequency induced voltage matrix according to the second induced voltage and the induced voltage of the detection coil array under the condition of a null field;
calculating a second electric field intensity when the high-frequency excitation signal is adopted to excite each coil respectively; the second electric field intensity is the electric field intensity of each pixel point in the imaging area corresponding to the detection coil array during each high-frequency excitation;
calculating the high-frequency sensitivity distribution of every two coils in the detection coil array according to the second electric field intensity under all high-frequency excitation;
determining a high-frequency sensitivity matrix from all the high-frequency sensitivity distributions;
and reconstructing an imaging region image under a high-frequency excitation signal by taking the minimum error between a reconstructed image and a real image as a target based on the high-frequency sensitivity matrix and the high-frequency induction voltage matrix.
Optionally, when there is a foreign object, comparing the image of the imaging region under the low-frequency excitation signal with the image of the imaging region under the high-frequency excitation signal, and determining whether the foreign object is a metal foreign object or a living foreign object, specifically including:
comparing the histograms of the imaging area image under the low-frequency excitation signal and the imaging area image under the high-frequency excitation signal, and judging whether the foreign matter is a metal foreign matter or a living foreign matter;
or, performing logical exclusive-or operation on pixels of the imaging area image under the low-frequency excitation signal and the imaging area image under the high-frequency excitation signal to judge whether the foreign matter is a metal foreign matter or a living body foreign matter.
Optionally, when there is a foreign object, after comparing the image of the imaging area under the low-frequency excitation signal with the image of the imaging area under the high-frequency excitation signal, and determining whether the foreign object is a metal foreign object or a living foreign object, the method further includes:
determining foreign matter information in an imaging area image under the low-frequency excitation signal and an imaging area image under the high-frequency excitation signal by adopting an image processing algorithm; the foreign matter information comprises the position of the foreign matter, the outline of the foreign matter and the center of mass of the foreign matter;
and removing the foreign matters according to the foreign matter information.
Optionally, the calculation formula of the low-frequency sensitivity distribution is as follows:
SAB＝EA·EB；
wherein S isABRepresenting the low frequency sensitivity profiles of the A-th coil and the B-th coil; eAThe first electric field intensity is corresponding to the low-frequency excitation of the A-th coil; eBThe first electric field strength is corresponding to the low-frequency excitation of the B-th coil.
Optionally, the reconstructing an image of an imaging region under a low-frequency excitation signal based on the low-frequency sensitivity matrix and the low-frequency induced voltage matrix with a target of minimum error between a reconstructed image and a real image specifically includes:
constructing an error function based on the low-frequency sensitivity matrix and the low-frequency induced voltage matrix; the error function is
Figure BDA0003217611170000041
Wherein e represents the error between the reconstructed image and the real image;
Figure BDA0003217611170000042
representing a desired induced voltage matrix; v represents a low frequency induced voltage matrix; sσRepresenting a low frequency sensitivity matrix; g represents an imaging area image under a low-frequency excitation signal;
based on the error function, calculating an imaging area image under a low-frequency excitation signal corresponding to each iteration by adopting a Landweber iteration algorithm; the imaging area image under the low-frequency excitation signal corresponding to the (m + 1) th iteration is as follows:
gm+1＝gm-αSσ T(Sσgm-v)；
wherein, gm+1An imaging area image under the low-frequency excitation signal corresponding to the (m + 1) th iteration; gmAn imaging area image under the low-frequency excitation signal corresponding to the mth iteration; α represents an iteration step size; sσ TA transpose representing a low frequency sensitivity matrix;
if the iteration stopping condition is met, determining an imaging area image under the low-frequency excitation signal corresponding to the (m + 1) th iteration as a final imaging area image under the low-frequency excitation signal, and otherwise, performing the next iteration; the iteration stopping condition is that the difference value between the imaging region image under the low-frequency excitation signal corresponding to the m +1 iteration and the imaging region image under the low-frequency excitation signal corresponding to the m +1 iteration is smaller than a set value when the m +1 reaches the set iteration number or the m +1 iteration.
The invention also provides a wireless charging foreign matter detection device for the electric vehicle, which comprises: the device comprises an excitation signal generating module, a multi-path switching module, a detection coil array, an induced voltage measuring module and a foreign matter detecting module;
the excitation signal generation module is connected with the multi-path switching module; the multi-path switching module is respectively connected with the detection coil array and the induction voltage measuring module; the foreign matter detection module is connected with the induction voltage measurement module; the detection coil array is arranged above a transmitting coil of the wireless charging system;
the excitation signal generation module is used for:
generating a low frequency excitation signal and a high frequency excitation signal;
the multi-path switching module is used for:
controlling the low-frequency excitation signal to respectively excite each coil in the detection coil array, and controlling the high-frequency excitation signal to respectively excite each coil;
controlling the switching of coils in the detection coil array in an excitation mode and an induction mode;
the induced voltage measurement module is used for:
measuring a first induced voltage and a second induced voltage; the first induction voltage is obtained by respectively exciting each coil by adopting the low-frequency excitation signal; the second induction voltage is obtained by respectively exciting each coil by adopting a high-frequency excitation signal;
the foreign matter detection module is used for:
according to the first induced voltage, reconstructing an imaging region image under a low-frequency excitation signal by adopting an electromagnetic tomography method;
according to the second induced voltage, reconstructing an imaging region image under a high-frequency excitation signal by adopting the electromagnetic tomography method; the imaging area image is a conductivity distribution image of the imaging area;
and respectively analyzing an imaging area image under the low-frequency excitation signal and an imaging area image under the high-frequency excitation signal according to a conductivity set threshold value, determining whether foreign matters exist in a charging area above the detection coil array, and comparing the imaging area image under the low-frequency excitation signal with the imaging area image under the high-frequency excitation signal when the foreign matters exist, so as to determine whether the foreign matters are metal foreign matters or living foreign matters.
Optionally, the wireless charging foreign matter detection system of electric vehicle further includes: a visual display module;
the visual display module is connected with the foreign matter detection module;
the visual display module is used for:
displaying foreign matter information and reminding a user to remove foreign matters according to the foreign matter information; the foreign matter information is extracted from an imaging region image under the low-frequency excitation signal and an imaging region image under the high-frequency excitation signal by the foreign matter detection module by adopting an image processing algorithm; the foreign matter information includes a position of the foreign matter, a contour of the foreign matter, and a centroid of the foreign matter.
Compared with the prior art, the invention has the beneficial effects that:
the embodiment of the invention provides a method and a device for detecting foreign matters in wireless charging of an electric vehicle, wherein a low-frequency excitation signal is adopted to excite each coil in a detection coil array to obtain a first induction voltage, and a high-frequency excitation signal is adopted to excite each coil to obtain a second induction voltage; reconstructing an imaging region image under a low-frequency excitation signal and an imaging region image under a high-frequency excitation signal by adopting an electromagnetic tomography method according to the first induction voltage and the second induction voltage; the imaging area image is a conductivity distribution image of the imaging area; under low-frequency excitation, metal foreign matters with high conductivity can appear on a reconstructed image, and living foreign matters with low conductivity can not appear on the image; under high-frequency excitation, both metal foreign matters and living foreign matters appear on a reconstructed image, so that an imaging area image under a low-frequency excitation signal and an imaging area image under a high-frequency excitation signal are respectively analyzed according to a conductivity set threshold value to determine whether foreign matters exist in a charging area above the detection coil array, and the imaging area image under the low-frequency excitation signal (reconstructed image) and the imaging area image under the high-frequency excitation signal (reconstructed image) are compared to determine whether the foreign matters are metal foreign matters or living foreign matters. The invention can simultaneously detect the metal foreign matters and the living foreign matters, thereby ensuring the safety of wireless charging.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
Fig. 1 is a flowchart of a method for detecting a foreign object in a wireless charging mode of an electric vehicle according to an embodiment of the present invention;
fig. 2 is a schematic diagram illustrating a relationship between a detection coil array and a foreign object according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a simulation model of a low-frequency sensitivity matrix according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a reconstructed image after interpolation according to an embodiment of the present invention;
fig. 5 is a schematic view of a wireless charging foreign object detection device for an electric vehicle according to an embodiment of the present invention;
fig. 6 is a schematic position diagram of a detection coil array according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
The concept of the wireless charging foreign matter detection method of the electric vehicle of the embodiment is as follows: the foreign matter affects the spatial magnetic field distribution, thereby affecting the mutual inductance of each coil in the detection coil array, and the induced voltage of the detection coil array changes. Under the condition that the induction voltage of the detection coil array is known, a conductivity distribution image can be obtained by combining a sensitivity matrix and an image reconstruction algorithm, and the reconstructed image can be regarded as the representation of the electromagnetic characteristic parameters of the foreign matters, so that the reconstructed image contains the information such as the size, the position, the mass center and the like of the foreign matters, the metal foreign matters and the living foreign matters can be detected, and the safety of wireless charging is ensured.
The implementation principle of the wireless charging foreign matter detection method for the electric vehicle in the embodiment is as follows: the conductivity of the metal foreign bodies is high, the reconstructed image obtained through the voltage amplitude data of the rest sub-coils can display the information of the metal foreign bodies under low-frequency excitation, the conductivity of the living body foreign bodies is low, and the metal foreign bodies can hardly appear under low-frequency excitation; under high-frequency excitation, both metallic foreign bodies and living foreign bodies can appear on the reconstructed image. The two reconstructed images are compared to determine whether the object is a metal foreign object or a living body foreign object. Based on the above concept and principle, the method for detecting the wireless charging foreign object of the electric vehicle of the present embodiment is described.
Fig. 1 is a flowchart of a method for detecting a foreign object in a wireless charging mode of an electric vehicle according to an embodiment of the present invention. Referring to fig. 1, the method includes:
step 101: acquiring a first induction voltage and a second induction voltage; the first induction voltage is obtained by respectively exciting each coil in the detection coil array by adopting a low-frequency excitation signal; the second induced voltage is obtained by respectively exciting the coils by adopting a high-frequency excitation signal. The low frequency excitation signal and the high frequency excitation signal may both be sine wave signals.
The detection coil array is arranged above a transmitting coil of the wireless charging system; the detection coil array is a planar coil array. As shown in fig. 2, 3 is a transmitting coil of the wireless charging system, 4 is a detection coil array, 9 is a foreign object, and the foreign object 9 affects the spatial magnetic field distribution, thereby affecting the mutual inductance of the coils in the detection coil array 4, and the induced voltage of the detection coil array 4 changes.
Step 101, specifically comprising:
sequentially exciting the coils by adopting a low-frequency excitation signal to obtain low-frequency mutual induction voltage of each coil; the first induction voltage comprises low-frequency mutual induction voltages of all coils; the low-frequency mutual induction voltage of the nth coil is the induction voltage of each coil except the nth coil in the detection coil array when the nth coil is excited by adopting a low-frequency excitation signal. For example, when the 1 st coil is excited at a low frequency, the induced voltages of the 2 nd to 16 th coils are recorded, and the induced voltages of the 2 nd to 16 th coils are the low-frequency mutual induction voltage of the 1 st coil.
Sequentially exciting each coil by adopting a high-frequency excitation signal to obtain the high-frequency mutual induction voltage of each coil; the second induced voltage comprises high-frequency mutual induction voltages of all coils; wherein, the high-frequency mutual induction voltage of the nth coil is the induction voltage of each coil except the nth coil in the detection coil array when the nth coil is excited by a high-frequency excitation signal.
Step 102: according to the first induced voltage, reconstructing an imaging region image under a low-frequency excitation signal by adopting an electromagnetic tomography method, and according to the second induced voltage, reconstructing an imaging region image under a high-frequency excitation signal by adopting the electromagnetic tomography method; the imaging region image is a conductivity distribution image of the imaging region.
According to the first induced voltage, an electromagnetic tomography method is adopted to reconstruct an imaging region image under a low-frequency excitation signal, and the method specifically comprises the following steps:
(1) and calculating a low-frequency induction voltage matrix according to the first induction voltage and the induction voltage of the detection coil array under the condition of a null field. The calculation formula of the low-frequency induced voltage matrix is as follows:
Figure BDA0003217611170000081
wherein v represents a low-frequency induced voltage matrix; v. ofobjRepresenting a first induced voltage; v. ofempIndicating the induced voltage of the array of detection coils in the case of a null field. Wherein v isempThe voltage signal of the detection coil array at the moment is recorded and set as original basic data under the condition that no metal foreign matter or living foreign matter exists in a charging area above the transmitting coil during initial installation, and the mutual induction voltage of each coil in the array is calculated and stored, so that the induction voltage of the detection coil array under the condition of an empty field is obtained.
(2) Calculating a first electric field intensity when the low-frequency excitation signal is adopted to excite each coil respectively; the first electric field intensity is the electric field intensity of each pixel point in an imaging area corresponding to the detection coil array when low-frequency excitation is performed each time.
(3) And calculating the low-frequency sensitivity distribution of every two coils in the detection coil array according to the first electric field intensity under all low-frequency excitation. The calculation formula for obtaining the low-frequency sensitivity distribution by adopting a field formula extraction method is as follows:
SAB＝EA·EB；
wherein S isABRepresenting the low frequency sensitivity profiles of the A-th coil and the B-th coil; eAThe first electric field intensity is corresponding to the low-frequency excitation of the A-th coil; eBThe first electric field strength is corresponding to the low-frequency excitation of the B-th coil.
(4) The low frequency sensitivity matrix is determined from all the low frequency sensitivity profiles.
The sensitivity matrix is sensitive field distribution data of the electromagnetic sensor and is a prerequisite for a reconstruction algorithm in electromagnetic tomography. Under ideal conditions, when the rest of the imaging region has no electrical parameter, the ratio of the variation of the output signal of the detection coil array to the variation of the electrical parameter of a region small enough inside the imaging region causing the signal variation. In this embodiment, the sensitivity matrix is the change of the induced voltage of the detection coil caused by the change of the conductivity of the area above the coil array sensor.
In practical application, the method for determining the low-frequency sensitivity matrix comprises the following steps:
in order to accurately and efficiently obtain the low-frequency sensitivity matrix, a coil array finite element simulation model needs to be established. Usually, there is a certain thickness of shell above the ground wireless charging pile, so this embodiment establishes a low-frequency sensitivity matrix at a position 1mm above the coil array, the simulation model is as shown in fig. 3, the dot matrix drawn by the imaging region is 34 × 34, and the interval is 3mm, where part (a) of fig. 3 shows the corresponding relationship between the detection coil and the imaging region, and part (b) of fig. 3 shows the imaging region. When the coil 1 (detection coil) is excited at low frequency, the electric field strength of each point (each pixel point in the imaging area) is calculated and recorded as E1(ii) a When the coil 2 is excited at low frequency, the electric field strength of each point is calculated and recorded as E2Substituting the low-frequency sensitivity distribution into the above calculation formula of the low-frequency sensitivity distribution, the low-frequency sensitivity distribution S of the coil 1 and the coil 2 can be obtained12By analogy therewith, by obtaining E1、E2、E3……E16Substituting into formula to calculate low-frequency sensitivity distribution S of coil 1 and coil 313 Coil 1 and coil 4 low frequency sensitivity profile S14… … low frequency sensitivity profiles of coil 2 and coil 3S23Coil 2 and coil 4 low frequency sensitivity profile S24… … low frequency sensitivity profiles S of coil 3 and coil 434 Coil 3 and coil 5 low frequency sensitivity profile S35… … low-frequency sensitivity profiles S of coil 14 and coil 151415Coil 14 and coil 16 low frequency sensitivity profile S1416Coil 15 and coil 16 low frequency sensitivity profile S1516。
(5) And based on the low-frequency sensitivity matrix and the low-frequency induced voltage matrix, reconstructing an imaging region image under a low-frequency excitation signal by adopting a reconstruction algorithm with the aim of minimizing the error between a reconstructed image and a real image. The reconstruction algorithm may be an iterative algorithm or a non-iterative algorithm, and the Landweber iterative algorithm is taken as an example for description in this embodiment. The method comprises the following steps:
in order to approximate the reconstructed image to a real image, an error needs to be calculated. Constructing an error function based on the low-frequency sensitivity matrix and the low-frequency induced voltage matrix; the error function is
Figure BDA0003217611170000103
Wherein e represents the error between the reconstructed image and the real image;
Figure BDA0003217611170000104
representing a desired induced voltage matrix; s. theσRepresenting a low frequency sensitivity matrix; g denotes an imaging area image under a low-frequency excitation signal.
When the error e is equal to 0, the reconstructed image can be regarded as a real image. The problem thus becomes the minimum f (g) of the solution error e two-norm squared:
Figure BDA0003217611170000101
to obtain the minimum value of f (g), the partial derivatives need to be calculated:
Figure BDA0003217611170000102
according to a steepest descent method, based on the error function, calculating an imaging region image under a low-frequency excitation signal corresponding to each iteration by adopting a Landweber iteration algorithm; wherein, the imaging area image under the low-frequency excitation signal corresponding to the (m + 1) th iteration is:
gm+1＝gm-αSσ T(Sσgm-v)；
wherein, gm+1An imaging area image under the low-frequency excitation signal corresponding to the (m + 1) th iteration; gmAn imaging area image under the low-frequency excitation signal corresponding to the mth iteration; α represents an iteration step size; sσ TRepresenting the transpose of the low frequency sensitivity matrix. Where α is set empirically, usually
Figure BDA0003217611170000111
Wherein beta ismaxIs a matrix
Figure BDA0003217611170000112
The iteration step size alpha in this embodiment is
Figure BDA0003217611170000113
If the iteration stopping condition is met, determining an imaging area image under the low-frequency excitation signal corresponding to the (m + 1) th iteration as a final imaging area image under the low-frequency excitation signal, and otherwise, performing the next iteration; the iteration stopping condition is that the difference value between the imaging region image under the low-frequency excitation signal corresponding to the m +1 th iteration and the imaging region image under the low-frequency excitation signal corresponding to the m +1 th iteration is smaller than a set value when the m +1 reaches the set iteration number or the m +1 th iteration is smaller than the set value. In this embodiment, the number of iterations is set to 100.
According to the second induced voltage, reconstructing an imaging region image under a high-frequency excitation signal by using the electromagnetic tomography method, specifically comprising:
(1) and calculating a high-frequency induction voltage matrix according to the second induction voltage and the induction voltage of the detection coil array under the condition of a null field. The calculation method of the high-frequency induced voltage matrix is the same as that of the low-frequency induced voltage matrix, and is not described herein again.
(2) Calculating a second electric field intensity when the high-frequency excitation signal is adopted to excite each coil respectively; the second electric field intensity is the electric field intensity of each pixel point in the imaging area corresponding to the detection coil array during each high-frequency excitation.
(3) And calculating the high-frequency sensitivity distribution of every two coils in the detection coil array according to the second electric field intensity under all high-frequency excitation, wherein the calculation method of the high-frequency sensitivity distribution is the same as that of the low-frequency sensitivity distribution, and is not repeated herein.
(4) The high-frequency sensitivity matrix is determined from all the high-frequency sensitivity profiles. The determination method of the high-frequency sensitivity matrix is the same as that of the low-frequency sensitivity matrix, and is not described herein again.
(5) And based on the high-frequency sensitivity matrix and the high-frequency induction voltage matrix, reconstructing an imaging region image under the high-frequency excitation signal by adopting a reconstruction algorithm with the aim of minimizing the error between a reconstructed image and a real image. The reconstruction method of the image of the imaging region under the high-frequency excitation signal is the same as that of the image of the imaging region under the low-frequency excitation signal, and is not described herein again.
In addition, the coil array is sequentially excited, the induced voltages of the other coils are recorded, the Landweber iterative image reconstruction algorithm is used for imaging the foreign matters by combining the null field induced voltage and the sensitivity matrix, and due to the fact that the sensitivity matrix is a 34 × 34 dot matrix unit, if pixel blurring is directly imaged, in order to obtain clearer images (an imaging area image under a low-frequency excitation signal and an imaging area image under a high-frequency excitation signal), the images are subjected to interpolation to become images of 500 × 500 pixels, as shown in fig. 4, it can be seen from fig. 4 that the reconstructed images after interpolation can well represent the positions, the number and the size of the foreign matters.
Step 103: and respectively analyzing an imaging area image under the low-frequency excitation signal and an imaging area image under the high-frequency excitation signal according to a conductivity set threshold value, determining whether foreign matters exist in a charging area above the detection coil array, and comparing the imaging area image under the low-frequency excitation signal with the imaging area image under the high-frequency excitation signal when the foreign matters exist, so as to determine whether the foreign matters are metal foreign matters or living foreign matters.
In step 103, a threshold is set according to the conductivity, and the method for determining whether there is a foreign object is as follows:
judging whether the conductivity in the imaging area image under the low-frequency excitation signal is larger than a conductivity set threshold value or not, and if so, determining that foreign matters exist in the imaging area image under the low-frequency excitation signal; and judging whether the conductivity in the image of the imaging area under the high-frequency excitation signal is greater than a conductivity set threshold value, and if so, determining that foreign matters exist in the image of the imaging area under the high-frequency excitation signal.
When foreign matter is present, the image alignment method may employ two methods:
the method comprises the following steps: comparing the histograms of the imaging area image under the low-frequency excitation signal and the imaging area image under the high-frequency excitation signal, and judging whether the foreign matter is a metal foreign matter or a living foreign matter, namely qualitatively judging whether the living foreign matter exists according to the comparison result of the histograms.
The second method comprises the following steps: and performing logical exclusive-or operation on pixels of the imaging area image under the low-frequency excitation signal and the imaging area image under the high-frequency excitation signal to judge whether the foreign matter is a metal foreign matter or a living body foreign matter. And performing logical exclusive-or operation on the pixels of the two images to obtain a new image, namely the living foreign body image.
Wherein, after step 103, further comprising:
step 104: determining foreign matter information in an imaging area image under the low-frequency excitation signal and an imaging area image under the high-frequency excitation signal by adopting an image processing algorithm; the foreign matter information includes a position of the foreign matter, a contour of the foreign matter, and a centroid of the foreign matter. And feeding the foreign matter information back to the charging console to remind a parking driver or a charging station worker to clean metal foreign matters, so that the foreign matter detection and foreign matter removal of the wireless charging system are completed.
In practical application, the process of extracting the foreign matter information in the image of the imaging area under the low-frequency excitation signal is as follows:
outline recognition is carried out on an image of an imaging area under a low-frequency excitation signal by using the Otsu method, which is an algorithm for carrying out binarization segmentation on the image, wherein the histogram of the image is divided into two groups of pixels (foreground and background), and the maximum inter-class variance is calculated to determine the optimal threshold value. The calculation steps are as follows: first, all pixels of the image are viewed and the number of occurrences of each pixel value is counted. Secondly, a pixel value is set as a threshold value of the current classification, and all pixels are divided into a foreground group and a background group. Finally, the inter-class variance V is calculated, which is expressed as follows:
V＝ω0(s0)ω1(s0)[u1(s0)-u0(s0)]2
wherein u is0And u1Average gray levels of foreground and background pixels, respectively; omega0And ω1Probability of foreground and background pixels, respectively; s0Is the threshold for the current classification.
When V is the maximum value, the threshold value is the optimum threshold value at this time. Once the optimal threshold is determined, the result is binarized as shown by:
Figure BDA0003217611170000131
wherein z (x, y) is the numerical value of each pixel in the binary image, q (x, y) is the gray value of each pixel in the reconstructed gray image, and s is the optimal threshold. After the OTSU method determines the optimal threshold, the image is automatically segmented, and the contour information of the reconstructed image is obtained. And after the foreign body contour is identified, carrying out centroid calculation, wherein the centroid calculation formula of the image area with the area size of C is as follows:
Figure BDA0003217611170000132
the process of extracting the foreign object information in the image of the imaging area under the high-frequency excitation signal is the same as the process of extracting the foreign object information in the image of the imaging area under the low-frequency excitation signal, and is not described herein again.
The wireless foreign matter detection that charges of electric motor car of this embodiment has following advantage:
1) the method comprises the steps of controlling a detection coil array to measure magnetic field distribution above a transmitting coil of the wireless charging system through a low-frequency excitation signal and a high-frequency excitation signal, performing electromagnetic tomography by using a LandWeber iteration method, realizing imaging above the transmitting coil, and judging whether foreign matters exist above the transmitting coil or not through methods such as histogram comparison or logic exclusive OR operation and the like, wherein the foreign matters are metal foreign matters or living foreign matters. The method can simultaneously detect the metal foreign matters with heating hidden danger and the living foreign matters with life safety hidden danger, thereby ensuring the safety of wireless charging.
2) Simple structure, low cost and convenient installation. The sensor is a low-price coil, and compared with detection means such as radars, machine vision and cameras, the cost is greatly reduced.
3) And the environmental adaptability is strong. The detection is carried out by depending on the magnetic field generated by the coil, the influence of rain and snow weather can be avoided, and particularly compared with an optical induction method, the method can not influence the detection due to dirt and mud at the bottom of the electric vehicle and can not be influenced by light.
4) High precision and high real-time performance. Compared with an infrared camera detection method which can detect the foreign matters only after the temperature of the metal foreign matters rises, the method is high in detection speed and almost real-time.
5) The method is a novel and effective non-contact detection method and has wide application prospect. The non-contact and non-invasive detection method can not cause abrasion to the automobile parts.
Referring to fig. 5, the present invention also provides a wireless charging foreign object detection apparatus for an electric vehicle, comprising: the device comprises an excitation signal generation module, a multi-path switching module, a detection coil array, an induced voltage measurement module and a foreign matter detection module.
The excitation signal generation module is connected with the multi-path switching module; the multi-path switching module is respectively connected with the detection coil array and the induction voltage measuring module; the foreign matter detection module is connected with the induction voltage measurement module; the detection coil array is arranged above the transmitting coil of the wireless charging system, the geometric centers of the detection coil array and the transmitting coil of the wireless charging system are overlapped in the vertical direction, as shown in fig. 6, 2 is the receiving coil of the wireless charging system, and bcois is the magnetic field generated by the transmitting coil 3 of the wireless charging system.
In practical applications, the detection coil array may be a planar detection coil array including 16 coils. The planar detection coil array can be a square array, the specifications of each coil forming the array are completely consistent, and the number of turns, the inner diameter, the outer diameter, the line width and the distance of the coils are designed and adjusted according to the transmission power of the transmitting coil in the wireless charging system of the electric vehicle. The number of coils needs to be adjusted according to the size of the wireless charging system of the electric vehicle and the detection precision of foreign matters during device design. The coil is fixed on the non-metallic material base by the enameled wire coiling, and the diameter of base slightly is lighter than the internal diameter of coil, the installation and the dismantlement of the coil of being convenient for, and the coil passes through the multiple switching module and is connected with induced voltage measurement module.
The excitation signal generation module is used for: a low frequency excitation signal and a high frequency excitation signal are generated.
The multi-path switching module is used for: and controlling the low-frequency excitation signal to respectively excite each coil in the detection coil array, controlling the high-frequency excitation signal to respectively excite each coil, and controlling the switching of the coils in the detection coil array in an excitation mode and an induction mode. The multi-way switching module can be a multi-way selector switch.
The induced voltage measurement module is used for:
measuring a first induced voltage and a second induced voltage; the first induction voltage is obtained by respectively exciting each coil by adopting the low-frequency excitation signal; the second induced voltage is obtained by respectively exciting the coils by adopting a high-frequency excitation signal.
The foreign matter detection module is used for:
and reconstructing an imaging region image under the low-frequency excitation signal by adopting an electromagnetic tomography method according to the first induced voltage.
According to the second induced voltage, reconstructing an imaging region image under a high-frequency excitation signal by adopting the electromagnetic tomography method; the imaging region image is a conductivity distribution image of the imaging region.
And respectively analyzing an imaging area image under the low-frequency excitation signal and an imaging area image under the high-frequency excitation signal according to a conductivity set threshold value, determining whether foreign matters exist in a charging area above the detection coil array, and comparing the imaging area image under the low-frequency excitation signal with the imaging area image under the high-frequency excitation signal when the foreign matters exist, so as to determine whether the foreign matters are metal foreign matters or living foreign matters.
As an optional implementation manner, the wireless charging foreign object detection system for an electric vehicle further includes: a visual display module; the visual display module is connected with the foreign matter detection module; the visual display module is used for: displaying foreign matter information and reminding a user to remove foreign matters according to the foreign matter information; the foreign matter information is extracted from an imaging region image under the low-frequency excitation signal and an imaging region image under the high-frequency excitation signal by the foreign matter detection module by adopting an image processing algorithm; the foreign matter information includes a position of the foreign matter, a contour of the foreign matter, and a centroid of the foreign matter.
As an optional implementation manner, the wireless charging foreign object detection system for an electric vehicle further includes: a power amplifier; the excitation signal generation module is connected with the multi-path switching module through the power amplifier.
In practical applications, taking a planar detection coil array including 16 coils as an example, the implementation process of the wireless charging foreign object detection device for the electric vehicle is as follows:
step 1: the excitation signal generation module generates a low-frequency excitation signal and a high-frequency excitation signal, 16 coils of the planar coil array 4 are sequentially excited by the multi-way selection switch after power amplification, the induction voltage measurement module collects the induction voltages of the other coils of the planar coil array under the low-frequency and high-frequency excitation signals (for example, when the coil 1 is excited, the induction voltage of the coil No. 2-16 is recorded, the coil 1 is in an excitation mode, the coil No. 2-16 is in an induction mode, when the coil 2 is excited, the induction voltages of the coil No. 1 and the coil No. 3-16 are recorded, the coil 2 is in the excitation mode, and the coil No. 1 and the coil No. 3-16 are in the induction mode), and voltage data are transmitted to the foreign matter detection module for subsequent calculation after passing through the instrument amplifier.
Step 2: and (2) calculating the voltage data acquired in the step (1), constructing a mutual inductance matrix, visualizing the foreign matter by using an electromagnetic tomography method according to the induction voltage amplitude information by using a foreign matter detection module, judging the metal foreign matter and the living foreign matter by using methods such as histogram comparison or logic exclusive-or operation and the like, generating position and contour image information of the foreign matter, and transmitting the position and contour image information of the foreign matter to a visual display module to prompt a user to remove the foreign matter by using characters, images and sounds.
The wireless charging foreign matter detection device for the electric vehicle can reconstruct an image above the detection coil array by using an electromagnetic tomography method through a low-frequency excitation signal and a high-frequency excitation signal generated by the excitation signal generation module by using the foreign matter detection module, judge whether the detected foreign matter is a metal foreign matter or a living foreign matter by using methods such as histogram comparison or logic exclusive or operation on two reconstructed images under low-frequency excitation and high-frequency excitation, give information such as the position and the contour of the foreign matter through an image processing algorithm, and display the information on a visual display module of a terminal to clean the foreign matter.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.

Claims (10)

1. A wireless charging foreign matter detection method for an electric vehicle is characterized by comprising the following steps:
acquiring a first induction voltage and a second induction voltage; the first induction voltage is obtained by respectively exciting each coil in the detection coil array by adopting a low-frequency excitation signal; the second induction voltage is obtained by respectively exciting each coil by adopting a high-frequency excitation signal; the detection coil array is arranged above a transmitting coil of the wireless charging system;
according to the first induced voltage, reconstructing an imaging region image under a low-frequency excitation signal by adopting an electromagnetic tomography method, and according to the second induced voltage, reconstructing an imaging region image under a high-frequency excitation signal by adopting the electromagnetic tomography method; the imaging area image is a conductivity distribution image of the imaging area;
and respectively analyzing an imaging area image under the low-frequency excitation signal and an imaging area image under the high-frequency excitation signal according to a conductivity set threshold value, determining whether foreign matters exist in a charging area above the detection coil array, and comparing the imaging area image under the low-frequency excitation signal with the imaging area image under the high-frequency excitation signal when the foreign matters exist, so as to determine whether the foreign matters are metal foreign matters or living foreign matters.
2. The method for detecting the foreign matter in the wireless charging of the electric vehicle as claimed in claim 1, wherein the obtaining of the first induced voltage and the second induced voltage specifically comprises:
sequentially exciting the coils by adopting a low-frequency excitation signal to obtain low-frequency mutual induction voltage of each coil; the first induced voltage comprises low-frequency mutual induction voltages of all coils; the low-frequency mutual induction voltage of the nth coil is the induction voltage of each coil except the nth coil in the detection coil array when the nth coil is excited by a low-frequency excitation signal;
sequentially exciting the coils by adopting a high-frequency excitation signal to obtain high-frequency mutual induction voltage of each coil; the second induced voltage comprises high-frequency mutual induction voltages of all coils; wherein, the high-frequency mutual induction voltage of the nth coil is the induction voltage of each coil except the nth coil in the detection coil array when the nth coil is excited by a high-frequency excitation signal.
3. The method for detecting the foreign matter in the wireless charging of the electric vehicle according to claim 1, wherein reconstructing an imaging region image under a low-frequency excitation signal by using an electromagnetic tomography method according to the first induced voltage specifically comprises:
calculating a low-frequency induction voltage matrix according to the first induction voltage and the induction voltage of the detection coil array under the condition of a null field;
calculating a first electric field intensity when the low-frequency excitation signal is adopted to excite each coil respectively; the first electric field intensity is the electric field intensity of each pixel point in an imaging area corresponding to the detection coil array during each low-frequency excitation;
calculating the low-frequency sensitivity distribution of every two coils in the detection coil array according to the first electric field intensity under all low-frequency excitation;
determining a low-frequency sensitivity matrix from all the low-frequency sensitivity profiles;
and reconstructing an imaging region image under a low-frequency excitation signal by taking the minimum error between a reconstructed image and a real image as a target based on the low-frequency sensitivity matrix and the low-frequency induced voltage matrix.
4. The method for detecting the foreign matter in the wireless charging of the electric vehicle according to claim 1, wherein reconstructing an image of an imaging region under a high-frequency excitation signal by using the electromagnetic tomography method according to the second induced voltage specifically comprises:
calculating a high-frequency induction voltage matrix according to the second induction voltage and the induction voltage of the detection coil array under the condition of a null field;
calculating a second electric field intensity when the high-frequency excitation signal is adopted to excite each coil respectively; the second electric field intensity is the electric field intensity of each pixel point in the imaging area corresponding to the detection coil array during each high-frequency excitation;
calculating the high-frequency sensitivity distribution of every two coils in the detection coil array according to the second electric field intensity under all high-frequency excitation;
determining a high-frequency sensitivity matrix from all the high-frequency sensitivity distributions;
and reconstructing an imaging region image under a high-frequency excitation signal by taking the minimum error between a reconstructed image and a real image as a target based on the high-frequency sensitivity matrix and the high-frequency induction voltage matrix.
5. The method for detecting the foreign object during the wireless charging of the electric vehicle according to claim 1, wherein when a foreign object exists, the method for determining whether the foreign object is a metal foreign object or a living foreign object by comparing the image of the imaging area under the low-frequency excitation signal with the image of the imaging area under the high-frequency excitation signal comprises:
comparing the histograms of the imaging area image under the low-frequency excitation signal and the imaging area image under the high-frequency excitation signal, and judging whether the foreign matter is a metal foreign matter or a living foreign matter;
or, performing logical exclusive-or operation on pixels of the imaging area image under the low-frequency excitation signal and the imaging area image under the high-frequency excitation signal to judge whether the foreign matter is a metal foreign matter or a living body foreign matter.
6. The method for detecting the foreign object during the wireless charging of the electric vehicle according to claim 1, wherein after comparing the image of the imaging area under the low-frequency excitation signal with the image of the imaging area under the high-frequency excitation signal to determine whether the foreign object is a metal foreign object or a living foreign object when the foreign object exists, the method further comprises:
determining foreign matter information in an imaging area image under the low-frequency excitation signal and an imaging area image under the high-frequency excitation signal by adopting an image processing algorithm; the foreign matter information comprises the position of the foreign matter, the outline of the foreign matter and the mass center of the foreign matter;
and removing the foreign matters according to the foreign matter information.
7. The method for detecting the foreign matter in the wireless charging of the electric vehicle as claimed in claim 3, wherein the calculation formula of the low-frequency sensitivity distribution is as follows:
SAB＝EA·EB；
wherein S isABRepresenting the low-frequency sensitivity distribution of the A coil and the B coil; eAThe first electric field intensity is corresponding to the low-frequency excitation of the A-th coil; eBThe first electric field strength is corresponding to the low-frequency excitation of the B-th coil.
8. The method for detecting the foreign matter in the wireless charging of the electric vehicle according to claim 3, wherein the reconstructing an image of an imaging area under a low-frequency excitation signal with a target of minimizing an error between a reconstructed image and a real image based on the low-frequency sensitivity matrix and the low-frequency induced voltage matrix specifically comprises:
constructing an error function based on the low-frequency sensitivity matrix and the low-frequency induced voltage matrix; the error function is
Figure FDA0003579147430000041
Wherein e represents the error between the reconstructed image and the real image;
Figure FDA0003579147430000042
representing a desired induced voltage matrix; v represents a low frequency induced voltage matrix; sσRepresenting a low frequency sensitivity matrix; g represents an imaging area image under a low-frequency excitation signal;
based on the error function, calculating an imaging area image under a low-frequency excitation signal corresponding to each iteration by adopting a Landweber iteration algorithm; wherein, the imaging area image under the low-frequency excitation signal corresponding to the (m + 1) th iteration is:
gm+1＝gm-αSσ T(Sσgm-v)；
wherein, gm+1An imaging area image under the low-frequency excitation signal corresponding to the (m + 1) th iteration; gmAn imaging area image under the low-frequency excitation signal corresponding to the mth iteration; α represents an iteration step size; s. theσ TA transpose representing a low frequency sensitivity matrix;
if the iteration stopping condition is met, determining an imaging area image under the low-frequency excitation signal corresponding to the (m + 1) th iteration as a final imaging area image under the low-frequency excitation signal, and otherwise, performing the next iteration; the iteration stopping condition is that the difference value between the imaging region image under the low-frequency excitation signal corresponding to the m +1 th iteration and the imaging region image under the low-frequency excitation signal corresponding to the m +1 th iteration is smaller than a set value when the m +1 reaches the set iteration number or the m +1 th iteration is smaller than the set value.
9. The utility model provides a foreign matter detection device that charges that electric motor car is wireless which characterized in that includes: the device comprises an excitation signal generating module, a multi-path switching module, a detection coil array, an induced voltage measuring module and a foreign matter detecting module;
the excitation signal generation module is connected with the multi-path switching module; the multi-path switching module is respectively connected with the detection coil array and the induction voltage measuring module; the foreign matter detection module is connected with the induction voltage measurement module; the detection coil array is arranged above a transmitting coil of the wireless charging system;
the excitation signal generation module is used for:
generating a low frequency excitation signal and a high frequency excitation signal;
the multi-path switching module is used for:
controlling the low-frequency excitation signal to respectively excite each coil in the detection coil array, and controlling the high-frequency excitation signal to respectively excite each coil;
controlling the switching of coils in the detection coil array in an excitation mode and an induction mode;
the induced voltage measurement module is used for:
measuring a first induced voltage and a second induced voltage; the first induction voltage is obtained by respectively exciting each coil by adopting the low-frequency excitation signal; the second induction voltage is obtained by respectively exciting each coil by adopting a high-frequency excitation signal;
the foreign matter detection module is used for:
according to the first induced voltage, reconstructing an imaging region image under a low-frequency excitation signal by adopting an electromagnetic tomography method;
according to the second induced voltage, reconstructing an imaging region image under a high-frequency excitation signal by adopting the electromagnetic tomography method; the imaging area image is a conductivity distribution image of the imaging area;
and respectively analyzing an imaging area image under the low-frequency excitation signal and an imaging area image under the high-frequency excitation signal according to a conductivity set threshold value, determining whether foreign matters exist in a charging area above the detection coil array, and comparing the imaging area image under the low-frequency excitation signal with the imaging area image under the high-frequency excitation signal when the foreign matters exist, so as to determine whether the foreign matters are metal foreign matters or living foreign matters.
10. The wireless charging foreign matter detection device of an electric vehicle according to claim 9, further comprising: a visual display module;
the visual display module is connected with the foreign matter detection module;
the visual display module is used for:
displaying foreign matter information and reminding a user to remove foreign matters according to the foreign matter information; the foreign matter information is extracted from an imaging region image under the low-frequency excitation signal and an imaging region image under the high-frequency excitation signal by the foreign matter detection module by adopting an image processing algorithm; the foreign matter information includes a position of the foreign matter, a contour of the foreign matter, and a centroid of the foreign matter.
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Family Cites Families (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5373443A (en) * 1993-10-06 1994-12-13 The Regents, University Of California Method for imaging with low frequency electromagnetic fields
CN1166942C (en) * 2002-04-26 2004-09-15 天津大学 Electromagnetic chromatographic imaged phase-based feedback search signal demodulating equipment and its method
EP1639389A2 (en) * 2003-06-11 2006-03-29 Konsulteurope Limited Limited Liability Joint Stoc Security scanners with capacitance and magnetic sensor arrays
US8552722B2 (en) * 2007-01-15 2013-10-08 Rapiscan Systems, Inc. Detector systems
US9724010B2 (en) * 2010-07-08 2017-08-08 Emtensor Gmbh Systems and methods of 4D electromagnetic tomographic (EMT) differential (dynamic) fused imaging
US9729003B1 (en) * 2016-12-21 2017-08-08 C-Corp International Co., Limited Wireless charging device and method thereof
WO2018197274A1 (en) * 2017-04-28 2018-11-01 Ge Healthcare Bio-Sciences Ab System and method for enabling a single use wireless sensor by optimizing electrical power
CN109038850B (en) * 2018-06-25 2020-07-24 华为技术有限公司 Device, equipment and method for detecting metal foreign matters in wireless charging system
CN111435126A (en) * 2019-12-17 2020-07-21 华北电力大学 Multi-parameter electromagnetic tomography device and method based on image fusion technology

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