CN117849511A - Wireless charging data analysis-based charging abnormality diagnosis method and system - Google Patents
Wireless charging data analysis-based charging abnormality diagnosis method and system Download PDFInfo
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Abstract
The invention discloses a method and a system for diagnosing charging abnormality based on wireless charging data analysis, which relate to the technical field of charging and comprise the following steps: acquiring a standard charging speed of wireless charging equipment; calculating to obtain the real-time charging speed of the object to be charged, and judging whether the real-time charging speed is equal to the standard charging speed; when the charging state is abnormal, diagnosing the cause of the abnormality; acquiring display numbers of the charge and discharge standard model; and when the wireless charging equipment fails, diagnosing the failure reason. By setting the data calculation module, the model establishment module and the abnormality judgment module, the abnormality reasons of the wireless charging are distinguished, whether the abnormality reasons are from the wireless charging or from the object to be charged can be judged, when the abnormality reasons are from the wireless charging, the specific reasons causing the abnormality can be determined according to the step detection mode, and then the wireless charging device can be adjusted in a targeted manner according to the specific reasons.
Description
Technical Field
The invention relates to the technical field of charging, in particular to a method and a system for diagnosing charging abnormality based on wireless charging data analysis.
Background
In the prior art, the charging abnormality detection process for wireless charging generally detects voltage and current, detects temperature inside the wireless charging, and analyzes voltage output or current output waveforms of the wireless charging to obtain corresponding charging abnormality information.
Disclosure of Invention
In order to solve the technical problems, the technical scheme provides a charging abnormality diagnosis method and a system based on wireless charging data analysis, which solve the problems that the detection method provided in the background art can judge whether the charging is abnormal, but can not determine whether the reason of the abnormality is from the wireless charging itself or an object to be charged, and can not determine whether the reason of the abnormality is from a power transmission coil or an input current.
In order to achieve the above purpose, the invention adopts the following technical scheme:
a method of diagnosing a charging anomaly based on wireless charging data analysis, comprising:
acquiring a standard charging speed of wireless charging equipment;
acquiring initial electric quantity of an object to be charged, acquiring real-time electric quantity of the object to be charged, acquiring real-time accumulated charging time of the object to be charged, calculating to obtain real-time charging speed of the object to be charged, judging whether the real-time charging speed is equal to a standard charging speed, if so, judging that the charging state is normal, and if not, judging that the charging state is abnormal;
when the charging state is normal, no treatment is carried out;
when the charging state is abnormal, diagnosing the cause of the abnormality;
setting a charge-discharge standard model at a preset distance from a power transmission coil in wireless charging equipment, wherein the charge-discharge standard model receives magnetic induction wires of the power transmission coil, and acquires display numbers of the charge-discharge standard model;
if the display number is a preset value, judging that the abnormality is caused by the fault of the object to be charged, and if not, judging that the abnormality is caused by the fault of the wireless charging equipment;
when the object to be charged fails, the object to be charged is taken away, and charging is stopped;
when the wireless charging equipment fails, diagnosing the failure cause;
acquiring input current entering a power transmission coil, judging whether the input current is equal to a preset current, and if not, judging that the fault cause is the intensity of the input current;
if yes, detecting the frequency of the input current, judging whether the frequency of the input current is equal to a preset frequency, and if not, judging that the fault reason is the frequency of the input current;
if so, acquiring the average temperature of the wireless charging equipment during charging, judging whether the average temperature is equal to the preset temperature, and if not, judging that the failure cause is resistance change of a power transmission coil of the wireless charging equipment due to aging;
if yes, acquiring magnetic induction intensity of the wireless charging equipment during charging, judging whether the magnetic induction intensity is equal to preset intensity, and if yes, reducing the overall performance of the wireless charging equipment due to the failure;
if not, the failure is due to deformation of the power transmission coil of the wireless charging device caused by heating.
Preferably, the calculating the real-time charging speed of the object to be charged includes the following steps:
the real-time electric quantity of the object to be charged and the initial electric quantity of the object to be charged are obtained;
and dividing the real-time charging electric quantity by the real-time accumulated charging time to obtain the real-time charging speed.
Preferably, the charge-discharge standard model is as follows:
a miniature power receiving coil is arranged in the charge-discharge standard model;
the miniature power receiving coil receives magnetic induction wires generated by the power transmitting coil, and induction current is generated in the miniature power receiving coil;
the miniature power receiving coil is connected with the ammeter in series, and the miniature power receiving coil is connected with the discharging equipment in series;
the discharging equipment discharges at a preset speed;
the ammeter displays the current in the miniature power receiving coil and is used as a display number of a charge-discharge standard model.
Preferably, the step of obtaining the average temperature of the wireless charging device when charging includes the following steps:
establishing a decay model of temperature with respect to distance;
setting a positioning circle at the center of a power transmission coil of the wireless charging equipment, wherein the radius of the positioning circle is a preset radius, and the center of the positioning circle coincides with the center of the power transmission coil;
equally dividing the positioning circles to obtain a preset number of identification points;
setting a temperature monitoring device at each identification point, and acquiring real-time temperature at the identification point by the temperature monitoring device;
according to a decay model of the temperature with respect to the distance, calculating to obtain a predicted temperature of each point in the power transmission coil coverage range of the wireless charging equipment;
integrating the predicted temperature in the coverage area of the power transmission coil to obtain a temperature integral value;
dividing the temperature integral value by the area of the coverage area of the power transmission coil to obtain the average temperature of the wireless charging equipment during charging.
Preferably, the establishing a decay model of temperature with respect to distance comprises the steps of:
uniformly dividing the coverage range of the power transmission coil into at least one positioning block, and selecting a positioning point at the center of the positioning block;
measuring the temperature at the positioning point to obtain at least one positioning temperature;
taking the distance from the positioning point to the center of the power transmission coil as a positioning distance, and corresponding the positioning temperature to the positioning distance;
in a coordinate system, making an image with a positioning distance as an abscissa and a positioning temperature as an ordinate;
and selecting a matched function model according to the image, wherein the temperature fitting model is used as a temperature fitting model, and the temperature fitting model comprises coefficient unknowns.
Preferably, the calculating the predicted temperature of each point in the coverage area of the power transmission coil of the wireless charging device includes the following steps:
judging whether the temperature fitting model is a linear function or not;
if yes, substituting the real-time temperature of the identification point and the distance from the center of the power transmission coil into a temperature fitting model, and obtaining a coefficient unknown number by using the Kramer method to obtain a temperature fitting function;
if not, substituting the real-time temperature of the identification point and the distance from the center of the power transmission coil into a temperature fitting model, and obtaining an approximate value of the coefficient unknown number by using a numerical method to obtain a temperature fitting function;
and obtaining the predicted temperature of each point in the power transmission coil coverage range according to the distance from each point in the power transmission coil coverage range to the center of the power transmission coil by using a temperature fitting function.
Preferably, the step of obtaining the magnetic induction intensity when the wireless charging device is charged includes the following steps:
establishing a decay model of the magnetic field with respect to the distance;
setting a targeting circle at the center of a power transmission coil of the wireless charging equipment, wherein the radius of the targeting circle is a preset radius, and the center of the targeting circle coincides with the center of the power transmission coil;
equally dividing the target circles to obtain a preset number of sampling points;
setting a magnetic field monitoring device at each sampling point, wherein the magnetic field monitoring device acquires a real-time magnetic field at the sampling point;
according to a decay model of the magnetic field with respect to the distance, calculating a predicted magnetic field of each point within the coverage range of a power transmission coil of the wireless charging equipment;
integrating the predicted magnetic field in the coverage area of the power transmission coil to obtain a magnetic field integral value;
dividing the magnetic field integral value by the coverage area of the power transmission coil to obtain the magnetic induction intensity when the wireless charging equipment is charged.
Preferably, the step of establishing a decay model of the magnetic field with respect to distance comprises the steps of:
uniformly dividing the coverage range of the power transmission coil into at least one positioning block, and selecting a positioning point at the center of the positioning block;
measuring the magnetic field at the positioning point to obtain at least one positioning magnetic field;
taking the distance from the positioning point to the center of the power transmission coil as a positioning distance, and corresponding the positioning magnetic field to the positioning distance;
in a coordinate system, making an image taking a positioning distance as an abscissa and a positioning magnetic field as an ordinate;
and selecting a matched function model according to the image as a magnetic field fitting model, wherein the magnetic field fitting model comprises unknown coefficients.
Preferably, the calculating the predicted magnetic field of each point in the coverage area of the power transmission coil of the wireless charging device includes the following steps:
judging whether the magnetic field fitting model is a linear function or not;
if yes, substituting the real-time magnetic field of the sampling point and the distance from the center of the power transmission coil into a magnetic field fitting model, and obtaining a coefficient unknown number by using the Kramer method to obtain a magnetic field fitting function;
if not, substituting the real-time magnetic field of the sampling point and the distance from the center of the power transmission coil into a magnetic field fitting model, and obtaining an approximate value of the coefficient unknowns by using a numerical method to obtain a magnetic field fitting function;
and obtaining a predicted magnetic field of each point in the power transmission coil coverage range according to the distance from each point in the power transmission coil coverage range to the center of the power transmission coil by using a magnetic field fitting function.
A charge anomaly diagnosis system based on wireless charge data analysis is used for realizing the charge anomaly diagnosis method based on wireless charge data analysis, and comprises the following steps:
the data acquisition module acquires the standard charging speed of the wireless charging equipment, acquires the initial electric quantity of the object to be charged, acquires the real-time accumulated charging time of the object to be charged, acquires the display number of the charging and discharging standard model and acquires the input current entering the power transmission coil;
the data calculation module is used for calculating the real-time charging speed of the object to be charged, acquiring the average temperature of the wireless charging equipment during charging and acquiring the magnetic induction intensity of the wireless charging equipment during charging;
the model building module is used for building a decay model of temperature with respect to distance and building a decay model of magnetic field with respect to distance;
and the abnormality judgment module is used for diagnosing the abnormality reasons and diagnosing the fault reasons.
Compared with the prior art, the invention has the beneficial effects that:
by setting the data calculation module, the model establishment module and the abnormality judgment module, the abnormality reasons of the wireless charging are distinguished, whether the abnormality reasons are from the wireless charging or from the object to be charged can be judged, when the abnormality reasons are from the wireless charging, the specific reasons causing the abnormality can be determined according to the step detection mode, and then the wireless charging device can be adjusted in a targeted manner according to the specific reasons.
Drawings
FIG. 1 is a flow chart of a method for diagnosing charging anomalies based on wireless charging data analysis according to the present invention;
FIG. 2 is a schematic diagram of a real-time charging speed flow for calculating an object to be charged according to the present invention;
FIG. 3 is a flow chart of a charge-discharge standard model according to the present invention;
fig. 4 is a schematic diagram of an average temperature flow chart of the wireless charging device when charging;
FIG. 5 is a schematic flow chart of a decay model of the invention with respect to distance for establishing temperature;
FIG. 6 is a schematic diagram of a predicted temperature flow for each point within the power coil coverage area of a wireless charging device calculated according to the present invention;
fig. 7 is a schematic diagram of a flow for obtaining magnetic induction intensity when a wireless charging device is charged in the present invention;
FIG. 8 is a schematic flow chart of a decay model of the magnetic field with respect to distance;
fig. 9 is a schematic diagram of a predicted magnetic field flow for each point in the coverage area of a power transmission coil of a wireless charging device calculated according to the present invention.
Detailed Description
The following description is presented to enable one of ordinary skill in the art to make and use the invention. The preferred embodiments in the following description are by way of example only and other obvious variations will occur to those skilled in the art.
Referring to fig. 1, a method for diagnosing a charging abnormality based on wireless charging data analysis includes:
acquiring a standard charging speed of wireless charging equipment;
acquiring initial electric quantity of an object to be charged, acquiring real-time electric quantity of the object to be charged, acquiring real-time accumulated charging time of the object to be charged, calculating to obtain real-time charging speed of the object to be charged, judging whether the real-time charging speed is equal to a standard charging speed, if so, judging that the charging state is normal, and if not, judging that the charging state is abnormal;
when the charging state is normal, no treatment is carried out;
when the charging state is abnormal, diagnosing the cause of the abnormality;
setting a charge-discharge standard model at a preset distance from a power transmission coil in wireless charging equipment, wherein the charge-discharge standard model receives magnetic induction wires of the power transmission coil, and acquires display numbers of the charge-discharge standard model;
if the display number is a preset value, judging that the abnormality is caused by the fault of the object to be charged, and if not, judging that the abnormality is caused by the fault of the wireless charging equipment;
when the object to be charged fails, the object to be charged is taken away, and charging is stopped;
when the wireless charging equipment fails, diagnosing the failure cause;
acquiring input current entering a power transmission coil, judging whether the input current is equal to a preset current, and if not, judging that the fault cause is the intensity of the input current;
if yes, detecting the frequency of the input current, judging whether the frequency of the input current is equal to a preset frequency, and if not, judging that the fault reason is the frequency of the input current;
if so, acquiring the average temperature of the wireless charging equipment during charging, judging whether the average temperature is equal to the preset temperature, and if not, judging that the failure cause is resistance change of a power transmission coil of the wireless charging equipment due to aging;
if yes, acquiring magnetic induction intensity of the wireless charging equipment during charging, judging whether the magnetic induction intensity is equal to preset intensity, and if yes, reducing the overall performance of the wireless charging equipment due to the failure;
the overall performance of the wireless charging equipment is reduced, and the wireless charging equipment needs to be replaced integrally;
if not, the failure cause is deformation of the power transmission coil of the wireless charging equipment due to heating;
in the detection process, when a corresponding abnormality cause is detected, the cause needs to be repaired, after the abnormality caused by the cause is relieved, the next step can be performed, otherwise, the existing abnormality cause can be detected in the following subsequent detection results.
Referring to fig. 2, calculating the real-time charging speed of the object to be charged includes the steps of:
the real-time electric quantity of the object to be charged and the initial electric quantity of the object to be charged are obtained;
dividing the real-time charging electric quantity by the real-time accumulated charging time to obtain a real-time charging speed;
when the charging is abnormal, the real-time charging speed is changed inevitably, the abnormal performance is realized too fast or too slow, the charging performance is reduced too fast, the charging temperature is possibly too high, the charging is continuously carried out, and the loss of the wireless charging device is higher than that of the normal situation, so that whether the charging is abnormal or not can be reversely obtained according to the abnormal condition of the real-time charging speed.
Referring to fig. 3, the charge-discharge standard model is as follows:
a miniature power receiving coil is arranged in the charge-discharge standard model;
the miniature power receiving coil receives magnetic induction wires generated by the power transmitting coil, and induction current is generated in the miniature power receiving coil;
the miniature power receiving coil is connected with the ammeter in series, and the miniature power receiving coil is connected with the discharging equipment in series;
the discharging equipment discharges at a preset speed;
the ammeter displays the current in the miniature power receiving coil and is used as a display number of a charge-discharge standard model;
the charge-discharge standard model distinguishes whether the abnormality is from wireless charge or an object to be charged, the charge-discharge standard model uses a miniature power receiving coil, the overall current loss is extremely small, the charge efficiency is not affected, and when the abnormality does not occur in the wireless charge, the display number of the charge-discharge standard model is a fixed value, so that the abnormality is judged from the wireless charge or the object to be charged according to the display number of the charge-discharge standard model, a discharge device is arranged in the charge-discharge standard model, and continuous charge is prevented, so that the charge-discharge standard model is overloaded in electric quantity.
Referring to fig. 4, obtaining the average temperature when the wireless charging device is charged includes the steps of:
establishing a decay model of temperature with respect to distance;
setting a positioning circle at the center of a power transmission coil of the wireless charging equipment, wherein the radius of the positioning circle is a preset radius, and the center of the positioning circle coincides with the center of the power transmission coil;
equally dividing the positioning circles to obtain a preset number of identification points;
setting a temperature monitoring device at each identification point, and acquiring real-time temperature at the identification point by the temperature monitoring device;
according to a decay model of the temperature with respect to the distance, calculating to obtain a predicted temperature of each point in the power transmission coil coverage range of the wireless charging equipment;
integrating the predicted temperature in the coverage area of the power transmission coil to obtain a temperature integral value;
dividing the temperature integral value by the area of the coverage area of the power transmission coil to obtain the average temperature of the wireless charging equipment during charging;
the magnetic field intensity of different positions of the power transmission coil is different, so that the temperature is different, a certain point is singly used as a data acquisition point, the fault tolerance is low, and measurement errors are easy to occur, so that the average temperature of the wireless charging equipment during charging is required to be acquired for judgment, the average temperature of the wireless charging equipment during charging corresponds to heat generated by the wireless charging equipment, the heat is generated by the current and the resistance of the power transmission coil together, and when the current is normal, the abnormal cause is necessarily that the resistance of the power transmission coil is changed, and the power transmission coil is aged after being continuously used.
Referring to fig. 5, the modeling of decay of temperature with respect to distance includes the steps of:
uniformly dividing the coverage range of the power transmission coil into at least one positioning block, and selecting a positioning point at the center of the positioning block;
measuring the temperature at the positioning point to obtain at least one positioning temperature;
taking the distance from the positioning point to the center of the power transmission coil as a positioning distance, and corresponding the positioning temperature to the positioning distance;
in a coordinate system, making an image with a positioning distance as an abscissa and a positioning temperature as an ordinate;
selecting a matched function model according to the image as a temperature fitting model, wherein the temperature fitting model comprises unknown coefficients;
the matched function model refers to that the image coincidence degree of the temperature fitting function obtained by fitting by using the function model and the positioning temperature and the positioning distance is high, but in actual measurement, the temperature can be different from the positioning temperature due to the change of current or resistance, so that the coefficient in the temperature fitting model is taken as an unknown quantity, and the corresponding temperature fitting function is obtained by re-solving according to actual data.
Referring to fig. 6, calculating a predicted temperature for each point within a power transmission coil coverage area of a wireless charging device includes the steps of:
judging whether the temperature fitting model is a linear function or not;
if yes, substituting the real-time temperature of the identification point and the distance from the center of the power transmission coil into a temperature fitting model, and obtaining a coefficient unknown number by using the Kramer method to obtain a temperature fitting function;
the simultaneous equations are solved to obtain the unknown number, the number of the identification points is the preset number, and the preset number is set to be larger than the number of the coefficient unknown number, so that enough data of the identification points can be obtained to solve the temperature fitting model;
if not, substituting the real-time temperature of the identification point and the distance from the center of the power transmission coil into a temperature fitting model, and obtaining an approximate value of the coefficient unknown number by using a numerical method to obtain a temperature fitting function;
when the temperature fitting model is nonlinear, the function may be complex, and only an approximate result can be solved for substitution;
and obtaining the predicted temperature of each point in the power transmission coil coverage range according to the distance from each point in the power transmission coil coverage range to the center of the power transmission coil by using a temperature fitting function.
Referring to fig. 7, the method for obtaining the magnetic induction intensity when the wireless charging device is charged includes the following steps:
establishing a decay model of the magnetic field with respect to the distance;
setting a targeting circle at the center of a power transmission coil of the wireless charging equipment, wherein the radius of the targeting circle is a preset radius, and the center of the targeting circle coincides with the center of the power transmission coil;
equally dividing the target circles to obtain a preset number of sampling points;
setting a magnetic field monitoring device at each sampling point, wherein the magnetic field monitoring device acquires a real-time magnetic field at the sampling point;
according to a decay model of the magnetic field with respect to the distance, calculating a predicted magnetic field of each point within the coverage range of a power transmission coil of the wireless charging equipment;
integrating the predicted magnetic field in the coverage area of the power transmission coil to obtain a magnetic field integral value;
dividing the magnetic field integral value by the coverage area of the power transmission coil to obtain the magnetic induction intensity when the wireless charging equipment is charged.
Referring to FIG. 8, the creation of a decay model of a magnetic field with respect to distance includes the steps of:
uniformly dividing the coverage range of the power transmission coil into at least one positioning block, and selecting a positioning point at the center of the positioning block;
measuring the magnetic field at the positioning point to obtain at least one positioning magnetic field;
taking the distance from the positioning point to the center of the power transmission coil as a positioning distance, and corresponding the positioning magnetic field to the positioning distance;
in a coordinate system, making an image taking a positioning distance as an abscissa and a positioning magnetic field as an ordinate;
and selecting a matched function model according to the image as a magnetic field fitting model, wherein the magnetic field fitting model comprises unknown coefficients.
Referring to fig. 9, calculating a predicted magnetic field for each point within the power transmission coil coverage area of the wireless charging device includes the steps of:
judging whether the magnetic field fitting model is a linear function or not;
if yes, substituting the real-time magnetic field of the sampling point and the distance from the center of the power transmission coil into a magnetic field fitting model, and obtaining a coefficient unknown number by using the Kramer method to obtain a magnetic field fitting function;
if not, substituting the real-time magnetic field of the sampling point and the distance from the center of the power transmission coil into a magnetic field fitting model, and obtaining an approximate value of the coefficient unknowns by using a numerical method to obtain a magnetic field fitting function;
and obtaining a predicted magnetic field of each point in the power transmission coil coverage range according to the distance from each point in the power transmission coil coverage range to the center of the power transmission coil by using a magnetic field fitting function.
A charge anomaly diagnosis system based on wireless charge data analysis is used for realizing the charge anomaly diagnosis method based on wireless charge data analysis, and comprises the following steps:
the data acquisition module acquires the standard charging speed of the wireless charging equipment, acquires the initial electric quantity of the object to be charged, acquires the real-time accumulated charging time of the object to be charged, acquires the display number of the charging and discharging standard model and acquires the input current entering the power transmission coil;
the data calculation module is used for calculating the real-time charging speed of the object to be charged, acquiring the average temperature of the wireless charging equipment during charging and acquiring the magnetic induction intensity of the wireless charging equipment during charging;
the model building module is used for building a decay model of temperature with respect to distance and building a decay model of magnetic field with respect to distance;
and the abnormality judgment module is used for diagnosing the abnormality reasons and diagnosing the fault reasons.
The working process of the charging abnormality diagnosis system based on wireless charging data analysis is as follows:
step one: the data acquisition module acquires the standard charging speed of the wireless charging equipment;
step two: acquiring initial electric quantity of an object to be charged, acquiring real-time electric quantity of the object to be charged, acquiring real-time accumulated charging time of the object to be charged, calculating to obtain real-time charging speed of the object to be charged by a data calculation module, judging whether the real-time charging speed is equal to a standard charging speed by an abnormality judgment module, if so, judging that the charging state is normal, and if not, judging that the charging state is abnormal;
step three: when the charging state is normal, no treatment is carried out;
when the charging state is abnormal, diagnosing the cause of the abnormality;
step four: setting a charge-discharge standard model at a preset distance from a power transmission coil in wireless charging equipment, wherein the charge-discharge standard model receives magnetic induction lines of the power transmission coil, and the data acquisition module acquires display numbers of the charge-discharge standard model;
if the display number is a preset value, the abnormality judgment module judges that the abnormality is caused by the fault of the object to be charged, and if not, the abnormality judgment module judges that the abnormality is caused by the fault of the wireless charging equipment;
when the object to be charged fails, the object to be charged is taken away, and charging is stopped;
step five: when the wireless charging equipment fails, the abnormality judgment module diagnoses the failure reason;
the data acquisition module acquires input current entering the power transmission coil, the abnormality judgment module judges whether the input current is equal to a preset current, and if not, the fault reason is the intensity of the input current;
if yes, the data acquisition module detects the frequency of the input current, the abnormality judgment module judges whether the frequency of the input current is equal to a preset frequency, and if not, the fault reason is the frequency of the input current;
if so, the data calculation module and the model building module coordinate to obtain the average temperature of the wireless charging equipment during charging, the abnormality judgment module judges whether the average temperature is equal to the preset temperature, and if not, the failure cause is resistance change of the power transmission coil of the wireless charging equipment due to aging;
if yes, the data calculation module and the model establishment module coordinate to obtain the magnetic induction intensity of the wireless charging equipment during charging, and the abnormality judgment module judges whether the magnetic induction intensity is equal to the preset intensity, if yes, the failure is caused by the reduction of the overall performance of the wireless charging equipment;
if not, the failure is due to deformation of the power transmission coil of the wireless charging device caused by heating.
Still further, the present disclosure provides a storage medium having a computer readable program stored thereon, the computer readable program when invoked performing the above-described method for diagnosing a charging abnormality based on wireless charging data analysis.
It is understood that the storage medium may be a magnetic medium, e.g., floppy disk, hard disk, magnetic tape; optical media such as DVD; or a semiconductor medium such as a solid state disk SolidStateDisk, SSD, etc.
In summary, the invention has the advantages that: by setting the data calculation module, the model establishment module and the abnormality judgment module, the abnormality reasons of the wireless charging are distinguished, whether the abnormality reasons are from the wireless charging or from the object to be charged can be judged, when the abnormality reasons are from the wireless charging, the specific reasons causing the abnormality can be determined according to the step detection mode, and then the wireless charging device can be adjusted in a targeted manner according to the specific reasons.
The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that the above embodiments and descriptions are merely illustrative of the principles of the present invention, and various changes and modifications may be made therein without departing from the spirit and scope of the invention, which is defined by the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (10)
1. The method for diagnosing the abnormal charging based on the wireless charging data analysis is characterized by comprising the following steps of:
acquiring a standard charging speed of wireless charging equipment;
acquiring initial electric quantity of an object to be charged, acquiring real-time electric quantity of the object to be charged, acquiring real-time accumulated charging time of the object to be charged, calculating to obtain real-time charging speed of the object to be charged, judging whether the real-time charging speed is equal to a standard charging speed, if so, judging that the charging state is normal, and if not, judging that the charging state is abnormal;
when the charging state is normal, no treatment is carried out;
when the charging state is abnormal, diagnosing the cause of the abnormality;
setting a charge-discharge standard model at a preset distance from a power transmission coil in wireless charging equipment, wherein the charge-discharge standard model receives magnetic induction wires of the power transmission coil, and acquires display numbers of the charge-discharge standard model;
if the display number is a preset value, judging that the abnormality is caused by the fault of the object to be charged, and if not, judging that the abnormality is caused by the fault of the wireless charging equipment;
when the object to be charged fails, the object to be charged is taken away, and charging is stopped;
when the wireless charging equipment fails, diagnosing the failure cause;
acquiring input current entering a power transmission coil, judging whether the input current is equal to a preset current, and if not, judging that the fault cause is the intensity of the input current;
if yes, detecting the frequency of the input current, judging whether the frequency of the input current is equal to a preset frequency, and if not, judging that the fault reason is the frequency of the input current;
if so, acquiring the average temperature of the wireless charging equipment during charging, judging whether the average temperature is equal to the preset temperature, and if not, judging that the failure cause is resistance change of a power transmission coil of the wireless charging equipment due to aging;
if yes, acquiring magnetic induction intensity of the wireless charging equipment during charging, judging whether the magnetic induction intensity is equal to preset intensity, and if yes, reducing the overall performance of the wireless charging equipment due to the failure;
if not, the failure is due to deformation of the power transmission coil of the wireless charging device caused by heating.
2. The method for diagnosing a charging abnormality based on wireless charging data analysis according to claim 1, wherein said calculating a real-time charging speed of an object to be charged comprises the steps of:
the real-time electric quantity of the object to be charged and the initial electric quantity of the object to be charged are obtained;
and dividing the real-time charging electric quantity by the real-time accumulated charging time to obtain the real-time charging speed.
3. The method for diagnosing a charging abnormality based on wireless charging data analysis according to claim 2, wherein the charging and discharging standard model is as follows:
a miniature power receiving coil is arranged in the charge-discharge standard model;
the miniature power receiving coil receives magnetic induction wires generated by the power transmitting coil, and induction current is generated in the miniature power receiving coil;
the miniature power receiving coil is connected with the ammeter in series, and the miniature power receiving coil is connected with the discharging equipment in series;
the discharging equipment discharges at a preset speed;
the ammeter displays the current in the miniature power receiving coil and is used as a display number of a charge-discharge standard model.
4. A method for diagnosing a charging abnormality based on analysis of wireless charging data as claimed in claim 3, wherein said obtaining an average temperature at the time of charging of the wireless charging device comprises the steps of:
establishing a decay model of temperature with respect to distance;
setting a positioning circle at the center of a power transmission coil of the wireless charging equipment, wherein the radius of the positioning circle is a preset radius, and the center of the positioning circle coincides with the center of the power transmission coil;
equally dividing the positioning circles to obtain a preset number of identification points;
setting a temperature monitoring device at each identification point, and acquiring real-time temperature at the identification point by the temperature monitoring device;
according to a decay model of the temperature with respect to the distance, calculating to obtain a predicted temperature of each point in the power transmission coil coverage range of the wireless charging equipment;
integrating the predicted temperature in the coverage area of the power transmission coil to obtain a temperature integral value;
dividing the temperature integral value by the area of the coverage area of the power transmission coil to obtain the average temperature of the wireless charging equipment during charging.
5. The method for diagnosing a charging abnormality based on wireless charging data analysis according to claim 4, wherein said modeling of decay of temperature with respect to distance comprises the steps of:
uniformly dividing the coverage range of the power transmission coil into at least one positioning block, and selecting a positioning point at the center of the positioning block;
measuring the temperature at the positioning point to obtain at least one positioning temperature;
taking the distance from the positioning point to the center of the power transmission coil as a positioning distance, and corresponding the positioning temperature to the positioning distance;
in a coordinate system, making an image with a positioning distance as an abscissa and a positioning temperature as an ordinate;
and selecting a matched function model according to the image, wherein the temperature fitting model is used as a temperature fitting model, and the temperature fitting model comprises coefficient unknowns.
6. The method for diagnosing a charging abnormality based on analysis of wireless charging data according to claim 5, wherein said calculating a predicted temperature of each point within a power transmitting coil coverage area of the wireless charging device includes the steps of:
judging whether the temperature fitting model is a linear function or not;
if yes, substituting the real-time temperature of the identification point and the distance from the center of the power transmission coil into a temperature fitting model, and obtaining a coefficient unknown number by using the Kramer method to obtain a temperature fitting function;
if not, substituting the real-time temperature of the identification point and the distance from the center of the power transmission coil into a temperature fitting model, and obtaining an approximate value of the coefficient unknown number by using a numerical method to obtain a temperature fitting function;
and obtaining the predicted temperature of each point in the power transmission coil coverage range according to the distance from each point in the power transmission coil coverage range to the center of the power transmission coil by using a temperature fitting function.
7. The method for diagnosing a charging abnormality based on wireless charging data analysis according to claim 6, wherein the step of obtaining the magnetic induction intensity when the wireless charging device is charged comprises the steps of:
establishing a decay model of the magnetic field with respect to the distance;
setting a targeting circle at the center of a power transmission coil of the wireless charging equipment, wherein the radius of the targeting circle is a preset radius, and the center of the targeting circle coincides with the center of the power transmission coil;
equally dividing the target circles to obtain a preset number of sampling points;
setting a magnetic field monitoring device at each sampling point, wherein the magnetic field monitoring device acquires a real-time magnetic field at the sampling point;
according to a decay model of the magnetic field with respect to the distance, calculating a predicted magnetic field of each point within the coverage range of a power transmission coil of the wireless charging equipment;
integrating the predicted magnetic field in the coverage area of the power transmission coil to obtain a magnetic field integral value;
dividing the magnetic field integral value by the coverage area of the power transmission coil to obtain the magnetic induction intensity when the wireless charging equipment is charged.
8. The method for diagnosing a charging abnormality based on wireless charging data analysis according to claim 7, wherein said establishing a decay model of the magnetic field with respect to distance comprises the steps of:
uniformly dividing the coverage range of the power transmission coil into at least one positioning block, and selecting a positioning point at the center of the positioning block;
measuring the magnetic field at the positioning point to obtain at least one positioning magnetic field;
taking the distance from the positioning point to the center of the power transmission coil as a positioning distance, and corresponding the positioning magnetic field to the positioning distance;
in a coordinate system, making an image taking a positioning distance as an abscissa and a positioning magnetic field as an ordinate;
and selecting a matched function model according to the image as a magnetic field fitting model, wherein the magnetic field fitting model comprises unknown coefficients.
9. The method for diagnosing a charging abnormality based on analysis of wireless charging data according to claim 8, wherein said calculating a predicted magnetic field for each point within a power transmission coil coverage area of the wireless charging device includes the steps of:
judging whether the magnetic field fitting model is a linear function or not;
if yes, substituting the real-time magnetic field of the sampling point and the distance from the center of the power transmission coil into a magnetic field fitting model, and obtaining a coefficient unknown number by using the Kramer method to obtain a magnetic field fitting function;
if not, substituting the real-time magnetic field of the sampling point and the distance from the center of the power transmission coil into a magnetic field fitting model, and obtaining an approximate value of the coefficient unknowns by using a numerical method to obtain a magnetic field fitting function;
and obtaining a predicted magnetic field of each point in the power transmission coil coverage range according to the distance from each point in the power transmission coil coverage range to the center of the power transmission coil by using a magnetic field fitting function.
10. A charging abnormality diagnosis system based on wireless charging data analysis for implementing the charging abnormality diagnosis method based on wireless charging data analysis according to any one of claims 1 to 9, comprising:
the data acquisition module acquires the standard charging speed of the wireless charging equipment, acquires the initial electric quantity of the object to be charged, acquires the real-time accumulated charging time of the object to be charged, acquires the display number of the charging and discharging standard model and acquires the input current entering the power transmission coil;
the data calculation module is used for calculating the real-time charging speed of the object to be charged, acquiring the average temperature of the wireless charging equipment during charging and acquiring the magnetic induction intensity of the wireless charging equipment during charging;
the model building module is used for building a decay model of temperature with respect to distance and building a decay model of magnetic field with respect to distance;
and the abnormality judgment module is used for diagnosing the abnormality reasons and diagnosing the fault reasons.
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