CN116995786A - Mobile phone charging intelligent control system based on artificial intelligence - Google Patents
Mobile phone charging intelligent control system based on artificial intelligence Download PDFInfo
- Publication number
- CN116995786A CN116995786A CN202311259095.4A CN202311259095A CN116995786A CN 116995786 A CN116995786 A CN 116995786A CN 202311259095 A CN202311259095 A CN 202311259095A CN 116995786 A CN116995786 A CN 116995786A
- Authority
- CN
- China
- Prior art keywords
- mobile phone
- charging
- wireless charger
- target
- electric quantity
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000013473 artificial intelligence Methods 0.000 title claims abstract description 17
- 238000004146 energy storage Methods 0.000 claims abstract description 60
- 238000012544 monitoring process Methods 0.000 claims abstract description 48
- 230000036541 health Effects 0.000 claims abstract description 33
- 238000012937 correction Methods 0.000 claims description 29
- 238000004458 analytical method Methods 0.000 claims description 21
- 238000000034 method Methods 0.000 claims description 9
- 230000003862 health status Effects 0.000 claims description 3
- 238000012545 processing Methods 0.000 claims description 3
- 230000002035 prolonged effect Effects 0.000 description 4
- 238000007792 addition Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
Classifications
-
- 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
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/00032—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries characterised by data exchange
- H02J7/00036—Charger exchanging data with battery
-
- 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
- H02J50/005—Mechanical details of housing or structure aiming to accommodate the power transfer means, e.g. mechanical integration of coils, antennas or transducers into emitting or receiving devices
-
- 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
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/0042—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries characterised by the mechanical construction
- H02J7/0045—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries characterised by the mechanical construction concerning the insertion or the connection of the batteries
-
- 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
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/0047—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries with monitoring or indicating devices or circuits
-
- 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
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/0047—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries with monitoring or indicating devices or circuits
- H02J7/0048—Detection of remaining charge capacity or state of charge [SOC]
-
- 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
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/0047—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries with monitoring or indicating devices or circuits
- H02J7/005—Detection of state of health [SOH]
-
- 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
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/0068—Battery or charger load switching, e.g. concurrent charging and load supply
Abstract
The invention belongs to the technical field of intelligent mobile phone charging control, and particularly discloses an intelligent mobile phone charging control system based on artificial intelligence. The invention analyzes two use states of the plug-in charging and the off-line charging of the wireless charger based on the constructed wireless charger state monitoring module, further obtains the health coefficient of the mobile phone battery of the wireless charger in the plug-in charging use state, analyzes the health coefficient of the mobile phone battery to further obtain the actual charging time of the mobile phone and the energy storage charging requirement of the wireless charger after the mobile phone is charged, obtains the magnetic attraction coincidence coefficient of the wireless charger in the off-line charging use state, analyzes the magnetic attraction coincidence coefficient of the wireless charger to further obtain the actual charging time of the mobile phone and the energy storage electric quantity of the wireless charger to meet the requirements of the mobile phone charging electric quantity, thereby being better convenient for people to arrange, also omitting the step of preparing a movable power supply in advance when people go out and facilitating the life of people.
Description
Technical Field
The invention belongs to the technical field of intelligent control of mobile phone charging, and relates to an intelligent mobile phone charging control system based on artificial intelligence.
Background
Along with the continuous development of scientific technology, mobile phones gradually become an indispensable tool in life of people, and the charging problem of mobile phones is followed, the main charging mode is to connect a power supply and a mobile phone by using a mobile phone charger and a data line for charging, and along with the continuous improvement of requirements of electric equipment on power supply quality, safety, reliability, convenience, instantaneity, special occasions, special geographic environments and the like, the contact type electric energy transmission mode is more and more incapable of meeting actual requirements. At present, wireless chargers are also gradually popularized, and the wireless chargers rely on electromagnetic wave propagation, then electromagnetic wave energy is converted into electric energy, and finally wireless charging is achieved.
However, the existing wireless chargers still have some defects: (1) At present, an existing wireless charger can only be plugged into a battery to charge a mobile phone, when people go out to carry the charger, the user needs to search for a power supply in addition to charge the mobile phone, and inconvenience caused by no power supply of the mobile phone after going out is not solved.
(2) The existing wireless charger can only monitor the electric quantity of the mobile phone, and charges the mobile phone to a full state according to the current electric quantity of the mobile phone, and the optimal charging electric quantity of the mobile phone corresponding to the current battery health condition of the mobile phone is not considered, so that the mobile phone battery can not be ensured to continuously maintain the optimal health state. And under the off-line charging state, the magnetic attraction degree of the magnetic attraction area of the wireless charger is possibly weakened due to the excessive use of the wireless charger, so that the mobile phone is offset in the charging process, the charging efficiency of the wireless charger to the mobile phone is further influenced, and the charging requirement of a corresponding user of the mobile phone cannot be met.
Disclosure of Invention
In view of this, in order to solve the problems set forth in the background art, an intelligent control system for charging a mobile phone based on artificial intelligence is proposed.
The aim of the invention can be achieved by the following technical scheme: the invention provides an intelligent mobile phone charging control system based on artificial intelligence, which comprises: the wireless charger state monitoring module is used for monitoring the working state of the target wireless charger, executing the mobile phone pre-charging duration setting module if the target wireless charger is in an inserting charging state, and executing the offline charging electric quantity monitoring module if the target wireless charger is in an offline charging state.
The mobile phone pre-charging duration setting module is used for obtaining the current information of the target mobile phone and further setting the pre-charging duration of the target mobile phone.
And the mobile phone battery health monitoring module is used for monitoring the charging information of the target mobile phone in a preset charging time period to obtain the health coefficient of the target mobile phone battery.
The mobile phone charging duration correction module is used for correcting and displaying the actual charging duration of the target mobile phone.
The charger charging demand analysis module is used for acquiring the model and the current energy storage electric quantity of the target wireless charger, analyzing the energy storage charging demand coefficient of the target wireless charger, further judging the energy storage charging demand of the target wireless charger, and processing the energy storage charging demand.
And the off-line charging electric quantity monitoring module is used for analyzing the electric quantity charging coincidence coefficient of the target wireless charger according to the current information of the target mobile phone and the current energy storage electric quantity of the target wireless charger, and executing the charger magnetic attraction data monitoring module if the electric quantity charging coincidence coefficient is smaller than or equal to a set electric quantity charging coincidence coefficient threshold value.
The charger magnetic attraction data monitoring module is used for monitoring magnetic attraction data of the target wireless charger in an offline use state, and further analyzing magnetic attraction coincidence coefficients of the target wireless charger.
The mobile phone actual charging duration correction module is used for correcting the actual charging electric quantity of the target mobile phone, so as to obtain and display the actual pre-charging duration of the target mobile phone.
The database is used for storing rated power, average charging rate and magnetic attraction area corresponding to each type of mobile phone, storing each standard charging temperature of each type of mobile phone in each preset charging time period, storing rated power corresponding to each type of wireless charger and storing standard magnetic attraction force and standard mobile phone sliding distance of each type of wireless charger in each placement state.
Preferably, the current information of the target mobile phone includes a mobile phone model and a current electric quantity of the target mobile phone, and the charging information of the target mobile phone in the preset charging time period includes a mobile phone electric quantity and a mobile phone temperature of the target mobile phone after the preset charging time period.
Preferably, the method for acquiring the precharge duration of the target mobile phone is as follows: hand for extracting target mobile phoneMatching the mobile phone model of the target mobile phone with the rated electric quantity and average charging rate of mobile phones of all models in a database to obtain the rated electric quantity and average charging rate of the target mobile phone, and further analyzing to obtain the pre-charging duration of the target mobile phoneWherein->Rated power of target mobile phone, +.>Optimal power duty weight for the set health status of the mobile phone, < ->For the current electric quantity of the target mobile phone, +.>Is the average charge rate of the target handset.
Preferably, the specific analysis mode of the health coefficient of the target mobile phone battery is as follows: extracting the mobile phone electric quantity and the mobile phone temperature of the target mobile phone after a preset charging time period, and respectively marking the mobile phone electric quantity and the mobile phone temperature asAnd->Analyzing health coefficients of target mobile phone batteryWherein->For a predetermined charging period of time, +.>For the standard charging temperature of the target mobile phone extracted from the database within the predetermined charging period, +.>、/>Is the set influence factor of the mobile phone electric quantity and the mobile phone temperature.
Preferably, the actual charging duration correction mode of the target mobile phone is as follows: extracting a health coefficient of a battery of a target mobile phone, and analyzing an actual precharge duration correction value of the target mobile phoneWherein->Correction value of actual pre-charge time length for set target mobile phone, +.>For the set standard battery health coefficient threshold value of the mobile phone, e is a natural constant, and the actual charging time length of the target mobile phone is further analyzed and obtained according to the natural constant>。
Preferably, the specific analysis mode of the energy storage and charging requirement of the target wireless charger is as follows: the method comprises the steps of obtaining the model and the current energy storage electric quantity of a target wireless charger, matching the model of the target wireless charger with rated electric quantity of wireless chargers of various models in a database to obtain the rated electric quantity of the target wireless charger, and further analyzing to obtain the energy storage demand coefficient of the target wireless chargerWherein->Rated power of target wireless charger, +.>Optimal electric quantity duty ratio weight for the set wireless charger health state>And the current energy storage electric quantity of the target wireless charger.
If it isWhen the energy storage and charging requirement of the target wireless charger is equal to 1, the energy storage and charging requirement of the target wireless charger is the charging requirement, if +.>And when the energy storage charging requirement of the target wireless charger is equal to 0, the energy storage charging requirement of the target wireless charger is a charging-free requirement.
Preferably, the specific analysis mode of the electric quantity charging coincidence coefficient of the target wireless charger is as follows: extracting the current energy storage electric quantity of the target wireless charger, the rated electric quantity and the current electric quantity of the target mobile phone, and analyzing the electric quantity charging coincidence coefficient of the target wireless chargerWherein->For the current energy storage electric quantity of the target wireless charger, if ∈>When the electric quantity charging is larger than the set electric quantity charging coincidence coefficient threshold value, the target mobile phone is charged through the target wireless charger, and if the electric quantity charging is in the range of ++>And executing the charger magnetic data monitoring module when the electric quantity charging meeting the coefficient threshold value is smaller than or equal to the set electric quantity charging meeting the coefficient threshold value.
Preferably, the magnetic data of the target wireless charger in the offline use state includes a placement state of the target wireless charger at each time point in a preset time period, a magnetic force of the target wireless charger in the placement state of each time point, a sliding distance of the target mobile phone, and an overlapping area of a magnetic area of the target mobile phone and the target wireless charger.
Preferably, the specific analysis mode of the magnetic attraction coincidence coefficient of the target wireless charger is as follows: the method comprises the steps of extracting the model of a target wireless charger and the model of a target mobile phone, matching the model of the target wireless charger with standard magnetic attraction force and standard mobile phone sliding distance of each type of wireless charger in a database to obtain standard magnetic attraction force and standard mobile phone sliding distance of each type of wireless charger in each placement state, obtaining standard magnetic attraction force and standard mobile phone sliding distance of each time point of the target wireless charger in a preset time period according to the placement state of each time point of the target wireless charger in the preset time period, and matching the model of the target mobile phone with the magnetic attraction area of each type of mobile phone in the database to obtain the magnetic attraction area of the target mobile phone.
The mobile phone model of the target mobile phone is extracted, compared with mobile phones of various models stored in a database, and the mobile phone model is matched with the magnetic attraction area of the mobile phone of the model corresponding to the target mobile phone and is used as the magnetic attraction area of the target mobile phone.
Analyzing magnetic attraction coincidence coefficient of target wireless chargerWherein->The first time of the target wireless charger in the preset time period>Magnetic attraction force under the placement state of each time point, sliding distance of target mobile phone, overlapping area of magnetic attraction areas of target mobile phone and target wireless charger, and +.>And->The first time of the target wireless charger in the preset time period>Standard magnetic attraction force and standard mobile phone sliding distance under the placement state of each time point, and +.>The area of the magnetic attraction area of the target mobile phone is +.>，/>For the number of each time point of the target wireless charger within the preset time period, +.>For the number of time points of the target wireless charger in the preset time period, < >>The magnetic attraction force, the sliding distance of the target mobile phone and the influence factor of the overlapping area of the magnetic attraction area of the target mobile phone and the target wireless charger are set as +.>Is a natural constant.
Preferably, the obtaining manner of the actual precharge duration of the target mobile phone is as follows: according to the magnetic attraction coincidence coefficient of the target wireless chargerAnalyzing a correction value of an actual stored energy capacity of the target wireless charger, wherein +.>The magnetic attraction of the wireless charger is set to meet the coefficient threshold value, and the actual pre-charging time length of the target mobile phone is further analyzed and obtained according to the magnetic attraction of the wireless charger>Wherein->And protecting the correction factor for the set stored energy electric quantity of the wireless charger.
Compared with the prior art, the invention has the following beneficial effects: 1. the wireless charger state monitoring module is based on the analysis of two use modes of the wireless charger, so that two functions of charging the mobile phone by plugging the wireless charger and charging the mobile phone offline as a movable power supply are realized, the problem that people only carry the charger when going out and face the embarrassment that the mobile phone is not powered by the power supply is solved, and the travel of people is facilitated.
According to the invention, the mobile phone charging duration correction module is utilized to obtain the health coefficient of the target mobile phone battery, and the pre-charging duration of the target mobile phone is further analyzed and corrected to obtain the actual charging duration of the mobile phone in the plug-in use state of the wireless charger by considering the influence of the mobile phone battery health state on the mobile phone charging, so that the service life of the mobile phone battery is prolonged.
According to the invention, the charger charging demand analysis module is used for analyzing whether the wireless charger needs to be charged and stored after the mobile phone is charged in the plug-in charging state, so that the wireless charger can automatically charge and store when the wireless charger has a charging and energy storage demand, and the inconvenience caused by people forgetting to store electric quantity for the wireless charger and going out is avoided.
The invention is based on the mobile phone actual charging duration correction module, analyzes the magnetic attraction coincidence coefficient of the target wireless charger, corrects the actual energy storage electric quantity of the target wireless charger to obtain the actual charging duration of the target mobile phone charged by the actual energy storage electric quantity of the target wireless charger, so that a user can better know the charging duration of the target wireless charger for charging the target mobile phone by the current energy storage, the arrangement of the user is convenient, the minimum remaining energy storage electric quantity protection of the target wireless charger in an offline charging state is considered, and the service life of the wireless charger is better prolonged.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed for the description of 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 that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of the system module connection of the present invention.
Description of the embodiments
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the present invention provides an intelligent control system for charging mobile phones based on artificial intelligence, and the specific module distribution is as follows: the mobile phone charging system comprises a wireless charger state monitoring module, a mobile phone pre-charging time length setting module, a mobile phone battery health monitoring module, a mobile phone charging time length correction module, a charger charging demand analysis module, an offline charging electric quantity monitoring module, a charger magnetic attraction data monitoring module, a mobile phone actual charging time length correction module and a database. The connection relation between the modules is as follows: the mobile phone pre-charging time length setting module is connected with the mobile phone battery health monitoring module, the mobile phone charging time length correction module is connected with the mobile phone battery health monitoring module, the charger magnetic attraction data monitoring module is connected with the mobile phone actual charging time length correction module, and the database is respectively connected with the mobile phone pre-charging time length setting module, the mobile phone battery health monitoring module, the charger charging requirement analysis module, the offline charging electric quantity monitoring module and the charger magnetic attraction data monitoring module.
The wireless charger state monitoring module is used for monitoring the working state of the target wireless charger, executing the mobile phone pre-charging duration setting module if the target wireless charger is in an inserting charging state, and executing the offline charging electric quantity monitoring module if the target wireless charger is in an offline charging state.
The wireless charger state monitoring module is based on the analysis of two use modes of the wireless charger, so that two functions of charging the mobile phone by plugging the wireless charger and charging the mobile phone offline as a movable power supply are realized, the problem that people only carry the charger when going out and face the embarrassment that the mobile phone is not powered by the power supply is solved, and the travel of people is facilitated.
The mobile phone pre-charging duration setting module is used for obtaining current information of the target mobile phone and further setting the pre-charging duration of the target mobile phone.
As an example, the current information of the target mobile phone includes a mobile phone model number and a current electric quantity of the target mobile phone.
It should be further described that, the obtaining mode of the mobile phone model and the current electric quantity of the target mobile phone is: after the target mobile phone is contacted with the target wireless charger, the target wireless charger performs information interaction with the target mobile phone through electromagnetic waves, and the mobile phone model and the current electric quantity of the target mobile phone are obtained.
As an example, the precharge duration of the target mobile phone is obtained by: extracting the mobile phone model and the current electric quantity of the target mobile phone, matching the mobile phone model of the target mobile phone with the rated electric quantity and average charging rate of mobile phones of all models in a database to obtain the rated electric quantity and average charging rate of the target mobile phone, and further analyzing to obtain the pre-charging duration of the target mobile phoneWherein->Rated power of target mobile phone, +.>Optimal power duty weight for the set health status of the mobile phone, < ->For the current electric quantity of the target mobile phone, +.>Is the average charge rate of the target handset.
It should be further described that the specific extraction modes of the rated power and the average charging rate of the target mobile phone are as follows: the mobile phone model of the target mobile phone is extracted, compared with mobile phones of various models stored in a database, and the mobile phone model is matched with the rated power and the average charging rate of the mobile phone of the model corresponding to the target mobile phone, and is used as the rated power and the average charging rate of the target mobile phone.
The mobile phone battery health monitoring module is used for monitoring charging information of the mobile phone in a preset charging time period to obtain a target mobile phone battery health coefficient.
As an example, the charging information of the target mobile phone in the predetermined charging period includes a mobile phone power and a mobile phone temperature of the target mobile phone after the predetermined charging period.
It should be further noted that, the method for obtaining the mobile phone electric quantity after the predetermined charging period of the target mobile phone is as follows:
as an example, the specific analysis method of the health coefficient of the target mobile phone battery is as follows: extracting the mobile phone electric quantity and the mobile phone temperature of the target mobile phone after a preset charging time period, and respectively marking the mobile phone electric quantity and the mobile phone temperature asAnd->Analyzing health coefficients of target mobile phone batteryWherein->For a predetermined charging period of time, +.>For the standard charging temperature of the target mobile phone extracted from the database within the predetermined charging period, +.>、/>Is the set influence factor of the mobile phone electric quantity and the mobile phone temperature.
The mobile phone charging duration correction module is used for correcting and displaying the actual charging duration of the target mobile phone.
As an example, the actual charging duration correction manner of the target mobile phone is: extracting a health coefficient of a battery of a target mobile phone, and analyzing an actual precharge duration correction value of the target mobile phoneWherein->Correction value of actual pre-charge time length for set target mobile phone, +.>For the set standard battery health coefficient threshold value of the mobile phone, e is a natural constant, and the actual charging time length of the target mobile phone is further analyzed and obtained according to the natural constant>。
According to the invention, the mobile phone charging duration correction module is utilized to obtain the health coefficient of the target mobile phone battery, and the pre-charging duration of the target mobile phone is further analyzed and corrected to obtain the actual charging duration of the mobile phone in the plug-in use state of the wireless charger by considering the influence of the mobile phone battery health state on the mobile phone charging, so that the service life of the mobile phone battery is prolonged.
The charger charging demand analysis module is used for acquiring the model and the current energy storage electric quantity of the target wireless charger, analyzing the energy storage charging demand coefficient of the target wireless charger, further judging the energy storage charging demand of the target wireless charger, and processing the energy storage charging demand.
As an example, the specific analysis manner of the energy storage requirement of the target wireless charger is: the method comprises the steps of obtaining the model and the current energy storage electric quantity of a target wireless charger, matching the model of the target wireless charger with rated electric quantity of wireless chargers of various models in a database to obtain the rated electric quantity of the target wireless charger, and further analyzing to obtain the energy storage demand coefficient of the target wireless chargerWherein->Rated power of target wireless charger, +.>Optimal electric quantity duty ratio weight for the set wireless charger health state>And the current energy storage electric quantity of the target wireless charger.
If it isWhen the energy storage and charging requirement of the target wireless charger is equal to 1, the energy storage and charging requirement of the target wireless charger is the charging requirement, if +.>And when the energy storage charging requirement of the target wireless charger is equal to 0, the energy storage charging requirement of the target wireless charger is a charging-free requirement.
It should be further described that the model acquisition mode of the target wireless charger is as follows: the target wireless charger directly obtains the model according to the internal storage chip of the target wireless charger.
The specific acquisition mode of the current energy storage electric quantity of the target wireless charger is as follows: the model of the target wireless charger is extracted, compared with the wireless chargers of all models stored in the database, and the model is matched with the rated electric quantity of the wireless charger of the model corresponding to the target wireless charger and is used as the rated electric quantity of the target wireless charger.
According to the invention, the charger charging demand analysis module is used for analyzing whether the wireless charger needs to be charged and stored after the mobile phone is charged in the plug-in charging state, so that the wireless charger can automatically charge and store when the wireless charger has a charging and energy storage demand, and the inconvenience caused by people forgetting to store electric quantity for the wireless charger and going out is avoided.
The off-line charging electric quantity monitoring module is used for analyzing the electric quantity charging coincidence coefficient of the target wireless charger according to the current information of the target mobile phone and the current energy storage electric quantity of the target wireless charger, and executing the charger magnetic attraction data monitoring module if the electric quantity charging coincidence coefficient is smaller than or equal to a set electric quantity charging coincidence coefficient threshold value.
As an example, the specific analysis manner of the electric quantity charging coincidence coefficient of the target wireless charger is as follows: extracting the current energy storage electric quantity of the target wireless charger, the rated electric quantity and the current electric quantity of the target mobile phone, and analyzing the electric quantity charging coincidence coefficient of the target wireless chargerWherein->For the current energy storage electric quantity of the target wireless charger, if ∈>When the electric quantity charging is larger than the set electric quantity charging coincidence coefficient threshold value, the target mobile phone is charged through the target wireless charger, and if the electric quantity charging is in the range of ++>And executing the charger magnetic data monitoring module when the electric quantity charging meeting the coefficient threshold value is smaller than or equal to the set electric quantity charging meeting the coefficient threshold value.
It should be further noted that the set charge compliance coefficient threshold may be set to 0, i.e. whenWhen the current energy storage electric quantity of the target wireless charger is larger than 0, the current energy storage electric quantity of the target wireless charger can meet the charging electric quantity required by the target mobile phone, then the target wireless charger is used for directly charging the target mobile phone, when +.>When the current stored energy of the target wireless charger is smaller than or equal to 0, the current stored energy of the target wireless charger cannot meet the charging energy required by the target mobile phone, and then the charger magnetic attraction data monitoring module is executed to further analyze the target wireless chargerThe current stored energy power may be provided to the target handset for a duration of charging.
The charger magnetic attraction data monitoring module is used for monitoring magnetic attraction data of the target wireless charger in an offline use state, and further analyzing magnetic attraction coincidence coefficients of the target wireless charger.
As an example, the magnetic attraction data of the target wireless charger in the offline use state includes a placement state of the target wireless charger at each time point in a preset time period, a magnetic attraction force of the target wireless charger in the placement state at each time point, a sliding distance of the target mobile phone, and an overlapping area of a magnetic attraction area of the target mobile phone and the target wireless charger.
It should be further noted that, the placement states of the target wireless charger at each time point in the preset time period are as follows: after the target mobile phone starts to charge, a time period is preset, the placement state of the target mobile phone is monitored through a level monitoring sensor arranged in the target wireless charger at fixed time intervals in the preset time period, when the level monitoring sensor arranged in the target wireless charger is in a level state, the placement state of the target wireless charger is in a level state, otherwise, the placement state of the target wireless charger is in a non-level state, and then the placement state of each time point of the target wireless charger in the preset time period is counted, wherein the placement state is in the level state or the non-level state.
The magnetic attraction degree acquisition mode is as follows: and detecting by using a Gaussian meter to obtain the magnetic attraction force of the target wireless charger in the placement state at each time point.
The sliding distance acquisition mode of the target mobile phone is as follows: the magnetic attraction area of the target mobile phone and the magnetic attraction area of the target wireless charger are obtained through monitoring by using a fluxmeter, and a coordinate system is established by taking the center point of the magnetic attraction area of the target wireless charger as an origin coordinateDetecting the coordinates of the center point of the magnetic attraction area of the target mobile phone on the target wireless charger in the placement state of each time point, and obtaining the sliding distance +.>Wherein->And numbering each time point of the target wireless charger in a preset time period.
The overlapping area acquisition mode of the magnetic attraction area of the target mobile phone and the target wireless charger is as follows: and monitoring the overlapping part of the magnetic field in the magnetic attraction area of the target mobile phone and the magnetic field in the magnetic attraction area of the target wireless charger by using a fluxgraph, and taking the area of the overlapping part of the magnetic attraction area of the target mobile phone and the magnetic field in the magnetic attraction area of the target wireless charger as the overlapping area of the magnetic attraction area of the target mobile phone and the magnetic attraction area of the target wireless charger.
As an example, the specific analysis mode of the magnetic attraction coincidence coefficient of the target wireless charger is as follows: the method comprises the steps of extracting the model of a target wireless charger and the model of a target mobile phone, matching the model of the target wireless charger with standard magnetic attraction force and standard mobile phone sliding distance of each type of wireless charger in a database to obtain standard magnetic attraction force and standard mobile phone sliding distance of each type of wireless charger in each placement state, obtaining standard magnetic attraction force and standard mobile phone sliding distance of each time point of the target wireless charger in a preset time period according to the placement state of each time point of the target wireless charger in the preset time period, and matching the model of the target mobile phone with the magnetic attraction area of each type of mobile phone in the database to obtain the magnetic attraction area of the target mobile phone.
Analyzing magnetic attraction coincidence coefficient of target wireless chargerWherein->The first time of the target wireless charger in the preset time period>Magnetic attraction force and target in placement state at each time pointThe mobile phone sliding distance, the superposition area of the magnetic attraction area of the target mobile phone and the target wireless charger, and the number of the magnetic attraction areas is +.>And->The first time of the target wireless charger in the preset time period>Standard magnetic attraction force and standard mobile phone sliding distance under the placement state of each time point, and +.>The area of the magnetic attraction area of the target mobile phone is +.>，/>For the number of each time point of the target wireless charger within the preset time period, +.>For the number of time points of the target wireless charger in the preset time period, < >>The magnetic attraction force, the sliding distance of the target mobile phone and the influence factor of the overlapping area of the magnetic attraction area of the target mobile phone and the target wireless charger are set as +.>Is a natural constant.
The mobile phone actual charging duration correction module is used for correcting the actual charging electric quantity of the target mobile phone, so as to obtain and display the actual pre-charging duration of the target mobile phone.
As an example, the actual precharge duration of the target mobile phone is obtained by: according to the magnetic attraction coincidence coefficient of the target wireless chargerAnalyzing a correction value of an actual stored energy capacity of the target wireless charger, wherein +.>The magnetic attraction of the wireless charger is set to meet the coefficient threshold value, and the actual pre-charging time length of the target mobile phone is further analyzed and obtained according to the magnetic attraction of the wireless charger>Wherein->And protecting the correction factor for the set stored energy electric quantity of the wireless charger.
The invention is based on the mobile phone actual charging duration correction module, analyzes the magnetic attraction coincidence coefficient of the target wireless charger, corrects the actual energy storage electric quantity of the target wireless charger to obtain the actual charging duration of the target mobile phone charged by the actual energy storage electric quantity of the target wireless charger, so that a user can better know the charging duration of the target wireless charger for charging the target mobile phone by the current energy storage, the arrangement of the user is convenient, the minimum remaining energy storage electric quantity protection of the target wireless charger in an offline charging state is considered, and the service life of the wireless charger is better prolonged.
The foregoing is merely illustrative and explanatory of the principles of this invention, as various modifications and additions may be made to the specific embodiments described, or similar arrangements may be substituted by those skilled in the art, without departing from the principles of this invention or beyond the scope of this invention as defined in the claims.
Claims (10)
1. An artificial intelligence based mobile phone charging intelligent control system, which is characterized by comprising:
the wireless charger state monitoring module is used for monitoring the working state of the target wireless charger, executing the mobile phone pre-charging duration setting module if the target wireless charger is in an inserting charging state, and executing the offline charging electric quantity monitoring module if the target wireless charger is in an offline charging state;
the mobile phone pre-charging duration setting module is used for acquiring current information of the target mobile phone and further setting the pre-charging duration of the target mobile phone;
the mobile phone battery health monitoring module is used for monitoring charging information of a target mobile phone in a preset charging time period to obtain a target mobile phone battery health coefficient;
the mobile phone charging duration correction module is used for correcting and displaying the actual charging duration of the target mobile phone;
the charger charging demand analysis module is used for acquiring the model and the current energy storage electric quantity of the target wireless charger, analyzing the energy storage charging demand coefficient of the target wireless charger, further judging the energy storage charging demand of the target wireless charger, and processing the energy storage charging demand;
the off-line charging electric quantity monitoring module is used for analyzing the electric quantity charging coincidence coefficient of the target wireless charger according to the current information of the target mobile phone and the current energy storage electric quantity of the target wireless charger, and executing the charger magnetic attraction data monitoring module if the electric quantity charging coincidence coefficient is smaller than or equal to a set electric quantity charging coincidence coefficient threshold value;
the charger magnetic attraction data monitoring module is used for monitoring magnetic attraction data of the target wireless charger in an offline use state, and further analyzing magnetic attraction coincidence coefficients of the target wireless charger;
the mobile phone actual charging duration correction module is used for correcting the actual charging electric quantity of the target mobile phone, so as to obtain and display the actual pre-charging duration of the target mobile phone;
the database is used for storing rated power, average charging rate and magnetic attraction area corresponding to each type of mobile phone, storing each standard charging temperature of each type of mobile phone in each preset charging time period, storing rated power corresponding to each type of wireless charger and storing standard magnetic attraction force and standard mobile phone sliding distance of each type of wireless charger in the placement state of each time point in the preset time period.
2. The intelligent control system for charging a mobile phone based on artificial intelligence according to claim 1, wherein: the current information of the target mobile phone comprises the mobile phone model and the current electric quantity of the target mobile phone, and the charging information of the target mobile phone in the preset charging time period comprises the mobile phone electric quantity and the mobile phone temperature of the target mobile phone after the preset charging time period.
3. The intelligent control system for charging mobile phone based on artificial intelligence as claimed in claim 2, wherein: the precharge duration acquisition mode of the target mobile phone is as follows:
extracting the mobile phone model and the current electric quantity of the target mobile phone, matching the mobile phone model of the target mobile phone with the rated electric quantity and average charging rate of mobile phones of all models in a database to obtain the rated electric quantity and average charging rate of the target mobile phone, and further analyzing to obtain the pre-charging duration of the target mobile phoneWherein->Rated power of target mobile phone, +.>Optimal power duty weight for the set health status of the mobile phone, < ->For the current electric quantity of the target mobile phone, +.>Is the average charge rate of the target handset.
4. The intelligent mobile phone charging control system based on artificial intelligence according to claim 3, wherein: the specific analysis mode of the health coefficient of the target mobile phone battery is as follows:
extracting mobile phone electric quantity and mobile phone temperature of target mobile phone after a preset charging time periodRespectively marked asAnd->Analyzing the health coefficient of the target mobile phone battery>Wherein->For a predetermined charging period of time, +.>For the standard charging temperature of the target mobile phone extracted from the database within the predetermined charging period, +.>、Is the set influence factor of the mobile phone electric quantity and the mobile phone temperature.
5. The intelligent control system for charging a mobile phone based on artificial intelligence according to claim 4, wherein: the actual charging time length correction mode of the target mobile phone is as follows:
extracting a health coefficient of a battery of a target mobile phone, and analyzing an actual precharge duration correction value of the target mobile phoneWherein->Correction value of actual pre-charge time length for set target mobile phone, +.>Mobile phone for settingThe standard battery health coefficient threshold value, e is a natural constant, and the actual charging time length of the target mobile phone is further analyzed and obtained according to the natural constant>。
6. The intelligent control system for charging a mobile phone based on artificial intelligence according to claim 1, wherein: the specific analysis mode of the energy storage and charging requirements of the target wireless charger is as follows:
the method comprises the steps of obtaining the model and the current energy storage electric quantity of a target wireless charger, matching the model of the target wireless charger with rated electric quantity of wireless chargers of various models in a database to obtain the rated electric quantity of the target wireless charger, and further analyzing to obtain the energy storage demand coefficient of the target wireless chargerWherein->Rated power of target wireless charger, +.>Optimal electric quantity duty ratio weight for the set wireless charger health state>The current energy storage electric quantity of the target wireless charger;
if it isWhen the energy storage and charging requirement of the target wireless charger is equal to 1, the energy storage and charging requirement of the target wireless charger is the charging requirement, if +.>And when the energy storage charging requirement of the target wireless charger is equal to 0, the energy storage charging requirement of the target wireless charger is a charging-free requirement.
7. The intelligent mobile phone charging control system based on artificial intelligence according to claim 3, wherein: the specific analysis mode of the electric quantity charging coincidence coefficient of the target wireless charger is as follows:
extracting the current energy storage electric quantity of the target wireless charger, the rated electric quantity and the current electric quantity of the target mobile phone, and analyzing the electric quantity charging coincidence coefficient of the target wireless chargerWherein->For the current energy storage electric quantity of the target wireless charger, if ∈>When the electric quantity charging is larger than the set electric quantity charging coincidence coefficient threshold value, the target mobile phone is charged through the target wireless charger, and if the electric quantity charging is in the range of ++>And executing the charger magnetic data monitoring module when the electric quantity charging meeting the coefficient threshold value is smaller than or equal to the set electric quantity charging meeting the coefficient threshold value.
8. The intelligent control system for charging a mobile phone based on artificial intelligence according to claim 7, wherein: the magnetic attraction data of the target wireless charger in the offline use state comprise each placement state of the target wireless charger at each time point in a preset charging time period, magnetic attraction force of the target wireless charger in each time point placement state, a sliding distance of the target mobile phone and a superposition area of the magnetic attraction areas of the target mobile phone and the target wireless charger.
9. The intelligent control system for charging mobile phone based on artificial intelligence as claimed in claim 8, wherein: the specific analysis mode of the magnetic attraction coincidence coefficient of the target wireless charger is as follows:
the method comprises the steps of extracting the model of a target wireless charger and the model of a target mobile phone, matching the model of the target wireless charger with standard magnetic attraction force and standard mobile phone sliding distance of each type of wireless charger in a database to obtain standard magnetic attraction force and standard mobile phone sliding distance of each type of wireless charger in each placement state, and according to the placement state of each time point of the target wireless charger in a preset time period, obtaining standard magnetic attraction force and standard mobile phone sliding distance of each time point of the target wireless charger in the preset time period, matching the model of the target mobile phone with the magnetic attraction area of each type of mobile phone in the database to obtain the magnetic attraction area of the target mobile phone;
analyzing magnetic attraction coincidence coefficient of target wireless chargerWherein->The first time of the target wireless charger in the preset time period>Magnetic attraction force under the placement state of each time point, sliding distance of target mobile phone, overlapping area of magnetic attraction areas of target mobile phone and target wireless charger, and +.>And->The first time of the target wireless charger in the preset time period>Standard magnetic attraction force and standard mobile phone sliding distance under the placement state of each time point, and +.>The area of the magnetic attraction area of the target mobile phone is +.>，/>For the number of each time point of the target wireless charger within the preset time period, +.>For the number of time points of the target wireless charger in the preset time period, < >>The magnetic attraction force, the sliding distance of the target mobile phone and the influence factor of the overlapping area of the magnetic attraction area of the target mobile phone and the target wireless charger are set as +.>Is a natural constant.
10. The intelligent control system for charging a mobile phone based on artificial intelligence according to claim 9, wherein: the actual pre-charging time length of the target mobile phone is obtained by the following steps:
according to the magnetic attraction coincidence coefficient of the target wireless chargerAnalyzing a correction value of an actual stored energy capacity of the target wireless charger, wherein +.>The magnetic attraction of the wireless charger is set to meet the coefficient threshold value, and the actual pre-charging time length of the target mobile phone is further analyzed and obtained according to the magnetic attraction of the wireless charger>Wherein->For setting wirelessThe stored energy electric quantity of the charger protects the correction factor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311259095.4A CN116995786B (en) | 2023-09-27 | 2023-09-27 | Mobile phone charging intelligent control system based on artificial intelligence |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311259095.4A CN116995786B (en) | 2023-09-27 | 2023-09-27 | Mobile phone charging intelligent control system based on artificial intelligence |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116995786A true CN116995786A (en) | 2023-11-03 |
| CN116995786B CN116995786B (en) | 2024-01-09 |
Family
ID=88534198
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311259095.4A Active CN116995786B (en) | 2023-09-27 | 2023-09-27 | Mobile phone charging intelligent control system based on artificial intelligence |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116995786B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117590893A (en) * | 2024-01-19 | 2024-02-23 | 维屿(深圳)科技有限公司 | Precious temperature intelligent monitoring system charges is inhaled to magnetism |
| CN117590893B (en) * | 2024-01-19 | 2024-05-14 | 维屿(深圳)科技有限公司 | Precious temperature intelligent monitoring system charges is inhaled to magnetism |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20190184842A1 (en) * | 2017-12-15 | 2019-06-20 | WiBotic Inc. | Wireless charging with multiple charging locations |
| CN112213641A (en) * | 2019-10-30 | 2021-01-12 | 蜂巢能源科技有限公司 | Battery management system and method for obtaining remaining time |
| CN113093041A (en) * | 2021-04-06 | 2021-07-09 | 吴炜 | Battery health state remote data acquisition and diagnosis analysis system of new energy automobile power system |
| CN116454949A (en) * | 2023-04-19 | 2023-07-18 | 国网宁夏电力有限公司 | Intelligent control system for light storage charge and discharge |
| CN116545077A (en) * | 2023-07-06 | 2023-08-04 | 深圳市磁迹科技有限公司 | Wireless charging method, device, equipment and storage medium based on artificial intelligence |
| CN116596643A (en) * | 2023-07-14 | 2023-08-15 | 深圳市古石科技有限公司 | Intelligent management system for charging of shared charger |
| CN116780713A (en) * | 2023-06-29 | 2023-09-19 | 深圳市洛沃克科技有限公司 | Wireless charging method, system, equipment and storage medium for magnetic mobile energy storage power supply |
-
2023
- 2023-09-27 CN CN202311259095.4A patent/CN116995786B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20190184842A1 (en) * | 2017-12-15 | 2019-06-20 | WiBotic Inc. | Wireless charging with multiple charging locations |
| CN112213641A (en) * | 2019-10-30 | 2021-01-12 | 蜂巢能源科技有限公司 | Battery management system and method for obtaining remaining time |
| CN113093041A (en) * | 2021-04-06 | 2021-07-09 | 吴炜 | Battery health state remote data acquisition and diagnosis analysis system of new energy automobile power system |
| CN116454949A (en) * | 2023-04-19 | 2023-07-18 | 国网宁夏电力有限公司 | Intelligent control system for light storage charge and discharge |
| CN116780713A (en) * | 2023-06-29 | 2023-09-19 | 深圳市洛沃克科技有限公司 | Wireless charging method, system, equipment and storage medium for magnetic mobile energy storage power supply |
| CN116545077A (en) * | 2023-07-06 | 2023-08-04 | 深圳市磁迹科技有限公司 | Wireless charging method, device, equipment and storage medium based on artificial intelligence |
| CN116596643A (en) * | 2023-07-14 | 2023-08-15 | 深圳市古石科技有限公司 | Intelligent management system for charging of shared charger |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117590893A (en) * | 2024-01-19 | 2024-02-23 | 维屿(深圳)科技有限公司 | Precious temperature intelligent monitoring system charges is inhaled to magnetism |
| CN117590893B (en) * | 2024-01-19 | 2024-05-14 | 维屿(深圳)科技有限公司 | Precious temperature intelligent monitoring system charges is inhaled to magnetism |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116995786B (en) | 2024-01-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| EP2849309B1 (en) | Apparatus and method for controlling operation for balancing charge capacity of secondary battery cells | |
| CN109228959A (en) | Electric bicycle intelligent charging system and charging method with fire-proof and explosion-proof function | |
| US20120101754A1 (en) | Method of estimating remaining constant current/constant voltage charging time | |
| CN101272057B (en) | Portable mobile charging power supply | |
| US11005287B1 (en) | Advanced mobile energy storage device | |
| CN111483350A (en) | Balance and micro-short circuit detection method for power battery pack | |
| CN111009937A (en) | Mobile internet of things terminal suitable for low-temperature environment | |
| CN101826744A (en) | Iron cell charging circuit | |
| CN202057756U (en) | Distribution network fault locating system based on fault indicator | |
| CN109802456B (en) | Automatic battery identification method | |
| CN106291386B (en) | A kind of method of quick detection rechargeable battery capacity | |
| CN106200365A (en) | A kind of intelligent watch and intelligent watch control method | |
| CN116995786B (en) | Mobile phone charging intelligent control system based on artificial intelligence | |
| CN206272263U (en) | New and old intelligent accummulator uses device with | |
| WO2022267827A1 (en) | Electric quantity state acquisition method and apparatus, charging apparatus, and charging system | |
| CN106787033B (en) | A kind of method and apparatus of more equipment wireless chargings | |
| CN104659845A (en) | Adaptive battery charger | |
| CN209329714U (en) | Communication of power system, which stores, uses battery remote charge/discharge system | |
| CN112072196A (en) | Quick charging method and device for lithium ion battery | |
| CN210669575U (en) | Lithium battery | |
| CN207265714U (en) | A kind of control system for sweeping robot | |
| CN206908313U (en) | A kind of pet tracker component | |
| CN204794044U (en) | Low -power consumption nickel -hydrogen battery overvoltage protector | |
| CN216086208U (en) | BMS application device based on lithium battery renting and replacing | |
| CN203967812U (en) | A kind of electric car charger with slow starting protection function |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |