Charging control method, electronic device and computer readable storage medium

Abstract

The present application relates to the field of terminal control, and in particular to a charging control method, an electronic device, and a computer-readable storage medium. The method includes: the electronic device determines whether the charging time is within the travel time period; if the charging time is within the travel time period, the electronic device can automatically charge at a higher power, thereby realizing the automatic setting of the charging power, effectively improving the intelligence of the electronic device charging, and improving the user experience.

Description

Technical Field

[0001] The present application relates to the field of terminal control, and in particular to a charging control method, an electronic device and a computer-readable storage medium. Background Art

[0002] At present, electronic devices usually have multiple charging modes, such as ultra-fast charging and super-fast charging. Different charging modes have different charging parameters. For example, the charging power of ultra-fast charging is higher than that of super-fast charging, and correspondingly, the charging speed of ultra-fast charging is also higher than that of super-fast charging. However, electronic devices cannot automatically set the charging mode and still require users to set it manually. The degree of intelligence of electronic devices for charging control is low, which affects the user experience. Summary of the invention

[0003] The present application provides a charging control method, an electronic device and a computer-readable storage medium, which solve the problem of low intelligence level of charging control of electronic devices in the prior art.

[0004] In order to achieve the above objectives, this application adopts the following technical solutions:

[0005] In a first aspect, a charging control method is provided, the method comprising:

[0006] At a first time point after the electronic device is connected to the charger, the charging power of the electronic device is set to a first power, and a first interface is displayed; wherein the first interface includes information indicating that the electronic device is charged at the first power;

[0007] After the first time point, if it is determined that the current time is within the travel time period, the charging power of the electronic device is set to a second power and a second interface is displayed; wherein the second interface includes information indicating that the electronic device is charged at the second power, and the second power is greater than the first power.

[0008] Take normal charging, super fast charging and extremely fast charging as examples. Among them, the charging power of the three charging modes is extremely fast charging, super fast charging and normal charging from high to low. It can be understood that the charging current / charging voltage of the three charging modes is extremely fast charging, super fast charging and normal charging from high to low. The charging speed of the three charging modes is extremely fast charging, super fast charging and normal charging from high to low.

[0009] Among them, the charging power of ordinary charging is the third power, the charging power of super fast charging is the first power, and the charging power of extreme speed charging is the second power.

[0010] It can be understood that, in the embodiments of the present application, charging of the electronic device refers to the electronic device being charged.

[0011] In the embodiment of the present application, the electronic device can determine whether the charging time is within the travel time period. If so, the electronic device can automatically charge at a higher power, thereby realizing automatic setting of the charging power, effectively improving the intelligence level of the electronic device charging, and helping to improve the user experience.

[0012] In an embodiment of the first aspect, the second interface includes a first control; and the method further includes:

[0013] In response to a user operation on the first control, a third interface is displayed; the third interface includes a first button;

[0014] In response to the user's operation of the first button, the charging power of the electronic device is set to the first power, and a fourth interface is displayed; wherein the fourth interface includes information indicating that the electronic device is charged at the first power.

[0015] Exemplarily, when the ultra-fast charging corresponds to the second power, the first control may be a capsule, the third interface may be a notification window, and the first button may be a "turn off ultra-fast charging" button. Accordingly, when the user clicks the capsule, the notification window is displayed in response to the user operation. When the user clicks the "turn off ultra-fast charging" button in the notification window, the electronic device turns off ultra-fast charging and sets it to super-fast charging, that is, the charging power of the electronic device is set to the first power.

[0016] In the embodiment of the present application, a user setting interface is provided, and after the electronic device automatically sets the charging power, the user can still manually set the charging mode to adjust the charging power. In this way, the flexibility of the solution is improved, which is conducive to improving the user experience.

[0017] In an embodiment of the first aspect, the method further comprises:

[0018] When the number of the first operation reaches the first number, after the first time point, if it is determined that the current time is within the travel time period, a fifth interface is displayed, and the fifth interface includes information prompting to set the second power;

[0019] The first operation is to set the charging power of the electronic device to the first power in response to a user's operation of the first button when the electronic device is charged at the second power.

[0020] In one implementation, when ultra-fast charging (corresponding to the second power) is automatically turned on, if the user manually turns off ultra-fast charging for m1 times (the first number), the next time the electronic device recognizes that the conditions for automatically turning on ultra-fast charging are met, the electronic device recommends turning on ultra-fast charging.

[0021] In another implementation, when high-speed charging is automatically turned on, if the electronic device performs N1 automatic starts, and the user manually turns off high-speed charging m1 times, then the next time the electronic device recognizes that the conditions for automatically turning on high-speed charging are met, the electronic device recommends turning on high-speed charging.

[0022] Compared with the two implementation methods, the former is equivalent to limiting the cumulative number of times the user manually turns off the ultra-fast charging, while the latter is equivalent to limiting the ratio between the number of times the user manually turns off the ultra-fast charging and the total number of times the electronic device automatically turns on the ultra-fast charging.

[0023] In the embodiment of the present application, through the feedback mechanism, after each setting mode is determined, the user operation can be recorded, and the setting mode can be adaptively adjusted by analyzing the user operation. In this way, the charging setting mode is more in line with user habits, effectively improving the intelligent level of electronic device charging and improving user experience.

[0024] In an embodiment of the first aspect, the method further comprises:

[0025] After the first time point, if it is determined that the current time is not within the travel time period and the first condition is met, a sixth interface is displayed, the sixth interface including information prompting to set the second power;

[0026] The first condition includes that the power of the electronic device when connected to the charger is lower than a preset power, or the predicted charging time is shorter than a preset time.

[0027] In the embodiment of the present application, when the power of the electronic device is connected to the charger, it indicates a low power scenario, and when the predicted charging time is less than the preset time, it indicates that it complies with the user's short-time charging habits. The electronic device can automatically identify the low power scenario and the user's short-time charging habits, and automatically set the charging power according to the identification result, thereby realizing the automatic setting of the charging power, effectively improving the intelligence of the electronic device charging, and helping to improve the user experience.

[0028] In an embodiment of the first aspect, the sixth interface includes a second button and a third button;

[0029] The method further comprises:

[0030] If the user operates the second button, in response to the user's operation of the second button, the charging power of the electronic device is set to the second power, and a seventh interface is displayed; wherein the seventh interface includes the information indicating that the electronic device is charged at the second power;

[0031] If the user operates the third button, in response to the user operation on the third button, charging is continued at the first power.

[0032] For example, the sixth interface may be a notification window for recommending turning on superfast charging, the second button may be a "turn on this time" button, and the third button may be a "ignore this time" button. Accordingly, when the user clicks the "turn on this time" button, the electronic device turns on superfast charging and charges at the second power; when the user clicks the "ignore this time" button, the electronic device keeps superfast charging and continues to charge at the first power.

[0033] In the embodiment of the present application, a user setting interface is provided, and after the electronic device automatically sets the charging power, the user can still manually set the charging mode to adjust the charging power. In this way, the flexibility of the solution is improved, which is conducive to improving the user experience.

[0034] In an embodiment of the first aspect, the method further comprises:

[0035] When the number of the second operation reaches the second number, after the first time point, if it is determined that the current time is not within the travel time period and the first condition is met, setting the power of the electronic device to the second power;

[0036] The second operation is to set the charging power of the electronic device to the second power in response to a user's operation on the second button when the electronic device is charged at the first power.

[0037] In one implementation, when it is recommended to enable ultra-fast charging (corresponding to the second power), if the user enables ultra-fast charging for m3 times (the second number), the electronic device will automatically enable ultra-fast charging the next time it recognizes that the conditions for enabling ultra-fast charging are met.

[0038] In another implementation, when it is recommended to enable ultra-fast charging, if the electronic device executes the recommendation N3 times, where the user enables ultra-fast charging m3 times, the electronic device automatically enables ultra-fast charging the next time it recognizes that the recommendation to enable ultra-fast charging is met.

[0039] Compared with the two implementation methods, the former is equivalent to limiting the cumulative number of times users turn on ultra-fast charging, while the latter is equivalent to limiting the ratio between the number of times users turn on ultra-fast charging and the total number of times the electronic device is recommended to turn on ultra-fast charging.

[0040] In the embodiment of the present application, through the feedback mechanism, after each setting mode is determined, the user operation can be recorded, and the setting mode can be adaptively adjusted by analyzing the user operation. In this way, the charging setting mode is more in line with user habits, effectively improving the intelligent level of electronic device charging and improving user experience.

[0041] In an embodiment of the first aspect, the method further comprises:

[0042] When the number of the third operation reaches the third number, after the first time point, if it is determined that the current time is not within the travel time period and the first condition is met, charging is continued at the first power;

[0043] The third operation is to keep charging at the first power in response to a user's operation on the third button when the electronic device is charged at the first power.

[0044] In one implementation, when it is recommended to turn on ultra-fast charging (corresponding to the second power), if the user ignores m2 times (the third number), the next time when it is recognized that the recommendation for turning on ultra-fast charging is met, the electronic device continues to maintain super-fast charging and is set to manually turn on ultra-fast charging.

[0045] In another implementation, when it is recommended to turn on ultra-fast charging, if the electronic device has executed the recommendation for N2 times, where the user has ignored it for m2 consecutive times, or has not operated it for N2 times (meaning neither turned it on nor ignored it), then the next time it recognizes that the recommendation for turning on ultra-fast charging is met, the electronic device will continue to maintain super-fast charging and be set to manually turn on ultra-fast charging.

[0046] In the embodiment of the present application, through the feedback mechanism, after each setting mode is determined, the user operation can be recorded, and the setting mode can be adaptively adjusted by analyzing the user operation. In this way, the charging setting mode is more in line with user habits, effectively improving the intelligent level of electronic device charging and improving user experience.

[0047] In an embodiment of the first aspect, the method further comprises:

[0048] Acquiring start data, wherein the start data is charging data when the electronic device is connected to the charger;

[0049] The charging time is predicted according to the starting data and the trained recognition model; wherein the recognition model is trained according to historical charging data.

[0050] In the embodiment of the present application, the charging duration of this charging can be predicted based on the start data of this charging to identify whether it meets the requirements of short-time charging. This is equivalent to automatically identifying the charging scenario based on the charging data, and then automatically setting the charging power based on the charging scenario, thereby improving the intelligence level of charging of electronic devices.

[0051] In an embodiment of the first aspect, predicting the charging duration according to the start data and the trained recognition model includes:

[0052] Acquiring location information of the electronic device when it is connected to the charger;

[0053] If the location information is a preset location, the charging time is predicted based on the start data and the trained recognition model.

[0054] The preset location may be a common location for charging the electronic device, for example, a home location or a company location.

[0055] In the embodiment of the present application, the charging position is taken into consideration. Since the preset position is the position where the user charges most frequently, the charging data of this position can better meet the charging habits of the user, so considering the charging position when judging the short-time charging habits can effectively improve the accuracy of the judgment result.

[0056] In an embodiment of the first aspect, the method further comprises:

[0057] Acquire historical charging data; the historical charging data includes time data and non-time data;

[0058] Setting a real label of the historical charging data according to the time data; wherein the real label includes a first label and a second label, the first label indicates that the charging time corresponding to the historical charging data is less than a preset time, and the second label indicates that the charging time corresponding to the historical charging data is greater than or equal to the preset time;

[0059] The recognition model is trained according to the historical charging data and the real labels of the historical charging data to obtain a trained recognition model.

[0060] Optionally, the historical charging data may include the start data when charging starts and the end data when charging ends. The start data may include the start time, charging date, start power, start temperature, charger type, and identification information indicating whether it is a working day, etc. The end data may include the end time (the time when the charger is disconnected), the full charge time (the time when the battery is fully charged), and the end power, etc.

[0061] Among them, the data related to time, such as the start time, charging date, end time and full charge time, can be called time data. The starting power, starting temperature, charger type and end power can be called non-time data.

[0062] Optionally, the electronic device can update the recognition model according to a preset period, such as triggering training once a day, every week or every month; it can also be triggered when the number of groups of historical charging data (sample data) received reaches a preset number; it can also be triggered after each charging, when new charging data (sample data) is received.

[0063] In one implementation, the historical charging data (sample data) can be automatically labeled according to preset conditions to obtain the real label of the historical charging data. The preset conditions can be a combination of multiple conditions. For example, the preset conditions are condition 1 and condition 2, where condition 1 is that the charging time (the interval between the end time and the start time) is less than X minutes, and condition 2 is that the duration of full charge (the interval between the end time and the full charge time) is less than Y minutes.

[0064] In an embodiment of the present application, the recognition model is trained using historical charging data so that the recognition result of the recognition pattern can more accurately reflect the user's charging habits, thereby facilitating improving the accuracy of subsequent automatic setting of the charging power.

[0065] In an embodiment of the first aspect, the method further comprises:

[0066] After the first time point, if it is determined that the current time is not within the travel time period and a second condition is met, then charging is continued at the first power;

[0067] The second condition includes that the power level of the electronic device when connected to the charger is not less than a preset power level, and the predicted charging time is not less than a preset time.

[0068] In this implementation, the user can set the charging mode and charging power by manual setting.

[0069] In an embodiment of the first aspect, the method further comprises:

[0070] At a second time point after the electronic device is connected to the charger, the charging power of the electronic device is set to a third power; wherein the second time point is before the first time point, and the third power is less than the first power.

[0071] For example, when super-fast charging corresponds to the first power and ultra-fast charging corresponds to the second power, ordinary charging corresponds to the third power. Accordingly, after the electronic device is connected to the charger, it can be charged with ordinary charging (third power) first. When the conditions for super-fast charging are identified, the electronic device switches to super-fast charging and charges with the first power; if the conditions for super-fast charging are not identified, the electronic device continues to charge with ordinary charging. When the conditions for ultra-fast charging are identified, the electronic device switches to ultra-fast charging and charges with the second power; if the conditions for ultra-fast charging are not identified in the super-fast charging mode, the electronic device continues to charge with super-fast charging.

[0072] In the embodiments of the present application, a variety of charging modes are provided, and the electronic device can automatically identify the charging scenario and automatically set the charging mode according to the charging scenario, thereby improving the intelligence level of the charging management and control of the electronic device and improving the user experience.

[0073] In an embodiment of the first aspect, the method further comprises:

[0074] After the first time point, obtaining current travel information;

[0075] The travel time period is determined according to the travel information.

[0076] Among them, travel information can include commuting information, flight time, train date, ticket information, taxi reservation information, home location, etc. Commuting information can include working time, leaving time, company location, etc.

[0077] In one implementation, the electronic device can obtain travel information through other applications. For example, the electronic device can obtain the user's taxi reservation information through a taxi application, obtain ticket information through a ticket application, obtain the user's clock-in information through a clock-in application, and thus obtain the commuting time and company location, etc.

[0078] In an embodiment of the present application, the electronic device can automatically identify the charging scenario based on travel information, and automatically set the charging mode according to the identified charging scenario, thereby improving the intelligence level of charging management and control of the electronic device and improving the user experience.

[0079] In a second aspect, an electronic device is provided, comprising a processor, wherein the processor is used to run a computer program stored in a memory to implement any method of the first aspect of the present application.

[0080] In a third aspect, a chip system is provided, including a processor, wherein the processor is coupled to a memory, and the processor executes a computer program stored in the memory to implement any method of the first aspect of the present application.

[0081] In a fourth aspect, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by one or more processors, the method of any one of the first aspects of the present application is implemented.

[0082] In a fifth aspect, an embodiment of the present application provides a computer program product, which, when executed on a device, enables the device to execute any one of the methods in the first aspect.

[0083] It can be understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] Figure 1 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application;

[0085] Figure 2 A software structure block diagram of the electronic device 100 provided in an embodiment of the present application;

[0086] Figure 3 A schematic diagram of a charging interface in a locked screen state provided in an embodiment of the present application;

[0087] Figure 4 A schematic diagram of a desktop charging interface provided in an embodiment of the present application;

[0088] Figure 5 A schematic diagram of a scenario for manually setting a charging mode provided in an embodiment of the present application;

[0089] Figure 6 A schematic diagram of a scenario for manually setting a charging mode provided in another embodiment of the present application;

[0090] Figure 7 A schematic diagram of a scenario for manually setting a charging mode provided in another embodiment of the present application;

[0091] Figure 8 A schematic diagram of a scenario for automatically starting high-speed charging provided in an embodiment of the present application;

[0092] Fig. 9 A schematic diagram of a recommended ultra-fast charging scenario provided in an embodiment of the present application;

[0093] Fig.10 A schematic diagram of the interaction process provided in the embodiment of the present application;

[0094] Fig.11 A schematic diagram of a charging mode setting scenario provided in an embodiment of the present application. DETAILED DESCRIPTION

[0095] In the following description, specific details such as specific system structures and technologies are provided for illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application can also be implemented in other embodiments without these specific details.

[0096] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0097] It should also be understood that in the embodiments of the present application, "one or more" refers to one, two or more than two; "and / or" describes the association relationship of associated objects, indicating that three relationships may exist; for example, A and / or B may represent: A exists alone, A and B exist at the same time, and B exists alone, where A and B may be singular or plural. The character " / " generally indicates that the associated objects before and after are in an "or" relationship.

[0098] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", "fourth", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0099] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0100] The embodiment of the present application provides a charging control method, which can be applied to electronic devices, such as tablet computers, mobile phones, wearable devices, laptop computers, ultra-mobile personal computers (UMPCs), netbooks, personal digital assistants (PDAs), etc. The embodiment of the present application does not limit the specific type of electronic devices.

[0101] Figure 1The electronic device 100 may include a processor 110, an external memory interface 120, an internal memory 121, a universal serial bus (USB) interface 130, a charging management module 140, a power management module 141, a battery 142, an antenna 1, an antenna 2, a mobile communication module 150, a wireless communication module 160, an audio module 170, a speaker 170A, a receiver 170B, a microphone 170C, an earphone interface 170D, a sensor module 180, a button 190, a motor 191, an indicator 192, a camera 193, a display screen 194, and a subscriber identification module (SIM) card interface 195. The sensor module 180 may include a pressure sensor 180A, a gyroscope sensor 180B, an air pressure sensor 180C, a magnetic sensor 180D, an acceleration sensor 180E, a distance sensor 180F, a proximity light sensor 180G, a fingerprint sensor 180H, a temperature sensor 180J, a touch sensor 180K, an ambient light sensor 180L, a bone conduction sensor 180M, etc.

[0102] It is to be understood that the structure illustrated in the embodiment of the present application does not constitute a specific limitation on the electronic device 100. In other embodiments of the present application, the electronic device 100 may include more or fewer components than shown in the figure, or combine some components, or split some components, or arrange the components differently. The components shown in the figure may be implemented in hardware, software, or a combination of software and hardware.

[0103] The processor 110 may include one or more processing units, for example, the processor 110 may include an application processor (AP), a modem processor, a graphics processor (GPU), an image signal processor (ISP), a controller, a memory, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural-network processing unit (NPU), etc. Different processing units may be independent devices or integrated into one or more processors.

[0104] The processor 110 may also be provided with a memory for storing instructions and data. In some embodiments, the memory in the processor 110 is a cache memory. The memory may store instructions or data that the processor 110 has just used or cyclically used. If the processor 110 needs to use the instruction or data again, it may be directly called from the memory. This avoids repeated access, reduces the waiting time of the processor 110, and thus improves the efficiency of the system.

[0105] The internal memory 121 can be used to store computer executable program codes, and the executable program codes include instructions. The processor 110 executes various functional applications and data processing of the electronic device 100 by running the instructions stored in the internal memory 121. The internal memory 121 may include a program storage area and a data storage area. Among them, the program storage area can store an operating system and an application required for at least one function (such as an image playback function, etc.). The touch sensor 180K is also called a "touch panel". The touch sensor 180K can be set on the display screen 194, and the touch sensor 180K and the display screen 194 form a touch screen, also known as a "touch screen". The touch sensor 180K is used to detect touch operations acting on or near it. The touch sensor can pass the detected touch operation to the application processor to determine the type of touch event. Visual output related to the touch operation can be provided through the display screen 194. In other embodiments, the touch sensor 180K can also be set on the surface of the electronic device 100, which is different from the position of the display screen 194.

[0106] The electronic device 100 implements the display function through a GPU, a display screen 194, and an application processor. The GPU is a microprocessor for image processing, which connects the display screen 194 and the application processor. The GPU is used to perform mathematical and geometric calculations for graphics rendering. The processor 110 may include one or more GPUs that execute program instructions to generate or change display information.

[0107] The display screen 194 is used to display images, videos, etc. The display screen 194 includes a display panel. The display panel can be a liquid crystal display (LCD), an organic light-emitting diode (OLED), an active-matrix organic light-emitting diode or an active-matrix organic light-emitting diode (AMOLED), a flexible light-emitting diode (FLED), Miniled, MicroLed, Micro-OLED, a quantum dot light-emitting diode (QLED), etc. In some embodiments, the electronic device 100 may include 1 or N display screens 194, where N is a positive integer greater than 1. For example, in the embodiments of the present application, Figure 3-Figure 6 The interfaces shown are all displayed by the monitor.

[0108] The above is a specific description of the embodiment of the present application using the electronic device 100 as an example. It should be understood that the structure illustrated in the embodiment of the present application does not constitute a specific limitation on the electronic device 100. The electronic device 100 may have more or fewer components than those shown in the figure, may combine two or more components, or may have different component configurations. The various components shown in the figure may be implemented in hardware, software, or a combination of hardware and software including one or more signal processing and / or application specific integrated circuits.

[0109] In addition, an operating system is running on the above components. The operating system of the electronic device 100 can adopt a layered architecture, an event-driven architecture, a micro-core architecture, a micro-service architecture, or a cloud architecture. The embodiment of the present application takes the Android system of the layered architecture as an example to illustrate the software structure of the electronic device 100.

[0110] See also Figure 2 , is a software structure block diagram of the electronic device 100 provided in an embodiment of the present application. The layered architecture of the electronic device 100 divides the software into several layers, each layer has a clear role and division of labor. The layers communicate with each other through software interfaces. In some embodiments, the Android system is divided into four layers, namely, the application layer, the application framework layer, the hardware abstraction layer, and the kernel layer from top to bottom.

[0111] The application layer can include a series of application packages, such as Figure 2 As shown, the application package may include a system charging application, a scene perception application, and a smart brain application.

[0112] Among them, the system charging application is used to control the charging mode of electronic devices. The scene perception application is used to identify the user's travel scenarios, such as flight itineraries, train itineraries, taxi itineraries, commuting itineraries, and movie itineraries. The smart brain application is used to train the recognition model and identify the user's short-term charging habits based on the charging data.

[0113] The application framework layer provides application programming interfaces (APIs) and programming frameworks for applications in the application layer, including various components and services to support developers' Android development. The application framework layer includes some predefined functions. Figure 2 As shown, the application framework layer may include a battery service module, etc.

[0114] The hardware abstraction layer may include a battery interface for abstracting the battery hardware and providing a battery interface for upper-layer applications.

[0115] The kernel layer is the layer between hardware and software. The kernel layer may include battery driver, hardware circuit for driving the battery.

[0116] Understandably, Figure 2 The components included in the software architecture shown do not constitute a specific limitation on the electronic device 100. In other embodiments of the present application, the electronic device 100 may include more or fewer components than shown, or combine some components, or split some components, or arrange the components differently.

[0117] At present, electronic devices usually have multiple charging modes, and different charging modes have different charging parameters, such as charging power, charging current, charging voltage, and charging speed.

[0118] For ease of explanation, the embodiments of the present application take three charging modes, namely normal charging, super fast charging and extreme fast charging, as examples for explanation.

[0119] Among them, the charging power of the three charging modes is from high to low, namely, ultra-fast charging, super-fast charging, and normal charging. It can be understood that the charging current / charging voltage of the three charging modes is from high to low, namely, ultra-fast charging, super-fast charging, and normal charging. The charging speed of the three charging modes is from high to low, namely, ultra-fast charging, super-fast charging, and normal charging.

[0120] It should be noted that normal fast charging can also be called normal charging, fast charging or the first charging mode, etc., super fast charging can also be called super charging, flash charging or the second charging mode, etc., and extreme charging can also be called super flash charging, extreme flash charging, turbo or the third charging mode, etc. The embodiments of the present application do not specifically limit the names of different charging modes. In addition, the embodiments of the present application do not limit the number of charging modes that an electronic device has. For example, an electronic device can have three charging modes, such as normal fast charging, super fast charging and extreme charging; an electronic device can also have four charging modes, such as conventional charging, normal fast charging, super fast charging and extreme charging.

[0121] In different charging modes, the charging logo can be different, so that the user can understand the current charging mode through the charging logo.

[0122] For example, see Figure 3 , is a schematic diagram of the charging interface in the locked screen state provided in an embodiment of the present application. As an example and not a limitation, Figure 3 As shown in the figure, from left to right are the charging interface diagrams of normal charging, super fast charging and ultra-fast charging. Figure 3 As shown, when the electronic device is in charging state and in lock screen state, the screen displays the charging logo, including charging bubbles, lightning icons, power logo and display words. Among them, the number of charging bubbles is different in the three charging modes. The more charging bubbles, the faster the charging speed. The lightning icon for normal charging is one lightning, and the lightning icons for super fast charging and ultra-fast charging are double lightning. The words "Max xxw" are displayed under the power logo of super fast charging, indicating that the charging power is XX watts; and the words "Extreme Speed ​​Charging" are displayed under the power logo of ultra-fast charging. In addition, the power logo of normal charging displays the integer "80%", while the power logo of super fast charging and ultra-fast charging displays the decimal "80.65%".

[0123] For another example, see Figure 4 , is a schematic diagram of a desktop charging interface provided in an embodiment of the present application. As an example and not a limitation, Figure 4 As shown in the figure, from left to right are the charging interface diagrams of normal charging, super fast charging and ultra fast charging. Figure 4 As shown, when the electronic device is in a charging state, a charging mark including a lightning icon, a power mark and display words are displayed in the capsule 41 at the top of the interface. Among them, the lightning icon of normal charging is a single lightning, and the words "normal charging" are displayed in the capsule 41; the lightning icon of super fast charging is a double lightning, and the words "super fast charging" are displayed in the capsule 41; the lightning icon of ultra-fast charging is a double lightning, and the words "ultra-fast charging" are displayed in the capsule 41.

[0124] from Figure 3 and Figure 4As can be seen from the example, different charging modes have different charging icons, and users can understand the current charging mode based on the lightning icon or displayed words.

[0125] It should be noted that Figure 3 and Figure 4 This is only an example of a charging interface, and the embodiments of the present application do not specifically limit the form of the charging interface and the charging logo on the charging interface.

[0126] Normally, users are required to manually set or modify the charging mode.

[0127] As an example of manual setting, when the electronic device is in lock screen state, the user can operate the charging icon on the lock screen interface to modify the charging mode.

[0128] like Figure 5 As shown in (a) of FIG. 1 , the user long presses the charging bubble in the charging logo. In response to the user operation, the electronic device switches from super fast charging to ultra fast charging and displays the following: Figure 5 The interface shown in (b).

[0129] As another example of manual settings, users can set the charging mode in the notification bar.

[0130] like Figure 6 As shown in (a) of FIG. 1 , the desktop of the electronic device is displayed with a capsule 61 on the desktop. The capsule 61 displays a charging logo, indicating that the electronic device is currently in a super-fast charging state. The user slides downward from the top of the screen, and in response to the user operation, the electronic device displays a notification bar. Figure 6 As shown in (b) of FIG. 1 , the interface of the notification bar displays a setting window 62 for ultra-fast charging. When the user clicks “Enable this time” in the setting window 62, in response to the user operation, the electronic device switches from super-fast charging to ultra-fast charging and displays the following information: Figure 6 The interface shown in (c) in the figure. Figure 6 As shown in (c), it is the desktop of the electronic device. The capsule 63 on the desktop displays a charging mark, indicating that the electronic device is currently in a fast charging state.

[0131] As another example of manual settings, users can set the charging mode in the Settings app.

[0132] like Figure 7As shown in (a) of the figure, it is the desktop of the electronic device, on which a capsule 71 is displayed, and a charging logo is displayed in the capsule 71, indicating that the electronic device is currently in a super-fast charging state. An icon 72 of the setting application is displayed on the desktop. When the user clicks the application 72, in response to the user operation, the electronic device enters the setting application; when the user selects a button related to the ultra-fast charging setting (such as a "battery" button, a "charging setting" button, etc.) in the setting application, in response to the user operation, the electronic device displays the following Figure 7 The setting interface shown in (b) is shown in the figure. Figure 7 As shown in (b) of FIG. 1 , the setting interface of the super-fast charging may include a switch button 73 for turning on / off super-fast charging, a switch button 74 for setting the power of super-fast charging, and an input box 75 for setting the power. When the user clicks the switch button 73 to turn on the switch button 73, the electronic device switches from super charging to super-fast charging in response to the user operation; when the user returns to the desktop through the operation, the electronic device displays the following Figure 7 In the interface shown in (c), a capsule 76 is displayed on the desktop, and a charging logo is displayed in the capsule 76, indicating that the current electronic device is in a high-speed charging state.

[0133] After the user clicks the switch button 74 and enters the power value in the input box 75, in response to the user operation, the electronic device starts the ultra-fast charging according to the power value in the input box 75. For example, assuming that the power value in the input box 75 is 20%, the electronic device monitors the power in the charging state, and if the power is less than or equal to 20%, the electronic device starts the ultra-fast charging. Figure 5 and Figure 6 It can be seen that users need to manually set the charging mode, and electronic devices cannot automatically start high-speed charging. Figure 7 In the application scenario shown, although the electronic device can automatically start ultra-fast charging according to the start-up conditions (i.e., power value) for ultra-fast charging after the user sets the start-up conditions for ultra-fast charging, this method still requires user intervention and has a low degree of intelligence.

[0134] Based on this, an embodiment of the present application provides a charging management method, whereby the electronic device can determine the user's charging scenario based on the charging data, and automatically set the charging method according to the charging scenario, thereby effectively improving the intelligence level of the electronic device's charging and improving the user experience.

[0135] First, we will introduce three ways to set the charging mode.

[0136] 1. Automatically open

[0137] After the electronic device is connected to the charger, it is charged in normal charging or super fast charging mode. When the electronic device detects that the user needs to charge urgently, it automatically turns on the ultra-fast charging mode, that is, switches from normal charging or super fast charging mode to ultra-fast charging mode.

[0138] For example, see Figure 8 , is a schematic diagram of a scenario of automatically starting high-speed charging provided in an embodiment of the present application. As an example and not a limitation, Figure 8 As shown in (a) in the figure, when the electronic device is connected to the charger, it is charged in the normal charging mode. Figure 8 As shown in (a) and (b) in FIG. 1 , when the electronic device recognizes that it meets the conditions for super-fast charging, it switches from normal charging to super-fast charging. Figure 8 As shown in (b) and (c) in the figure, when the electronic device detects that it is in urgent need of charging, it automatically turns on the ultra-fast charging and switches from super-fast charging to ultra-fast charging ( Figure 8 The interface shown in (b) is the first interface. Figure 8 The interface shown in (c) is the second interface).

[0139] In this scenario, users can manually turn off high-speed charging. Figure 8 As shown in (c) of FIG. 1 , the electronic device displays a capsule 81 (first control) in the ultra-fast charging mode. The capsule 81 includes a charging mark, which is used to indicate that the electronic device is currently in the ultra-fast charging state. When the user clicks the capsule 81, in response to the user operation, the electronic device displays the following Figure 8 The interface shown in (d) (the third interface). Figure 8 As shown in (d) in FIG. 8 , a notification window 82 is displayed on the top of the screen, and the notification window 82 includes a “turn off high-speed charging” button 83 (first button).

[0140] When the user clicks the "turn off ultra-fast charging" button 83, in response to the user operation, the electronic device turns off ultra-fast charging, switches from ultra-fast charging to super-fast charging, and displays the following information: Figure 8 The interface shown in (e) (the fourth interface). Figure 8 The interface shown in (e) shows a capsule 84 , and a charging logo is displayed in the capsule 84 , indicating that the current electronic device is in a super fast charging state.

[0141] In the automatic start mode, the specific implementation method of the electronic device detecting the user's urgent need to charge can be seen below Fig.10 Description in S109 embodiment.

[0142] 2. Recommended to enable

[0143] After the electronic device is connected to the charger, it is charged in normal charging or super fast charging mode. When the electronic device detects low power or recognizes the user's short charging habit, it recommends ultra-fast charging to the user, allowing the user to choose whether to turn on ultra-fast charging.

[0144] For example, see Fig. 9 , is a schematic diagram of a recommended ultra-fast charging scenario provided in an embodiment of the present application. As an example and not a limitation, Fig. 9 As shown in (a) in the figure, when the electronic device is connected to the charger, it is charged in the normal charging mode. Fig. 9 As shown in (a) and (b) in FIG. 1 , when the electronic device recognizes that it meets the conditions for super-fast charging, it switches from normal charging to super-fast charging. Fig. 9 As shown in (b) and (c) in FIG. 1 , when the electronic device detects low battery or recognizes the user's short charging habit, the electronic device recommends ultra-fast charging to the user and displays the following information: Fig. 9 The interface described in (c) (the sixth interface). Fig. 9 The interface shown in (c) includes a notification window 91 , and the notification window 91 includes an “open this time” button 92 (second button) and an “ignore this time” button 93 (third button).

[0145] When the user clicks the "Start this time" button 92, in response to the user operation, the electronic device starts the ultra-fast charging, that is, switches from super fast charging to ultra-fast charging, and displays the following information: Fig. 9 The interface shown in (d) (the seventh interface). Fig. 9 The interface shown in (d) shows a capsule 94 , and a charging logo is displayed in the capsule 94 , indicating that the electronic device is currently in a high-speed charging state.

[0146] When the user clicks the "Ignore this time" button 93, in response to the user operation, the electronic device continues to charge in the super fast charging mode and displays the following information: Fig. 9 The interface shown in (e) in the figure. Fig. 9 The interface shown in (e) shows a capsule 95 , and a charging logo is displayed in the capsule 95 , indicating that the current electronic device is in a super fast charging state.

[0147] In the recommended mode, the specific implementation of electronic devices detecting low battery conditions and identifying users' short-time charging habits can be found in the following Fig.10 Description in S109 embodiment.

[0148] 3. Manual opening

[0149] After the electronic device is connected to the charger, it is charged in normal charging or super fast charging mode. If the electronic device does not detect that the user needs to charge urgently or the battery is low, and does not recognize the user's short-time charging habits, the user needs to manually start super fast charging. For the method of manually starting super fast charging, please refer to Figures 5 to 7 The description in the embodiments will not be repeated here.

[0150] It should be noted that one way to switch the charging mode is as follows: Figure 8 and Fig. 9 In the embodiment, the normal charging is switched to the super charging, and then the super charging is switched to the ultra-fast charging. In other words, in this switching mode, after the electronic device enters the super charging mode, it performs the steps of detecting the user's urgent need to charge, low battery, and identifying the user's short-time charging habits.

[0151] Another way to switch the charging mode is to switch from normal charging to ultra-fast charging. In other words, under this switching mode, after the electronic device enters the normal charging mode, it can execute the steps of detecting the user's urgent need to charge, low battery, and identifying the user's short-time charging habits. When the electronic device detects that the user is in urgent need of charging in the normal charging mode, it switches from normal charging to ultra-fast charging without going through the super charging mode. When the electronic device detects low battery or identifies the user's short-time charging habits in the normal charging mode, it recommends ultra-fast charging to the user. After the user turns on ultra-fast charging, the electronic device switches from normal charging to ultra-fast charging.

[0152] The following is an introduction to the charging control method provided by the implementation of this application based on the above three settings.

[0153] The charging control method provided in the embodiment of the present application involves two processes, namely, a training process and a setting process. The training process is used to train the recognition model, and the trained recognition model is used to identify the user's short-time charging habits. The setting process refers to the process of setting the charging mode.

[0154] For ease of explanation, the training process is first introduced.

[0155] In the embodiment of the present application, the charging control method can be Figure 2 The application program execution of the application program layer in the software architecture shown. For the convenience of explanation, in the embodiments of the present application, the system charging application, the scene perception application and the smart brain application are used as examples for explanation.

[0156] Among them, the system charging application is used to control the charging mode of electronic devices. The scene perception application is used to identify the user's travel scenarios, such as flight itineraries, train itineraries, taxi itineraries, commuting itineraries, and movie itineraries. The smart brain application is used to train the recognition model and identify the user's short-term charging habits based on the charging data.

[0157] It should be noted that in the embodiment of the present application, in order to facilitate distinction, the above three applications are given different names, and the names of the applications involving the charging control method are not specifically limited, and can also be distinguished by the first application, the second application, and the third application. In addition, three applications are used for illustration in order to distinguish different tasks in charging control. In actual applications, the charging control tasks of the above three applications can also be performed by one, two or more applications, and the embodiment of the present application does not specifically limit this.

[0158] For example, see Fig.10 , is a schematic diagram of the interaction process provided in the embodiment of the present application. As an example and not a limitation, Fig.10 As shown, the training process may include the following steps:

[0159] S101, when the electronic device is connected to the charger, the system charging application obtains the charging data of this charging.

[0160] Optionally, the charging data may include start data when charging starts and end data when charging ends. The start data may include start time, charging date, start power, start temperature, charger type, and identification information indicating whether it is a working day. The end data may include end time (time when the charger is disconnected), full charge time (time when fully charged), and end power.

[0161] It is understandable that the user's charging habits are closely related to the charging time each time. Therefore, training the recognition model based on the charging time (start time, end time and full charging time) can more accurately reflect the user's charging habits.

[0162] There is an intrinsic connection between the user's charging habits and the starting power and starting temperature. For example, when the starting power is low, the user may take a long time to charge or need to charge very quickly; when the starting temperature is high, the user may take a short time to charge or do not need to charge very quickly, etc. Therefore, using the starting power and starting temperature as input variables for the training model enables the model to better learn the user's charging habits, thereby being able to more accurately identify the user's charging habits.

[0163] Information such as whether it is a weekday and the type of charger can also indirectly reflect the user's charging habits. For example, users usually charge at high speed on weekdays, but often use super-fast charging on non-working days. For another example, when users use a high-power charger, they usually use high-speed charging, and when using a normal-power charger, they usually use super-fast charging. Therefore, using information such as whether it is a weekday and the type of charger as input variables for the training model enables the model to better learn the user's charging habits, and thus to more accurately identify the user's charging habits.

[0164] In some implementations, when the electronic device is connected to the charger, the system charging application obtains the current start data and monitors the connection status between the charger and the electronic device; when it is detected that the electronic device is disconnected from the charger, the system charging application obtains the current end data, and then packages the start data and end data into the charging data for this charging, and sends it to the scene perception application.

[0165] by Figure 2 Taking the software architecture shown in the figure as an example, the system charging application can issue acquisition instructions for acquiring charging data through the battery service module of the application framework layer, the battery interface of the hardware abstraction layer, and the battery driver of the kernel layer in sequence. Correspondingly, the battery hardware circuit reports charging data to the system charging application through the battery driver of the kernel layer, the battery interface of the hardware abstraction layer, and the battery service module of the application framework layer in sequence.

[0166] S102, the system charging application sends the current charging data to the scene perception application.

[0167] S103, the scene perception application identifies the scene information of this charging.

[0168] Steps S103 and S102 may be performed in any order.

[0169] The scenario information may include travel information related to the current charging, etc. The travel information may include commuting information, flight time, train date, ticket information, taxi reservation information, home location, etc. Commuting information may include working hours, leaving hours, company location, etc.

[0170] Scenario-aware applications can interact with other applications to obtain scenario information. For example, scenario-aware applications can interact with taxi-hailing applications to obtain the user's taxi reservation information. Scenario-aware applications can interact with ticketing applications to obtain ticketing information. Scenario-aware applications can interact with clock-in applications to obtain the user's clock-in information, thereby obtaining the commuting time and company location, etc.

[0171] S104, the scene perception application sends the charging data and scene information of this charging to the smart brain application.

[0172] In one implementation, the scene perception application packages the charging data and scene information of the current charging and sends them to the smart brain application.

[0173] In another implementation, the system charging application and the scene perception application send the charging data and scene information with the charging number to the smart brain application respectively. Correspondingly, after receiving the charging data and scene data, the smart brain application generates a set of sample data (historical charging data) from the charging data and scene information belonging to the same charging process according to the charging number.

[0174] S105, after triggering the training, the smart brain application trains the recognition model based on the charging data and scene information of at least one charging that has been received.

[0175] As described in S104, the charging data and scene information corresponding to one charging process are a set of sample data.

[0176] Among them, training can be triggered according to a preset cycle, such as once a day, every week or every month; training can also be triggered when the number of groups of sample data received reaches a preset number; training can also be triggered after new sample data is received after each charging.

[0177] Since the training process of the recognition model is an internal implementation of the system, it is inconvenient for humans to participate in the process, that is, it is impossible to manually annotate sample data. Based on this, the embodiment of the present application provides a training method that can automatically annotate sample data according to preset conditions. Specifically, the smart brain application determines whether the sample data meets the preset conditions; if it does, the sample data is annotated with a first label, indicating that it complies with the short-time charging habit; if it does not, the sample data is annotated with a second label, indicating that it does not comply with the short-time charging habit. Input multiple groups of sample data into the recognition model, and output the predicted label for each group of sample data; calculate the loss value based on the predicted label and the true label (such as the annotated first label or second label) of the same group of sample data; adjust the parameters of the recognition model according to the loss value until the prediction accuracy of the recognition model reaches the preset accuracy, and obtain the trained recognition model.

[0178] The preset condition may be a combination of multiple conditions. For example, the preset condition is condition 1 and condition 2, where condition 1 is that the charging time (the interval between the end time and the start time) is less than X minutes, and condition 2 is that the duration of full charge (the interval between the end time and the full charge time) is less than Y minutes. Specific examples are shown in Table 1 below:

[0179] Table 1

[0180]

[0181] Assume X=10, Y=5. As shown in Table 1 above, in the first group of sample data, the start time is 15:30 and the end time is 15:35. The calculated charging time is 5 minutes, which is less than X=10, and meets condition 1; the full charge time is 0, which means that it is not fully charged when the charger is disconnected. The calculated duration of full charge is 0, which is less than Y=5, and meets condition 2; both conditions 1 and 2 are met, that is, the preset conditions are met, and the first label is set to 1 for this group of sample data. In the second group of sample data, the start time is 15:30 and the end time is 16:00. The calculated charging time is 30 minutes, which is greater than X=10, and does not meet condition 1; the full charge time is 15:45, and the calculated duration of full charge is 15 minutes, which is greater than Y=5, and does not meet condition 2; therefore, the second group of sample data does not meet the preset conditions, and the second label is set to 0 for the second group of sample data.

[0182] Continuing with Table 1 above as an example, the end time and full charge time in the sample data are used to mark the labels. Since the real labels are used in the training process, it is equivalent to considering the intrinsic relationship between the end time and full charge time and other charging data. Therefore, during the training process, the start time, starting power and starting temperature in the sample data can be input into the recognition model, without the need to input the data used to mark the expression (such as the end time and full charge time) into the recognition model, thereby effectively reducing the data processing amount of the model and improving the processing efficiency of the model.

[0183] It should be noted that the above table is only an example of preset conditions and labels, and the embodiments of the present application do not specifically limit the form of the preset conditions and labels.

[0184] In some implementations, the scene information and sample data can also be input into the recognition model for training. For example, the location information in the scene information (such as the location of the home, the location of the company, etc.) and the sample data can be input into the recognition model for training. In this way, the recognition model can learn the user's travel information and location information, thereby improving the intelligence of the recognition model.

[0185] Based on the above training process, the setting process is introduced below.

[0186] For example, see Fig.10 ,like Fig.10 As shown, the setup process may include the following steps:

[0187] S106, when the electronic device is connected to the charger, the system charging application obtains the start data of this charging and sends the start data to the scene perception application.

[0188] The start data is the same as the start data described in S101, and the details can refer to the description in S101.

[0189] S107, the scene perception application identifies the scene information of this charging.

[0190] S108, the scene perception application sends the charging data and scene information of this charging to the smart brain application.

[0191] The implementation of steps S107-S108 is the same as that of steps S103-S104, and for details, please refer to the description in the embodiment of steps S103-S104.

[0192] S109, the smart brain application generates a decision result based on the charging data, scene information and trained recognition model of this charging.

[0193] As described in the above embodiment, the three settings correspond to the situation of urgent need for charging, the situation of low battery and the situation of short-time charging habit. Therefore, the smart brain application needs to judge the above three situations.

[0194] For situations where charging is urgently needed, one way to judge is that the smart brain application calculates the time range of the user's itinerary based on the scene information, and determines whether the start time in the charging data is within the time range; if so, it is determined that this charging is within the user's itinerary, that is, this charging is a situation where the user urgently needs to charge; if not, it is determined that this charging is not within the user's itinerary.

[0195] For example, if the ticket information in the scenario information indicates that the flight time is 15:00-17:00, the time range of the user's flight itinerary is calculated to be 13:00-19:00 based on this information. If the start time of this charging is 13:40, within the time range, it is determined that this charging is in the user's itinerary, that is, this charging is in urgent need of charging for the user.

[0196] For another example, assuming that the working time in the scenario information is 08:00, the time range of the user's working trip is calculated to be 07:00-08:00 based on this information. If the start time of this charging is 07:40, within the time range, it is determined that this charging is in the user's trip, that is, this charging is in urgent need of charging for the user.

[0197] For situations where charging is urgently needed, another way to determine is that the scene perception application identifies whether the current charging process is within the user's itinerary based on the scene information of this charging; if it is within the user's itinerary, a third tag is sent to the smart brain; if it is not within the user's itinerary, a fourth tag is sent to the smart brain, indicating that the user is not in urgent need of charging. The smart brain application determines whether the current charging process is within the user's itinerary based on the tags sent by the scene perception application.

[0198] For low battery situations, one way to judge is that the smart brain application determines whether the starting battery level in the start data is less than the preset battery level; if so, it is determined to be a low battery situation.

[0199] For the case of short-time charging habits, one way to judge is that the smart brain application will start inputting data into the trained recognition model, output a predicted label (first label or second label), and judge whether it is a short-time charging habit based on the predicted label.

[0200] For the case of short-time charging habits, another judgment method is that the smart brain application determines whether the charging location is at home or at work based on the location information in the scene information; if at home or at work, the smart brain application inputs the charging data into the trained recognition model, outputs the predicted label (first label or second label), and determines whether it is a short-time charging habit based on the predicted label; if not at home or at work, the smart brain application determines it as other scenarios.

[0201] In the latter judgment method, the charging location is taken into account. Since home and work are the locations where users charge most frequently, the charging data of these two locations can better match the charging habits of users. Therefore, considering the charging location when judging short-term charging habits can effectively improve the accuracy of the judgment results.

[0202] In one implementation of S109, the smart brain application can identify the above-mentioned situations in parallel.

[0203] In another implementation of S109, the smart brain uses serial recognition of the above-mentioned situations. For example, the situation of urgent need for charging is first recognized; if it does not meet the requirements, the low battery situation is then recognized; if it still does not meet the requirements, the short-time charging habit situation is further recognized.

[0204] In the serial recognition method, if the first judged situation is met, there is no need to judge the subsequent situations, which can effectively reduce the judgment steps and thus help improve processing efficiency.

[0205] S110, the smart brain application sends the decision result of this charging to the system charging application.

[0206] In one implementation, the smart brain application can send labels corresponding to various situations as decision results to the system charging application. For example, when the smart brain application identifies that the current charging is in urgent need of charging, a third label is generated as a decision result. When the smart brain application identifies a low battery situation, a fourth label is generated as a decision result. When the smart brain application identifies a short-time charging habit, the first label output by the recognition model is used as a decision result. When the smart brain application identifies other situations, the second label output by the recognition model is used as a decision result.

[0207] S111, the system charging application determines the charging setting method according to the decision result of this charging.

[0208] Exemplarily, several situations in which the intelligent brain application generates decision results are shown in Table 2 below.

[0209] Table 2

[0210]

[0211] As shown in Table 2, the smart brain application can first determine whether the current charging is within the user's itinerary based on the scenario information; if it is within the user's itinerary, it means that the current scenario is in urgent need of charging, and a third tag is generated and sent to the system charging application; accordingly, after the system charging application receives the third tag, it determines that the setting mode is automatically turned on.

[0212] If it is not within the user's itinerary, the smart brain application determines whether it is a low-battery situation based on the starting power in the start data of this charging; if it is, a fourth tag is generated and sent to the system charging application; accordingly, after receiving the fourth tag, the system charging application determines that the setting method is recommended to be turned on.

[0213] If the battery is not low, the Smart Brain application will input the start data of this charging into the trained recognition model and output a predicted label. If the predicted label is the first label, it means that the charging habit is in line with the short-time charging situation. The Smart Brain application will determine whether the charging location is home or work based on the scene information. If it is home or work, the first label will be sent to the system charging application. Accordingly, after receiving the first label, the system charging application will determine that the setting method is recommended to be turned on.

[0214] If the predicted tag is the first tag, but the location of this charging is neither home nor company, the second tag is sent to the system charging application; accordingly, after receiving the second tag, the system charging application determines that the setting mode is manually turned on.

[0215] If the predicted tag is the second tag, indicating other situations, the second tag is sent to the system charging application; accordingly, after receiving the second tag, the system charging application determines that the setting mode is manually turned on.

[0216] It should be noted that the above table is an example of determining the setting method, and the embodiment of the present application does not specifically limit the correspondence between user scenarios and setting methods, the division method of user scenarios, etc.

[0217] As described in the example of Table 2 above, the system charging application can determine the setting mode of the ultra-fast charging according to the tag sent by the smart brain application. In another implementation, the system charging application can also consider the state of the electronic device and determine the setting mode of the ultra-fast charging according to the state of the electronic device and the tag sent by the smart brain application.

[0218] Exemplarily, the state of the electronic device may include temperature and the state of charge of the battery. If the tag sent by the smart brain application is the third tag, and the temperature of the electronic device is lower than the preset temperature and the state of charge is lower than the preset value, the system charging application setting is automatically turned on. If the tag sent by the smart brain application is the third tag, but the temperature of the electronic device is higher than the preset temperature, or the state of charge is greater than the preset value, the system charging application setting is recommended to be turned on.

[0219] If the tag sent by the Smart Brain application is the first tag, and the temperature of the electronic device is lower than the preset temperature, and the state of charge is lower than the preset value, the system charging application setting is recommended to be turned on. If the tag sent by the Smart Brain application is the first tag, but the temperature of the electronic device is higher than the preset temperature, or the state of charge is greater than the preset value, the system charging application setting is manually turned on.

[0220] It is understandable that after turning on ultra-fast charging, the temperature of the electronic device will rise. If the temperature of the current electronic device is already high, do not set automatic start or recommended start. In addition, when the state of charge of the electronic device is greater than the preset value, it means that the battery capacity is sufficient. In this case, ultra-fast charging is usually not required. Therefore, it is not necessary to set automatic start or recommended start.

[0221] Through the above method, combined with the status of the electronic device and the tag sent by the smart brain application, the charging scenario can be judged more accurately, so that a more appropriate setting method can be set, which is conducive to improving the intelligence level of electronic device charging.

[0222] In the embodiment of the present application, the electronic device can judge the user's charging scenario based on the charging data, and automatically set the charging method according to the charging scenario. When charging is urgently needed, the electronic device can automatically start ultra-fast charging; and in the case of low battery and short charging time, the electronic device can recommend to the user to start ultra-fast charging. Through the above method, the intelligent level of electronic device charging is effectively improved, which is conducive to improving the user experience.

[0223] In order to improve user experience, in some embodiments, a user feedback mechanism may be designed in the system charging application to adaptively set the charging mode according to user feedback operations.

[0224] As an example of a feedback mechanism, see Fig.11 , is a schematic diagram of a charging mode setting scenario provided in an embodiment of the present application. As an example and not a limitation, Fig.11 As shown, for the automatic start setting mode, if the electronic device performs N1 automatic starts, and the user manually turns it off m1 times (the first number), the system charging application is set to recommend start the next time it recognizes an urgent need for charging. Where N1 is an integer greater than m1, and m1 is a positive integer.

[0225] For example, in the automatic start setting mode, if the user manually turns off the automatic start of high-speed charging for 2 out of 3 times, the system charging application is set to recommend starting the next time it recognizes an urgent need for charging, as shown in the display Fig. 9 The interface shown in (c).

[0226] In one implementation, for the automatic start-up setting, it can be set that if the user turns off the automatic start-up for m1 times in a row, the system charging application is set to be recommended to be turned on the next time an urgent need for charging is identified.

[0227] For the recommended start-up setting, if the electronic device performs the recommended start-up N2 times, and the user ignores m2 times (the third number), or the user does not perform any operation for N2 times (meaning that the ultra-fast charging is not turned on and not ignored), then the system charging application is set to manual start the next time it recognizes low battery or short charging habits. For example, for the manual start-up setting, you can use Figure 5 , Figure 6 or Figure 7 to set it.

[0228] For the recommended activation setting, if the electronic device performs the recommended activation N3 times, and the user activates the ultra-fast charging m3 times (the second time), the system charging application setting will automatically activate when low battery or short-time charging habits are detected next time, as shown in the display Figure 8 The interface shown in (d).

[0229] Wherein, N2 is an integer greater than m2, m2 is a positive integer, N3 is an integer greater than m3, m3 is a positive integer.

[0230] For example, if the electronic device performs the recommended activation 3 times, and the user ignores it 2 times, or the user does not activate the ultra-fast charging 3 times, the system charging application is set to be manually activated the next time the low battery or short charging habit is detected. If the electronic device performs the recommended activation 5 times, and the user activates the ultra-fast charging 3 times, the system charging application is set to be automatically activated the next time the low battery or short charging habit is detected.

[0231] In one implementation, for the recommended activation setting, it can be set that if the user ignores the recommended activation for m2 consecutive times, the system charging application is set to be manually activated the next time low battery or short charging habits are detected. If the user activates high-speed charging for m3 consecutive times, the system charging application is set to be automatically activated the next time low battery or short charging habits are detected.

[0232] For the manual start setting, the system charging application can set the recommended start at a fixed time, or, when the user manually starts N4 times of ultra-fast charging, the system charging application sets the recommended start next time when low battery, short charging habits, or urgent charging are detected, where N4 is a positive integer.

[0233] In one implementation, after a period of time has passed since the recommended on-state was switched to manual on-state, if the user manually turns on ultra-fast charging, the next time low battery, short charging habits, or urgent charging are detected, the system charging application setting is recommended to be turned on. For example, if it is recommended to be turned on 4 times, but the user turns it off 4 times, then it will be switched to manual on-state; one month after the recommended on-state was switched to manual on-state, if the user manually turns on ultra-fast charging, the next time low battery, short charging habits, or urgent charging are detected, the system charging application setting is recommended to be turned on.

[0234] In one implementation, for the manual activation setting, it can be set that if the user turns on ultra-fast charging for N4 consecutive times, the system charging application setting will be recommended to be turned on the next time low battery, short charging habits or urgent charging is detected.

[0235] In some cases, if the conditions for automatic opening are met in the manual opening mode, the manual opening mode can be switched to the automatic opening mode. If the conditions for recommended opening are met in the manual opening mode, but the conditions for automatic opening are not met, the manual opening mode can be switched to the recommended opening mode.

[0236] For example, in the manual activation mode, if the user has activated the ultra-fast charging for m3 consecutive times, that is, the conditions for automatic activation are met, then the system charging application setting will be automatically activated the next time low battery, short charging habits, or urgent charging are detected. In the manual activation mode, if the user has activated the ultra-fast charging for N4 consecutive times, but N4 is less than m3, that is, the conditions for recommended activation are met, but the conditions for automatic activation are not met, then the system charging application setting will be recommended to be activated the next time low battery, short charging habits, or urgent charging are detected.

[0237] In other cases, if the conditions for automatic activation are met in manual activation, the mode can be switched from manual activation to recommended activation; if the conditions for automatic activation are met in recommended activation, the mode can be switched from recommended activation to automatic activation.

[0238] It is understood that in the above example, the electronic device performs 1 automatic start, which means that when the electronic device detects an urgent need for charging, the electronic device automatically starts ultra-fast charging. The electronic device performs 1 recommended start, which means that when the electronic device detects low battery or recognizes a short charging habit, the electronic device recommends starting ultra-fast charging.

[0239] Optionally, each time the electronic device determines the setting mode, a corresponding prompt message may be sent to the user.

[0240] For example, every time an electronic device is set to automatically turn on, the user can be prompted that "according to your charging needs, ultra-fast charging has been intelligently turned on." Every time an electronic device is set to recommend turning on, the user can be prompted that "according to your charging needs, it is recommended to turn on ultra-fast charging."

[0241] It should be noted that Fig.11 This is only one implementation of the feedback mechanism. In actual applications, different feedback mechanisms can be set according to different needs, and the embodiments of the present application do not make specific limitations on this.

[0242] In the embodiment of the present application, through the feedback mechanism, after each setting mode is determined, the user operation can be recorded, and the setting mode can be adaptively adjusted by analyzing the user operation. In this way, the charging setting mode is more in line with user habits, effectively improving the intelligent level of electronic device charging and improving user experience.

[0243] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0244] The embodiment of the present application further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed on an electronic device, the steps in the above-mentioned method embodiments can be implemented.

[0245] The embodiment of the present application also provides a computer program product. When the computer program product is run on an electronic device or a wireless router, the electronic device can implement the steps in the above-mentioned various method embodiments.

[0246] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may at least include: any entity or device that can carry the computer program code to the first device, a recording medium, a computer memory, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), an electric carrier signal, a telecommunication signal, and a software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0247] The embodiment of the present application further provides a chip, the chip includes a processor, the processor is coupled to a memory, and the processor calls a computer program stored in the memory to implement the steps of any method embodiment of the present application. The chip can be a single chip or a chip module composed of multiple chips.

[0248] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0249] Those of ordinary skill in the art will appreciate that the units and method steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0250] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A charging control method, characterized in that: include: At a first time point after the electronic device is connected to the charger, the charging power of the electronic device is set to a first power, and a first interface is displayed; wherein the first interface includes information indicating that the electronic device is charged at the first power; After the first time point, identifying scene information of this charging; the scene information includes travel information related to this charging; the scene information is obtained from at least one application of the electronic device; Generate a decision result according to the scene information of this charging, the start data of this charging and the trained recognition model; wherein the recognition model is trained according to the historical charging data; the start data is the charging data when the electronic device is connected to the charger; the decision result includes a scene of short-time charging habit, a scene of urgent charging and a scene of low battery; Determining a charging setting mode according to the decision result, wherein the setting mode includes automatic start, recommended start and manual start; If the decision result is a scenario where charging is urgently needed, determining that the setting mode is automatically turned on; If the setting mode is to turn on automatically, the charging power of the electronic device is set to a second power, and a second interface is displayed; wherein the second interface includes information indicating that the electronic device is charged at the second power, and the second power is greater than the first power.

2. The method according to claim 1, characterized in that The second interface includes a first control; the method further includes: In response to a user operation on the first control, a third interface is displayed; the third interface includes a first button; In response to the user's operation of the first button, the charging power of the electronic device is set to the first power, and a fourth interface is displayed; wherein the fourth interface includes information indicating that the electronic device is charged at the first power.

3. The method according to claim 2, characterized in that The method further comprises: When the number of the first operation reaches the first number, after the first time point, if it is determined that the current time is within the travel time period, a fifth interface is displayed, and the fifth interface includes information prompting to set the second power; The first operation is to set the charging power of the electronic device to the first power in response to a user's operation of the first button when the electronic device is charged at the second power.

4. The method according to claim 1, characterized in that: The method further comprises: After the first time point, if it is determined that the current time is not within the travel time period and the first condition is met, a sixth interface is displayed, the sixth interface including information prompting to set the second power; The first condition includes that the power of the electronic device when connected to the charger is lower than a preset power, or the predicted charging time is shorter than a preset time.

5. The method according to claim 4, characterized in that The sixth interface includes a second button and a third button; The method further comprises: If the user operates the second button, in response to the user's operation of the second button, the charging power of the electronic device is set to the second power, and a seventh interface is displayed; wherein the seventh interface includes the information indicating that the electronic device is charged at the second power; If the user operates the third button, in response to the user operation on the third button, charging is continued at the first power.

6. The method according to claim 5, characterized in that The method further comprises: When the number of the second operation reaches the second number, after the first time point, if it is determined that the current time is not within the travel time period and the first condition is met, setting the power of the electronic device to the second power; The second operation is to set the charging power of the electronic device to the second power in response to a user's operation on the second button when the electronic device is charged at the first power.

7. The method according to claim 5, characterized in that The method further comprises: When the number of the third operation reaches the third number, after the first time point, if it is determined that the current time is not within the travel time period and the first condition is met, charging is continued at the first power; The third operation is to keep charging at the first power in response to a user's operation on the third button when the electronic device is charged at the first power.

8. The method according to claim 4, characterized in that The method further comprises: Acquiring start data, wherein the start data is charging data when the electronic device is connected to the charger; The charging time is predicted according to the starting data and the trained recognition model; wherein the recognition model is trained according to historical charging data.

9. The method according to claim 8, characterized in that The predicting of charging duration according to the start data and the trained recognition model includes: Acquiring location information of the electronic device when it is connected to the charger; If the location information is a preset location, the charging time is predicted based on the start data and the trained recognition model.

10. The method according to claim 8, characterized in that The method further comprises: Acquire historical charging data; the historical charging data includes time data and non-time data; Setting a real label of the historical charging data according to the time data; wherein the real label includes a first label and a second label, the first label indicates that the charging time corresponding to the historical charging data is less than a preset time, and the second label indicates that the charging time corresponding to the historical charging data is greater than or equal to the preset time; The recognition model is trained according to the historical charging data and the real labels of the historical charging data to obtain a trained recognition model.

11. The method according to claim 1, characterized in that: The method further comprises: After the first time point, if it is determined that the current time is not within the travel time period and a second condition is met, then charging is continued at the first power; The second condition includes that the power level of the electronic device when connected to the charger is not less than a preset power level, and the predicted charging time is not less than a preset time.

12. The method according to claim 1, characterized in that The method further comprises: At a second time point after the electronic device is connected to the charger, the charging power of the electronic device is set to a third power; wherein the second time point is before the first time point, and the third power is less than the first power.

13. An electronic device, characterized in that: The electronic device comprises a processor, and the processor is used to run a computer program stored in a memory to implement the method according to any one of claims 1 to 12.

14. A chip system, characterized in that: The chip system includes a processor coupled to a memory, and the processor is used to run a computer program stored in the memory to implement the method according to any one of claims 1 to 12.

15. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by one or more processors, the method according to any one of claims 1 to 12 is implemented.

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