Battery Control Method, Device and Storage Medium

Abstract

The present disclosure relates to a battery control method, device and storage medium, including: obtaining battery usage data of a battery in a target terminal in a first target period; determining the battery capacity decay rate of the battery in a second target period according to the battery usage data; and determining the battery discharge cut-off voltage corresponding to the battery capacity decay rate as the target discharge cut-off voltage in the second target period. The battery capacity decay rate that may occur in the next period of time is predicted by obtaining the historical usage data corresponding to the battery in the target terminal, and the discharge cut-off voltage of the battery in the next period of time is determined according to the predicted battery capacity decay rate. In this way, the battery aging can be prevented in a targeted manner according to the actual usage of the battery by the target terminal, further improving the effect of preventing aging.

Description

Technical Field

[0001] The present disclosure relates to the field of batteries, and in particular, to a battery control method, apparatus, and storage medium. Background Art

[0002] In the related art, battery discharge control is usually used to slow down battery aging. Among them, most control schemes set the discharge cut-off voltage of the battery at different ambient temperatures based on empirical values at the initial stage of the battery discharge control design, and the discharge cut-off voltage is a fixed value. However, different user usage behaviors and usage environments will result in different battery aging characteristics. For different battery aging characteristics and different user usage behaviors, the fixed discharge cut-off voltage cannot meet the requirement of slowing down battery aging, and may even accelerate the battery aging trend. For example, when the battery of a user's mobile phone is in a low-temperature environment for a long time and has gone through more than 200 cycles, if the same charging strategy as under normal usage conditions is still adopted, it will lead to accelerated battery aging. Moreover, when the battery aging degree is relatively high, problems such as battery swelling that can sharply shorten the battery service life may even occur, and even affect the battery usage safety. Summary of the Invention

[0003] To overcome the problems in the related art, the present disclosure provides a battery control method, apparatus, and storage medium.

[0004] According to a first aspect of an embodiment of the present disclosure, a battery control method is provided, including

[0005] Obtaining battery usage data of a battery in a target terminal during a first target period;

[0006] Determining a battery capacity attenuation rate of the battery during a second target period according to the battery usage data;

[0007] Determining a battery discharge cut-off voltage corresponding to the battery capacity attenuation rate as a target discharge cut-off voltage during the second target period.

[0008] Optionally, the determining the battery capacity attenuation rate of the battery during the second target period according to the battery usage data includes:

[0009] Inputting the battery usage data into a pre-trained regression model according to the battery cell system of the battery to obtain the battery capacity attenuation rate of the battery during the second target period;

[0010] Wherein, the regression model is trained by actual usage data and actual battery capacity attenuation rates of other batteries with the same battery cell system as the battery.

[0011] Optionally, the battery usage data and the actual usage data include the external environmental temperature of the battery and the number of charge-discharge cycles of the battery.

[0012] Optionally, the number of days included in the first target period is not less than 1, the battery usage data is the battery usage data corresponding to each day in the first target period, and the battery capacity attenuation rate is the battery capacity attenuation rate corresponding to each day in the second target period.

[0013] Optionally, the regression model is a neural network classifier.

[0014] Optionally, determining the battery discharge cut-off voltage corresponding to the battery capacity attenuation rate as the target discharge cut-off voltage within the second target period includes:

[0015] Determining the target attenuation rate interval in which the battery capacity attenuation rate is located;

[0016] Determining the battery discharge cut-off voltage corresponding to the target attenuation rate interval as the target discharge cut-off voltage within the second target period.

[0017] According to a second aspect of the embodiments of the present disclosure, there is provided a battery control device, including:

[0018] A first acquisition module, configured to acquire battery usage data of a battery in a target terminal during a first target period;

[0019] A first determination module, configured to determine a battery capacity attenuation rate of the battery during a second target period according to the battery usage data;

[0020] A second determination module, configured to determine the battery discharge cut-off voltage corresponding to the second battery capacity attenuation rate as the target discharge cut-off voltage within the second target period.

[0021] Optionally, the first determination module is further configured to:

[0022] Input the battery usage data into a pre-trained regression model according to the cell system of the battery, so as to obtain the battery capacity attenuation rate of the battery during the second target period;

[0023] Wherein, the regression model is trained by the actual usage data and the actual battery capacity attenuation rate of other batteries with the same cell system as the battery.

[0024] Optionally, the battery usage data and the actual usage data include the external environmental temperature of the battery and the number of charge-discharge cycles of the battery.

[0025] Optionally, the number of days included in the first target period is not less than 1, the battery usage data is the battery usage data corresponding to each day in the first target period, and the battery capacity decay rate is the battery capacity decay rate corresponding to each day in the second target period.

[0026] Optionally, the regression model is a neural network classifier.

[0027] Optionally, the second determining module includes:

[0028] A first determination submodule is configured to determine a target decay rate interval in which the battery capacity decay rate is located;

[0029] The second determination submodule is configured to determine the battery discharge cut-off voltage corresponding to the target decay rate interval as the target discharge cut-off voltage within the second target time period.

[0030] According to a third aspect of an embodiment of the present disclosure, there is provided a battery control device, including:

[0031] processor;

[0032] a memory for storing processor-executable instructions;

[0033] Wherein, the processor is configured to:

[0034] Acquire battery usage data of a battery in a target terminal during a first target period;

[0035] Determine a battery capacity decay rate of the battery within a second target time period according to the battery usage data;

[0036] A battery discharge cut-off voltage corresponding to the battery capacity decay rate is determined as a target discharge cut-off voltage within the second target period.

[0037] According to a fourth aspect of an embodiment of the present disclosure, a computer-readable storage medium is provided, on which computer program instructions are stored. When the program instructions are executed by a processor, the steps of the battery control method provided in the first aspect of the present disclosure are implemented.

[0038] The technical solution provided by the embodiments of the present disclosure may have the following beneficial effects:

[0039] By acquiring the historical usage data corresponding to the battery in the target terminal, the battery capacity decay rate that may occur in the next period of time is predicted, and the discharge cut-off voltage of the battery in the next period of time is determined based on the predicted battery capacity decay rate. In this way, battery aging can be prevented in a targeted manner according to the actual usage of the battery by the target terminal, further improving the effect of aging prevention.

[0040] It should be understood that the above general description and the following detailed description are merely exemplary and explanatory, and should not limit the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The drawings herein are incorporated into and constitute a part of this specification, showing embodiments consistent with the present disclosure, and are used together with the specification to explain the principles of the present disclosure.

[0042] Figure 1 FIG. is an application scenario diagram of a battery control method shown according to an exemplary embodiment of the present disclosure.

[0043] Figure 2 FIG. is a flowchart of a battery control method shown according to an exemplary embodiment.

[0044] Figure 3 FIG. is a flowchart of a battery control method shown according to another exemplary embodiment.

[0045] Figure 4 FIG. is a flowchart of a battery control method shown according to another exemplary embodiment.

[0046] Figure 5 FIG. is a structural block diagram of a battery control device shown according to an exemplary embodiment.

[0047] Figure 6 FIG. is a block diagram of a device shown according to an exemplary embodiment.

[0048] Figure 7 FIG. is a block diagram of a device shown according to an exemplary embodiment. DETAILED DESCRIPTION

[0049] Exemplary embodiments will be described in detail herein, and examples thereof are shown in the drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0050] Figure 1 FIG. is an application scenario diagram of a battery control method shown according to an exemplary embodiment of the present disclosure. As Figure 1As shown, this battery control method can be applied to the terminal 1 and the cloud server 7. Among them, the terminal 1 may include a first network system 2, a first storage system 3, a first processing system 4, a charging system 5, and a battery management system 6. The cloud server 7 may include a central database system 8, a data collection and synchronization system 9, a network management center 10, a backbone network 11, and multiple management servers 12. Each management server 12 may further include a second network system 13, a second storage system 14, a second processing system 15, and a data input / output unit 16.

[0051] The battery usage data generated during the use of the terminal 1 and the battery capacity attenuation rate corresponding to the battery usage data can be saved in the first storage system 3 after being generated and calculated. Then, the first processing system 4 in the terminal 1 retrieves it from the first storage system 3 and sends it to the second network system 13 in the management server 12 in the cloud server 7 through the first network system 2. Among them, the battery usage data may include the external environmental temperature of the battery and the number of battery cycles; the battery usage data can be recorded on a daily basis; for example, the external environmental temperature of the battery can be the median or average value of all the temperatures detected by the temperature detector used to detect the external environment of the battery on October 1, 2020. The number of battery cycles can be the cumulative number of cycles that the battery has undergone by the end of October 1, 2020. The number of cycles is also the number of times the battery reaches a complete charge-discharge cycle; then the battery usage data can include the external environmental temperature of the battery corresponding to October 1, 2020 and the number of battery cycles of the battery. In addition, the terminal 1 can also estimate the battery capacity of the battery through the information of the battery voltage, voltage, temperature, and impedance monitored by the battery management system 6, and further convert it into a battery capacity attenuation rate. The battery capacity attenuation rate is the degree of attenuation of the current battery capacity relative to the total battery capacity and is stored in the first storage system 3. The battery capacity attenuation rate can also be estimated on a daily basis. In this way, the terminal 1 can obtain the battery usage data for each day and the battery capacity attenuation rate corresponding to the battery usage data. The battery capacity attenuation rate can also be sent to the management server 12 in the cloud server 7 through the same transmission method as the battery usage data.

[0052] After receiving the battery usage data sent by the terminal 1, the management server 12 may store it in the second storage system 14, or directly input it into the second processing system 15 through the data input / output unit 16 for processing, so as to obtain the target discharge cut-off voltage for controlling the battery in the terminal 1, and output it to the second network system 13. It is sent to the terminal 1 through the connection between the second network system 13 and the first network system 2 in the terminal 1, so that the charging system 5 and the battery management system 6 in the terminal 1 can control the battery in the terminal 1 according to the target discharge cut-off voltage.

[0053] In addition, the management server 12 may also upload the battery usage data obtained from the terminal 1 and the corresponding battery capacity attenuation rate to the backbone network 11, and save them in the central database system 8 through the network management center 10. The battery usage data and battery capacity attenuation rate of all terminals saved in the central database system 8 can be synchronized to each management server 12 through the data collection and synchronization system 9, so that each management server 12 can obtain the battery usage data and the corresponding battery capacity attenuation rate generated by a large number of different terminals under different environments and different usage conditions.

[0054] In addition, in a possible implementation manner, the process of determining the target discharge cut-off voltage for controlling the battery in the terminal 1 may also be completed by the first processing system 4 in the terminal 1. The management server 12 may send a large amount of data such as the battery usage data and the corresponding battery capacity attenuation rate generated by various different terminals saved in the cloud server 7 to the terminal 1 through the second network system 13, so that the terminal 1 can determine the target discharge cut-off voltage. However, considering the computational complexity, it is preferably performed in the second processing system 15 in the cloud server 7.

[0055] Figure 2 It is a flowchart of a battery control method shown according to an exemplary embodiment, as Figure 2 shown, including the following steps.

[0056] In step S201, obtain the battery usage data of the battery in the target terminal during the first target period.

[0057] The battery usage data may include, for example, the above-mentioned external environmental temperature and the number of battery cycles. The first target period may be, for example, one day, one week, or one month, etc.

[0058] Among them, when the battery usage data is obtained on a daily basis, the battery usage data is the battery usage data corresponding to each day in the first target period, and the number of days included in the first target period is not less than 1. If the battery usage data is obtained in units of two days, the number of days included in the first target period should be not less than 2, and the battery usage data is the battery usage data corresponding to every two days in the first target period, and so on.

[0059] In step S202, the battery capacity attenuation rate of the battery within the second target period is determined according to the battery usage data. When the battery usage data is obtained on a daily basis, the battery capacity attenuation rate is the battery capacity attenuation rate corresponding to each day in the second target period. For example, when the first target period is from August 1, 2020 to August 10, 2020, and the battery usage data is the battery usage data corresponding to each day in the first target period, the determined battery capacity attenuation rate is the battery capacity attenuation rate of each day in the second target period. The second target period can be any future period, such as from August 11, 2020 to September 1, 2020, or it can also be from October 1, 2020 to October 10, 2020, etc. When the first target period is July, the second target period can be August. The duration included in the second target period is similar to the number of days included in the first target period. When the battery usage data is obtained on a daily basis, the number of days included in the second target period is not less than 1. If the battery usage data is obtained in units of two days, the number of days included in the first target period should be not less than 2.

[0060] The battery usage data is used to represent the characteristics of the usage mode of the battery in the terminal. For example, the external environmental temperature can characterize the temperature characteristics of the terminal, and the number of cycles can characterize the usage habits of the user of the battery in the terminal, etc. By analyzing the battery capacity attenuation rate and its corresponding battery usage data of different terminals of different users, it can be obtained that for most batteries, when the external environmental temperature is lower, the degree of battery capacity attenuation shows an increasing trend, and for most batteries, the number of cycles of the battery is also negatively correlated with the battery capacity, that is, the more the number of cycles of the battery, the more the battery capacity attenuation rate will show an increasing trend. Therefore, in addition to the external environmental temperature and the number of cycles of the battery, the battery usage data can also include other data parameters related to the battery capacity attenuation rate.

[0061] When the battery usage data is obtained, the battery capacity decay rate that may occur in a future period of time, i.e., the second target period, can be predicted based on the temperature characteristics represented by the battery usage data and the battery's habitual characteristics when used by the user.

[0062] In step S203, a battery discharge cut-off voltage corresponding to the battery capacity decay rate is determined as a target discharge cut-off voltage within the second target period.

[0063] The corresponding relationship between the battery capacity attenuation rate and the battery discharge cut-off voltage can be obtained through a preset corresponding relationship table. The corresponding relationship table can be calibration data determined after analyzing and calculating a large amount of sampled data. The calibration data can be recalibrated according to the actual application model.

[0064] After determining the battery discharge cut-off voltage corresponding to the second battery capacity decay rate, the battery discharge cut-off voltage may be determined as the target discharge cut-off voltage within the second target cycle to control the discharge of the battery.

[0065] In a possible implementation, the battery discharge cut-off voltage corresponding to the second battery capacity decay rate can also be determined in the following manner: according to a correspondence table between the second battery capacity decay rate and the cut-off voltage adjustment threshold, the cut-off voltage adjustment threshold corresponding to the second battery capacity decay rate is determined, and then the discharge cut-off voltage adjusted by the cut-off voltage adjustment threshold corresponding to the second battery capacity decay rate is determined as the target cut-off voltage.

[0066] Among them, when the second battery capacity attenuation rate is greater, the target discharge cut-off voltage is higher, and when the second battery capacity attenuation rate is smaller, the target discharge cut-off voltage is lower, but the target discharge cut-off voltage will not exceed the preset safe discharge cut-off voltage range, thereby ensuring the safety of battery discharge.

[0067] By acquiring the historical usage data corresponding to the battery in the target terminal, the battery capacity decay rate that may occur in the next period of time is predicted, and the discharge cut-off voltage of the battery in the next period of time is determined based on the predicted battery capacity decay rate. In this way, battery aging can be prevented in a targeted manner according to the actual usage of the battery by the target terminal, further improving the effect of aging prevention.

[0068] Among them, the above step 201 can be completed by the terminal 1. After the terminal obtains the battery usage data for the target period, it can send the data to the management server 12 in the cloud server 7. Then, the second processing system 15 in the management server 12 can specify step 202 according to the battery usage data. After the management server 12 determines the battery capacity attenuation rate, it can directly send the battery capacity attenuation rate to the terminal 1, so that the first processing system 4 in the terminal 1 executes step 203. Or the second processing system 15 in the management server 12 can directly execute step 203, and then directly send the determined target discharge cut-off voltage to the terminal 1, so that the charging system 5 and the battery management system 6 in the terminal 1 control the discharge cut-off voltage of the battery to be the target discharge cut-off voltage.

[0069] Figure 3 is a flowchart of a battery control method according to another exemplary embodiment of the present disclosure. As Figure 3 shown, the method further includes step 301.

[0070] In step 301, according to the cell system of the battery, the battery usage data is input into a pre-trained regression model to obtain the battery capacity attenuation rate of the battery during the second target period.

[0071] Among them, the regression model is trained by using the actual usage data and the actual battery capacity attenuation rate of other batteries with the same cell system as the battery. That is, through the battery usage data actually generated by other batteries with the same cell system as the battery during use and the battery capacity attenuation rate corresponding to the actually generated battery usage data, a regression model corresponding to the cell system can be obtained through a regression algorithm. The regression model is a model that can characterize the battery capacity attenuation trend of the battery with this cell system.

[0072] The regression model can be trained before step 201. For example, it can be the second processing system 15 in the management server 12, which is trained by a regression algorithm according to a large amount of battery usage data of other batteries obtained from the central database system 8 of the cloud server 7 and the corresponding battery capacity attenuation rate. Moreover, in the second processing system 15, regression models corresponding to multiple different cell systems can be pre-trained, and according to the cell system of the battery corresponding to the battery usage data obtained in step 201, the corresponding regression model can be selected.

[0073] Among them, the regression model can be, for example, a neural network classifier.

[0074] Through the above technical solution, a large amount of battery usage data generated by batteries of different cell systems during actual use can be obtained through the cloud server 7, as well as the actual battery capacity attenuation rate generated when using the battery according to the battery usage data. Several different regression models corresponding to different cell systems, that is, different battery capacity attenuation trends, can be obtained through a regression algorithm. Due to the differences in cell systems, as well as various conditions such as the usage method of the battery and the ambient temperature at which the battery is usually located during use, all of which will affect the battery capacity attenuation rate. Therefore, after training a regression model based on a large amount of usage data, after obtaining the battery usage data of the battery in the terminal in use, the battery capacity attenuation rate of the battery in the terminal can be predicted. In this way, the regression model trained through a large amount of actual data can predict a more accurate battery capacity attenuation rate.

[0075] Figure 4 is a flowchart of a battery control method shown according to another exemplary embodiment of the present disclosure. As Figure 4 shown, the method further includes step 401 and step 402.

[0076] In step 401, determine the target attenuation rate interval in which the battery capacity attenuation rate is located.

[0077] The target attenuation rate interval is any attenuation rate interval in the pre-divided temperature interval in which the battery capacity attenuation rate in the second target period falls.

[0078] In step 402, determine the battery discharge cut-off voltage corresponding to the target attenuation rate interval as the target discharge cut-off voltage within the second target period.

[0079] That is, in addition to directly determining the target discharge cut-off voltage based on the battery capacity attenuation rate in the second target period, the target discharge cut-off voltage can also be determined based on the target attenuation rate interval in which the battery capacity attenuation rate in the second target period is located.

[0080] In addition, when determining the target discharge cut-off voltage according to the target attenuation rate interval in which the battery capacity attenuation rate in the second target period is located, the corresponding cut-off voltage adjustment threshold can also be determined first according to the target attenuation rate interval in which the battery capacity attenuation rate in the second target period is located, and then the battery discharge cut-off voltage adjusted by the cut-off voltage adjustment threshold is determined as the target discharge cut-off voltage. For example, as shown in Table 1 below:

[0081] Table 1

[0082] Target attenuation rate range Cut-off voltage adjustment threshold Target discharge cut-off voltage First interval First threshold Delta1 3.4V - 0.5 * Delta1 Second interval Second threshold Delta2 3.4V - 0.5 * Delta2 Third interval Third threshold Delta3 3.4V - 0.5 * Delta3

[0083] The 3.4V shown in Table 1 also represents the calibrated total voltage of the battery. When the dielectric voltage adjustment threshold is determined according to this target attenuation rate range, the target discharge cut-off voltage can be obtained by adjusting on the basis of this calibrated total voltage.

[0084] Figure 5 It is a structural block diagram of a battery control device shown according to an exemplary embodiment. Referring to Figure 5 , the device includes: a first acquisition module 10 configured to acquire battery usage data of a battery in a target terminal during a first target period; a first determination module 20 configured to determine a battery capacity attenuation rate of the battery during a second target period according to the battery usage data; a second determination module 30 configured to determine the battery discharge cut-off voltage corresponding to the second battery capacity attenuation rate as the target discharge cut-off voltage during the second target period.

[0085] By obtaining the historical usage data corresponding to the battery in the target terminal, the possible battery capacity attenuation rate of the battery in the next period of time is predicted, and the discharge cut-off voltage of the battery in the next period of time is determined according to the predicted battery capacity attenuation rate. In this way, the aging of the battery can be specifically prevented according to the actual usage situation of the battery by the target terminal, and the effect of preventing aging is further improved.

[0086] In a possible implementation manner, the first determination module 20 is further configured to: input the battery usage data into a pre-trained regression model according to the battery cell system of the battery to obtain the battery capacity attenuation rate of the battery during the second target period; wherein, the regression model is trained by the actual usage data and the actual battery capacity attenuation rate of other batteries with the same battery cell system as the battery.

[0087] In a possible implementation manner, the battery usage data and the actual usage data include the external environmental temperature of the battery and the number of battery cycles.

[0088] In a possible implementation manner, the number of days included in the first target period is not less than 1, the battery usage data is the battery usage data corresponding to each day in the first target period, and the battery capacity attenuation rate is the battery capacity attenuation rate corresponding to each day in the second target period.

[0089] In a possible implementation manner, the regression model is a neural network classifier.

[0090] In a possible implementation, the second determination module 30 includes: a first determination sub-module configured to determine a target decay rate interval in which the battery capacity decay rate is located; a second determination sub-module configured to determine the battery discharge cut-off voltage corresponding to the target decay rate interval as the target discharge cut-off voltage during the second target period.

[0091] In a possible implementation, the present disclosure further provides a battery control device, including: a processor; a memory for storing processor-executable instructions; wherein, the processor is configured to: obtain battery usage data of a battery in a first target period in a target terminal; determine a battery capacity decay rate of the battery during a second target period according to the battery usage data; and determine the battery discharge cut-off voltage corresponding to the battery capacity decay rate as the target discharge cut-off voltage during the second target period.

[0092] Regarding the device in the above embodiments, the specific manners in which each module performs operations have been described in detail in the embodiments related to the method, and will not be elaborated herein.

[0093] Figure 6 FIG. 600 is a block diagram of a device 600 for battery control according to an exemplary embodiment. For example, the device 600 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

[0094] Referring to Figure 6 , the device 600 may include one or more of the following components: a processing component 602, a memory 604, a power component 606, a multimedia component 608, an audio component 610, an input / output (I / O) interface 612, a sensor component 614, and a communication component 616.

[0095] The processing component 602 generally controls the overall operation of the device 600, such as operations associated with display, telephone call, data communication, camera operation, and recording operation. The processing component 602 may include one or more processors 620 to execute instructions to complete all or part of the steps of the above battery control method. In addition, the processing component 602 may include one or more modules to facilitate the interaction between the processing component 602 and other components. For example, the processing component 602 may include a multimedia module to facilitate the interaction between the multimedia component 608 and the processing component 602.

[0096] The memory 604 is configured to store various types of data to support the operation of the device 600. Examples of such data include instructions for any application or method operating on the device 600, contact data, phone book data, messages, pictures, videos, and the like. The memory 604 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, a magnetic disk, or an optical disk.

[0097] The power component 606 provides power to the various components of the device 600. The power component 606 may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power for the device 600.

[0098] The multimedia component 608 includes a screen that provides an output interface between the device 600 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen can be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors can not only sense the boundaries of the touch or swipe actions, but also detect the duration and pressure associated with the touch or swipe operation. In some embodiments, the multimedia component 608 includes a front camera and / or a rear camera. When the device 600 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera can receive external multimedia data. Each of the front camera and the rear camera can be a fixed optical lens system or have a focal length and optical zoom capabilities.

[0099] The audio component 610 is configured to output and / or input audio signals. For example, the audio component 610 includes a microphone (MIC) that is configured to receive external audio signals when the device 600 is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals can be further stored in the memory 604 or transmitted via the communication component 616. In some embodiments, the audio component 610 further includes a speaker for outputting audio signals.

[0100] The I / O interface 612 provides an interface between the processing component 602 and a peripheral interface module, which can be a keyboard, a click wheel, buttons, etc. These buttons can include, but are not limited to: a home button, a volume button, a power-on button, and a lock button.

[0101] The sensor assembly 614 includes one or more sensors for providing a status assessment of various aspects of the device 600. For example, the sensor assembly 614 can detect the on / off state of the device 600, the relative positioning of components, such as the display and keypad of the device 600. The sensor assembly 614 can also detect a change in the position of the device 600 or a component of the device 600, the presence or absence of user contact with the device 600, the orientation or acceleration / deceleration of the device 600, and the temperature change of the device 600. The sensor assembly 614 can include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor assembly 614 can also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 614 can further include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0102] The communication component 616 is configured to facilitate communication between the device 600 and other devices in a wired or wireless manner. The device 600 can access a wireless network based on communication standards, such as WiFi, 2G, or 3G, or a combination thereof. In an exemplary embodiment, the communication component 616 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 616 further includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0103] In an exemplary embodiment, the device 600 can be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components for performing the above battery control method.

[0104] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 604 including instructions that can be executed by a processor 620 of the device 600 to complete the above battery control method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0105] In another exemplary embodiment, a computer program product is also provided. The computer program product includes a computer program executable by a programmable device. The computer program has a code portion for performing the above battery control method when executed by the programmable device.

[0106] Figure 7 FIG. 4 is a block diagram of a device 700 for battery control shown according to an exemplary embodiment. For example, the device 700 may be provided as a server. Referring to Figure 7 FIG. 4, the device 700 includes a processing component 722, which further includes one or more processors, and memory resources represented by a memory 732 for storing instructions executable by the processing component 722, such as application programs. The application programs stored in the memory 732 may include one or more modules each corresponding to a set of instructions. In addition, the processing component 722 is configured to execute instructions to perform the above battery control method.

[0107] The device 700 may also include a power component 726 configured to perform power management of the device 700, a wired or wireless network interface 750 configured to connect the device 700 to a network, and an input / output (I / O) interface 758. The device 700 may operate based on an operating system stored in the memory 732, such as Windows Server TM , Mac OS X TM , Unix TM , Linux TM , FreeBSD TM or the like.

[0108] Those skilled in the art will readily conceive of other embodiments of the present disclosure after considering the specification and practicing the present disclosure. This application is intended to cover any variations, uses, or adaptations of the present disclosure, which follow the general principles of the present disclosure and include known common knowledge or conventional technical means in the technical field not disclosed in the present disclosure. The specification and embodiments are only to be considered as exemplary, and the true scope and spirit of the present disclosure are pointed out by the following claims.

[0109] It should be understood that the present disclosure is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present disclosure is only limited by the appended claims.

Claims

1. A battery control method, characterized in that, Including: Obtain battery usage data of the battery in the target terminal at multiple different time points within the first target period; Determine the battery capacity attenuation rate of the battery within the second target period according to the battery usage data; Determine the battery discharge cut-off voltage corresponding to the battery capacity attenuation rate as the target discharge cut-off voltage within the second target period.

2. The method according to claim 1, characterized in that, The determining the battery capacity attenuation rate of the battery within the second target period according to the battery usage data includes: According to the cell system of the battery, input the battery usage data into a pre-trained regression model to obtain the battery capacity attenuation rate of the battery within the second target period; Wherein, the regression model is trained by the actual usage data and the actual battery capacity attenuation rate of other batteries with the same cell system as the battery.

3. The method according to claim 2, characterized in that, The battery usage data and the actual usage data include the external environmental temperature of the battery and the number of battery cycles.

4. The method according to claim 1, characterized in that The number of days included in the first target period is not less than 1, the battery usage data is the battery usage data corresponding to each day in the first target period, and the battery capacity attenuation rate is the battery capacity attenuation rate corresponding to each day in the second target period.

5. The method according to any one of claims 2-4, characterized in that, The regression model is a neural network classifier.

6. The method according to claim 1, characterized in that, The determining the battery discharge cut-off voltage corresponding to the battery capacity attenuation rate as the target discharge cut-off voltage within the second target period includes: Determine the target attenuation rate interval where the battery capacity attenuation rate is located; Determine the battery discharge cut-off voltage corresponding to the target attenuation rate interval as the target discharge cut-off voltage within the second target period.

7. A battery control device, characterized in that, Including: A first acquisition module configured to obtain battery usage data of the battery in the target terminal at multiple different time points within the first target period; A first determination module configured to determine the battery capacity attenuation rate of the battery within the second target period according to the battery usage data; A second determination module configured to determine the battery discharge cut-off voltage corresponding to the battery capacity attenuation rate as the target discharge cut-off voltage within the second target period.

8. The device according to claim 7, characterized in that, The first determination module is further configured to: According to the cell system of the battery, input the battery usage data into a pre-trained regression model to obtain the battery capacity attenuation rate of the battery within the second target period; Wherein, the regression model is trained by the actual usage data and the actual battery capacity attenuation rate of other batteries with the same cell system as the battery.

9. A battery control device, characterized in that, Including: A processor; A memory for storing processor-executable instructions; Wherein, the processor is configured to: Obtain battery usage data of the battery in the target terminal at multiple different time points within the first target period; Determine the battery capacity attenuation rate of the battery within the second target period according to the battery usage data; Determine the battery discharge cut-off voltage corresponding to the battery capacity attenuation rate as the target discharge cut-off voltage within the second target period.

10. A computer-readable storage medium having computer program instructions stored thereon, characterized in that, When the program instructions are executed by the processor, the steps of the method according to any one of claims 1-6 are implemented.

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