Battery control method and electronic equipment

Abstract

The invention provides a battery control method and electronic equipment. The battery control method comprises the following steps: obtaining charging and discharging data of a battery assembly of the electronic equipment in a target statistical period; determining user portrait information of a target user based on the charging and discharging data; based on a target battery management strategy matched with the user portrait information, performing management control on the battery assembly in a first statistical period; wherein the first statistical period is later than the target statistical period, and the target statistical period comprises at least one statistical period.

Description

Technical Field

[0001] The present application relates to, but is not limited to, the field of battery control technology, and in particular to a battery control method and electronic equipment. Background Art

[0002] Existing technologies typically control charging and discharging based on preset rules or fixed battery management strategies, such as triggering charging or discharging limits based on battery charge thresholds. Some solutions attempt to adjust battery management behavior based on user habits, but these often rely on simple parameter settings and lack in-depth modeling and dynamic adaptation of user behavior characteristics. Summary of the Invention

[0003] In view of this, embodiments of the present application at least provide a battery control method and an electronic device.

[0004] The technical solution of the embodiment of the present application is implemented as follows:

[0005] In a first aspect, an embodiment of the present application provides a battery control method, comprising: obtaining charge and discharge data of a battery component of an electronic device within a target statistical period; determining user portrait information of a target user based on the charge and discharge data; and executing management control of the battery component within a first statistical period based on a target battery management strategy that matches the user portrait information; wherein the first statistical period is later than the target statistical period, and the target statistical period includes at least one statistical period.

[0006] In a second aspect, an embodiment of the present application provides a battery control device, comprising: an acquisition module for obtaining charge and discharge data of a battery component of an electronic device within a target statistical period; a determination module for determining user portrait information of a target user based on the charge and discharge data; and an execution module for executing management control of the battery component within a first statistical period based on a target battery management strategy matching the user portrait information; wherein the first statistical period is later than the target statistical period, and the target statistical period includes at least one statistical period.

[0007] In a third aspect, an embodiment of the present application provides an electronic device comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and the processor is used to perform at least one of the following operations: obtaining charge and discharge data of a battery component of the electronic device within a target statistical period; determining user portrait information of a target user based on the charge and discharge data; and performing management control of the battery component within a first statistical period based on a target battery management strategy that matches the user portrait information; wherein the first statistical period is later than the target statistical period, and the target statistical period includes at least one statistical period.

[0008] In some embodiments, the electronic device further includes at least one processing model, which can be called by the battery management system chip of the battery assembly or the processor to generate user portrait information of the target user based on the charging and discharging data.

[0009] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, which implements some or all of the steps in the above method when executed by a processor.

[0010] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program or instructions, which, when executed by a processor, implements some or all of the steps in the above method.

[0011] It should be understood that the above general description and the following detailed description are merely exemplary and explanatory, and do not limit the technical solutions of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The drawings herein are incorporated into and constitute a part of the specification. These drawings illustrate embodiments consistent with the present application and, together with the specification, are used to illustrate the technical solutions of the present application.

[0013] Figure 1 A schematic diagram of an implementation flow of a battery control method provided in an embodiment of the present application;

[0014] Figure 2 A schematic diagram of an implementation flow of a battery control method provided in an embodiment of the present application;

[0015] Figure 3 A schematic diagram of an implementation flow of a battery control method provided in an embodiment of the present application;

[0016] Figure 4 A schematic diagram of an implementation flow of a battery control method provided in an embodiment of the present application;

[0017] Figure 5 A schematic diagram of an implementation flow of a battery control method provided in an embodiment of the present application;

[0018] Figure 6 A schematic diagram of an implementation flow of a battery control method provided in an embodiment of the present application;

[0019] Figure 7 A logic diagram for detecting charge and discharge provided in an embodiment of the present application;

[0020] Figure 8 A schematic diagram of an implementation flow of a battery control method provided in an embodiment of the present application;

[0021] Figure 9a A schematic diagram of implementing charge and discharge management provided in an embodiment of the present application;

[0022] Figure 9b A schematic diagram of implementing charge and discharge management provided in an embodiment of the present application;

[0023] Figure 10a A schematic diagram of the implementation flow of the over-discharge protection method provided in an embodiment of the present application;

[0024] Figure 10b A schematic diagram of a discharge protection method according to an embodiment of the present invention;

[0025] Figure 11 A schematic diagram of the structure of a power supply control device provided in an embodiment of the present application;

[0026] Figure 12 A hardware entity diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical solutions and advantages of this application clearer, the technical solutions of this application are further elaborated in detail below with reference to the accompanying drawings and embodiments. The described embodiments should not be regarded as limiting this application. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0028] In the following description, references to "some embodiments" describe a subset of all possible embodiments. However, it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict. The terms "first / second / third" are merely used to distinguish similar objects and do not represent a specific ordering of the objects. It is understood that the specific order or sequence of "first / second / third" may be interchanged where permitted, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein.

[0029] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application pertains. The terms used herein are for the purpose of describing this application only and are not intended to limit this application.

[0030] The lifespan of lithium batteries is strongly correlated with user habits. Extending the lifespan requires considering factors such as temperature, charging current, overcharging, and over-discharging. Existing solutions restrict battery use to specific scenarios and lack control solutions tailored to individual user habits.

[0031] To address the above issues, an embodiment of the present application provides a battery control method, comprising: obtaining charge and discharge data of a battery assembly of an electronic device within a target statistical period; determining user profile information of a target user based on the charge and discharge data; and executing management and control of the battery assembly within a first statistical period based on a target battery management policy that matches the user profile information; wherein the first statistical period is later than the target statistical period, and the target statistical period includes at least one statistical period. A user profile can be determined based on the charge and discharge data of the user within the target statistical period, and the battery assembly can be controlled based on the target battery management policy corresponding to the user profile; thereby, a corresponding battery management policy can be matched for each user, thereby improving battery life.

[0032] Figure 1 This is a schematic diagram of a battery control method provided in an embodiment of the present application, which can be executed by a processor of an electronic device. Figure 1 As shown, the method includes the following steps S101 to S103, combining Figure 1 The steps shown are explained.

[0033] Step S101: Obtain charge and discharge data of a battery assembly of an electronic device within a target statistical period.

[0034] In some embodiments, the electronic device may refer to a server, a laptop computer, a tablet computer, a desktop computer, a smart TV, a set-top box, a mobile device (such as a mobile phone, a portable video player, a personal digital assistant, a dedicated messaging device, a portable gaming device), or other device with data processing capabilities.

[0035] In some embodiments, the battery assembly is used to store energy and power electronic devices; wherein the battery assembly may include one battery pack or may be composed of multiple battery packs, which is not limited in this application.

[0036] In some embodiments, the statistical period represents the time period used to collect and analyze battery charge and discharge data, which can be one or more continuous or non-continuous time units (such as hours, days, weeks, months, etc.) to evaluate the user's usage behavior within a specific time period.

[0037] In some embodiments, the target statistical period may include one statistical period or multiple statistical periods; wherein, a statistical period is preset for different types of electronic devices or different users; for example, for large-capacity electronic devices such as servers, the statistical period may be 15 days or 30 days; for small-capacity electronic devices such as mobile phones, the statistical period may be 3 days or 7 days.

[0038] In some embodiments, the charge and discharge data of the battery assembly may include the charge and discharge capacity, charge and discharge current, charge and discharge power, charge and discharge temperature, etc. of the battery.

[0039] In some embodiments, the charge and discharge data of the battery assembly within the target statistical period can be read through the application programming interface (API) provided by the system of the electronic device; illustratively, the battery status is monitored through the battery management (Battery Manager) interface in the mobile phone or computer system to obtain the battery's charge and discharge capacity, charge and discharge current, charge and discharge power, charge and discharge temperature, etc.

[0040] Step S102: Determine user portrait information of the target user based on the charge and discharge data.

[0041] In some embodiments, the target user may be the owner of the electronic device (the electronic device owner); or when the electronic device is a household device or a public device, the usage data of each family member or each user may be recorded, and the usage habit category of a certain member or a specific user may be determined.

[0042] In some embodiments, the user portrait information can at least represent the user's usage habits of the battery component.

[0043] In some embodiments, user portrait information is a data model generated by analyzing the user's battery charging and discharging behavior within a certain statistical period (such as the number of charge and discharge times, time, capacity changes, etc.), which is used to characterize the user's battery usage habits and behavioral characteristics, such as whether the user is a light, moderate, or heavy user, or a desktop user who uses the battery for a long time.

[0044] In some embodiments, the basic characteristic data of the user is first extracted from the charging and discharging data, including the device type, charging habits, and discharging habits. Among them, the device type can be determined based on the charging and discharging power in the charging and discharging data, and the user's charging method (mobile power supply, fixed power supply) is determined; the charging habits may include the user's charging frequency, charging period, single charging duration, etc. of the electronic device; for example, the number of daily charges and single charging duration of the user in the target statistical period are obtained, and the distribution of the user's charging period for the electronic device is analyzed (such as concentrated charging from 22:00 to 8:00 the next day at night, which may be a home user; charging from 12:00 to 14:00 in the afternoon, which may be an office scene user); wherein, the discharging habits may include the user's discharge period, single discharge duration, discharge frequency, energy consumption, etc.; for example, the number of daily uses and single use duration of the user in the target statistical period, the distribution of discharge periods, and energy consumption, etc. are obtained; thereby determining the user's usage habits and usage types (entertainment, office, etc.). Secondly, user tags are generated based on the determined basic user feature data; including basic tags, behavioral tags, scenario tags, etc.; among them, basic tags include device type (mobile phone / tablet / computer / smart wearable device, etc.), charging method (mobile power supply / adapter), etc., behavioral tags include charging time preference (night type / day type), charging frequency (high frequency / medium frequency / low frequency), power consumption intensity (high / medium / low), etc.; scenario tags include usage habits (regular charging and discharging / staying up late charging and discharging), professional tendencies (office workers / students / freelancers), etc.; finally, user portrait information of the target user is generated based on the user tags.

[0045] Among them, user portrait information may include light users, moderate users, heavy users, desktop users, idle users, etc.

[0046] Step S103: Execute management control of the battery assembly within the first statistical period based on the target battery management strategy that matches the user portrait information.

[0047] The first statistical period is later than the target statistical period, and the target statistical period includes at least one statistical period.

[0048] In some embodiments, the first statistical cycle may be the currently ongoing charge and discharge cycle, or the next charge and discharge cycle, which is not limited in this application.

[0049] In some embodiments, the battery management strategy is a set of control logic or parameter configurations based on user profile information matching, which is used to optimize the working status of the battery components in the subsequent statistical period, including but not limited to the battery's full charge capacity, charging rate, discharge cut-off voltage, trigger conditions for entering the shipping mode, etc.

[0050] In some embodiments, the target battery management strategy includes a battery charge and discharge strategy, battery management configuration parameters, etc.; wherein the charge and discharge strategy can represent a battery charge and discharge mode; and the battery management configuration parameters can represent a battery charge and discharge power, etc.

[0051] In some embodiments, the target battery management strategy may be pre-generated, or generated in real time based on the user's charging and discharging data.

[0052] In some embodiments, the battery management strategy of the battery assembly can be obtained by a battery management system provided in the electronic device; wherein the battery management system includes a battery management module and a battery algorithm module.

[0053] Among them, the battery management module includes safety protection, which is used to monitor the working status of the battery, prevent the occurrence of dangerous situations such as overcharging, over-discharging, overcurrent, and short circuit, and ensure that the battery operates within a safe range; power consumption management, which is used to optimize the energy use of the battery, reduce system power consumption, and improve the battery life; communication management, which is used for communication with external devices to ensure accurate transmission and interaction of information; failure monitoring, which is used to monitor the performance parameters of the battery in real time, promptly detect abnormal conditions of the battery, such as battery aging and damage, and take corresponding measures; storage management, which is used to store historical data of the battery, such as charge and discharge records, fault records, etc.; charge and discharge management, which is used to control the charging and discharging process of the battery to ensure safe and efficient charging and discharging; balancing management, which is used to balance the power of each battery in the battery pack, prevent individual batteries from overcharging or over-discharging, and extend the service life of the battery pack; configuration management, which is used to configure and manage the parameters of the BMS to adapt to different battery types and application scenarios.

[0054] Among them, the battery algorithm module includes power estimation, which is used to estimate the remaining power of the battery through an algorithm to provide users with accurate power information; dynamic discharge control, which is used to dynamically adjust the discharge current according to the battery status and load requirements to ensure safe and efficient discharge of the battery; and intelligent charging algorithm, which is used to optimize the charging process, improve charging efficiency, and extend battery life.

[0055] In some embodiments, the battery management strategy generates different battery management strategies based on different usage frequencies, different usage scenarios, and different charging and discharging habits of the battery.

[0056] For example, for users with high frequency of use, a segmented fast charging strategy is adopted, such as using high-power fast charging from 0-80% and using trickle charging from 80% to 100%.

[0057] In some embodiments, a match is performed among multiple battery management strategies based on the user portrait information to obtain a target battery management strategy corresponding to the user portrait information, so as to perform management control of the battery component within the first statistical period.

[0058] For example, if the user portrait information indicates that the user is a heavy user, the battery management strategy matched is a segmented fast charging strategy, and the battery components are controlled to charge based on the segmented fast charging strategy in the current charging cycle or the next charging cycle.

[0059] In an embodiment of the present application, by obtaining the charge and discharge data of the battery components of the electronic device by the user within a target statistical period, the user profile information of the target user can be determined; a target battery management policy corresponding to the user profile information is then matched to manage and control the battery components within a first statistical period based on the target management policy. Compared to the existing technology that manages batteries through only a few fixed scenarios, the present application adopts independent battery management policies for users with different usage types. This improves charging efficiency, extends battery life, and thus enhances the user experience.

[0060] Figure 2 The present invention provides a battery control method according to an embodiment of the present invention. The method can be executed by a processor of an electronic device. Figure 1 , Figure 1 Step S102 in the above example can be updated to step S201 or step S202, which will be combined with Figure 2 The steps shown are explained.

[0061] Step S201: Determine user portrait information of a target user based on at least one of charge and discharge capacity change data, charge and discharge times, and charge and discharge duration of the battery assembly within a second statistical period.

[0062] The second statistical period is a statistical period that is earlier than and adjacent to the first statistical period, or a statistical period that is earlier than the first statistical period and matches the target user.

[0063] In some embodiments, the adjacent statistical period represents the previous statistical period of the first statistical period; it is understandable that the user's usage habits are determined only through the charging and discharging data of the previous statistical period of the first statistical period, thereby determining the user portrait information.

[0064] In some embodiments, the statistical period matching the target user represents the statistical period before the first statistical period. It can be understood that it is a historical statistical period related to the target user. The statistical period matching the target user may be adjacent to the first statistical period or may not be adjacent to the first statistical period.

[0065] In some embodiments, the charge and discharge capacity change data represents the charge change data of the battery component. For example, if the charging process is from 30% to 80%, the capacity change data of the charging process is 50%; if the discharging process is from 70% to 30%, the capacity change data of the discharging process is 40%.

[0066] In some embodiments, the charging and discharging duration may include the user's cumulative charging duration, the user's cumulative discharging duration, the user's single charging duration, the user's single discharging duration, etc.

[0067] In some embodiments, the user profile information can at least characterize the target user's usage habits of the battery assembly. The usage habits characterize the user's charging and discharging habits of the electronic device, and may include at least light use, moderate use, heavy use, idle use, and desktop use.

[0068] In some embodiments, the user portrait information may also characterize the device type of the electronic device, such as a personal device, a public device, etc.

[0069] In some embodiments, based on the charge and discharge capacity change data, charge and discharge times, and charge and discharge duration in a statistical period earlier than the first statistical period, or a statistical period related to the target user earlier than the first statistical period, the user's basic feature data, including charging and discharging habits, electronic device type, etc., is determined, and the user tag is determined based on the basic feature data, thereby generating user portrait information corresponding to the user based on the user characterization.

[0070] For example, based on the target user's charge and discharge capacity change data, charge and discharge times, and charge and discharge duration in the second statistical period, the user's basic characteristic data is determined, and the user is characterized as a heavy user, and a heavy user user portrait is generated.

[0071] Step S202: Determine user portrait information of the target user based on at least one of the charge and discharge capacity change data, charge and discharge times, and charge and discharge duration of the battery assembly within multiple third statistical periods.

[0072] The third statistical period is earlier than the first statistical period and is related to the target user.

[0073] In some embodiments, the third statistical period includes a statistical period related to the user; it is understandable that multiple statistical periods related to the user are selected from all statistical periods earlier than the first statistical period as multiple third statistical periods.

[0074] In some embodiments, the basic characteristic data of the user is determined based on the charge and discharge capacity change data, charge and discharge times, and charge and discharge duration within multiple third statistical periods; the user's label is determined based on the user's basic characteristic data, thereby determining the user's user portrait information.

[0075] For example, the basic feature data indicates that the user's charging and discharging frequency is low and the charging and discharging time is short, and a label indicating that the user has light usage is generated, thereby generating a user profile indicating light usage.

[0076] In the embodiments of the present application, a user profile is determined by analyzing charge and discharge capacity change data, charge and discharge frequency, and charge and discharge duration data within a statistical cycle prior to and adjacent to the first statistical cycle or a statistical cycle related to the user; or by analyzing charge and discharge capacity change data, charge and discharge frequency, and charge and discharge duration data within multiple statistical cycles related to the user prior to the first statistical cycle. This improves the accuracy of determining user profile information, thereby improving the accuracy of subsequent matching of target battery management strategies, thereby improving the accuracy of battery management and extending battery life.

[0077] Figure 3 This is a schematic diagram of a battery control method provided in an embodiment of the present application, which can be executed by a processor of an electronic device. Figure 2 , Figure 1 Step S102 in the above example can be updated to step S301 to step S302 or step S303, which will be combined with Figure 3 The steps shown are explained.

[0078] Step S301: Determine the type of the electronic device based on usage data of the electronic device.

[0079] In some embodiments, usage data may include usage object data (single-person use, multi-person use), usage location (home or mobile location), usage mode (for screen projection, as a processing host, as an audio and video playback device, etc.), usage time (time period), functional services used (playing games, audio and video playback or office applications, etc.), etc.

[0080] In some embodiments, the type of electronic device may include a personal device, a public device, or a home device.

[0081] In some embodiments, if the usage data indicates that the electronic device is used by a single person or for personal use (the device has a single login account), then the electronic device can be characterized as a personal device; if the usage data indicates that there are multiple account switching and multiple account logins, then the electronic device can be characterized as a public device or a home device, which is further determined in combination with the location of use.

[0082] Step S302: When the electronic device belongs to the first type of device, determine the user portrait information of the target user based on the charge and discharge data of the battery assembly in the second statistical period or multiple third statistical periods.

[0083] The target user is the only user of the electronic device.

[0084] In some embodiments, the first type of device represents that the electronic device is a personal device; it can be understood that the electronic device is a personal device of the target user.

[0085] In some embodiments, when the electronic device is a personal device of the target user, the user portrait information of the target user is determined based on the charge and discharge capacity change data, charge and discharge times, and charge and discharge duration of the battery component in a statistical period that is earlier than the first statistical period and adjacent to the first statistical period, or in a statistical period that is earlier than the first statistical period and matches the target user.

[0086] In some embodiments, when the electronic device is a personal device of the target user, the user portrait information of the target user is determined based on the charge and discharge capacity change data, charge and discharge times, and charge and discharge duration in multiple statistical periods that are earlier than the first statistical period and related to the target user.

[0087] Step S303: When the electronic device belongs to the second type of device, determine the user portrait information of the target user based on the target charge and discharge data of the battery assembly in multiple third statistical periods.

[0088] The target user is one of the non-unique users of the electronic device, and the target charge and discharge data is data associated with the target user.

[0089] In some embodiments, the second type of device represents that the electronic device is a public device or a home device, such as a public computer, a home television, etc.

[0090] In some embodiments, when the electronic device belongs to the second type of device, the target user may include multiple users; it can be understood that the accounts of multiple users who have logged into the public computer generate user portrait information corresponding to each user based on the charging and discharging data corresponding to each user.

[0091] In some embodiments, when the electronic device belongs to the second type of device, if there are multiple target users, the target charge and discharge data corresponding to one target user in one statistical period are relatively small, and it is necessary to generate user portrait information corresponding to each target user based on the target charge and discharge data corresponding to the target users in multiple third statistical periods.

[0092] Among them, since the second type of device supports multi-user use, when building a user portrait, the system needs to determine which user is performing the current operation based on user identification (such as login ID, fingerprint, facial recognition, etc.), and extract the related charging and discharging data accordingly.

[0093] In some embodiments, user portrait information of the target user is determined based on charge and discharge capacity change data, charge and discharge times, and charge and discharge duration within multiple third cycles.

[0094] In the embodiment of the present application, the type of electronic device is determined by the usage data of the electronic device, and the user profile information is further refined based on the type of electronic device. This can more accurately match the user's usage scenario, thereby formulating a more personalized battery management strategy, which can effectively extend the battery life and improve the user experience.

[0095] Figure 4 The present invention provides a battery control method according to an embodiment of the present invention. The method can be executed by a processor of an electronic device. Figure 1 , Figure 1 Step S102 in the above example can be updated to step S401 or step S402, which will be combined with Figure 4 The steps shown are explained.

[0096] Step S401: Analyze the parameter range of at least one of the charge and discharge capacity change data, charge and discharge times, and charge and discharge duration of the battery assembly within a target statistical period to obtain user portrait information of the target user.

[0097] In some embodiments, the parameter range is used to determine the category of user portrait information of the target user; for example, light, idle, heavy, moderate, desktop type users, etc. are determined based on the parameter range.

[0098] In some embodiments, the parameter range is a numerical interval of different usage patterns divided by historical data. For example, if a user discharges less than 5% of the battery capacity per day on average over a month, the user is classified as light user; whereas if the user discharges more than 30% of the battery capacity per day, the user may be classified as heavy user.

[0099] Exemplarily, the parameter ranges corresponding to the charge and discharge capacity change data include 0-10%, 10%-30%, 30%-60%, and 60%-90%. If the charge and discharge capacity change data of the battery component within the target statistical period is in the parameter range of 60%-90%, the user portrait information of the target user is determined to be a heavy user.

[0100] Step S402: Use the first processing model to generate and process the charge and discharge data of the battery assembly within the target statistical period to obtain user portrait information of the target user.

[0101] The first processing model is deployed in the electronic device or in a processing device connected to the electronic device.

[0102] In some embodiments, the first processing model is an algorithmic model for extracting and processing battery charge and discharge data. The algorithm can run on a local electronic device (such as a laptop) or be deployed on a remote server or cloud platform. This model typically uses machine learning or a rule engine to extract features, classify, and predict the input charge and discharge data, ultimately outputting user profile information, such as user type (light / moderate / heavy) and typical usage scenarios (office / entertainment / creative).

[0103] In some embodiments, if the first processing model is deployed on a local device, real-time response can be achieved, but it is limited by computing power; if it is deployed on a remote server, it relies on network communication, but has stronger processing power and scalability.

[0104] In some embodiments, the charge and discharge data of the current statistical period and the historical statistical period are input into the first processing model to obtain user portrait information of the target user.

[0105] In the embodiments of this application, by analyzing the user's charging and discharging behavior within the target statistical period and using the processing model for intelligent identification, a more accurate user profile can be constructed. This allows the development of a battery management strategy that better suits the user's usage habits, thereby improving the battery's safety and stability, and effectively extending the life of the lithium battery.

[0106] Figure 5 This is a schematic diagram of a battery control method provided in an embodiment of the present application, which can be executed by a processor of an electronic device. Figure 1 , Figure 1 Step S102 in the above example can be updated to step S501 or step S502 or step S503 or step S504 or step S505, which will be combined with Figure 5 The steps shown are explained.

[0107] Step S501: If the charge and discharge data indicates that the discharge ratio of the battery assembly within a target statistical period is within a first ratio range and the single discharge capacity change is within a first capacity range, it is determined that the target user belongs to the first type of user.

[0108] In some embodiments, the first type of user represents a light battery usage user, which is characterized by a relatively low battery discharge ratio and a small change in single battery discharge capacity in a cumulative cycle.

[0109] In some embodiments, the first ratio range includes the discharge ratio of light battery usage users within the target statistical period; the first capacity range includes the single discharge capacity change of light battery usage users within the target statistical period.

[0110] For example, the first ratio range is 0 to 20%, and the first capacity range is 0 to 10%. If the discharge ratio within the target statistical period is between 0 and 20% and the single discharge change is between 0 and 10%, it indicates that the target user belongs to the first type of user, that is, a light battery usage user.

[0111] Step S502: If the charge and discharge data indicates that the discharge ratio of the battery assembly within the target statistical period is within a second ratio range and the single discharge capacity change is within a second capacity range, it is determined that the target user belongs to the second type of user.

[0112] In some embodiments, the second type of user characterizes the target user as a moderate battery usage user, which is characterized by a moderate battery discharge ratio and a moderate change in single battery discharge capacity in a cumulative cycle.

[0113] In some embodiments, the second ratio range includes the discharge ratio of moderate battery usage users within the target statistical period; the second capacity range includes the change in single discharge capacity of moderate battery usage users within the target statistical period.

[0114] For example, the second ratio range is 20% to 50%, and the second capacity range is 10% to 30%. If the discharge ratio within the target statistical period is between 20% and 50% and the single discharge change is between 10% and 30%, it indicates that the target user belongs to the second type of user, that is, a moderate battery usage user.

[0115] In some embodiments, the medium usage type includes office usage and entertainment usage, and the charge and discharge data includes average discharge power and maximum discharge power.

[0116] In some embodiments, when the average discharge power is greater than a first power threshold and the maximum discharge power is greater than a second power threshold, the category is determined to be entertainment type; and the second power threshold is greater than the first power threshold.

[0117] In some embodiments, when the average discharge power is not greater than a first power threshold and / or the maximum discharge power is not greater than a second power threshold, the category is determined to be office type.

[0118] Step S503: If the charge and discharge data indicates that the discharge ratio of the battery assembly within the target statistical period is within a third ratio range and the single discharge capacity change is within a third capacity range, it is determined that the target user belongs to the third type of user.

[0119] In some embodiments, the third type of user represents the target user as a heavy battery user, whose typical characteristics are that, in a cumulative cycle, the battery discharge ratio is high and the single battery discharge capacity changes greatly.

[0120] In some embodiments, the third ratio range includes the discharge ratio of heavy battery users within the target statistical period; and the third capacity range includes the change in single discharge capacity of heavy battery users within the target statistical period.

[0121] In some embodiments, the third ratio range is greater than 50% and the second capacity range is greater than 30%. If the discharge ratio within the target statistical period is greater than 50% and the single discharge change is greater than 30%, it indicates that the target user belongs to the third type of user, that is, a heavy battery user.

[0122] Step S504: If the charge and discharge data indicates that the discharge ratio of the battery assembly within the target statistical period is within a fourth ratio range and the single discharge capacity change is within a fourth capacity range, it is determined that the target user belongs to the fourth type of user.

[0123] In some embodiments, the fourth type of user represents a target user who is a desktop user. The user is characterized in that, in a cumulative cycle, the user basically uses the device with an adapter, has an extremely low battery discharge ratio, and has an extremely small change in single battery discharge capacity.

[0124] In some embodiments, the fourth ratio range typically indicates that the battery undergoes almost no discharge, with an extremely low discharge ratio, such as less than 5%. The fourth capacity range indicates that the capacity change during each discharge is very small, even close to zero. This type of user primarily uses the device in a fixed location and rarely unplugs the adapter, such as desktop users. To protect the battery, the system can fix its battery capacity at a lower level, such as 60%, and adopt a slow charging strategy to prevent the battery from being fully charged for a long time, which may cause swelling or shorten its lifespan.

[0125] Step S505: If the charge and discharge data indicates that the discharge ratio and single discharge capacity of the battery assembly within the target statistical period are in a random state, determine that the target user is a fifth type of user.

[0126] In some embodiments, the fifth type of user characterization target user is an idle user, whose typical characteristics are that, in a cumulative cycle, the computer is occasionally used, the charging time is not fixed, the usage time is not fixed, the single discharge capacity is not fixed, the adapter working time is very short, and the battery power calculation time is short.

[0127] In some embodiments, the random state refers to the user's discharge behavior within the target statistical period without obvious patterns, and the discharge ratio and capacity change fluctuate greatly. This may be due to unstable user usage habits or irregular device usage time, such as idle users. For such users, the system should set a higher battery full charge threshold (such as 90%), and determine whether to enter the sleep or shutdown state based on historical records, and appropriately adjust the low voltage protection mechanism to avoid over-discharge of the battery due to long-term non-use.

[0128] In some embodiments, the charge and discharge data further includes power access time (adapter access time) and battery idle time. When the power access time is less than a first time threshold, the category is determined to be idle.

[0129] If the battery idle time is greater than a second time threshold, the category is determined to be idle type; the battery idle time is the time during which the battery discharge current is less than a current threshold. The current threshold is the battery discharge current during sleep.

[0130] In the embodiments of the present application, a refined battery management strategy is implemented by classifying user behavior based on charge and discharge data. This can effectively match the usage habits of different users, thereby extending battery life and improving the overall user experience and safety of the device.

[0131] Figure 6 This is a schematic diagram of a battery control method provided in an embodiment of the present application, which can be executed by a processor of an electronic device. Figure 1 , Figure 1 Step S103 in the above example can be updated to step S601 or step S602, which will be combined with Figure 6 The steps shown are explained.

[0132] Step S601: Based on the user portrait information, a target processing model is called from any one of the battery management system chip of the battery component, the battery management system bridge component provided in the electronic device, or the cloud-based battery management system signal-connected to the battery management system bridge component to configure a corresponding target battery management strategy for the battery component, so as to control the working parameters of the battery component within the first statistical period based on the target battery management strategy.

[0133] In some embodiments, a battery management system (BMS) chip refers to a dedicated microcontroller unit embedded within a battery pack. It collects real-time battery status parameters (such as voltage, current, temperature, and capacity) and manages battery charge and discharge according to a preset algorithm. BMS chips are typically integrated into portable electronic devices such as laptops and power banks, and their operating logic directly determines the battery's efficiency and lifespan.

[0134] In some embodiments, the Battery Management System (BMS) Bridge Component refers to an intermediate module located between the host (such as the motherboard) and the BMS chip, responsible for communication protocol conversion, data transmission, and some decision support functions. This component can transmit user profile information to the BMS chip and assist it in making more refined management decisions, such as dynamically adjusting the charging rate or limiting the depth of discharge.

[0135] In some embodiments, a cloud-based battery management system (CBMS) refers to a remote management platform deployed on a server that communicates with a local BMS chip or bridge component via a network connection to enable cross-device data sharing and policy optimization. The cloud-based system can aggregate the usage behavior patterns of multiple users to provide more intelligent, personalized battery management strategies.

[0136] In some embodiments, the target processing model refers to an algorithm model constructed based on user portrait information, which is used to predict the user's battery usage needs in specific scenarios and generate corresponding management strategies.

[0137] In some embodiments, the processing models called by different chips may be different, and may be processing models deployed in respective storage areas.

[0138] In some embodiments, the operating parameters may include operating modes and charge and discharge parameters, which can control the charge and discharge current of the battery, and also control at what point the battery enters a specific operating mode, such as entering ship mode or fast charging, slow charging, correction, etc.

[0139] For example, for light users, the target processing model recommends a lower charging limit and a higher discharge protection threshold; while for heavy users, the default fast charging strategy may be adopted and the discharge limit may be relaxed.

[0140] In some embodiments, user profile information is first received by a cloud system or bridge component, then transmitted to the BMS chip, which ultimately executes specific operational instructions, such as adjusting charging current and limiting discharge power. This layered architecture ensures system flexibility and scalability while also enhancing the intelligence of battery management.

[0141] Step S602: When target reference data is obtained, a corresponding target battery management strategy is configured for the battery component based on the target reference data and the user portrait information, so as to control the working parameters of the battery component within the first statistical period based on the target battery management strategy. The target reference data triggers reconfiguration of the preset battery management strategy.

[0142] In some embodiments, the target reference data may be input data manually adjusted or actively fed back by the user for changing or reconfiguring the preset management strategy; it may be the instruction input or operation of the user to manually update the BMS FW; it may be detection of a new BMS FW pushed by the manufacturer; it may be that a preset update timing duration meets the conditions; it may be replacement of other components in the electronic device; it may be a change in the user of the electronic device, a change in the place of use (such as switching from the original 220v to 110v power supply), a change in the purpose of use, etc.

[0143] In some embodiments, a target processing model is called based on the BMS cloud, and a corresponding battery management strategy is configured for the battery component based on the target reference data and the user portrait information through the target processing model.

[0144] In some embodiments, a model is called based on the BMS Bridge ic set in the electronic device (which can be other processors of the electronic device, such as a CPU, etc.) to execute the generated processing to call the target processing model, and the target processing model is used to configure the corresponding battery management strategy for the battery assembly based on the target reference data and the user portrait information.

[0145] In an embodiment of the present application, by obtaining target reference data, the target battery management strategy is configured based on the target reference data and user portrait information. In this way, the strategy can be adjusted in time when the environment changes or the user behavior shifts, thereby enhancing the dynamic response capability of battery management, thereby extending battery life and improving system stability.

[0146] In some embodiments, the execution of management control of the battery assembly in the first statistical period based on the target battery management strategy matching the user portrait information may also be implemented in the following manner:

[0147] In a case where the target user belongs to a first type of user, the full charge capacity and / or charging rate of the battery assembly is configured based on a first battery management strategy.

[0148] In some embodiments, the first type of user refers to a light battery user, typically characterized by a low battery discharge percentage and minimal change in single-discharge capacity over a cumulative cycle. For this type of user, the system employs the first battery management strategy, which sets the battery's full capacity to 60% plus the user's previously used maximum capacity minus 40%. If the result is less than 40%, no adjustment is made. Furthermore, the charging rate defaults to fast charging. This approach prevents the battery from being in a high-voltage state for extended periods, thereby extending battery life.

[0149] In some embodiments, in actual applications, for users who frequently use laptop computers for short periods of time, such as students or users who occasionally work from home, the first battery management strategy can effectively reduce battery loss while meeting the user's fast charging needs.

[0150] In a case where the target user belongs to the second type of user, the full charge capacity and / or charging rate of the battery assembly is configured with a corresponding second battery management strategy based on the usage scenario of the electronic device.

[0151] In some embodiments, the second type of user includes moderate battery usage users, which are further divided into two categories: office users (low average load) and entertainment or performance creation users (higher average load and with a history of large discharge power). For office users, the battery capacity retention value is set to the maximum usage RSOC in the past statistical period + 10%; for entertainment or performance creation users, it is set to the maximum usage RSOC in the past statistical period + 20%. The charging speed limit for both is the default fast charge. This strategy takes into account battery health and usage efficiency under different workloads.

[0152] In practical applications, for users who frequently use computers in the office, such as administrative staff or general clerical staff, this strategy can ensure that the battery is neither overcharged nor over-discharged, maintaining a better battery life.

[0153] In a case where the target user belongs to the third type of user, the full charge capacity and / or charging rate of the battery assembly is configured based on a default third battery management strategy.

[0154] In some embodiments, the third type of user is a heavy battery user, characterized by frequent discharges within a cycle, resulting in large variations in single-discharge capacity. For this type of user, the system uses the default battery management state, with the upper limit of the charging speed set to the default value, i.e., fast charging mode. Due to the user's frequent movement and use, stability and safety are prioritized over optimizing battery life.

[0155] In actual applications, for users who frequently travel or work away from home for long periods of time, such as sales personnel or engineers, this strategy can ensure that the battery can still operate stably under high-intensity use and prevent battery abnormalities caused by overly aggressive management.

[0156] In a case where the target user belongs to the fourth type of user, the battery assembly is configured to have a first full charge capacity and a first charging rate.

[0157] In some embodiments, the fourth type of user is a desktop user, whose primary usage scenario is adapter-powered and rarely uses battery power. To this end, the system fixes the battery's full charge capacity to 60% and sets a low charge rate (e.g., 0.5C). This configuration can significantly reduce the rate of battery aging, because the battery's long-term low charge state helps slow chemical degradation.

[0158] In actual applications, this policy is suitable for most desktop users or laptop users who use the computer for a long time, such as home office workers or corporate employees. It helps protect battery health and extend battery life.

[0159] In a case where the target user belongs to the fifth type of user, the battery assembly is configured to have a second full charge capacity and target trigger conditions for entering a shipping mode.

[0160] In some embodiments, the fifth type of user is an idle user, characterized by extremely low usage frequency, irregular charge and discharge times, and low battery discharge current. For this type of user, the system sets the battery's full charge to 90%. If the system detects prolonged periods of dormant or shutdown conditions, it appropriately increases the battery's low-voltage protection level and shortens the time it takes to enter ship mode. This prevents overdischarge or abnormal swelling of the battery due to prolonged inactivity, which can damage the battery structure.

[0161] In practical applications, this strategy is suitable for users who rarely use their computers, such as spare devices, collection devices, or devices that are sealed for a long time. It can effectively protect the battery from environmental factors and improve the safety and reliability of the battery.

[0162] In the embodiment of the present application, by classifying and formulating corresponding battery management strategies according to user usage habits, user behavior patterns can be matched more accurately, thereby optimizing battery charge and discharge control, thereby significantly extending battery life and improving battery safety.

[0163] The above-mentioned execution of management and control of the battery assembly in the first statistical period based on the target battery management strategy matching the user profile information also includes the following real-time methods:

[0164] When the target user belongs to the fifth type of user, the battery component is configured to have a second full charge capacity; and when the electronic device is in the first power state, the discharge cut-off voltage of the battery component is configured based on the remaining capacity and discharge time of the battery component.

[0165] In some embodiments, when the target user belongs to the fifth type of user, the full charge capacity of the battery component is configured to be set to 90%.

[0166] In some embodiments, the first power state may be that the discharge current of the battery assembly is greater than 5 mA.

[0167] In some embodiments, when the discharge current of the battery assembly of the electronic device is greater than 5 mA, the remaining capacity and discharge time configuration of the battery assembly are obtained. If the remaining capacity of the battery assembly is greater than 80% and the discharge time configuration is greater than 16 hours, the discharge cut-off voltage is increased.

[0168] When the target user belongs to the fifth type of user, the battery assembly is configured to have a second full charge capacity; and when the electronic device is in a second power state, the battery assembly is controlled to enter a shipping mode based on a fourth battery management strategy.

[0169] In some embodiments, the second power state may be that the discharge current of the battery assembly is less than 5 mA.

[0170] In some embodiments, the fourth battery management strategy includes: when the discharge current of the battery assembly of the electronic device is less than 5mA, obtaining the remaining capacity and discharge time configuration of the battery assembly; if the remaining capacity of the battery assembly is greater than 80% and the discharge time is greater than 3 days, increasing the discharge cut-off voltage; and continuing to obtain the discharge time configuration; when the discharge time is greater than 7 days, controlling the battery assembly to enter the shipping mode.

[0171] In the embodiment of the present application, by dynamically configuring the discharge cut-off voltage based on the remaining capacity and discharge duration in the first power state, and controlling the battery to enter the shipping mode according to the fourth battery management strategy in the second power state, differentiated battery management can be implemented based on different power states and user types, effectively extending battery life while improving the safety and stability of device use, thereby meeting diverse user needs and enhancing the user experience.

[0172] The following describes an exemplary application of a power control method provided in an embodiment of the present application in a practical scenario.

[0173] The lifespan of lithium batteries is closely tied to user habits. Extending the lifespan requires careful attention to the following key factors: temperature, overcharging, and over-discharging. Controlling the charging current is also an effective approach. Mainstream computer manufacturers currently have algorithms that limit battery usage in specific scenarios, but these restrictions are either uniform or tiered, without specific user-specific details.

[0174] In response to the above technical problems, an embodiment of the present application provides a method for detecting a battery usage environment, wherein it is first necessary to obtain battery parameters, including system time T, battery voltage V, battery charging current Ic, battery discharging current Id, discharge power pd, battery temperature Temp, battery capacity ROSC, and user action behavior (keyboard, mouse, touch, etc.) ACT; and determine the user's battery usage habits based on the parameters.

[0175] Specifically, the time recording area in the fuel gauge module records the time the user connects to the charger based on the user's charging habits and accumulates it according to different cycles (weekly or monthly), such as the charging start time T1, T2, T3... and the average temperature Temp during the charging process. After a complete cycle, the user's charging start pattern can be derived, for example, often starting charging at 9:00 am, and the earliest charging is at 8:00 am.

[0176] Specifically, based on the user's discharge habits, the time recording area in the fuel gauge module records the time the user removes the adapter and accumulates it according to different cycles (weekly or monthly), such as the discharge start time Ta, Tb, Tc..., and the average temperature Temp and discharge power Pd1 and Pd2 during the discharge process. After a complete cycle, the user's discharge start pattern can be determined, for example, often starting discharge at 10:00 am, the earliest discharge is at 9:00 am, and the average and maximum battery mode discharge power Pd.

[0177] Figure 7 A logic diagram for detecting charge and discharge is provided in an embodiment of the present application, wherein Ta1 represents the time point when the adapter is connected, that is, the time point when charging begins, and Tan represents the time point when the adapter is removed, that is, the time point when charging ends; Td1 represents the time point when discharge begins, and Tdn represents the time point when discharge ends, that is, the time point when the adapter is connected. The blocks in the figure represent the subdivision time periods of the charge and discharge points. For example, there are three time periods in Ta2 during the charging phase, that is, Ta2 is divided into three time periods. If Ta2 is 60 minutes, Ta2 can be divided into three 20-minute time periods. Each time period is detected to obtain accurate charging data for each time period.

[0178] In some embodiments, the adapter usage time and battery usage time are determined based on the user usage habits obtained above. Here, user adapter time = T adapter removal time - T adapter connection time; user battery usage time = T power calculation end (battery) - T power calculation start (battery); plugged-in unused time = T adapter user inaction end - T adapter user inaction start; battery mode computer unused time = T no power calculation end (battery) - T no power calculation start (battery); user battery usage change ROSC = ROSC2 - ROSC1 (battery discharge start capacity - battery discharge end capacity).

[0179] In some embodiments, user habits are categorized based on the above parameters, including:

[0180] 1. Light battery users: Their typical characteristics are that in a cumulative cycle, the battery discharge ratio is relatively low and the change in single battery discharge capacity is small;

[0181] 2. Moderate battery users: their typical characteristics are that, in a cumulative cycle, the battery discharge ratio is moderate and the change of single battery discharge capacity is moderate;

[0182] 3. Heavy battery users: Their typical characteristics are that in a cumulative cycle, the battery discharge ratio is high and the single battery discharge capacity changes greatly;

[0183] 4. Desktop users are typically used with an adapter, with a very low battery discharge ratio and minimal change in single battery discharge capacity.

[0184] 5. Idle users: Their typical characteristics are that, in a cumulative cycle, the computer is used occasionally, the charging time is not fixed, the usage time is not fixed, the single discharge capacity is not fixed, the adapter working time is very short, and the battery power calculation time is short.

[0185] In some embodiments, a battery management algorithm is developed based on different user habits, including:

[0186] 1. For users with light battery usage, the battery is fully charged at 60% of full charge + the maximum capacity used - 40% (the positive value is taken; if it is < 40%, no adjustment is made). The charging speed is the default fast charge.

[0187] 2. For moderate battery usage users, office users (typically low average load) have a battery capacity retention value of RSOC + 10% of the maximum usage in the past statistical period; for entertainment or performance creation users (typically high average load, but with a history of large discharge power), the battery capacity retention value is RSOC + 20% of the maximum usage in the past statistical period; the upper limit of their charging speed is set to fast charging by default;

[0188] 3. For heavy battery users, the battery uses the default management state and the charging speed limit is the default;

[0189] 4. For desktop battery users, the battery capacity is fixed at 60%, and the charging speed is as low as 0.5C; that is, the charging current is 0.5 times the rated capacity of the battery;

[0190] 5. For users with idle batteries, the battery is set to 90% full charge. Based on the accumulated history of long periods of inactivity, if the battery discharge current is <20mA, the computer is considered in hibernation mode, and if the battery discharge current is <4mA, the computer is considered shut down. The battery fuel gauge calculates the hibernation or shutdown time. If this time differs significantly from normal use, the following adjustments will be made: a. Appropriately increase the battery low voltage protection level; b. Shorten the time it triggers the battery ship mode protection.

[0191] Figure 8 A schematic diagram of a battery control method according to an embodiment of the present application includes steps S801 and S802. Figure 8 The steps shown are explained.

[0192] Step S801: In the initial state, collect periodic user usage habits.

[0193] In some embodiments, the period represents a statistical period for a user's use of the system. A statistical period may be 3 days, 7 days, 15 days, etc. The period may be one statistical period or multiple statistical periods.

[0194] In some embodiments, the user habits include desktop users, light users, medium users, heavy users, and idle users.

[0195] Step S802: Determine an independent battery management strategy for each user's usage habits.

[0196] In some embodiments, for desktop users, the battery capacity is fixed at 60%, and its charging speed is as low as 0.5C; that is, the charging current is 0.5 times the rated capacity of the battery; for light users, the battery is fully charged at 60% of the full charge + the maximum capacity used - 40% (take the positive value, if <40%, no adjustment is made), and the charging speed is the default fast charge; for moderate battery users, office users (typically low average load) the battery capacity retention value is the maximum usage RSOC in the past statistical period + 10%; for entertainment or performance creation users (typically high average load, but with a large discharge power), the battery capacity retention value is the maximum usage RSOC in the past statistical period + 20%; its charging speed upper limit is set to the default fast charge; for heavy users, the battery uses the default management state, and the charging speed upper limit is the default; for idle users, the battery full charge is set to 90%, and based on the long-term non-use of the computer in the past cumulative cycle, if the battery discharge current is <20mA, it is determined to be dormant, and if the battery discharge current is <4mA, it is determined to be shut down. The battery gauge calculates sleep or shutdown time. If this time differs significantly from normal use, make the following adjustments: a. Appropriately increase the battery low voltage protection value; b. Shorten the battery ship mode protection trigger time.

[0197] Among them, for users with light, moderate and heavy usage, the accumulated user charging time model can be used to control the charging to the set value at a certain time before the next removal of the adapter, avoiding the battery being in a high voltage state for a long time, thereby improving battery safety.

[0198] In the embodiment of the present application, by segmenting user usage habits and matching each usage habit with an independent point battery management strategy, the usage habits of each user are adapted to maintain the battery status at the best state; for idle users, the possibility of battery over-discharge is reduced, the battery service life is extended and abnormal battery expansion is avoided.

[0199] In some embodiments, the battery has an optimal storage capacity, for example, 60% power is the optimal storage capacity of the battery, which can be adjusted according to the usage habits of different users. For example, for users with entertainment habits, the optimal storage capacity of the battery can be increased by 20% based on 60%. If the optimal storage capacity is 80%, then for users with non-heavy usage habits, the optimal storage capacity of the battery can be controlled below 90%.

[0200] Figure 9aA schematic diagram of an implementation of charge and discharge management provided in an embodiment of the present application, wherein 901 is a management solution of the prior art, which divides the battery power into 7 levels, with the 7th level being 35% and the 1st level being 90%. By detecting the minimum capacity of the battery discharge within the cumulative window time, the battery is charged and discharged based on the level of the minimum capacity. For example, if the minimum capacity of the battery discharge is at level 7, the optimal storage capacity of the battery will be increased to level 1 during the next charging.

[0201] Figure 9b A schematic diagram of the implementation of charge and discharge management provided in an embodiment of the present application, wherein 902 is the charge and discharge management solution provided in the present application, which adjusts the charge and discharge by detecting the change in discharge capacity within the cumulative window and the preset battery capacity; for example, the life of a battery is best when the capacity is maintained at 70%, and a 20% margin needs to be reserved to cope with the user's usage habits. The user discharges the battery from 70% to 20% on a certain occasion, that is, the corresponding change is 50%, and 20% of the margin is not used. The next maximum capacity is still maintained at 70% and will not be adjusted. If the remaining capacity after 20% is used, such as another 10%, the next capacity calculation cycle will add 10% to 15% to the upper limit of the battery capacity. If all 20% is discharged, the next calculation cycle will set the battery to be fully charged to 100%.

[0202] In some embodiments, the existing charging scheme only has a night charging mode and a default charging mode, and the default charging mode is also a fast charging mode; while the embodiment of the present application records the user's use of the adapter and the plug-in usage time based on the accumulated user usage habits, determines the user's usage habits, and automatically adjusts the charging window and speed, thereby improving the charging efficiency and battery life.

[0203] Figure 10a The schematic diagram of the implementation flow of the over-discharge protection method provided in the embodiment of the present application includes steps S1001 to S1003, which will be combined with Figure 10a The steps shown are explained.

[0204] Step S1001: When the discharge current is less than a first preset current, start counting the discharge time.

[0205] In some embodiments, if the battery is in an idle state, the battery discharge current is continuously detected, and if it is less than 10 mA, the discharge time is started to be measured.

[0206] Step S1002: When the discharge time is greater than or equal to a first preset time, obtain the current battery capacity.

[0207] In some embodiments, if the discharge time is greater than 14 days, the current capacity is obtained.

[0208] Step S1003: Control the battery based on the battery capacity.

[0209] In some embodiments, when the battery capacity is less than 30%, the battery is controlled to enter a shipping mode to protect the battery before shipment.

[0210] Figure 10b A schematic diagram of a discharge protection method according to an embodiment of the present application is provided, including steps S1011 to S1015, which are combined with Figure 10b The steps shown are explained.

[0211] Step S1011: Detect the number of times the battery is idle or the number of times the low voltage protection is triggered.

[0212] In some embodiments, the number of times the battery is idle or the number of times the low voltage protection is triggered is continuously detected during a cumulative time period. When the number of times the battery is idle or the number of times the low voltage protection is triggered reaches a preset number, it indicates that the battery is in an idle state.

[0213] Step S1012: When the number of idle times reaches a first preset number or the number of times the low voltage protection is triggered reaches a second preset number, obtaining the discharge current and battery capacity of the battery.

[0214] In some embodiments, the number of idle times reaching a first preset number or the number of times the low voltage protection is triggered reaching a second preset number indicates that the battery is in an idle state.

[0215] In some embodiments, when the number of idle times is greater than 2 or the number of low voltage protection times is greater than 3 within the cumulative time period, the discharge current and battery capacity of the battery are obtained.

[0216] Step S1013: When the discharge current and battery capacity reach a preset state, counting the discharge time.

[0217] In some embodiments, when the battery charge is less than 80% and the discharge current is greater than 5 mA, the discharge time is counted.

[0218] In some embodiments, when the battery charge is less than 80% and the discharge current is less than 5 mA, the discharge time is counted.

[0219] Step S1014: when the discharge time is greater than a preset time, increasing the discharge cut-off voltage.

[0220] In some embodiments, the preset time includes a first preset time and a second preset time.

[0221] In some embodiments, if the discharge current is greater than 5 mA, the discharge cut-off voltage is increased when the discharge time is greater than the first preset time of 16 hours.

[0222] In some embodiments, if the discharge current is less than 5 mA, the discharge cut-off voltage is increased when the discharge time is greater than the second preset time of 3 days.

[0223] Step S1015: When the discharge current is less than a preset value, continue counting the discharge time of the battery and when the discharge time is greater than a third discharge time, control the battery to enter a shipping mode.

[0224] In some embodiments, if the discharge current is less than 5 mA and the discharge cut-off voltage is increased, the battery discharge time is continuously counted. If the battery discharge time is greater than 7 days, the battery is controlled to be in shipping mode to protect the battery before shipment.

[0225] Based on the foregoing embodiments, an embodiment of the present application provides a power supply control device, which includes the units included and the modules included in each unit, and can be implemented by a processor in an electronic device; of course, it can also be implemented by a specific logic circuit; in the implementation process, the processor can be a central processing unit (CPU), a microprocessor (MPU), a digital signal processor (DSP) or a field programmable gate array (FPGA), etc.

[0226] Figure 11 A schematic diagram of the structure of a power supply control device provided in an embodiment of the present application is shown in FIG. Figure 11 As shown, the power control device 1100 includes: an acquisition module 1101, a determination module 1102, and an execution module 1103, wherein: the acquisition module 1101 is used to obtain the charge and discharge data of the battery component of the electronic device within a target statistical period; the determination module 1102 is used to determine the user portrait information of the target user based on the charge and discharge data; the execution module 1103 is used to perform management control of the battery component within a first statistical period based on a target battery management strategy matching the user portrait information; wherein, the first statistical period is later than the target statistical period, and the target statistical period includes at least one statistical period.

[0227] In some embodiments, the determination module 1102 is further used to determine the user portrait information of the target user based on at least one of the charge and discharge capacity change data, charge and discharge times, and charge and discharge duration of the battery component within a second statistical period, where the second statistical period is a statistical period that is earlier than and adjacent to the first statistical period, or a statistical period that is earlier than the first statistical period and matches the target user; and to determine the user portrait information of the target user based on at least one of the charge and discharge capacity change data, charge and discharge times, and charge and discharge duration of the battery component within multiple third statistical periods, where the third statistical period is a statistical period that is earlier than the first statistical period and related to the target user; wherein the user portrait information can at least characterize the target user's usage habits of the battery component.

[0228] In some embodiments, the determination module 1102 is further used to determine the type of the electronic device based on usage data of the electronic device; when the electronic device belongs to the first type of device, the user portrait information of the target user is determined based on the charge and discharge data of the battery component within the second statistical period or multiple third statistical periods, wherein the target user is the only user of the electronic device; when the electronic device belongs to the second type of device, the user portrait information of the target user is determined based on the target charge and discharge data of the battery component within multiple third statistical periods, wherein the target user is one of the non-unique users of the electronic device, and the target charge and discharge data is data associated with the target user.

[0229] In some embodiments, the determination module 1102 is further used to analyze the parameter range of at least one of the charge and discharge capacity change data, charge and discharge times, and charge and discharge duration of the battery component within the target statistical period to obtain user portrait information of the target user; and use a first processing model to generate and process the charge and discharge data of the battery component within the target statistical period to obtain user portrait information of the target user, and the first processing model is deployed in the electronic device or in a processing device connected to the electronic device.

[0230] In some embodiments, the determination module 1102 is further used to determine that the target user belongs to the first type of user if the charge and discharge data indicates that the discharge ratio of the battery component within the target statistical period is within a first ratio range and the single discharge capacity change is within a first capacity range; if the charge and discharge data indicates that the discharge ratio of the battery component within the target statistical period is within a second ratio range and the single discharge capacity change is within a second capacity range, determine that the target user belongs to the second type of user; if the charge and discharge data indicates that the discharge ratio of the battery component within the target statistical period is within a third ratio range and the single discharge capacity change is within a third capacity range, determine that the target user belongs to the third type of user; if the charge and discharge data indicates that the discharge ratio of the battery component within the target statistical period is within a fourth ratio range and the single discharge capacity change is within a fourth capacity range, determine that the target user belongs to the fourth type of user; if the charge and discharge data indicates that the discharge ratio and single discharge capacity of the battery component within the target statistical period are in a random state, determine that the target user is output as a fifth type of user.

[0231] In some embodiments, the execution module 1102 is also used to call the target processing model from any one of the battery management system chip of the battery component, the battery management system bridge component set in the electronic device, or the cloud-based battery management system signal-connected to the battery management system bridge component based on the user portrait information to configure a corresponding target battery management strategy for the battery component, so as to control the working parameters of the battery component within the first statistical period based on the target battery management strategy; or, when target reference data is obtained, configure a corresponding target battery management strategy for the battery component based on the target reference data and the user portrait information, so as to control the working parameters of the battery component within the first statistical period based on the target battery management strategy, and the target reference data triggers reconfiguration of the preset battery management strategy.

[0232] In some embodiments, the execution module 1102 is also used to configure the full charge capacity and / or charging rate of the battery component based on the first battery management strategy when the target user belongs to the first type of user; configure the full charge capacity and / or charging rate of the battery component with the corresponding second battery management strategy based on the usage scenario of the electronic device when the target user belongs to the second type of user; configure the full charge capacity and / or charging rate of the battery component based on the default third battery management strategy when the target user belongs to the third type of user; configure the battery component to have a first full charge capacity and a first charging rate when the target user belongs to the fourth type of user; and configure the battery component to have a second full charge capacity and a target trigger condition for entering the shipment mode when the target user belongs to the fifth type of user.

[0233] In some embodiments, the execution module 1102 is also used to configure the battery component to have a second full charge capacity when the target user belongs to the fifth type of user; and to configure the discharge cut-off voltage of the battery component based on the remaining capacity and discharge time of the battery component when the electronic device is in the first power state; and to control the battery component to enter the shipping mode based on the fourth battery management strategy when the electronic device is in the second power state.

[0234] The description of the above device embodiment is similar to the description of the above method embodiment and has similar beneficial effects as the method embodiment. In some embodiments, the functions or modules included in the device provided in the embodiments of the present application can be used to perform the methods described in the above method embodiments. For technical details not disclosed in the device embodiments of the present application, please refer to the description of the method embodiments of the present application for understanding.

[0235] It should be noted that, in the embodiment of the present application, if the above method is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes to the relevant technology can be embodied in the form of a software product, which is stored in a storage medium and includes a number of instructions for enabling an electronic device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a U disk, a mobile hard disk, a read-only memory (ROM), a magnetic disk or an optical disk. In this way, the embodiment of the present application is not limited to any specific hardware, software or firmware, or any combination of hardware, software and firmware.

[0236] An embodiment of the present application provides an electronic device, including a memory, a processor, and at least one processing model, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the program, some or all of the steps in the above method are implemented.

[0237] The present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements some or all of the steps in the above method. The computer-readable storage medium may be transient or non-transient.

[0238] An embodiment of the present application provides a computer program, including computer-readable code. When the computer-readable code runs in an electronic device, a processor in the electronic device executes some or all of the steps for implementing the above method.

[0239] An embodiment of the present application provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and when the computer program is read and executed by a computer, implements some or all of the steps in the above method. The computer program product can be implemented specifically by hardware, software, or a combination thereof. In some embodiments, the computer program product is embodied as a computer storage medium. In other embodiments, the computer program product is embodied as a software product, such as a software development kit (SDK), etc.

[0240] It should be noted that the descriptions of the various embodiments above tend to emphasize the differences between the various embodiments, and their similarities or similarities can be referenced to each other. The descriptions of the above device, storage medium, computer program, and computer program product embodiments are similar to the descriptions of the above method embodiments and have similar beneficial effects as the method embodiments. For technical details not disclosed in the embodiments of the device, storage medium, computer program, and computer program product of this application, please refer to the description of the method embodiments of this application for understanding.

[0241] Figure 12 A hardware entity diagram of an electronic device provided in an embodiment of the present application is shown as follows: Figure 12 As shown, the hardware entity of the electronic device 1200 includes: a processor 1201, a memory 1202, and a processing model 1203, wherein the memory 1202 stores a computer program that can be run on the processor 1201, and when the processor 1201 executes the program, the steps in the method of any of the above embodiments are implemented.

[0242] The memory 1202 stores computer programs that can be run on the processor. The memory 1202 is configured to store instructions and applications executable by the processor 1201. It can also cache data to be processed or processed by the processor 1201 and various modules in the electronic device 1200 (for example, image data, audio data, voice communication data, and video communication data). This can be implemented through flash memory (FLASH) or random access memory (RAM).

[0243] The processing model 1203 can be called by the battery management system chip of the battery assembly or the processor to generate user portrait information of the target user based on the charging and discharging data.

[0244] When the processor 1201 executes the program, the steps of any of the above methods are implemented. The processor 1201 generally controls the overall operation of the electronic device 1200.

[0245] An embodiment of the present application provides a computer storage medium, which stores one or more programs. The one or more programs can be executed by one or more processors to implement the steps of the method of any of the above embodiments.

[0246] It should be noted that the description of the above storage medium and device embodiments is similar to the description of the above method embodiments and has similar beneficial effects as the method embodiments. For technical details not disclosed in the storage medium and device embodiments of this application, please refer to the description of the method embodiments of this application for understanding.

[0247] The processor may be at least one of an application-specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a central processing unit (CPU), a controller, a microcontroller, and a microprocessor. It is understood that the electronic device that implements the functions of the processor may also be other electronic devices, which are not specifically limited in the embodiments of the present application.

[0248] The above-mentioned computer storage medium / memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic random access memory (FRAM), a flash memory (Flash Memory), a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD-ROM); it can also be various terminals including one or any combination of the above-mentioned memories, such as mobile phones, computers, tablet devices, personal digital assistants, etc.

[0249] It should be understood that "one embodiment" or "an embodiment" mentioned throughout the specification means that the specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned steps / processes does not mean the order of execution, and the execution order of each step / 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. The above-mentioned serial numbers of the embodiments of the present application are for description only and do not represent the advantages and disadvantages of the embodiments.

[0250] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or apparatus comprising the element.

[0251] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0252] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed across multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the scheme of this embodiment.

[0253] In addition, the functional units in the embodiments of the present application can all be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the above-mentioned integrated unit can be implemented in the form of hardware or in the form of hardware plus software functional units. It can be understood by ordinary technicians in this field that all or part of the steps of the above-mentioned method embodiments can be completed by hardware related to program instructions, and the above-mentioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above-mentioned method embodiments; and the above-mentioned storage medium includes: various media that can store program codes, such as mobile storage devices, read-only memories (ROMs), magnetic disks or optical disks.

[0254] Alternatively, if the above-mentioned integrated unit of the present application is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the relevant technology, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for enabling an electronic device (which can be a personal computer, server, or network device, etc.) to execute all or part of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROMs, magnetic disks, or optical disks.

[0255] The above is only an implementation method of the present application, but the scope of protection of the present application is not limited thereto. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed in this application, which should be covered by the scope of protection of the present application.

Claims

1. A battery control method, comprising: Obtaining charge and discharge data of the battery components of the electronic device within a target statistical period; Determine user profile information of the target user based on the charging and discharging data; Executing management control of the battery assembly within a first statistical period based on a target battery management strategy that matches the user portrait information; The first statistical period is later than the target statistical period, and the target statistical period includes at least one statistical period.

2. The method according to claim 1, wherein determining user profile information of the target user based on the charge and discharge data comprises at least one of the following: Determining user profile information of the target user based on at least one of charge and discharge capacity change data, charge and discharge times, and charge and discharge duration of the battery assembly within a second statistical period, where the second statistical period is a statistical period that is earlier than and adjacent to the first statistical period, or a statistical period that is earlier than the first statistical period and matches the target user; Determining user profile information of a target user based on at least one of charge and discharge capacity change data, charge and discharge times, and charge and discharge duration of the battery assembly within a plurality of third statistical periods, wherein the third statistical period is a statistical period earlier than the first statistical period and related to the target user; in, The user portrait information can at least represent the target user's usage habits of the battery component.

3. The method according to claim 2, wherein determining user profile information of the target user based on the charge and discharge data comprises: determining a type of the electronic device based on usage data of the electronic device; In a case where the electronic device belongs to a first type of device, determining user portrait information of a target user based on charge and discharge data of the battery assembly in a second statistical period or multiple third statistical periods, wherein the target user is the only user of the electronic device; In the case that the electronic device belongs to the second type of device, user portrait information of the target user is determined based on the target charge and discharge data of the battery component in multiple third statistical periods, wherein the target user is one of the non-unique users of the electronic device, and the target charge and discharge data is data associated with the target user.

4. The method according to claim 1, wherein determining user profile information of the target user based on the charge and discharge data comprises at least one of the following: Analyzing the parameter range of at least one of the charge and discharge capacity change data, the number of charge and discharge times, and the charge and discharge duration of the battery assembly within a target statistical period to obtain user profile information of the target user; The first processing model is used to generate and process the charge and discharge data of the battery component within the target statistical period to obtain user portrait information of the target user. The first processing model is deployed in the electronic device or in a processing device connected to the electronic device.

5. The method according to claim 1 or 4, wherein determining user portrait information of the target user based on the charge and discharge data comprises at least one of the following: If the charge and discharge data indicates that the discharge ratio of the battery assembly within the target statistical period is within a first ratio range, and the single discharge capacity change is within a first capacity range, determining that the target user belongs to the first type of user; If the charge and discharge data indicates that the discharge ratio of the battery assembly within the target statistical period is within a second ratio range, and the single discharge capacity change is within a second capacity range, determining that the target user belongs to the second type of user; If the charge and discharge data indicates that the discharge ratio of the battery assembly within the target statistical period is within a third ratio range, and the single discharge capacity change is within a third capacity range, determining that the target user belongs to the third type of user; If the charge and discharge data indicates that the discharge ratio of the battery assembly within the target statistical period is within a fourth ratio range, and the single discharge capacity change is within a fourth capacity range, determining that the target user belongs to the fourth type of user; If the charge and discharge data indicates that the discharge ratio and single discharge capacity of the battery assembly within the target statistical period are in a random state, the target user is determined to be a fifth type of user.

6. The method according to claim 1, wherein the step of executing management control of the battery assembly within a first statistical period based on a target battery management strategy that matches the user profile information comprises: Based on the user portrait information, a target processing model is called from any one of the battery management system chip of the battery assembly, the battery management system bridge component provided in the electronic device, or the cloud battery management system signal-connected to the battery management system bridge component to configure a corresponding target battery management strategy for the battery assembly, so as to control the operating parameters of the battery assembly in a first statistical period based on the target battery management strategy; or, When target reference data is obtained, a corresponding target battery management strategy is configured for the battery component based on the target reference data and the user portrait information to control the working parameters of the battery component within the first statistical period based on the target battery management strategy. The target reference data triggers reconfiguration of the preset battery management strategy.

7. The method according to claim 1 or 6, wherein the performing management control of the battery assembly in the first statistical period based on the target battery management strategy matching the user profile information comprises: When the target user belongs to the first type of user, configuring the full charge capacity and / or charging rate of the battery assembly based on a first battery management strategy; When the target user belongs to the second type of user, configuring the full charge capacity and / or charging rate of the battery assembly according to the corresponding second battery management policy based on the usage scenario of the electronic device; When the target user belongs to the third type of user, configuring the full charge capacity and / or charging rate of the battery assembly based on a default third battery management policy; When the target user belongs to the fourth type of user, configuring the battery assembly to have a first full charge capacity and a first charging rate; In a case where the target user belongs to the fifth type of user, the battery assembly is configured to have a second full charge capacity and target trigger conditions for entering a shipping mode.

8. The method according to claim 7, wherein the performing management control of the battery assembly in the first statistical period based on the target battery management strategy matching the user profile information further comprises: When the target user belongs to the fifth type of user, configuring the battery assembly to have a second full charge capacity; as well as, When the electronic device is in a first power state, configuring a discharge cut-off voltage of the battery assembly based on the remaining capacity and discharge duration of the battery assembly; When the electronic device is in the second power state, the battery assembly is controlled to enter a shipping mode based on a fourth battery management strategy.

9. An electronic device comprising a processor and a memory, wherein the memory stores a computer program executable on the processor, and the processor is configured to perform at least one of the following operations: Obtaining charge and discharge data of the battery components of the electronic device within a target statistical period; Determine user profile information of the target user based on the charging and discharging data; Executing management control of the battery assembly within a first statistical period based on a target battery management strategy that matches the user portrait information; in, The first statistical period is later than the target statistical period, and the target statistical period includes at least one statistical period.

10. The electronic device according to claim 9 further comprises at least one processing model, which can be called by the battery management system chip of the battery assembly or the processor to generate user portrait information of the target user based on the charging and discharging data.

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