Electronic device and control method thereof

Abstract

A method and / or corresponding device for on-device real-time customization of a charging profile of a battery in an electronic device. The method may include determining at least one charging behavior parameter of the battery during each charging cycle. Further, the method may include determining at least one discharge behavior parameter of the battery after each charge cycle. Further, the method may include generating a charging profile for charging the battery based on the at least one charging behavior parameter and the at least one discharging behavior parameter. Further, the method may include charging the battery using the generated charging profile for a subsequent charge-discharge cycle.

Description

Technical Field

[0001] Certain example embodiments relate to battery management systems and / or methods, and, for example, to methods and / or electronic devices for on-device, real-time customization of a charging profile of a battery in an electronic device. Background Art

[0002] Existing methods and systems provide a static implementation of a charging profile for a battery. The charging profile takes neither the needs of the user nor the battery health status into account, resulting in a reduced user experience and reduced battery performance. In addition, battery temperature and usage behavior (behavior) have a huge impact on battery charging, and they are still not taken into account. Under different operating conditions, it cannot be assumed that a fixed charging profile meets the controlled environment results. In addition, existing methods and systems do not cater well to different operating / usage conditions (e.g., temperature limits of the battery, user involvement of the battery, etc.), resulting in a reduced user experience.

[0003] In addition, existing methods and systems attempt to generate an adaptive charging profile for a battery, but the existing methods and systems require additional circuit / hardware components and lookup data information. Existing methods cannot generate a customized real-time charging profile according to user requirements.

[0004] It would therefore be desirable to address the above-mentioned shortcomings or other deficiencies or at least provide a useful alternative. Summary of the invention

[0005] Certain example embodiments provide a method and / or electronic device for on-device real-time customization of a charging profile of a battery in an electronic device to provide a personalized experience with enhanced battery performance. The charging profile can be modified at runtime to meet the user's demand for enhanced battery performance. The modification may require a minimal or reduced amount of change. Safety constraints can be easily applied through the proposed method. The impact of the charging profile on the temperature limit of the battery is safe. The proposed method may be able to generate a customized real-time charging profile according to the user's requirements.

[0006] An example embodiment provides a method for on-device real-time customization of a charging profile of a battery in an electronic device. The method may include determining, by the electronic device, at least one charging behavior parameter of the battery during each charging cycle. In addition, the method may include determining, by the electronic device, at least one discharge behavior parameter of the battery after each charging cycle. In addition, the method may include generating, by the electronic device, a charging profile for charging the battery based on at least one charging behavior parameter and at least one discharge behavior parameter. In addition, the method may include charging the battery using the generated charging profile for subsequent charge-discharge cycles by the electronic device.

[0007] In an example embodiment, a plurality of charging profiles may be generated by applying at least one machine learning model to at least one charging behavior parameter and at least one discharging behavior parameter of a battery.

[0008] In an example embodiment, the method may include determining, by the electronic device, a usage characteristic of the electronic device. Furthermore, the method includes modifying, by the electronic device, the generated charging profile based on the usage characteristic of the electronic device. Furthermore, the method may include charging the battery using the modified charging profile by the electronic device.

[0009] In an example embodiment, the usage characteristics may include at least one of: a user type, a current location of the electronic device, a calendar event, a current health characteristic of the battery, and a current context of the user.

[0010] In an example embodiment, user types may include an aggressive user with full fast charging requirements, an aggressive user with partial fast charging requirements, a passive user with better life fast charging requirements, a passive user with balanced charging requirements, and a passive user with life squeeze charging requirements.

[0011] In an example embodiment, the at least one charging behavior parameter may include a charging duration that the battery is charged, a cable plug-in time, a number of times the cable is plugged in, a charging rate, a charging instance during a day, and a cable unplug time.

[0012] In an example embodiment, at least one discharge behavior parameter may include the amount of battery consumed by each application of the electronic device, the duration of battery consumption by each application of the electronic device, calendar input, a discharge rate of the battery, and a day's discharge instances for significantly different discharge rates.

[0013] In an example embodiment, the current health characteristics of the battery may include the battery's state of charge, the battery's state of health, the temperature of the device and surrounding environment, the battery's resistance or equivalent, battery failure / abuse, and the battery's remaining useful life.

[0014] Therefore, an example embodiment may provide an electronic device for on-device real-time customization of a charging profile of a battery in an electronic device. The electronic device may include a charging profile customization controller, which is directly or indirectly coupled to a memory and a processor including a processing circuit. The charging profile customization controller including the processing circuit may be configured to determine at least one charging behavior parameter of the battery during each charging cycle. In addition, the charging profile customization controller may be configured to determine at least one discharge behavior parameter of the battery after each charging cycle. In addition, the charging profile customization controller may be configured to generate a charging profile for charging the battery based on at least one charging behavior parameter and at least one discharge behavior parameter. In addition, the charging profile customization controller may be configured to charge the battery using the generated charging profile for subsequent charge-discharge cycles.

[0015] When considered in conjunction with the following description and the accompanying drawings, these and other aspects of the embodiments herein will be better appreciated and understood. However, it should be understood that the following description, although indicating preferred embodiments and many specific details thereof, is provided by way of illustration and not limitation. Without departing from the scope of the embodiments herein, many changes and modifications may be made within the scope of the embodiments herein, and the embodiments herein include all such modifications. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Example embodiments are shown in the accompanying drawings, and the same reference numerals indicate corresponding parts in the various figures throughout the drawings. Example embodiments of the present invention will be better understood from the following description with reference to the accompanying drawings, wherein:

[0017] Figure 1 Various hardware components of an electronic device for on-device real-time customization of a charging profile of a battery in an electronic device are shown according to certain example embodiments;

[0018] Figure 2 is a flow chart illustrating a method for on-device real-time customization of a charging profile of a battery in an electronic device according to certain example embodiments; and

[0019] Figure 3 is an example flow chart illustrating a method for adjusting a user profile for charging a battery in an electronic device, according to certain example embodiments.

[0020] Figure 4 Operations for managing a battery of an example electronic device are shown.

[0021] Figure 5 is a view provided to explain example user factors (or user types).

[0022] Figure 6is a graph provided to explain charging time and current according to one or more example embodiments.

[0023] Figure 7 is a graph provided to explain charging time and current according to one or more example embodiments.

[0024] Figure 8 are views provided to explain an example operation of determining a battery profile according to user behavior.

[0025] Fig. 9 are views provided to explain example battery-related operations of an electronic device.

[0026] Fig.10 is a diagram provided to explain the relationship between charging time and battery status according to various example user factors.

[0027] Fig.11 is a view provided to explain a control method of an electronic device according to one or more example embodiments. DETAILED DESCRIPTION

[0028] The embodiments of this article and its various features and advantageous details are explained more fully with reference to the non-limiting embodiments shown in the drawings and described in detail in the following description. The description of known components and processing techniques is omitted so as not to unnecessarily obscure the embodiments of this article. In addition, the various embodiments described herein are not necessarily mutually exclusive, because some embodiments can be combined with one or more other embodiments to form new embodiments. Unless otherwise stated, the term "or" as used herein refers to a non-exclusive or. The examples used herein are intended only to facilitate understanding of the manner in which the embodiments of this article can be practiced, and further enable those skilled in the art to practice the embodiments of this article. Therefore, the examples should not be interpreted as limiting the scope of the embodiments of this article.

[0029] As is conventional in the art, embodiments may be described and illustrated in terms of blocks that perform one or more functions described. These blocks (which may be referred to herein as managers, units, modules, hardware components, etc.) are physically implemented by analog and / or digital circuits (such as logic gates, integrated circuits, microprocessors, microcontrollers, memory circuits, passive electronic components, active electronic components, optical components, hard-wired circuits, etc.), and may be optionally driven by firmware and software. The circuit may be, for example, embodied in one or more semiconductor chips, or embodied on a substrate support such as a printed circuit board. The circuits that constitute the blocks may be implemented by dedicated hardware, or by a processor (e.g., one or more programmed microprocessors and associated circuits), or by a combination of dedicated hardware that performs some functions of the blocks and processors that perform other functions of the blocks. Without departing from the scope of the present disclosure, each block of the embodiment may be physically divided into two or more interactive and discrete blocks. Similarly, without departing from the scope of the present disclosure, the blocks of the embodiment may be physically combined into more complex blocks. Therefore, for example, each module and unit herein may include a circuit.

[0030] Therefore, embodiments of the present invention disclose a method for on-device real-time customization of a charging profile of a battery in an electronic device. The method includes determining, by the electronic device, at least one charging behavior parameter of the battery during each charging cycle. In addition, the method includes determining, by the electronic device, at least one discharge behavior parameter of the battery after each charging cycle. In addition, the method includes generating, by the electronic device, a charging profile for charging the battery based on at least one charging behavior parameter and at least one discharge behavior parameter. In addition, the method includes charging the battery using the generated charging profile for subsequent charge-discharge cycles by the electronic device.

[0031] The proposed method can be used to provide a personalized charging profile that keeps each user more satisfied with the electronic device / battery performance and provides battery brand value enhancement. The charging profile can be modified at runtime to meet the user's demand for enhanced battery performance. The modification requires no changes, minimal changes, or very little changes, and requires less time. Safety constraints can be easily applied through the proposed method. The impact of the charging profile on the temperature limit of the battery is safe. The proposed method provides more understanding about the user in order to enhance the user experience at runtime. The proposed method can be used to control personalized charging profiles in electronic devices with less time and lower cost.

[0032] The proposed method can be used to support different charging profiles using the same adapter to provide personalized battery performance. The proposed method can be used to handle preemptive temperature limits to avoid battery heating and charge to full capacity in the battery.

[0033] The proposed method can be used to support multiple fast charging profiles utilizing the same adapter in order to avoid battery heating with minimal or reduced battery degradation. The proposed method can be used to support multiple life saving profiles so that battery life can be extended and have a positive impact on battery brand value. Life saving is a type of charging profile that charges the battery in a manner that minimizes or reduces degradation with a slight increase in charging time.

[0034] The proposed method can take user input to suggest relevant charging profiles according to user needs in order to provide personalized battery performance. The proposed method can be used to provide a charging profile with a mix of time and life saving criteria in order to save time with an initial fast burst, control battery life and provide personalized battery performance. The proposed method is able to generate customized real-time charging profiles according to user needs.

[0035] Referring now to the drawings and more particularly to Figures 1 to 3 , wherein like reference numerals indicate corresponding features throughout the several views, there is shown a preferred embodiment.

[0036] Figure 1 Various hardware components of an electronic device (100) for on-device real-time customization of a charging profile of a battery (160) in the electronic device (100) are shown according to certain example embodiments. The electronic device (100) may be, for example, but not limited to, a laptop computer, a desktop computer, a notebook, a relay device, a device-to-device (D2D) device, a vehicle-to-everything (V2X) device, a smart phone, a tablet computer, an immersive device, and an Internet of Things (IoT) device. The battery (160) may be, for example, but not limited to, a lithium (Li) ion battery, a Li polymer battery, a nickel-cadmium battery, a lead-acid battery, etc.

[0037] In an embodiment, an electronic device (100) includes a processor (110), a communicator (120), a memory (130), a charging profile customization controller (140), a machine learning model controller (150), and a battery (160). The processor (110) is coupled with the communicator (120), the memory (130), the charging profile customization controller (140), the machine learning model controller (150), and the battery (160).

[0038] The charging profile customization controller (140) determines one or more charging behavior parameters of the battery (160) during each charging cycle. The one or more charging behavior parameters may be, for example, but not limited to, the charging duration, cable plug-in time, number of cable plug-ins, charging rate, charging instances per day, and cable unplug time that the battery (160) is charged.

[0039] In addition, the charging profile customization controller (140) determines one or more discharge behavior parameters of the battery (160) after each charging cycle. The one or more discharge behavior parameters can be, for example, but not limited to, the amount of battery (160) consumed by each application of the electronic device (100), the duration of battery consumption by each application of the electronic device (100), calendar input, the discharge rate of the battery (160), and a day's discharge example for significantly different discharge rates. The application can be, for example, but not limited to, a game application, a chat application, a social media application, a map application, etc.

[0040] Based on one or more charging behavior parameters and one or more discharging behavior parameters, a charging profile customization controller (140) generates a charging profile for charging a battery (160). The charging profile is generated by applying one or more machine learning (ML) models to the one or more charging behavior parameters and one or more discharging behavior parameters of the battery (160) using a machine learning model controller (150). In addition, the charging profile customization controller (140) charges the battery (160) using the generated charging profile for subsequent charge-discharge cycles.

[0041] After analyzing the user's charging and discharging behavior, a charging profile is customized for a specific user. The charging profile is customized based on the charging time, charging trajectory, and degradation. The charging profile can be, for example, but not limited to, a retro charging profile, an optimistic charging profile, an aggressive charging profile, and a balanced charging profile.

[0042] The Retro Charging Profile is used by users who always have the charger cable plugged in. The Retro Charging Profile can be used for overnight charging, during long work hours, while driving, etc. The Optimistic Charging Profile is used by users who get more life from the battery (160) with minimal or small increase in charging time. The Aggressive Charging Profile provides a quick charge before a meeting, or a quick boost when the battery (160) is completely depleted or when unexpected travel plans with no charging connection available, etc. The Aggressive Charging Profile provides fast charging at EV stations for electric vehicles (EVs). The Balanced Charging Profile is used by users who need an initial quick burst and still want to maintain a decent battery life.

[0043] In another embodiment, the charge profile customization controller (140) measures the amount of time the battery (160) is charged during each charge cycle and monitors the discharge pattern due to use of the electronic device (100) after each charge cycle. The charge profile customization controller (140) applies a charge profile in response to the measured time and discharge pattern so that battery operation is optimized (e.g., minimal degradation, temperature control, charge time, etc.).

[0044] In addition, the charging profile customization controller (140) generates an AI model that includes the correlation of time, discharge mode, and a charging profile that minimizes or reduces the discharge rate of the battery (160). The AI ​​model selects a charging profile in response to the time and discharge mode of the battery (160). Current battery characteristics (e.g., the temperature of the battery) are also fed as input to the AI ​​model.

[0045] In addition, the charging profile customization controller (140) determines the usage characteristics of the electronic device (100) and modifies the generated charging profile based on the usage characteristics of the electronic device (100). The usage characteristics may be, for example, but not limited to, the user type, the current location of the electronic device (100), calendar events, the current health characteristics of the battery (160), and the current context of the user. The user type may be, for example, but not limited to, an active user with a full fast charging requirement, an active user with a partial fast charging requirement, a passive user with a fast charging requirement for better life, a passive user with a balanced charging requirement, and a passive user with a life squeeze charging requirement. The current health characteristics of the battery (160) may be, for example, but not limited to, the state of charge of the battery (160), the health state of the battery (160), the temperature of the electronic device (100), the surrounding environment of the electronic device (100), the resistance of the battery (160) or an equivalent, a fault of the battery (160), and the remaining service life of the battery (160). Using the modified charging profile, the charging profile customization controller (140) charges the battery (160).

[0046] The charging profile customization controller (140) is physically implemented by analog and / or digital circuits (such as logic gates, integrated circuits, microprocessors, microcontrollers, memory circuits, passive electronic components, active electronic components, optical components, hard-wired circuits, etc.) and may optionally be driven by firmware.

[0047] In addition, the processor (110) is configured to execute instructions stored in the memory (130) and perform various processes. The communicator (120) including the communication circuit is configured to communicate internally between the internal hardware components and communicate with external devices via one or more networks. The memory (130) also stores instructions to be executed by the processor (110). The memory (130) may include a non-volatile storage element. Examples of such non-volatile storage elements may include a magnetic hard disk, an optical disk, a floppy disk, a flash memory, or an electrically programmable memory (EPROM) or an electrically erasable programmable (EEPROM) memory. In addition, in some examples, the memory (130) may be considered to be a non-transitory storage medium. The term "non-transitory" may indicate that the storage medium is not embodied in a carrier or propagation signal. However, the term "non-transitory" should not be interpreted as the memory (130) being non-removable. In some examples, the non-transitory storage medium may store data that may change over time (e.g., in a random access memory (RAM) or a cache memory).

[0048] In addition, a machine learning model controller (150) can be used to implement at least one of the multiple modules / controllers through an AI model. The data-driven controller can be a controller based on an ML model and a controller based on an AI model. Functions associated with the AI ​​model can be performed by a non-volatile memory, a volatile memory, and a processor (110). The processor (110) may include one or more processors. At this time, the one or more processors may be a general-purpose processor (such as a central processing unit (CPU), an application processor (AP), etc.), a graphics-specific processing unit (such as a graphics processing unit (GPU)), a visual processing unit (VPU) and / or an AI-specific processor (such as a neural processing unit (NPU)).

[0049] One or more processors control the processing of input data according to predefined operating rules or AI models stored in non-volatile memory and volatile memory. Predefined operating rules or artificial intelligence models are provided through training or learning.

[0050] Here, by learning, a predefined operating rule or AI model indicating that a desired characteristic is formed by applying a learning algorithm to a plurality of learning data is provided. The learning can be performed in the device itself in which the AI ​​according to the embodiment is executed, and / or can be implemented by a separate server / system.

[0051] The AI ​​model may include multiple neural network layers. Each layer has multiple weight values, and the layer operation is performed by the calculation of the previous layer and the operation of multiple weights. Examples of neural networks include, but are not limited to, convolutional neural networks (CNNs), deep neural networks (DNNs), recurrent neural networks (RNNs), restricted Boltzmann machines (RBMs), deep belief networks (DBNs), bidirectional recurrent deep neural networks (BRDNNs), generative adversarial networks (GANs), and deep Q networks.

[0052] A learning algorithm is a method for training a predetermined target device (e.g., a robot) using multiple learning data to enable, allow, or control the target device to make a determination or prediction. Examples of learning algorithms include, but are not limited to, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning.

[0053] although Figure 1 Various hardware components of the electronic device (100) are shown, but it should be understood that other embodiments are not limited thereto. In other embodiments, the electronic device (100) may include fewer or greater numbers of components. In addition, the labels or names of the components are for illustrative purposes only and do not limit the scope. One or more components may be combined together to perform the same or substantially similar functions in the electronic device (100).

[0054] Figure 2 is a flow chart (S200) illustrating a method for on-device real-time customization of a charging profile of a battery (160) in an electronic device (100) according to certain example embodiments. Operations (S202-S214) are processed by a charging profile customization controller (140).

[0055] At S202, the method includes determining a charging behavior parameter of the battery (160) during each charging cycle. At S204, the method includes determining a discharging behavior parameter of the battery (160) after each charging cycle. At S206, the method includes generating a charging profile for charging the battery (160) based on the charging behavior parameter and the discharging behavior parameter. At S208, the method includes charging the battery (160) using the generated charging profile for subsequent charge-discharge cycles.

[0056] At S210, the method includes determining a usage characteristic of the electronic device (100). At S212, the method includes modifying the generated charging profile based on the usage characteristic of the electronic device (100). At S214, the method includes charging the battery (160) using the modified charging profile.

[0057] The proposed method can be used to support different charging profiles using the same adapter to provide personalized battery performance. The proposed method can be used to handle preemptive temperature limits to avoid battery heating and charge the battery (160) to full capacity. The proposed method can also be used to support multiple fast charging profiles using the same adapter to avoid battery heating without battery degradation, or with only minimal or reduced battery degradation. The proposed method can be used to support multiple life saving profiles so that the battery life can be extended and the battery brand value can be positively affected.

[0058] The proposed method can take user input to suggest relevant charging profiles according to user needs in order to provide personalized battery performance. The proposed method provides a charging profile with a mix of time and life saving criteria in order to save time through an initial fast burst, control battery life and provide personalized battery performance.

[0059] When the battery charging behavior is found to be of a chronic nature, the charging profile results in a longer life of the battery (160).

[0060] Figure 3 is an example flow chart (S300) illustrating a method for adjusting a user profile for charging a battery (160) in an electronic device (100) according to certain example embodiments. Operations (S302-S310) are processed by a charging profile customization controller (140).

[0061] At S302, the electronic device (100) uses a default charging profile. At S304, the electronic device (100) uses an ML model to understand the user behavior during the time period. At S306, the electronic device (100) loads an appropriate charging profile based on the user behavior. At S308, the electronic device (100) determines whether the user behavior has changed after "x" cycles? In response to determining that the user behavior has changed after "x" cycles, at S306, the electronic device (100) loads an appropriate charging profile based on the user behavior after "x" cycles. In response to determining that the user behavior has not changed after "x" cycles, at S310, the electronic device (100) adjusts the user profile via online learning.

[0062] The proposed method can also be applied to electric vehicles (EV), hybrid vehicles, etc.

[0063] The various behaviors, actions, blocks, steps, etc. in the flow chart (S200 and S300) can be performed in the order presented, in a different order, or simultaneously. In addition, in some embodiments, some of the behaviors, actions, blocks, steps, etc. can be omitted, added, modified, skipped, etc. without departing from the scope.

[0064] The foregoing description of the specific embodiments will so fully reveal the general nature of the embodiments herein that others can easily modify and / or adapt these specific embodiments for various applications by applying current knowledge without departing from the general concepts, and therefore, these adaptations and modifications should and are intended to be understood to be within the meaning and scope of equivalents of the disclosed embodiments. It should be understood that the wording or terminology employed herein is for descriptive and not limiting purposes. Therefore, although the embodiments herein have been described according to preferred embodiments, those skilled in the art will recognize that the embodiments herein can be practiced by modification within the spirit and scope of the embodiments as described herein.

[0065] Figure 4 Operations for managing a battery of an electronic device are shown.

[0066] The electronic device (100) may include at least one of a factor storage device (410), a battery profile unit (420), or a battery management unit (430).

[0067] The factor storage device (410) may obtain a plurality of factors of a battery profile. The battery profile may include at least one of a charging profile or a discharging profile.

[0068] The battery profile may indicate a detailed control method related to charging or discharging of the battery. For example, the battery profile may include detailed parameters capable of controlling charging speed, discharging speed, charging time, discharging time, etc.

[0069] A battery profile may be described as a battery usage profile.

[0070] A battery profile may be described as a charge / discharge profile.

[0071] A battery profile may be described as a battery usage profile.

[0072] A battery profile may be described as a battery usage profile.

[0073] The charging profile may include at least one parameter for charging a battery of the electronic device (100).

[0074] The discharge profile includes at least one parameter for discharging a battery of the electronic device (100).

[0075] Parameters included in the charging profile and parameters included in the discharging profile may partially overlap.

[0076] The plurality of factors may be stored as factor information including at least one of an internal factor, an external factor, or a user factor.

[0077] The internal factors may include information corresponding to hardware / software components of the electronic device ( 100 ).

[0078] The hardware component of the internal factor may include information about at least one of memory usage, remaining battery power, or whether to operate a specific hardware configuration.

[0079] For example, the information on whether a specific hardware configuration is operated may include whether a communication interface is operated or whether an image of a display is output.

[0080] The software component of the internal factor may include information related to the application being executed. The information related to the application may include at least one of a name, a type, a required memory, or an execution time.

[0081] The external factors may include information related to the location of the external device (100). The information related to the location may be described as environmental information.

[0082] The information related to the location may indicate information that affects the charging speed or discharging speed of the battery. For example, the information related to the location may include at least one of temperature or humidity.

[0083] The electronic device (100) may obtain external factors through at least one sensor of the electronic device (100). The electronic device (100) may obtain temperature information around the electronic device (100) through a temperature sensor. The electronic device (100) may obtain humidity information around the electronic device (100) through a humidity sensor.

[0084] The user factor may include information related to user behavior. The user behavior may include at least one of charging behavior or discharging behavior. The user factor may be described as a user type.

[0085] The charging behavior may include a behavior for charging a battery of the electronic device (100). For example, a habit of quick charging once a day or the like may correspond to the charging behavior.

[0086] The discharge behavior may include a behavior for discharging a battery of the electronic device (100). For example, a habit of using an application that consumes the battery quickly, etc. may be included in the discharge behavior.

[0087] The electronic device (100) may store at least one factor of the battery profile in a factor storage device (410).

[0088] The factor storage device (410) may transmit the stored at least one factor to the battery profile unit (420).

[0089] The battery profile unit (420) may obtain at least one factor from the factor storage device (410). The battery profile unit (420) may analyze at least one factor. The battery profile unit (420) may obtain a battery profile based on at least one factor. The battery profile unit (420) may send the battery profile to the battery management unit (430). Each "unit" herein may include a circuit.

[0090] According to at least one embodiment, the battery profile unit (420) may generate a battery profile based on at least one factor.

[0091] According to at least one embodiment, the battery profile unit (420) may update (or change) the battery profile based on at least one factor. The updated battery profile may be a profile that has been generated in the battery profile unit (420) at a time before the update operation is performed.

[0092] The battery profile unit (420) may transmit the generated battery profile (or updated battery profile) to the battery management unit (430).

[0093] The battery management unit (430) may receive the generated battery profile (or updated battery profile). The battery management unit (430) may perform a function corresponding to the battery based on the received battery profile. The battery management unit (430) may perform a charging function (or a discharging function) related to the battery based on the received battery profile.

[0094] The battery management unit (430) may control the electronic device (100) based on the received battery profile. The battery management unit (430) may charge the battery based on the received battery profile.

[0095] For example, the battery management unit (430) may control a processor included in the electronic device (100) based on the received battery profile so that performance degradation of the electronic device 100 is minimized or reduced.

[0096] For example, the battery management unit (430) may control the temperature of the electronic device (100) based on the received battery profile. The electronic device 100 may control the temperature of the electronic device (100) to be lower than a threshold value. The electronic device (100) may perform a predetermined operation so that the temperature of the electronic device (100) remains below the threshold value.

[0097] The predetermined operation may include at least one of operating a fan, changing a rotation intensity of the fan to a high speed, or performing a cooling function.

[0098] For example, the battery management unit (430) may control the charging time (or discharging time) of the battery based on the received battery profile.

[0099] The electronic device (100) may increase (or decrease) the charging time of the battery based on the received battery profile. The electronic device (100) may charge (or discharge) the battery based on the charging time corresponding to the battery profile.

[0100] Figure 5 A view is provided to explain example user factors (or user types).

[0101] Referring to the embodiment (510), the user factors may be divided into an active user type and a passive user type.

[0102] The active user type can be divided into a full fast charging (active I) type and a partial fast charging (active II) type.

[0103] Passive user types can be divided into fast charging (optimistic) type with better lifespan, balanced charging (Pro, Epic) type and lifespan squeeze (retro) type.

[0104] The full fast charging (Active I) type, the partial fast charging type (Active II), the fast charging for better life (Optimistic) type, the balanced charging (Pro, Epic) type, and the life squeezing (Retro) type can be described as the first user type, the second user type, the third user type, the fourth user type, and the fifth user type, respectively.

[0105] Referring to the table (520), the electronic device (100) may identify a user factor (or a user type) based on at least one of the discharge speed average value or the battery remaining amount average value.

[0106] The electronic device (100) may obtain at least one of a discharge speed or a battery remaining amount during a predetermined period. The electronic device (100) may obtain at least one of a discharge speed average value or a battery remaining amount average value based on at least one of the discharge speed or the battery remaining amount during the predetermined period.

[0107] The electronic device (100) can identify the full fast charge (active I) type based on at least one of the discharge speed average value or the battery remaining amount average value.

[0108] Based on the fact that the discharge speed average value is included in the threshold range (eg, 81% to 100%), the electronic device (100) can identify the user factor as a full fast charge (aggressive I) type.

[0109] Based on the battery remaining amount average value being included in the threshold range (eg, 0% to 20%), the electronic device (100) can identify the user factor as a full fast charge (aggressive I) type.

[0110] Based on the discharge speed average being included in the threshold range (e.g., 81% to 100%) and based on the battery remaining amount average being included in the threshold range (e.g., 0% to 20%), the electronic device (100) can identify the user factor as a full fast charge (active I) type.

[0111] The electronic device (100) can identify the partial fast charging (aggressive II) type based on at least one of the discharge speed average or the battery remaining amount average.

[0112] Based on the fact that the discharge speed average value is included in the threshold range (for example, 61% to 80%), the electronic device (100) can identify the user factor as a partial fast charge (aggressive II) type.

[0113] Based on the battery remaining amount average value being included in the threshold range (for example, 21% to 40%), the electronic device (100) can identify the user factor as a partial fast charging (aggressive II) type.

[0114] Based on the discharge speed average being included in the threshold range (e.g., 61% to 80%) and based on the battery remaining amount average being included in the threshold range (e.g., 21% to 40%), the electronic device (100) can identify the user factor as a partial fast charging (active II) type.

[0115] The electronic device (100) can identify a fast charging (optimistic) type with a better lifespan based on at least one of an average value of a discharge speed or an average value of a remaining battery amount.

[0116] Based on the fact that the discharge speed average value is included in the threshold range (eg, 41% to 60%), the electronic device (100) can identify the user factor as a fast charging (optimistic) type with a better lifespan.

[0117] Based on the battery remaining amount average value being included in the threshold range (eg, 41% to 60%), the electronic device (100) can identify the user factor as a fast charging (optimistic) type with a better lifespan.

[0118] Based on the discharge speed average being included in a threshold range (e.g., 41% to 60%) and based on the battery remaining amount average being included in a threshold range (e.g., 41% to 60%), the electronic device (100) can identify the user factor as a fast charging (optimistic) type with better life.

[0119] The electronic device (100) can identify the type of balanced charging (Pro, Epic) based on at least one of an average value of the discharge speed or an average value of the remaining battery amount.

[0120] Based on the fact that the average value of the discharge speed is included in a threshold range (eg, 21% to 40%), the electronic device (100) can identify the user factor as a balanced charging (Pro, Epic) type.

[0121] Based on the average value of the remaining battery amount being included in a threshold range (for example, 61% to 80%), the electronic device (100) can identify the user factor as a balanced charging (Pro, Epic) type.

[0122] Based on the discharge speed average being included in a threshold range (e.g., 21% to 40%) and based on the battery remaining amount average being included in a threshold range (e.g., 61% to 80%), the electronic device (100) can identify the user factor as a balanced charging (Pro, Epic) type.

[0123] The electronic device (100) can identify the life squeeze (retrofit) type based on at least one of a discharge speed average value or a battery remaining amount average value.

[0124] Based on the fact that the discharge speed average value is included in a threshold range (eg, 0% to 20%), the electronic device (100) can identify the user factor as a life squeeze (retro) type.

[0125] Based on the battery remaining amount average value being included in the threshold range (eg, 81% to 100%), the electronic device (100) may identify the user factor as a life squeeze (retro) type.

[0126] Based on the discharge speed average being included in the threshold range (e.g., 0% to 20%) and based on the battery remaining amount average being included in the threshold range (e.g., 81% to 100%), the electronic device (100) can identify the user factor as a life squeeze (retro) type.

[0127] Figure 6 is a graph provided to explain charging time and current according to one or more embodiments.

[0128] exist Figure 6 In the graph (610) of FIG. 1 , an embodiment of charging a battery using the MSCCCV (Multi-Step Constant Current Constant Voltage) type and an embodiment of charging a battery using a battery profile corresponding to the Active I type can be compared.

[0129] In an embodiment of charging the battery using the MSCCCV type, the electronic device 100 can start charging using about 5A and complete charging in about 4000 seconds. When charging is complete, the electronic device 100 can charge the battery using about 1.5A.

[0130] In an embodiment of charging the battery using a battery profile corresponding to the aggressive I type, the electronic device 100 can start charging using about 6A to 7A and complete charging in about 3200 seconds. When charging is complete, the electronic device (100) can charge the battery using about 1.5A.

[0131] An embodiment using the Aggressive I type to charge the battery may have a charging time of approximately 800 seconds less than an embodiment using the MSCCCV type to charge the battery.

[0132] Figure 7 is a graph provided to explain charging time and current according to one or more embodiments.

[0133] exist Figure 7 In the graph (710) of FIG. 1 , an embodiment of charging a battery using the MSCCCV (Multi-step Constant Current Constant Voltage) type and an embodiment of charging a battery using a battery profile corresponding to the retro type can be compared.

[0134] In an embodiment using the MSCCCV type to charge the battery, the electronic device 100 can start charging using about 5A and complete charging in about 4000 seconds. When charging is complete, the electronic device (100) can charge the battery using about 1.5A.

[0135] In an embodiment of charging the battery using a battery profile corresponding to a retro type, the electronic device (100) can start charging using about 5 A and complete charging in about 6200 seconds. When charging is complete, the electronic device (100) can charge the battery using about 1.25 A.

[0136] The embodiment using the retro type to charge the battery can be charged for about 2200 seconds longer than the embodiment using the MSCCCV type to charge the battery. However, when the retro type is used to charge the battery, it takes more time to charge, but the battery life can be extended.

[0137] Figure 8 is a view provided to explain an operation of determining a battery profile according to user behavior.

[0138] refer to Figure 8 According to the table (810) in FIG. 1 , the electronic device (100) may collect user behaviors and determine a battery profile based on the collected user behaviors.

[0139] If there is information about the user having a habit of "fast charging EV at an EV station", the electronic device (100) may identify the user factor as a positive I type.

[0140] If there is information about the user having a habit of "quickly charging before a meeting, or quickly boosting when the battery is completely exhausted or planning a sudden trip without a charging connection available, etc.", the electronic device (100) may identify the user factor as a positive II type.

[0141] If there is information about the user having a habit of "desiring a longer battery life with minimal and small increase in charging time", the electronic device (100) can identify the user factor as an optimistic type.

[0142] If there is information about the user having a habit of "needing an initial fast burst and still wanting to maintain a decent battery life", the electronic device (100) may identify the user factor as an Epic / Pro type.

[0143] If there is information about the user having a habit of "keeping the cable plugged in all the time for charging overnight, during long working hours, while traveling by car, etc.", the electronic device (100) may identify the user factor as a retro type.

[0144] Fig. 9 are views provided to explain example battery-related operations of an electronic device.

[0145] Reference Fig. 9 According to the table (910), the electronic device (100) can perform various control operations related to the battery.

[0146] The electronic device (100) can control (or execute) "different charging profiles using the same adapter" based on the "charging current". The electronic device (100) can obtain the effect of "personalized battery performance".

[0147] The electronic device (100) can control (or execute) "anticipatory temperature limit" and "small change in charging current" based on "temperature limit". The electronic device (100) can obtain the effects of "similar charging time", "full capacity" and "avoiding battery heating".

[0148] The electronic device (100) can control (or execute) "multiple fast charging profiles using the same adapter" based on "fast charging". The electronic device (100) can obtain the effects of "less battery degradation" and "avoiding battery heating".

[0149] The electronic device (100) can control (or execute) "a plurality of life saving profiles" based on "life extension". The electronic device (100) can obtain the effects of "battery life can be extended by an additional 1.5 years" and "positive impact on brand value".

[0150] The electronic device (100) can control (or execute) "understanding user adaptation" based on "user participation". The electronic device (100) can obtain the effect of "providing burst / fast / life saving profiles accordingly".

[0151] The electronic device (100) can control (or execute) "a clever way of imposing any number of software-based constraints" based on "security constraints". The electronic device (100) can achieve the effect of "no need for separate coding and configuration for each constraint".

[0152] The electronic device (100) can control (or execute) "obtaining user input to suggest a relevant charging profile as needed" based on "user input". The electronic device (100) can obtain the effect of "personalized battery performance".

[0153] The electronic device (100) can control (or execute) "providing a profile with a mixture of time and life saving criteria" based on the "balanced profile". The electronic device (100) can obtain the effects of "saving time with an initial rapid surge and also controlling life" and "personalizing battery performance".

[0154] Fig.10 is a view provided to explain the relationship between the charging time and the battery status according to various user factors.

[0155] Reference Fig.10 In the embodiment (1010), the reference type among the various types may be the fifth type of MSCCCV (multi-step constant current constant voltage).

[0156] Fig.10 The embodiment (1010) may indicate that as the charging time becomes longer (or shorter) than the charging time of the fifth type, the battery life becomes longer (or shorter) than the battery life of the fifth type.

[0157] “Additional days to reach MSCCCV SOH (state of health)” may indicate the life span of the battery profile.

[0158] The faster the charging speed, the shorter the battery life.

[0159] The shorter the time it takes to charge a certain amount (eg, full charge time), the longer the life of the battery.

[0160] The slower the charging speed, the longer the battery life.

[0161] The longer it takes to charge to a certain amount (eg, full charge time), the longer the life of the battery.

[0162] exist Figure 5, the active type III is not described. However, the charging speed of the active type III may be slower than the charging speed of the active type II, and faster than the charging speed of the MSCCCV.

[0163] exist Figure 5 In the , there is no distinction between Epic type and Pro type. However, the Pro type can be charged faster than the Epic type.

[0164] Fig.11 is a view provided to explain a control method of an electronic device (100) according to one or more embodiments.

[0165] Reference Fig.11 , the electronic device (100) may obtain factor information including at least one of an internal factor, an external factor, or a user factor (S1105).

[0166] The internal factors may include information corresponding to hardware / software components of the electronic device ( 100 ).

[0167] The external factors may include information related to the location of the electronic device (100) (or environmental information).

[0168] User factors may include information related to user behavior.

[0169] Since already in Figure 4 A detailed description about the factor information is described in , so the overlapping description will be omitted.

[0170] The electronic device (100) may determine whether a predetermined event is recognized (S1110).

[0171] The electronic device (100) may determine whether a predetermined event is recognized based on a user input or factor information including at least one of an internal factor, an external factor, or a user factor.

[0172] The predetermined event may be an event in which a user input for changing a battery usage mode is received.

[0173] The predetermined event may be an event in which the remaining battery is recognized to be equal to or less than a threshold value.

[0174] The predetermined event may be an event of executing a predetermined application. The predetermined application may be an application that consumes battery faster than other applications. The predetermined application may be set to an application type or a required battery.

[0175] For example, the predetermined application may be a game application. When the application classified as a game application is executed, the electronic device (100) may determine that a predetermined event is recognized.

[0176] For example, the predetermined application may be an application whose required memory is equal to or greater than a threshold value. A plurality of applications may store information about required memory. The required memory of the first application may be a first value, and the required memory of the second application may be a second value. The electronic device (100) may check whether the first value or the second value may be equal to or greater than the threshold value. When the first value is equal to or greater than the threshold value, the electronic device (100) may set the first application as the predetermined application.

[0177] Based on the failure to identify the predetermined event (S1110-N), the electronic device (100) may repeatedly obtain factor information.

[0178] Each embodiment herein may be used in combination with any other embodiment described herein.

[0179] Upon identifying the predetermined event (S1110-Y), the electronic device (100) may identify a battery profile based on the factor information (S1115).

[0180] The electronic device (100) identifies a battery profile based on factor information, the factor information including at least one of an internal factor, an external factor or a user factor.

[0181] The battery profile may include a charging profile.

[0182] According to at least one of the embodiments, the electronic device (100) may identify a charging profile based on factor information. The electronic device (100) may identify a charging profile based on information related to user behavior included in the factor information.

[0183] Already in Figure 5 and Figure 8 The operation of specifying a charging profile (battery profile) according to user behavior is described in , so the overlapping description is omitted.

[0184] The electronic device (100) may obtain charging parameters corresponding to the battery profile (S1120).

[0185] The electronic device (100) may obtain charging parameters based on the battery profile.

[0186] The electronic device (100) can perform battery charging suitable for a specific battery profile.

[0187] For battery charging, detailed parameters that influence the charging method must be determined.

[0188] The charging parameters may include at least one of a charging current, a charging voltage, a charging time, a temperature of the electronic device (100), control of a cooling module, or control of a background application.

[0189] The electronic device (100) may perform a function corresponding to charging the battery based on the charging parameter (S1125).

[0190] The electronic device (100) may adjust (or change) the charging current based on the battery profile.

[0191] For example, the electronic device (100) can perform charging by greatly changing the charging current based on a battery profile requiring fast charging.

[0192] The electronic device (100) may adjust (or change) the charging voltage based on the battery profile.

[0193] For example, the electronic device (100) can perform charging by greatly changing the charging voltage based on a battery profile requiring fast charging.

[0194] The electronic device (100) may adjust (or change) the charging time based on the battery profile.

[0195] For example, the electronic device (100) may change the charging method to reduce the charging time based on a battery profile that requires fast charging.

[0196] The electronic device (100) may adjust (or change) the temperature of the electronic device (100) based on the battery profile.

[0197] For example, the electronic device (100) may perform charging by lowering the temperature (or setting the temperature) based on a battery profile requiring fast charging.

[0198] The electronic device (100) may adjust (or change) control of the cooling module based on the battery profile.

[0199] The electronic device (100) may include a cooling module, which includes a circuit. The cooling module may perform a function of lowering the temperature. For example, the cooling module may control a fan to lower the temperature.

[0200] For example, the electronic device (100) can perform charging by greatly changing the performance (or output) of the cooling module based on a battery profile that requires fast charging.

[0201] The electronic device (100) may adjust (or change) control of background applications based on the battery profile.

[0202] The electronic device (100) may control whether to run an application in consideration of the resources of the background application. For example, the electronic device (100) may forcibly terminate a background application whose resources are equal to or greater than a threshold by considering the battery profile during charging.

[0203] The electronic device (100) may limit the number of background applications in consideration of the resources of the background resources. For example, the electronic device (100) may limit the number of running background applications to 10 and forcefully terminate any background applications exceeding 10. The applications that are not terminated may be determined based on a predetermined priority (or importance).

[0204] Although the present disclosure has been shown and described with reference to various embodiments, it should be understood that the various embodiments are intended to be illustrative rather than restrictive. It will be further understood by those skilled in the art that various changes may be made in form and detail without departing from the true spirit and full scope of the present disclosure (including the appended claims and their equivalents). It should also be understood that any embodiment described herein may be used in combination with any other embodiment described herein.

Claims

1. A method for on-device real-time customization of a charging profile of a battery in an electronic device, the method comprising: determining at least one charging behavior parameter of the battery during each charging cycle of a plurality of charging cycles; determining at least one discharge behavior parameter of the battery after each of the charging cycles in the plurality of charging cycles; generating a charging profile for charging the battery based on the at least one charging behavior parameter and the at least one discharging behavior parameter; as well as For at least some subsequent charge-discharge cycles, the battery is charged using the generated charging profile.

2. The method according to claim 1, wherein: The charging profile is generated by applying at least one machine learning model to at least the at least one charging behavior parameter and the at least one discharging behavior parameter of the battery.

3. The method according to claim 1, wherein: The method comprises: determining usage characteristics of the electronic device; modifying the generated charging profile based on the usage characteristics of the electronic device; and The battery is charged by the electronic device using the modified charging profile.

4. The method according to claim 3, wherein: The usage characteristics include at least one of: a user type, a current location of the electronic device, a calendar event, a current health characteristic of the battery, and a current context of the user.

5. The method according to claim 4, wherein: The user type includes at least one of: an active user with full fast charging requirement, an active user with partial fast charging requirement, a passive user with better life fast charging requirement, a passive user with balanced charging requirement, and a passive user with life squeeze charging requirement.

6. The method according to claim 1, wherein: The at least one charging behavior parameter includes at least one of: a charging duration during which the battery is charged, a cable plug-in time, a number of times the cable is plugged in, a charging rate, a charging instance in a day, and a cable unplug time.

7. The method according to claim 1, wherein: The at least one discharge behavior parameter includes at least one of: an amount of battery consumed by each application of the electronic device, a duration of battery consumption by each application of the electronic device, a calendar input, a discharge rate of the battery, and a one-day discharge instance for significantly different discharge rates.

8. The method according to claim 4, wherein: The current health characteristics of the battery include the battery's state of charge, the battery's state of health, the temperature of the electronic device, the electronic device's surroundings, the battery's resistance and / or equivalent, the battery's faults, and the battery's remaining useful life.

9. An electronic device, for performing on-device real-time customization of a charging profile of a battery in the electronic device, the electronic device comprising: Memory; processor; as well as A charging profile customization controller, the charging profile customization controller comprising a processing circuit, coupled to the memory and the processor, wherein the charging profile customization controller is configured to: determining at least one charging behavior parameter of the battery during each charging cycle of a plurality of charging cycles; determining at least one discharge behavior parameter of the battery after each of the charging cycles in the plurality of charging cycles; generating a charging profile for charging the battery based on the at least one charging behavior parameter and the at least one discharging behavior parameter; and For at least some subsequent charge-discharge cycles, the battery is charged using the generated charging profile.

10. The electronic device according to claim 9, wherein: The controller is configured such that the charging profile is generated by applying at least one machine learning model to at least the at least one charging behavior parameter and the at least one discharging behavior parameter of the battery.

11. The electronic device according to claim 9, wherein: The charging profile customization controller is configured to: determining usage characteristics of the electronic device; modifying the generated charging profile based on the usage characteristics of the electronic device; as well as The battery is charged using the modified charging profile.

12. The electronic device according to claim 11, wherein: The usage characteristics include at least one of: a user type, a current location of the electronic device, a calendar event, a current health characteristic of the battery, and a current context of the user.

13. The electronic device according to claim 12, wherein: The user type includes at least one of: an active user with full fast charging requirement, an active user with partial fast charging requirement, a passive user with better life fast charging requirement, a passive user with balanced charging requirement, and a passive user with life squeeze charging requirement.

14. The electronic device according to claim 9, wherein: The at least one charging behavior parameter includes a charging duration during which the battery is charged, a cable plug-in time, a number of times the cable is plugged in, a charging rate, a charging instance during a day, and a cable unplug time.

15. The electronic device according to claim 9, wherein: The at least one discharge behavior parameter includes the amount of battery consumed by each application of the electronic device, the duration of battery consumption by each application of the electronic device, calendar input, the discharge rate of the battery, and one-day discharge instances for significantly different discharge rates.

Images