Abstract: According to one illustrative, non-limiting embodiment, an IHS may include computer-executable instructions for receiving individual-specific raw data instances associated with an individual, and other raw data instances that are not associated with the individual to perform a native artificial intelligence (AI) process to generate one or more native features according to the received other raw data instances and the individual-specific raw data instances, and a native AI model from the one or more native features. The instructions also perform a differential AI process to generate one or more differential features according to the received other raw data instances, and a differential model from the one or more differential features.

Abstract: The measured capacity of a rechargeable battery provides the full charge capacity of the battery, but does not reflect degradation of the battery capacity between measurements. Embodiments initiate a first measurement of a rechargeable battery capacity. Parameters of use of the rechargeable battery are monitored, such as the depth and number of discharge cycles of the battery. Until a second capacity measurement is initiated, a battery capacity correction factor is generated based on the monitored parameters of the use of the rechargeable battery. During this interval until the second measurement, a remaining available capacity of the rechargeable battery is reported based on an adjustment of the first capacity measurement using the generated correction factor. The correction factor for a particular battery may be based on learned battery degradation for a large number of batteries and also based on events and conditions of use of that particular battery.

Abstract: Systems and methods manage use of rechargeable battery power of Information Handling Systems (IHSs). In managing power draws from the batteries of an IHS, use of software applications of the IHS is monitored and use is detected of a software application that has been designated as prioritized for use of the IHS batteries. A power throttling factor is selected for use in drawing power from the rechargeable batteries of the IHS while the prioritized software application remains in use. The selected power throttling factor is transmitted to an embedded controller of the IHS and the embedded controller is notified when the prioritized software application is no longer in use by a user of the IHS. The embedded controller receives the power throttling factor and, while the prioritized software application remains in use, the embedded controller limits power drawn from the IHS rechargeable batteries according to the power throttling factor.

Abstract: An information handling system may determine that a first process of a list of processes is a top-ranked process and may adjust one or more settings of the information handling system associated with the first process. The information handling system may monitor performance parameters of the information handling system following the adjustment of the settings. Based on monitoring the performance parameters, the information handling system may determine that a performance score of the information handling system is below a threshold performance score and may reduce a ranking of the first process based on the determination. The ranking of the first process may be reduced such that a second process becomes a new top-ranked process. The information handling system may then adjust one or more settings associated with the second process.

Abstract: Systems and methods for managing battery runtime and performance based upon presence detection are described. In some embodiments, a method may include: receiving a first amount of energy from a power source directed to supporting operation of an Information Handling System (IHS); receiving a second amount of energy from the power source directed to charging a battery of the IHS; determining a user's presence state with respect to the IHS; and modifying the first and second amounts in response to the presence state.

Abstract: In one or more embodiments, one or more systems, one or more methods, and/or one or more processes may determine a historical discharge rate (dh) from multiple discharge rates a battery of an information handling system (IHS) while the IHS operates on electrical power provided by the battery; receive a current discharge rate (dc) of the battery; determine a full charge capacity correction factor value (Cfcc) associated with the battery; determine a weighting factor (?); determine a difference between a full charge capacity value (FCC) and Cfcc; determine ?·dh; determine (1??)·dc; determine a sum of dh·? and dc·?; determine a quotient value of FCC?Cfcc and ?·dh+(1??)·dc; scale the quotient value based at least on a relative state of charge of the battery to determine an estimated time remaining for the IHS to operate on the electrical power provided by the battery; and display the estimated time remaining.

Abstract: The measured capacity of a rechargeable battery provides the full charge capacity of the battery, but does not reflect degradation of the battery capacity between measurements. Embodiments initiate a first measurement of a rechargeable battery capacity. Parameters of use of the rechargeable battery are monitored, such as the depth and number of discharge cycles of the battery. Until a second capacity measurement is initiated, a battery capacity correction factor is generated based on the monitored parameters of the use of the rechargeable battery. During this interval until the second measurement, a remaining available capacity of the rechargeable battery is reported based on an adjustment of the first capacity measurement using the generated correction factor. The correction factor for a particular battery may be based on learned battery degradation for a large number of batteries and also based on events and conditions of use of that particular battery.

Abstract: An information handling system may determine that a first process of a list of processes is a top-ranked process and may adjust one or more settings of the information handling system associated with the first process. The information handling system may monitor performance parameters of the information handling system following the adjustment of the settings. Based on monitoring the performance parameters, the information handling system may determine that a performance score of the information handling system is below a threshold performance score and may reduce a ranking of the first process based on the determination. The ranking of the first process may be reduced such that a second process becomes a new top-ranked process. The information handling system may then adjust one or more settings associated with the second process.

Abstract: Settings on an information handling system may be adjusted to set priority levels for processes executing on the information handling system in view of desired operational characteristics of the information handling system for a user persona and in view of expected future events for the information handling system. A score may be generated based on a user persona (e.g., whether a user is a light gamer, heavy gamer, corridor warrior, or desk worker) and expected future computer contexts (e.g., an expectation that a user will play a game in one hour). That score may be used to determine policies (e.g., high performance, balanced, or battery saver) to implement through settings on the computer system. Consideration of user persona classifications, associated group behaviors, and dynamic system contexts (including resource extremas, location, temporal context, and predicted future events) improve use of system resources through prioritization and governing of diverse optimization methods.

Abstract: Systems and methods for managing battery runtime and performance based upon presence detection are described. In some embodiments, a method may include: receiving a first amount of energy from a power source directed to supporting operation of an Information Handling System (IHS); receiving a second amount of energy from the power source directed to charging a battery of the IHS; determining a user's presence state with respect to the IHS; and modifying the first and second amounts in response to the presence state.

Abstract: Embodiments of systems and methods for managing performance optimization of applications executed by an Information Handling System (IHS) are described. In an illustrative, non-limiting embodiment, a method may include: identifying, by an IHS, a first application; assigning a first score to the first application based upon: (i) a user's presence state, (ii) a foreground or background application state, (iii) a power adaptor state, and (iv) a hardware utilization state, detected during execution of the first application; identifying, by the IHS, a second application; assigning a second score to the second application based upon: (i) another user's presence state, (ii) another foreground or background application state, (iii) another power adaptor state, and (iv) another hardware utilization state, detected during execution of the second application; and prioritizing performance optimization of the first application over the second application in response to the first score being greater than the second score.

Abstract: Systems and methods for remotely applying battery management policies based on local user behavior. In an illustrative, non-limiting embodiment, an Information Handling System (IHS) may include: a processor and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, cause the IHS to: receive a battery management policy from a remote server; and apply the battery management policy to the IHS, wherein the battery management policy is selected based upon a local user's behavior.

Abstract: A method and system for generating a secure random seed uses chemical processes in a battery of an information handling system as an entropy source for randomness. The secure random seed may be used by a pseudo-random number generator to create a secure pseudorandom bit stream usable to generate secure encryption keys.

Abstract: A method and system for generating a secure random seed uses chemical processes in a battery of an information handling system as an entropy source for randomness. The secure random seed may be used by a pseudo-random number generator to create a secure pseudorandom bit stream usable to generate secure encryption keys.

Abstract: Systems and methods for remotely applying battery management policies based on local user behavior. In an illustrative, non-limiting embodiment, an Information Handling System (IHS) may include: a processor and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, cause the IHS to: receive a battery management policy from a remote server; and apply the battery management policy to the IHS, wherein the battery management policy is selected based upon a local user's behavior.

Abstract: Methods and systems for implementing a user-personalized wake policy may enable learning of actual user behavior over daily, weekly, and/or monthly time scales. Based on actual usage patterns of a user of an information handling system, the user-personalized wake policy may automatically wake the information handling system in advance of when the user is predicted to desire to use the information handling system. Other actions, such as network data updates, may be automatically performed by the user-personalized wake policy in advance of the user-personalized wake times.

Abstract: In accordance with the present disclosure, a system and method are herein disclosed for providing in-service diagnostics based on health signatures of an information handling system. In one embodiment, the health of an information handling system is periodically probed by a software agent running as a service. The service polls a set of probes from interfaces on the host system and tracks parameters indicative of system and component health and performance. An analytics engine processes the data to identify anomalies and outliers, and to detect signatures that are precursors to potential service incidents. A rule set matches signatures to potential actions. Based on the detected signatures and rule sets, the service is operable to select, schedule, and execute one or more diagnostic tests. If an information handling system or component thereof fails a diagnostic test, the results are archived to persistent storage and communicated to an administrator.

Abstract: In accordance with the present disclosure, a system and method are herein disclosed for providing in-service diagnostics based on health signatures of an information handling system. In one embodiment, the health of an information handling system is periodically probed by a software agent running as a service. The service polls a set of probes from interfaces on the host system and tracks parameters indicative of system and component health and performance. An analytics engine processes the data to identify anomalies and outliers, and to detect signatures that are precursors to potential service incidents. A rule set matches signatures to potential actions. Based on the detected signatures and rule sets, the service is operable to select, schedule, and execute one or more diagnostic tests. If an information handling system or component thereof fails a diagnostic test, the results are archived to persistent storage and communicated to an administrator.

Abstract: Embodiments of methods for preventing internal short circuits in a lithium-ion battery cell. In an embodiment, a method of manufacturing a lithium-ion battery cell may include providing a cathode, providing an anode, providing a separator disposed between the cathode and the anode, and covering an edge of the cathode to prevent a short between the cathode and the anode through the separator. The method may also include winding the cathode, the anode, and the separator into an electrode roll.

Abstract: Methods and systems for performing diagnostic testing based on information handling system variables include receiving a first indication specifying diagnostic tests to be performed on an information handling system, receiving a second indication specifying diagnostic test conditions respectively associated with the diagnostic tests, receiving a third indication specifying health condition severity of the information handling system, and receiving a fourth indication specifying a user profile including user usage patterns. Based on the first indication, the second indication, the third indication, and the fourth indication, a schedule for executing diagnostic tests is generated.