Abstract: The preset invention relates to an identification code allocating device for battery management categories, a sequencing device for the battery management categories, and a battery management method using the same and the identification code allocating device includes: a unique identification code allocating unit allocating a unique identification code for a plurality of battery management categories each; a cycle identification code allocating unit allocating a cycle identification code for each of the plurality of battery management categories to correspond to a cycle of each of the plurality of battery management categories; and a dependency identification code allocating unit allocating a dependency identification code for each of the plurality of battery management categories to correspond to dependency relationships among the plurality of battery management categories.

Abstract: The preset invention relates to an identification code allocating device for battery management categories, a sequencing device for the battery management categories, and a battery management method using the same and the identification code allocating device includes: a unique identification code allocating unit allocating a unique identification code for a plurality of battery management categories each; a cycle identification code allocating unit allocating a cycle identification code for each of the plurality of battery management categories to correspond to a cycle of each of the plurality of battery management categories; and a dependency identification code allocating unit allocating a dependency identification code for each of the plurality of battery management categories to correspond to dependency relationships among the plurality of battery management categories.

Abstract: Effective scheduling of battery charge and discharge activities, by making the most of battery characteristics, can extend the battery pack's operation-time and lifetime. A system and method for scheduling battery activities is disclosed. This framework dynamically adapts battery activities to load demands and to the condition of individual battery cells, thereby extending the battery pack's operation-time and making them robust to anomalous voltage imbalances. The scheduling framework includes two components. An adaptive filter estimates the upcoming load demand. Based on the estimated load demand, a scheduler can determine the number of parallel-connected battery cells to be discharged. The scheduler also effectively partitions the battery cells in a pack, allowing the battery cells to be simultaneously charged and discharged in coordination with a reconfigurable battery circuit.

Abstract: A dynamically reconfigurable battery framework for management of a large-scale battery system systems is provided. The framework monitors, reconfigures, and controls large-scale battery systems online. The framework is built upon a topology-based bypassing mechanism that provides a set of rules for changing the battery-pack configuration, and a semantic bypassing mechanism by which the battery-cell connectivity is reconfigured to recover from a battery-cell failure. More specifically, the semantic bypassing mechanism implements a constant-voltage-keeping policy and a dynamic-voltage-allowing policy. The former policy is effective in preventing unavoidable voltage drops during the battery lifetime, while the latter policy is effective in supplying different amounts of power to meet a wide-range of application requirements.

Abstract: A dynamically reconfigurable battery framework for management of a large-scale battery system systems is provided. The framework monitors, reconfigures, and controls large-scale battery systems online. The framework is built upon a topology-based bypassing mechanism that provides a set of rules for changing the battery-pack configuration, and a semantic bypassing mechanism by which the battery-cell connectivity is reconfigured to recover from a battery-cell failure. More specifically, the semantic bypassing mechanism implements a constant-voltage-keeping policy and a dynamic-voltage-allowing policy. The former policy is effective in preventing unavoidable voltage drops during the battery lifetime, while the latter policy is effective in supplying different amounts of power to meet a wide-range of application requirements.

Abstract: A dynamically reconfigurable battery framework for management of a large-scale battery system systems is provided. The framework monitors, reconfigures, and controls large-scale battery systems online. The framework is built upon a topology-based bypassing mechanism that provides a set of rules for changing the battery-pack configuration, and a semantic bypassing mechanism by which the battery-cell connectivity is reconfigured to recover from a battery-cell failure. More specifically, the semantic bypassing mechanism implements a constant-voltage-keeping policy and a dynamic-voltage-allowing policy. The former policy is effective in preventing unavoidable voltage drops during the battery lifetime, while the latter policy is effective in supplying different amounts of power to meet a wide-range of application requirements.

Abstract: A system is presented for detecting malware applications residing on a mobile device powered by a battery. The system includes a power monitoring module, a data analysis module and a data store that stores a plurality of known power signatures signifying a power consumption anomaly. The power monitoring module measures power drawn from the battery and the data analysis module extracts a power history signature from the power measures. The data analysis module then compares the power history signature with the plurality of known power signatures and initiates a protective operation if the power history signature is closely correlated to one or more of the known power signatures.

Abstract: A dynamically reconfigurable framework is provided for a large-scale battery system. The framework is comprised of a plurality of battery circuits arranged adjacent to each other to form a battery-cell array that is coupled to an application load. A given battery circuit includes: a battery cell with an input terminal and an output terminal; a first switch connected between the load and an input terminal of the battery cell; a second switch is connected between an input terminal of the battery cell and an output terminal of a battery cell in an immediately adjacent battery circuit; and a third switch connected between the output terminal of the battery cell and the output terminal of the battery cell in the adjacent battery circuit. The battery-cell array also includes a local controller that selectively controls the switches in the plurality of battery circuits.

Abstract: Effective scheduling of battery charge and discharge activities, by making the most of battery characteristics, can extend the battery pack's operation-time and lifetime. A system and method for scheduling battery activities is disclosed. This framework dynamically adapts battery activities to load demands and to the condition of individual battery cells, thereby extending the battery pack's operation-time and making them robust to anomalous voltage imbalances. The scheduling framework includes two components. An adaptive filter estimates the upcoming load demand. Based on the estimated load demand, a scheduler can determine the number of parallel-connected battery cells to be discharged. The scheduler also effectively partitions the battery cells in a pack, allowing the battery cells to be simultaneously charged and discharged in coordination with a reconfigurable battery circuit.

Abstract: A system is presented for detecting malware applications residing on a mobile device powered by a battery. The system includes a power monitoring module, a data analysis module and a data store that stores a plurality of known power signatures signifying a power consumption anomaly. The power monitoring module measures power drawn from the battery and the data analysis module extracts a power history signature from the power measures. The data analysis module then compares the power history signature with the plurality of known power signatures and initiates a protective operation if the power history signature is closely correlated to one or more of the known power signatures.

Abstract: A dynamically reconfigurable battery framework for management of a large-scale battery system systems is provided. The framework monitors, reconfigures, and controls large-scale battery systems online. The framework is built upon a topology-based bypassing mechanism that provides a set of rules for changing the battery-pack configuration, and a semantic bypassing mechanism by which the battery-cell connectivity is reconfigured to recover from a battery-cell failure. More specifically, the semantic bypassing mechanism implements a constant-voltage-keeping policy and a dynamic-voltage-allowing policy. The former policy is effective in preventing unavoidable voltage drops during the battery lifetime, while the latter policy is effective in supplying different amounts of power to meet a wide-range of application requirements.

Abstract: A dynamically reconfigurable framework is provided for a large-scale battery system. The framework is comprised of a plurality of battery circuits arranged adjacent to each other to form a battery-cell array that is coupled to an application load. A given battery circuit includes: a battery cell with an input terminal and an output terminal; a first switch connected between the load and an input terminal of the battery cell; a second switch is connected between an input terminal of the battery cell and an output terminal of a battery cell in an immediately adjacent battery circuit; and a third switch connected between the output terminal of the battery cell and the output terminal of the battery cell in the adjacent battery circuit. The battery-cell array also includes a local controller that selectively controls the switches in the plurality of battery circuits.