Abstract:
A new and/or improved method, apparatus and/or system is disclosed which aids in extending correct behavioral models to include fault modes and in fault mode analysis of components and/or systems in simulated model environments, including, e.g., FMEA and FMECA and diagnostic fault tree generation.
Abstract:
A monitoring and management system (MMS) includes one or more fiber optic cables arranged within or on portions of an energy storage device. Each fiber optic cable includes multiple optical sensors. At least one of the optical sensors is configured to sense a parameter of the energy storage device that is different from a parameter of the energy storage device sensed by at least another optical sensor of the multiple optical sensors. The MMS includes a light source configured to provide light to the one or more fiber optic cables and a detector configured to detect light reflected by the optical sensors. The detector generates an electrical signal based on the reflected light. A processor is coupled to receive the electrical signal, to analyze the electrical signal, and to determine state of the energy storage device based on analysis of the electrical signal.
Abstract:
Systems and methods for controlling and operating a hybrid vehicle having a high degree of hybridization are disclosed. A power flow control system predicts vehicle power demand to drive the hybrid vehicle based on changing conditions during operation of the hybrid vehicle. The power flow control system controls the power flow so as to provide power to drive the hybrid vehicle based on the predicted vehicle power demand, wherein the predicted vehicle power demand is greater than a maximum
Abstract:
A system includes utilizes optical sensors arranged within or on portions of an electrochemical energy device (e.g., a rechargeable Li-ion battery, supercapacitor or fuel cell) to measure operating parameters (e.g., mechanical strain and/or temperature) of the electrochemical energy device during charge/recharge cycling. The measured parameter data is transmitted by way of light signals along optical fibers to a controller, which converts the light signals to electrical data signal using a light source/analyzer. A processor then extracts temperature and strain data features from the data signals, and utilizes a model-based process to detect intercalation stage changes (i.e., characteristic crystalline structure changes caused by certain concentrations of guest species, such as Li-ions, within the electrode material of the electrochemical energy device) indicated by the data features. The detected intercalation stage changes are used to generate highly accurate operating state information (e.g., state-of-charge and state-of-health), and management/control signals for optimizing charge/discharge rates.
Abstract:
The following relates generally to defense mechanisms and security systems. Broadly, systems and methods are disclosed that detect an anomaly in an Embedded Mission Specific Device (EMSD). Disclosed approaches include a meta-material antenna configured to receive a radio frequency signal from the EMSD, and a central reader configured to receive a signal from the meta-material antenna. The central reader may be configured to: build a finite state machine model of the EMSD based on the signal received from the meta-material antenna; and detect if an anomaly exists in the EMSD based on the built finite state machine model.
Abstract:
An electrochemical metal alloy identification device employing electrolytes to measure and identify different potentials of alloys is presented. This includes physical structure, disposables, electrical systems, control circuitry, and algorithms to identify alloys.
Abstract:
Systems and methods for controlling and operating a hybrid vehicle having a high degree of hybridization are disclosed. A power flow control system predicts vehicle power demand to drive the hybrid vehicle based on changing conditions during operation of the hybrid vehicle. The power flow control system controls the power flow so as to provide power to drive the hybrid vehicle based on the predicted vehicle power demand, wherein the predicted vehicle power demand is greater than a maximum.
Abstract:
A system includes a first optical sensor sensitive to both a parameter of interest, Parameter1, and at least one confounding parameter, Parameter2 and a second optical sensor sensitive only to the confounding parameter. Measurement circuitry measures M1 in response to light scattered by the first optical sensor, where M1=value of Parameter1+K*value of Parameter2. The measurement circuitry also measures M2 in response to light scattered by the second optical sensor, where M2=value of Parameter2. Compensation circuitry determines a compensation factor, K, for the confounding parameter based on measurements of M1 and M2 taken over multiple load/unload cycles or over one or more thermal cycles. The compensation factor is used to determine the parameter of interest.
Abstract:
A battery management system includes one or more fiber optic sensors configured to be disposed within an electrochemical battery. Each fiber optic sensor is capable of receiving input light and providing output light that varies based on the input light and an amount of free or dissolved gas present within the battery. A detector detects the output light and generates an electrical detector signal in response to the output light. Battery management circuitry determines the state of the battery based at least in part on the detector signal.
Abstract:
A system includes utilizes optical sensors arranged within or on portions of an electrochemical energy device (e.g., a rechargeable Li-ion battery, supercapacitor or fuel cell) to measure operating parameters (e.g., mechanical strain and/or temperature) of the electrochemical energy device during charge/recharge cycling. The measured parameter data is transmitted by way of light signals along optical fibers to a controller, which converts the light signals to electrical data signal using a light source/analyzer. A processor then extracts temperature and strain data features from the data signals, and utilizes a model-based process to detect intercalation stage changes (i.e., characteristic crystalline structure changes caused by certain concentrations of guest species, such as Li-ions, within the electrode material of the electrochemical energy device) indicated by the data features. The detected intercalation stage changes are used to generate highly accurate operating state information (e.g., state-of-charge and state-of-health), and management/control signals for optimizing charge/discharge rates.