General Electric Company

Samsung Electronics Co., Ltd.

Atanu Talukdar

Maria Cecilia Mazzaro

Frederick William Block

Mark Andrew Runkle

Charles Scott Sealing

Pablo Enrique Acevedo Giraldi

Shashishekara Parampalli Adiga

Anshul Kaushik

Subrat Nanda

Achalesh Kumar Pandey

Sameer Vittal

Rajkumar Subhash Patil

Daebong Jung

Johan Michael Reimann

Guruprasad Srinivasan

Hardev Singh

Kotesh Kummamuri Rao

Venkatesh Kattigari Madyastha

Jose Mendoza

Jose Leon Vega

Arunava Naha

Yan Chen

Fred Gorum Graham, Iii

Achalesh Kumar Panley

Fred Gorum Graham Iii

A method for estimating a plurality of parameters pertaining to an electrochemical model of a cell may include: obtaining, by a device, an Electrochemical Impedance Spectroscopy (EIS) spectrum and a Constant Current-Constant Voltage (CC-CV) charge-Constant Current (CC) discharge response of the cell; extracting, by the device, a plurality of features from the EIS spectrum and a plurality of features from the CC-CV charge-CC discharge response of the cell; and estimating, by the device, the plurality of parameters based on at least one of the plurality of features of the EIS spectrum and at least one of the plurality of features of the CC-CV charge-CC discharge response of the cell.

Methods and systems for estimating parameters of a cell at various charge-discharge profiles

The present disclosure relates to a method and apparatus for accurately detecting an operating status of a battery in a battery system, where the method includes determining a charging profile of a battery in a battery system, identifying a constant voltage and a corresponding constant current in a charging cycle of the charging profile, estimating at least one of a decay constant or an internal resistance associated with the battery, using at least one of the constant voltage or the constant current, comparing the decay constant with a first threshold value or comparing the internal resistance with a second threshold value, and detecting an operating status of the battery to be faulty or healthy, based on the comparison.

Method and system for detecting operating status of battery

A controller includes a processor and memory. The memory stores instructions that, when executed, are configured to cause the processor to receive measurements pertaining to a measured operation parameter of at least a portion of a turbine system. The instructions are also configured to cause the processor to generate a customized model for the at least the portion of the turbine system. Moreover, the instructions are configured to cause the processor to estimate an estimated value using the received measurements. The estimated value pertains to a parameter of the turbine system. Furthermore, the instructions are configured to cause the processor to using the customized model, reduce or remove at least some environmental conditions from a corrected estimated value derived from the estimated value.

Model-based performance estimation

A system may include a model library configured to model a system, wherein the model library includes a plurality of subsystem models, and each of the plurality of subsystem models is configured to derive a reliability measure. The system further includes a fault tolerance input and a maintenance policy input. The system further includes a dynamic risk calculation engine (DRCE) configured to use a user-defined set of the plurality of subsystem models, the fault tolerance input and the maintenance policy input, to derive a system risk for an apparatus.

Systems and methods for improved reliability operations

A system may include a model library configured to model a safety system, wherein the model library comprises a plurality of subsystem models, and each of the plurality of subsystem models is configured to derive a reliability measure. The system further includes a fault tolerance input and a maintenance policy input. The system further includes a dynamic risk calculation engine (DRCE) configured to use a user-defined set of the plurality of subsystem models, the fault tolerance input and the maintenance policy input, to derive a system risk for an apparatus.

A system may include a dynamic risk calculation engine (DRCE) system. The DRCE includes a model library configured to model a system, wherein the model library comprises a plurality of subsystem models, and each of the plurality of subsystem models is configured to derive a reliability measure. The DRCE further includes a fault tolerance input and a maintenance policy input. The DRCE additionally includes a run-time risk calculation engine configured to use a user-defined set of the plurality of subsystem models, the fault tolerance input, and the maintenance policy input, to derive a system risk for an apparatus.

Systems and methods for dynamic risk derivation

A turbine performance diagnostic system creates a performance report for one or more turbines and includes an assessment module that receives operating data from at least one turbine and produces a performance report from the operating data. The assessment module includes a change detection module configured to determine when at least one parameter has changed beyond an associated threshold and generate an alarm and a root cause analyzer coupled to the change detection module that predicts a root cause of the alarm utilizing a Bayesian Belief Network (BBN). The performance report includes an indication of the predicted root cause.

Turbine performance diagnostic system and methods

Methods and systems for use in predicting wind turbine failures are provided. One example method includes determining a parametric profile for a component of a wind turbine from operating data of a plurality of wind turbines, determining an anomaly profile for the component of the wind turbine from anomaly alerts from a plurality of wind turbines, and determining a probability of failure for the component of the wind turbine based on the parametric profile and the anomaly profile. The parametric profile defines at least one parametric event associated with the component prior to failure of the component, and the anomaly profile defines at least one anomaly associated with the component prior to failure of the component.

System and method for predicting wind turbine component failures

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Karnataka, India

Atanu Talukdar