Abstract: An apparatus for estimating a condition of a battery includes a mode identifying unit configured to identify a usage mode of the battery during a period of time and its corresponding attenuation curve, according to recorded data on battery usage, stored usage modes of the battery and attenuation curves corresponding to the various usage modes, the attenuation curve representing a change of a fully charged capacity of the battery with battery usage; and a condition estimating unit configured to calculate battery degradation according to the recorded data, the identified usage mode and its corresponding attenuation curve, the degradation representing a quantity of the fully charged capacity of the battery that is reduced over the battery usage. The condition of the battery is estimated so as to rationally judge the residual value of the battery in operation.

Abstract: To generate a charging path for a battery, a method includes generating simulation data for charging currents based on a battery model indicating an internal state of a battery, generating an initial look-up table (LUT) for the charging currents and preset battery voltage limits based on the simulation data, the initial LUT representing initial charging limit conditions of the battery for stages corresponding to the charging currents, generating a modified LUT by adjusting at least one of the initial charging limit conditions of the initial LUT, in response to the initial LUT failing to satisfy a threshold, determining a final LUT based on the modified LUT, in response to the modified LUT satisfying the threshold, and generating a charging path for the battery based on the final LUT.

Abstract: The subject matter disclosed herein provides methods for conducting tests on a medical device. A request to conduct a test on a medical device module remotely located from a party initiating the request can be received. The module can have an inductive receiver and be part of a medical device system having an inductive backplane and multiple mounting seats. Each mounting seat can have an inductive transmitter, and the module can be inductively powered when affixed to a first mounting seat. The test can relate to an attribute of the first mounting seat's inductive transmitter or the module's inductive receiver. The request can identify the module and test to conducted. A message representative of the request can be transmitted to the system. Test data relating to an attribute of the inductive transmitter or inductive receiver can be received and provided. Related methods, apparatus, systems, techniques and articles are also described.

Abstract: A battery management apparatus for changing a control condition according to a degradation pattern in a charge situation of a battery cell. Since not only the degradation degree of the battery cell but also the degradation acceleration degree of the battery cell is estimated, the present degradation state of the battery cell may be more accurately estimated, and the future degradation state of the battery cell may also be predicted more accurately.

Abstract: A wash optimization system and related methods are provided that increase the efficiency and the effectiveness of engine washes. A system comprising at least one processor receives sensor data representing one or more measured parameters of a turbine engine and determines at least one performance parameter based on the sensor data. The at least one performance parameter represents one or more particulate values associated with the turbine engine. The system generates a health state for the turbine engine based on the at least one performance parameter and generates a wash identifier based on the health state of the turbine engine.

Abstract: The present disclosure relates to a state of charge (SOC) estimating apparatus and method, and more particularly, to a SOC estimating apparatus and method for estimating an initial SOC when a starting light ignition (SLI) battery starts a vehicle. According to an aspect of the present disclosure, there is an advantage of accurately estimating the initial SOC of a vehicle-starting battery that always uses a current regardless of a driving mode or a parking mode of the vehicle.

Abstract: A method and system are presented for monitoring measurement of parameters of patterned structures based on a predetermined fitting model. The method comprises: (a) providing data indicative of measurements in at least one patterned structure; and (b) applying at least one selected verification mode to said data indicative of measurements, said at least one verification mode comprising: I) analyzing the data based on at least one predetermined factor and classifying the corresponding measurement result as acceptable or unacceptable, II) analyzing the data corresponding to the unacceptable measurement results and determining whether one or more of the measurements providing said unacceptable result are to be disregarded, or whether one or more parameters of the predetermined fitting model are to be modified.

Abstract: A battery system includes a multi-cell rechargeable energy storage system (RESS) and an electronic controller configured to process RESS cell data. The controller is programmed with a battery cell open circuit voltage (OCV) versus state of charge (SOC) data table used to calculate a peak OCV movement for a representative battery cell at predetermined capacity and maximum discharge/charge rate. The controller is configured to acquire voltage data for one of the cells during active RESS cycling. The controller is also configured to pass the acquired voltage data through a first-order lag filter algorithm to generate an overpredicted OCV for the subject cell. The controller is additionally configured to determine an overpredicted SOC value for the subject cell in the data table using an OCV value from the overpredicted OCV. Furthermore, the controller is configured to regulate the RESS using the determined overpredicted SOC value for the subject cell.

Abstract: Systems and methods are provided for algorithm-optimized voltage and/or current windows for lithium-silicon batteries. A lithium-ion cell may be managed, with the managing including controlling voltage and/or current of the lithium-ion cell using an enhanced algorithm. The controlling includes adjusting voltage and/or current limits applied during one or both of charging and discharging of the lithium-ion cell, and the enhanced algorithm is configured to control a voltage range and/or a current range of the lithium-ion cell to maximize a combination of one or more variable associated with the lithium-ion cell including one or more of cycle life, energy density, cumulative capacity before end of life, and cumulative energy before end of life. The lithium-ion cell may be a silicon-dominant cell having a silicon-dominant anode with silicon >50% of active material of the anode, and the enhanced algorithm may be configured based on characteristic(s) unique to silicon-dominant cells.

Abstract: A short circuit detection method includes obtaining battery data associated with a state of a battery from a charging cycle of the battery, estimating an error in the battery data using an estimation model, determining a state indicator corresponding to the error in the battery data, and detecting a short circuit of the battery based on a result of comparing the state indicator and a short circuit threshold.

Abstract: The invention relates to a method and a device for measuring, in real time and in situ, thermodynamic data of a battery (enthalpy and entropy). The object of the invention is to provide a reliable method for measuring, in situ, online and in real time, the variation in entropy (?S) of a battery.

Abstract: A method for determining an open circuit voltage of an electrochemical device, including: a. collecting measurement data of the device, the measurements i. including at least the current It and the voltage Ut at the terminals of the device, ii. being time-stamped, and iii. being acquired during an uninterrupted and operational functional period of the device; b. calculating, for a plurality of times t, iv. a corrected intensity by applying a correction function to the measured intensity It, and v. an instantaneous charge based on a time series of the corrected intensity so as to obtain, for each time t, a set of collected and calculated data; c. grouping the data sets into ranges of instantaneous charge values based on the charge value of each set; and d. separately for each group, calculating an open circuit voltage of the device.

Abstract: A computer system generates a virtual three-dimensional (3D) model of a hydrocarbon reservoir using a machine learning algorithm. The machine learning algorithm is trained using information obtained from multiple hydrocarbon wells. The virtual 3D model includes a reservoir pressure model of the hydrocarbon reservoir indicating variations in reservoir pressure in accordance with time. A fluid saturation model of the hydrocarbon reservoir indicates variations in reservoir saturation in accordance with time. The computer system executes the machine learning algorithm to determine the variations in the reservoir pressure and the variations in the reservoir saturation with respect to the multiple hydrocarbon wells based on the virtual 3D model. A display device of the computer system generates a graphical representation of the variations in the reservoir pressure and the variations in the reservoir saturation in accordance with time.

Abstract: A battery capacity estimation system executes a charging and discharging process (S1), an alternating current impedance acquiring process (S2 and S3), and a battery capacity estimating process (S4 to S6). The charging and discharging process involves charging and discharging a target secondary battery. The alternating current impedance acquiring process involves acquiring a measurement result of an alternating current impedance of a target secondary battery, by applying an alternating current signal within a specific frequency range to the target secondary battery after completion of the charging and discharging in the charging and discharging process and before a predetermined maximum waiting time elapses. The battery capacity estimating step involves estimating a battery capacity of the target secondary battery based on the measurement result of the alternating current impedance.

Abstract: A method identifies a measure that is not provided for by a manufacturer on or using a removable battery pack having at least one energy storage cell and a monitoring unit. The method includes detecting and storing a voltage of the removable battery pack and/or a cell voltage of the at least one energy storage cell using the monitoring unit before the monitoring unit is set to a quiescent state or when the removable battery pack is set to a state other than a charging operating state. The method also includes comparing the detected voltage of the removable battery pack and/or the detected cell voltage with a previously-stored voltage of the removable battery pack or a previously-stored cell voltage using the monitoring unit when the monitoring unit is set to an operating state or when the removable battery pack is in the state other than the charging operating state.

Abstract: In a battery management controller, analog-to-digital conversion circuitry converts analog signals, indicative of a battery voltage, a battery current, and a battery temperature, to digital signals. A memory stores a remaining-capacity lookup table that includes multiple groups of data. Each group of data includes a voltage, a current, a temperature, and a parameter associated with a remaining capacity corresponding to the voltage, the current and the temperature. A processor searches the lookup table for a current parameter value and an end-of-discharge parameter value based on the digital signals, and determines a full available charge capacity of the battery based on the current parameter value and the end-of-discharge parameter value. The processor also counts the number of charges flowing through the battery based on a battery current. The processor further determines an available state of charge of the battery according to the full available charge capacity and the number of charges.

Abstract: Systems and methods for detecting and identifying arcing are disclosed. A method of detecting arcing includes obtaining data indicative of voltage and data indicative of current, determining a waveform of a cycle of a primary load current according to the data indicative of current, determining at least one noise signal according to the determined waveform of a cycle of the primary load current and the data indicative of current, determining a probability density of the noise signal according to a time window, and comparing the probability density of the noise signal with at least one model probability density.

Abstract: A battery control unit has an SOCv operation unit which calculates a state of charge SOCv based on voltage of a battery, a ?SOCi operation unit which calculates an amount of change ?SOCi of the state of charge based on current value of the battery, a weight operation unit which calculates a weight W, and an SOCc operation unit which calculates a final SOC (SOCc) based on the SOCv, the ?SOCi and the weight W. Terms forming an operational expression of the SOCc are retained, by using a determination threshold, as a sum SOCc_Big of terms of a large value group and a sum SOCc_Small of terms of a small value group, and used in calculating the SOCc of a subsequent operation period. By using the SOCc_Big and the SOCc_Small, it is possible to prevent the accumulation of errors caused by information loss that occurred when repeatedly operating the SOCc.

Abstract: A system and method are provided for operating a power generating asset. Accordingly, a plurality of operational data sets are received by a controller. The operational data sets include at least one indication of a performance anomaly. A plurality of predictive models are implemented by the controller to determine a plurality of potential root causes of the performance anomaly and a plurality of corresponding probabilities for each of the potential root causes. A consolidation model is generated for classifying the plurality of potential root causes and corresponding probabilities. The consolidation model is trained via a training data set to correlate the plurality of potential root causes to an actual root cause for the performance anomaly. The consolidation model is implemented by the controller to determine the actual root cause of the performance anomaly based on the plurality of potential root causes and corresponding probabilities.

Abstract: A vibratory flowmeter (5) for meter verification is provided, including meter electronics (20) coupled to the first and second pickoff sensors (170L, 170R) and coupled to a driver (180), with the meter electronics (20) configured to: vibrate the flowmeter assembly (10) in a single mode using the driver (180), determine a single mode current (230) of the driver (180) and determine first and second response voltages (231) generated by the first and second pickoff sensors (170L, 170R), respectively, compute frequency response functions for the determined first and second response voltages (231) from the determined single mode current (230), fit the generated frequency response functions to a pole-residue model, and verify proper operation of the vibratory flowmeter (5) using the meter stiffness value (216), residual flexibility (218), and the meter mass (240) in embodiments.