Abstract: Provided is a power supply device which includes a plurality of battery modules each having a secondary battery and in which the battery modules are connected in series with one another according to a gate driving signal from a controller. An SOC control target value that is a target value for states-of-charge of the battery modules is changed according to the number of the battery modules that are available to be connected in series.

Abstract: The disclosure relates to systems, methods and apparatus for analyzing an infrastructure system including measurement of a parameter associated with the infrastructure system, electronically recording the measured parameter as a data, transferring the data to an infrastructure unit which may be remote from the infrastructure system, analyzing the data to generate a risk model, and predicting a characteristic of the infrastructure system according to the risk. An implementation plan may be generated, and/or maintenance services may be performed as per the characteristic that is predicted.

Abstract: A PaaS platform-based ultra-low power consumption soil near-ground wireless sensing system includes a plurality of sensors mounted in soil, a signal transceiver module is arranged in the sensor, the signal transceiver module transmits a signal to a LoRaWan gateway through LoRa wireless communication, and the LoRaWan gateway is successively connected to a PaaS platform and a user group; and the sensors include a soil moisture sensor, a soil salinity sensor and a rainfall sensor. The PaaS platform-based ultra-low power consumption soil near-ground wireless sensing system of the invention enables sensor nodes to have ultra-low power consumption; and through fusion with a LoRa communication technology, a node network with ultra-low power consumption and long-distance transmission is constructed.

Abstract: The battery residual value display device includes: a battery information receiving module; an attenuation function determining module; a second residual value determining module; a graph output module configured to output a graph of which one axis indicates residual values of a battery and another axis indicates information on an elapsed time from a time of manufacture of the battery; and a display unit. The graph output module is configured to output: in the graph, a display indicating a first residual value; a display indicating boundaries between a plurality of residual value ranks obtained by dividing the residual values in accordance with a level of a second residual value; and a display indicating boundaries between a plurality of groups, indicating types of applications in which the battery can be used, obtained by dividing the plurality of residual value ranks in accordance with the level of the second residual value.

Abstract: Disclosed are a system for and a method of determining the cause of a defect of a battery, which is specifically attributable to a human error, through electrochemical impedance spectroscopy (EIS). The system includes an impedance measurement unit for measuring an impedance value of a battery while sequentially applying AC current signals of respective frequencies to the battery, a controller for determining the cause of the defect of the battery on the basis of the measured impedance value, and a table in which each of impedance value ranges is associated with a cause of a defect. The controller determines a cause of a defect of the battery by comparing the measured impedance value and each of the impedance value ranges.

Abstract: This disclosure provides a state estimation method and a battery pack. The method includes: obtaining aging factor data, predetermined discharge data and predetermined capacity loss changing data; recording measured discharge data of a to-be-measured battery; calculating to obtain discharge voltage difference data according to the predetermined discharge data and the measured discharge data; determining a specific interval Sa according to the discharge voltage difference data, and obtaining a voltage difference statistical value ?V2,Stats in the specific interval Sa; calculating an estimation capacity loss ?QD of the to-be-measured battery according to the aging factor data and the voltage difference statistical value ?V2,Stats; and determining whether the to-be-measured battery is abnormal or not according to the predetermined capacity loss changing data and the estimation capacity loss ?QD.

Abstract: A method for monitoring power consumption of an appliance within a space is provided. The method includes obtaining a first set of data indicative of power consumption of the appliance during an interval of time and determining a profile indicative of power consumption of the appliance based, at least in part, on the first set of data. The method includes obtaining a second set of data indicative of power consumption of the appliance subsequent to obtaining the first set of data. The method includes determining whether power consumption of the appliance deviates from the profile based, at least in part, on the second set of data. Furthermore, in response to determining power consumption of the appliance deviates from the profile, the method includes providing a notification indicative of power consumption of the appliance deviating from the profile.

Abstract: A method (400) of determining blade tip deflection characteristics is applied to moving rotor blades (R1, R2) in a turbomachine (10) comprising a housing and rotor including a shaft with the rotor blades attached thereto and at least one proximity probe (202). The method (400) includes measuring ((402) a proximity signal caused by a presence of a proximate tip of a moving rotor blade (R1) and calculating (404) by a control module (212) a shaft Instantaneous Angular Position (IAP) as a function of time, and performing (410) an order tracking process which includes expressing (412) the measured proximity signal in the angular domain and resampling (414) the expressed proximity signal to render it equidistant in the angular domain.

Abstract: Provided are a method and a system for optimizing a BMS model. The method includes: creating a BMS model based on test data of a battery; selecting sample vehicles from real driving data of vehicles equipped with this type of battery through active learning approach, and giving a corresponding weight to each of the selected sample vehicles; optimizing the BMS model based on the data of the selected sample vehicles.

Abstract: An analyzing apparatus includes a memory unit that stores analysis conditions of each standards specifying analysis conditions for each analytical technique, a control unit, and an analysis unit that performs an analysis in accordance with a predetermined analytical technique. The control unit reads out the analysis conditions of the standard, and the control unit displays analysis conditions in time sequence, the displayed analysis conditions being necessary for the analysis and selected from out of the read-out analysis conditions, or the control unit prompts to input the analysis conditions in time sequence. When the analysis conditions are input, the control unit determines whether or not the input analysis conditions comply with the read-out analysis conditions, and in a case where a result of the determination is positive, the control unit displays a next analysis condition being necessary for the analysis, or the control unit prompts to input the next analysis condition.

Abstract: A storage unit stores ranking information including an index value relating to past rainfall and a corresponding date-time and damage information including details of damage that occurred due to past rainfall and a corresponding date-time. A real-time data reception unit acquires a spot value and a forecast value of current precipitation. Also, a comparison operation unit computes an index value relating to current rainfall using the acquired spot value and forecast value. The comparison operation unit specifies, with reference to the ranking information, the date-time of an index value relating to past rainfall whose similarity to the computed index value relating to current rainfall is not less than a threshold value. An information output unit presents, with reference to the damage information, details of damage that occurred in a period whose difference from the specified date-time of the index value relating to past rainfall is in a predetermined range.

Abstract: An apparatus and method for testing a secondary battery. The apparatus includes a test path, test terminals provided at two ends of the test path and electrically connected to a positive terminal and a negative terminal of the secondary battery respectively, a sensor unit provided on the test path and configured to measure a discharge current of the secondary battery, a constant voltage generation unit provided on the test path and configured to maintain a constant voltage between the secondary battery and the sensor unit, and a control unit configured to receive data indicating the discharge current from the sensor unit, measure an inflection point on a profile of the discharge current, measure an intensity of the discharge current on the basis of the inflection point, and test a level of self-discharge of the secondary battery based on the intensity of the discharge current.

Abstract: A device for interfacing between a battery management system and groups of battery cells including at least one set of local units and at least one global unit that is connected to the local units of the at least one set. Each local unit is configured to compare a parameter related to a group of cells and associated with a first setpoint value, the first setpoint value originating from the at least one global unit, and to generate an output signal representative of the result of the comparison, and the at least one global unit is configured to receive the first setpoint value and includes an electronic module having an operating parameter having a global value that is dependent on the output signals generated by the local units of the at least one set.

Abstract: A field map generating system includes: a crop data obtaining unit that obtains crop data over time; a position information obtaining unit that obtains position information, indicating a harvesting position of the crop, over time; polygon constructing units that construct a polygon on the basis of a work width and speed of a harvester, for each piece of crop data obtained by the crop data obtaining unit; data assigning units that assign crop data or crop information based on the crop data to the constructed polygons; a position information assigning unit that assigns position information to the constructed polygons; and field map generating units that generate a field polygon map, which is an aggregate of the polygons, by aggregating the polygons.

Abstract: A method and a system for fatigue life prediction of additive manufactured components accounting for localized material properties. The method and the system is employed for prediction of fatigue life properties of an additive manufactured element, with a data collection step in which several data points for maximum stress vs. cycles to failure for different given processing steps of the element are collected, with a training step in which a Machine Learning system is trained with the collected data, and with an evaluation step in which the trained Machine Learning system is confronted with actual processing steps and used to predict the fatigue life properties of the element.

Abstract: Disclosed are systems and methods for processing broadband acoustic signals acquired by a plurality of acoustic sensors, using an array-signal-processing technique to compute fused-signal maps in the frequency domain for a plurality of frequency bins. In accordance with various embodiments, the fused-signal maps are combined across the frequency bins, with respective weightings that are based on eigenvalues of covariance matrices computed for the plurality of frequency bins. The combined maps can be used to locate an acoustic source in a wellbore.

Abstract: A method and a system for identifying third-order model parameters of a lithium battery based on a likelihood function are provided, which relates to a method for estimating battery model parameters of a lithium battery under different temperatures, different system-on-chips (SOCs), and charge-discharge currents. The method includes the following steps. A third-order battery model of the lithium battery is established. A battery model output voltage Ud and a total battery current I under different temperatures, different SOCs, and charge-discharge currents are collected. The likelihood function is adopted to construct an identification model, and the collected data is substituted into the identification model to calculate the battery model parameters. Identified parameters are substituted into the third-order battery model to obtain a battery terminal voltage to be compared with a measured terminal voltage.

Abstract: A sensing system and a sensing signal measuring method thereof are provided. The sensing system includes a signal source, a connecting device, a frequency sweep circuit, and a controller. In the method, the signal source is activated to generate a specific signal. The controller controls the frequency sweep circuit to switch a frequency band of a frequency sweep signal to a first frequency band corresponding to each of a plurality of types of multi-point sensors. The controller receives a sensor signal of each multi-point sensor through the connecting device, where the sensor signal is a variation of a measurement signal output by each multi-point sensor in response to the specific signal and the frequency sweep signal. The controller executes an adaptive algorithm on the sensor signal to construct a correspondence between an eigenvalue of each multi-point sensor and a location of the first frequency band, and records the correspondence.

Abstract: Systems, methods, and storage media for generating a predicted discharge profile of a vehicle battery pack are disclosed. A method includes receiving, by a processing device, data pertaining to cells within a battery pack installed in each vehicle of a fleet of vehicles operating under a plurality of conditions, the data received from at least one of each vehicle in the fleet of vehicles, providing, by the processing device, the data to a machine learning server, directing, by the processing device, the machine learning server to generate a predictive model, the predictive model based on machine learning of the data, generating, by the processing device, the predicted discharge profile of the vehicle battery pack from the predictive model, and providing the discharge profile to an external device.

Abstract: A spectrum y includes a waveform-of-interest component and a baseline component serving as a wide-band component. An optimum solution of a signal model x is determined according to a first condition to fit a corresponding portion SIFx of a baseline model Fx with respect to a representative portion yI of the baseline component, and a second condition to minimize an Lp norm (wherein p?1) of the signal model x. An estimated baseline component determined from the optimum solution of the signal model x is subtracted from the spectrum y.