Abstract: A charging method for a battery pack includes sending, by a battery management module of the battery pack, a charging request for a first current to a charging pile for charging, controlling, by the battery management module in response to determining that first-current charging of the battery pack meets a first predetermined condition, the battery pack to perform pulse discharge, and controlling, by the battery management module in response to determining that the pulse discharge of the battery pack meets a second predetermined condition, the battery pack to stop discharging, and sending a charging request for a second current to the charging pile for charging. The second current is less than the first current.

Abstract: Machine learning segmentation methods and systems that perform segmentation quickly, efficiently, cheaply, and optionally provides an interactive feature that allows a user to alter the segmentation until a desired result is obtained. The automated machine learning segmentation tool receives all potentially important attributes and provides segmentation of items. It also receives information about important features of the data and finds how best to differentiate between groups using cluster-based machine learning algorithms. In addition, visualization of the segmentation explains to a user how the segmentation was obtained.

Abstract: This application discloses a negative electrode plate, a preparation method thereof, a secondary battery, a battery module, a battery pack, and an electric apparatus. The negative electrode plate may include a negative electrode current collector and a negative electrode film layer, where the negative electrode film layer may be provided on at least one surface of the negative electrode current collector and may include a negative electrode active material; where at least part of surface of the negative electrode active material may be provided with an artificial solid electrolyte interface film, where the artificial solid electrolyte interface film may include a first inorganic lithium salt, and the first inorganic lithium salt may be selected from one or two of Li2CO3 and Li2SO3.

Abstract: Embodiments of the present application provide a detection method and detection device for a battery, a battery management system, and a storage medium. The method may include: acquiring a current voltage of a battery; sending a charging request to a charging device, the charging request including a requested voltage, the charging request being used to request the charging device to output the requested voltage to the battery, where the requested voltage may be smaller than the current voltage; acquiring a current of the battery within a duration in which the charging device outputs the requested voltage to the battery; and determining an internal short circuit condition of the battery according to the current.

Abstract: A sticking machine able to automatically remove films on either side of a sheet to be pasted to a workpiece includes a sheet supply component, a sheet selection component, a drive component, a first film-removing component, a second film-removing component, a carrier, and a transmission line. The sheet supply component stores sheets. The sheet selection component applies suction to the sheet. The first film-removing component tears off a first film, the second film-removing component tears off a second film on the reverse side. The transmission line carries the workpiece to the carrier. The sticking machine is fed by the sheet supply component, and after removal of the first film, the sheet selection component lays the sheet on the surface of the workpiece, then the second film-removing component tears off the second film, realizing automatic sticking of the sheet on the workpiece, improving the processing efficiency and accuracy.

Abstract: A method and system for a machine learning duster analysis of historical lead time data, which is augmented by one or more features. The data can also be divided into groups, based on time-density of the data, with clustering performed on each group. Furthermore, clustering can also be projected onto two dimensions. in addition, the historical lead time data is separated into a plurality of tolerance zones based on tolerance criteria. The clusters are separated in accordance with a tolerance zone of each group; and further separated according to one or more lead time identifiers to provide one or more separated clusters.

Abstract: Systems and methods for features engineering, in which internal and external signals are received and fused. The fusing is based on meta-data of each of the one or more internal signals and each of the one or more external signals. A set of features is generated based on one or more valid combinations that match a transformation input, the transformation forming part of library of transformations. Finally, a set of one or more features is selected from the plurality of features, based on a predictive strength of each feature. The set of selected features can be used to train and select a machine learning model.

Abstract: A method for charging a traction battery includes obtaining an actual charging current of a traction battery during a charging process of the traction battery, and determining, based on a degree of the actual charging current exceeding a requested charging current, whether to control the traction battery to be discharged.

Abstract: A method for charging a traction battery includes obtaining a battery parameter of the traction battery that includes a state of charge and/or an open-circuit voltage, and, during a charging process of the traction battery, controlling the traction battery to discharge or stop being charged in response to the battery parameter changing by a parameter gap value. The parameter gap value is a first preset parameter gap value in a scenario in which the battery parameter of the traction battery is in a first parameter interval, and is a second preset parameter gap value in a scenario in which the battery parameter of the traction battery is in a second parameter interval. The first preset parameter gap value is greater than the second preset parameter gap value, and the battery parameter in the first parameter interval is less than the battery parameter in the second parameter interval.

Abstract: An electrolyte includes an organic solvent and one or more of a compound represented by general formula (I) or general formula (II): A content of the compound in the electrolyte is 0.01 wt %-5 wt % and a content of ethylene carbonate in the organic solvent is less than or equal to 3 wt %.

Abstract: A method for charging a traction battery applied to a battery management system (BMS) for the traction battery, includes obtaining a temperature and a battery parameter of the traction battery, determining a parameter threshold based on the temperature of the traction battery, and during a charging process of the traction battery, controlling the traction battery to discharge or stop being charged in response to the battery parameter of the traction battery being greater than or equal to the parameter threshold and the battery parameter of the traction battery changing by a parameter gap value. The battery parameter includes at least one of a state of charge (SOC) or an open-circuit voltage (OCV).

Abstract: A method and system for a machine learning duster analysis of historical lead time data, which is augmented by one or more features. The data can also be divided into groups, based on time-density of the data, with clustering performed on each group. Furthermore, clustering can also be projected onto two dimensions. In addition, the historical lead time data is separated into a plurality of tolerance zones based on tolerance criteria. The clusters are separated in accordance with a tolerance zone of each group; and further separated according to one or more lead time identifiers to provide one or more separated clusters.

Abstract: Systems and methods for obtaining product information via a conversational user interface. The communication channel receives communication from a user, the intent and entities of which are deduced by the NLP. These are communicated by the fulfillment API to the knowledge engine which retrieves information that fulfills the intent. The information is communicated to the fulfillment API, which converts the intent into a response, which in turn is forwarded by the NLP to the communication channel, and back to the user.

Abstract: Systems and methods for obtaining product information via a conversational user interface. The communication channel receives communication from a user, the intent and entities of which are deduced by the NLP. These are communicated by the fulfillment API to the knowledge engine which retrieves information that fulfills the intent. The information is communicated to the fulfillment API, which converts the intent into a response, which in turn is forwarded by the NLP to the communication channel, and back to the user.

Abstract: A method for preparing amantadine includes chlorinating adamantane with chlorine gas in a solvent in the presence of a Lewis acid catalyst to obtain a reaction liquid, and then removing the solvent and residues containing the catalyst in the reaction liquid, to obtain a chlorinated product. The chlorinated product is mixed with urea to a mixture, and the mixture is subjected to an amination reaction, to obtain amantadine. The results of examples show that the purity of the prepared amantadine could reach 99.5% or more.

Abstract: A method and system for a machine learning cluster analysis of historical lead time data, which is augmented by one or more features. The data can also be divided into groups, based on time-density of the data, with clustering performed on each group. Furthermore, clustering can also be projected onto two dimensions. In addition, the historical lead time data is separated into a plurality of tolerance zones based on tolerance criteria. The clusters are separated in accordance with a tolerance zone of each group; and further separated according to one or more lead time identifiers to provide one or more separated clusters.

Abstract: The present disclosure provides a system and a method for manipulating a robotic device. The system includes a human interface device for obtaining information associated with a position and/or movement of a user's finger using the human interface device; and a robotic device for simulating the position and/or movement of the user's finger in real time. The robotic device is in communication with the human interface device. The operating system of the robotic device of the present disclosure can accurately simulate the functions of human hand.

Abstract: Systems and methods for dynamic demand sensing in a supply chain in which constantly-updated data is used to select a machine learning model or retrain a pre-selected machine learning model, for forecasting sales of a product at a specific location. The updated data includes product information and geographic information.

Abstract: Systems and methods for features engineering, in which internal and external signals are received and fused. The fusing is based on meta-data of each of the one or more internal signals and each of the one or more external signals. A set of features is generated based on one or more valid combinations that match a transformation input, the transformation forming part of library of transformations. Finally, a set of one or more features is selected from the plurality of features, based on a predictive strength of each feature. The set of selected features can be used to train and select a machine learning model.

Abstract: Systems and methods for features engineering, in which internal and external signals are received and fused. The fusing is based on meta-data of each of the one or more internal signals and each of the one or more external signals. A set of features is generated based on one or more valid combinations that match a transformation input, the transformation forming part of library of transformations. Finally, a set of one or more features is selected from the plurality of features, based on a predictive strength of each feature. The set of selected features can be used to train and select a machine learning model.