Described herein is a device for autonomously monitoring a battery is provided. The device is integrated with the battery (e.g., by being electrically coupled to the battery). The device obtains measurement data by injecting electrical signals into the battery and measuring an electrical response of the battery. The device participates in an authentication protocol with a computing device to verify a unique identity of the device to the computing device. After performing the authentication protocol verifying the unique identity of the device, the device transmits battery data to the computer. Further, techniques for verifying the identity of the battery using measurement data obtained by the device are described herein. The techniques generate a battery signature using the measurement data that is then used to verify the identity of the battery. For example, the battery signature may be used to determine whether the battery is counterfeit or defective.

A method, apparatus, system for batter material screening is disclosed. First, microstructure generation parameters for a plurality of microstructures are received, where the microstructure generation parameters include microstructure characteristics. Microstructure statistics are generated using a first artificial intelligence (“AI”) model, where the received microstructure generation parameters are inputs for the first AI model. Microstructure properties are predicted using a second AI model for the microstructures based on the generated microstructure statistics, the received microstructure generation parameters, and battery cell characteristics. It is determined whether at least one of the microstructures is within a predefined energy profile range based on the predicted microstructure properties.

A method, apparatus, system for batter material screening is disclosed. First, microstructure generation parameters for a plurality of microstructures are received, where the microstructure generation parameters include microstructure characteristics. Microstructure statistics are generated using a first artificial intelligence (“AI”) model, where the received microstructure generation parameters are inputs for the first AI model. Microstructure properties are predicted using a second AI model for the microstructures based on the generated microstructure statistics, the received microstructure generation parameters, and battery cell characteristics. It is determined whether at least one of the microstructures is within a predefined energy profile range based on the predicted microstructure properties.

An apparatus is provided for measuring the power of electrolytes at different positions of a flow battery by switching six-way valves without reconnecting channels. With the measurements at the positions, weighting is processed to obtain power corresponding to charging statuses for determining accurate power. The charging and discharging of voltage and current of the battery are controlled for constant operations with high efficiency. Consequently, the efficiency of power conversion is improved; energy consumption is reduced; and the battery is always run within a safe power-range for avoiding accidents or damages to the battery. In addition, the present invention is further applicable to a device monitoring the features of a battery unit. The six-way valves online monitor the power at center positions by switching. The values measured at different positions are aimed at the abnormality of the battery unit for processing adjustment or offline replacement to maintain best operation performance.

An apparatus is provided for measuring the power of electrolytes at different positions of a flow battery by switching six-way valves without reconnecting channels. With the measurements at the positions, weighting is processed to obtain power corresponding to charging statuses for determining accurate power. The charging and discharging of voltage and current of the battery are controlled for constant operations with high efficiency. Consequently, the efficiency of power conversion is improved; energy consumption is reduced; and the battery is always run within a safe power-range for avoiding accidents or damages to the battery. In addition, the present invention is further applicable to a device monitoring the features of a battery unit. The six-way valves online monitor the power at center positions by switching. The values measured at different positions are aimed at the abnormality of the battery unit for processing adjustment or offline replacement to maintain best operation performance.

A system includes a first storage unit configured to store a result of an endurance test actually carried out over a first period under a first use condition as training data, and a first arithmetic unit having a machine learning model configured to perform machine learning using the training data stored in the first storage unit. The machine learning model is configured to estimate a result when the endurance test is carried out under a second use condition. The first use condition is a use condition in which a predetermined operation parameter that influences degradation of the fuel cell system appears with equal frequency over an entire domain of the operation parameter. The second use condition is a use condition in which the operation parameter appears with unequal frequency in at least part of the domain of the operation parameter.

A system includes a first storage unit configured to store a result of an endurance test actually carried out over a first period under a first use condition as training data, and a first arithmetic unit having a machine learning model configured to perform machine learning using the training data stored in the first storage unit. The machine learning model is configured to estimate a result when the endurance test is carried out under a second use condition. The first use condition is a use condition in which a predetermined operation parameter that influences degradation of the fuel cell system appears with equal frequency over an entire domain of the operation parameter. The second use condition is a use condition in which the operation parameter appears with unequal frequency in at least part of the domain of the operation parameter.

A battery classification apparatus includes: a measuring unit configured to measure a voltage of a battery and measure a resistance corresponding to the voltage of the battery; a profile generating unit configured to obtain battery information about the voltage and the resistance of the battery measured by the measuring unit and generate a resistance profile representing a corresponding relationship between the voltage and the resistance based on the battery information; and a control unit configured to determine a criterion resistance based on a resistance value in the resistance profile, determine a reference resistance corresponding to a highest voltage in the resistance profile, and classify a type of the battery based on the criterion resistance and the reference resistance according to a content of nickel contained in the battery.

A battery classification apparatus includes: a measuring unit configured to measure a voltage of a battery and measure a resistance corresponding to the voltage of the battery; a profile generating unit configured to obtain battery information about the voltage and the resistance of the battery measured by the measuring unit and generate a resistance profile representing a corresponding relationship between the voltage and the resistance based on the battery information; and a control unit configured to determine a criterion resistance based on a resistance value in the resistance profile, determine a reference resistance corresponding to a highest voltage in the resistance profile, and classify a type of the battery based on the criterion resistance and the reference resistance according to a content of nickel contained in the battery.

An apparatus for inspecting disconnection of an electrode tab of a battery cell includes a measurement part which measures impedance values and impedance angles of an inspection target battery cell over frequency; a calculation part which calculates real part resistance values of impedance of the inspection target battery cell over frequency from the impedance values and the impedance angles; and a determination part which determines whether an electrode tab of the battery cell is disconnected by comparing real part resistance values in a real part resistance value range in a resonance frequency range of good battery cells having the same type as the inspection target battery cell with the real part resistance values of the impedance of the inspection target battery cell in the same frequency range as the resonance frequency range.