Abstract: An apparatus for controlling viscosity of a slurry includes a mixing module mixing raw materials for a secondary battery, and a processor performing machine learning for prediction of viscosity of the slurry, predicting viscosity of the slurry in real time during a mixing process through machine learning, and adjusting conditions of the mixing process performed by the mixing module such that a predictive viscosity of the slurry meets a target viscosity.

Abstract: A battery system includes: a battery; a detection device to detect a voltage, a current, and a temperature from the battery; and a battery management system (BMS) to: estimate a state of charge (SOC) based on the voltage, the current, and the temperature detected from the detection device; store a profile generated by measuring a physical state of the battery in an event count format based on battery state data including the voltage, the current, and the temperature and the SOC; generate a virtual scenario for driving a representative battery based on the profile; and estimate a life of the battery through the virtual scenario.

Abstract: A method for detecting an abnormal battery cell includes periodically generating a voltage value and a current value for each of battery cells, updating, in real time by using an adaptive filter, a G parameter value and an H parameter value of each of battery cells, based on the voltage value and the current value, calculating a representative G parameter value and a representative H parameter value, and determining whether each of the battery cells is an abnormally deteriorated cell based on the G parameter value and the H parameter value of each of the battery cells, the representative G parameter value, and the representative H parameter value. The G parameter indicates sensitivity of voltage with respect to a change in current of the battery cell, and the H parameter indicates an effective potential determined by a local equilibrium potential distribution and a resistance distribution in the battery cell.

Abstract: Provided is a method of estimating the state of health of the battery according to various embodiments. The method of estimating the state of health of the battery comprises: measuring a voltage and current of a battery in use to periodically generate a voltage value and a current value; using an adaptive filter to periodically update a G parameter value and an H parameter value in real time from the voltage value and the current value, said parameters indicating the present state of the battery; and using an initial value and a final value of the G parameter that is preset and a present value of the G parameter to estimate the state of health of the battery in real time. The G parameter is a parameter that represents the sensitivity of the voltage to changes in the current of the battery, and the H parameter is a parameter that represents an effective potential determined by the local equilibrium potential distribution and resistance distribution inside the battery.

Abstract: An internal short-circuit cell detection method includes detecting a voltage and current of each of a plurality of battery cells, updating in real time G and H parameter values by using an adaptive filter, calculating a G parameter representative value, and calculating an H parameter representative value, and determining whether a short circuit occurs in each of the plurality of battery cells, based on the G and H parameter value of each of the plurality of battery cells, the G parameter representative value, and the H parameter representative value. The G parameter is a parameter indicating a sensitivity of a voltage to a change in current of each of the plurality of battery cells, and the H parameter is a parameter indicating an effective potential determined by a local equilibrium potential distribution and a resistance distribution in each of the plurality of battery cells.

Abstract: A method of estimating a state of charge of a battery, includes: generating a present voltage value Vt(k) and a present current value IL(k) by detecting a voltage and a current of the battery; determining a reference open-circuit voltage value VOC,ref(k) based on a state-of-charge estimation value SOC(k); estimating first to third parameter values ?1(k), ?2(k), and ?3(k) from the present voltage value Vt(k), the reference open-circuit voltage value VOC,ref(k), the present current value IL(k), and a previous current value IL(k?1) by using recursive least squares (RLS); and determining, using an extended Kalman filter (EKF), a next state-of-charge estimation value SOC(k+1) of the battery from the state-of-charge estimation value SOC(k), the present voltage value Vt(k), the reference open-circuit voltage value VOC,ref(k), the present current value IL(k), the previous current value IL(k?1), and the first to third parameter values ?1(k), ?2(k), and ?3(k).

Abstract: A method of estimating a state-of-charge (SOC) of a battery includes: setting an initial SOC value and an initial Kalman error covariance value; receiving an estimated G parameter value, a current current value, and a current voltage value of the battery; updating a current SOC value and a current Kalman error covariance value of the battery by inputting the estimated G parameter value, the current current value, and the current voltage value to an extended Kalman filter; and outputting the current SOC value. (Representative Drawing: FIG.

Abstract: Provided is a battery simulation method performed by a computing device including a processor and a memory.

Abstract: A method of simulating a battery pack, the method being performed by a computing device including a processor and a memory, is provided. The method includes: selecting a connection relationship of battery cells included in the battery pack and an equivalent circuit model (ECM) of the battery cells; determining parameter initial values of each of the battery cells, and an initial value of a G parameter and an initial value of an H parameter of the battery pack; receiving one of a pack current value and a pack voltage value of the battery pack; based on the one of the pack current value and the pack voltage value and the initial value of the G parameter and the initial value of the H parameter of the battery pack, determining the other of the pack current value and the pack voltage value of the battery pack.

Abstract: An internal short-circuit cell detection method according to various embodiments includes detecting a voltage and current of each of a plurality of battery cells that are electrically connected to one another between first and second terminals and are being used, to periodically generate a voltage value and a current value of each of the plurality of battery cells, updating in real time a G parameter value and an H parameter value obtained by digitizing a G parameter and an H parameter indicating a present state of each of the plurality of battery cells from the voltage value and the current value of each of the plurality of battery cells, by using an adaptive filter, calculating a G parameter representative value representing the G parameter values of the plurality of battery cells, and calculating an H parameter representative value representing the H parameter values of the plurality of battery cells, and determining whether a short circuit occurs in each of the plurality of battery cells, based on the G p

Abstract: A method for detecting an abnormal battery cell includes periodically generating a voltage value and a current value for each of battery cells, updating, in real time by using an adaptive filter, a G parameter value and an H parameter value of each of battery cells, based on the voltage value and the current value, calculating a representative G parameter value and a representative H parameter value, and determining whether each of the battery cells is an abnormally deteriorated cell based on the G parameter value and the H parameter value of each of the battery cells, the representative G parameter value, and the representative H parameter value. The G parameter indicates sensitivity of voltage with respect to a change in current of the battery cell, and the H parameter indicates an effective potential determined by a local equilibrium potential distribution and a resistance distribution in the battery cell.

Abstract: A battery state estimation method includes: periodically measuring voltage and current of a battery in use to generate a voltage value and a current value; using an adaptive filter to generate a G parameter value for a G parameter and an H parameter value for an H parameter in real time from the voltage value and the current value, the G and H parameters indicating a present state of the battery; and using the G parameter value and the H parameter value to estimate the present state of the battery in real time. The G parameter is a parameter that represents sensitivity of the voltage to changes in the current of the battery, and the H parameter is a parameter that represents an effective potential determined by local equilibrium potential distribution and resistance distribution inside the battery.

Abstract: Provided is a method of estimating the state of health of the battery according to various embodiments. The method of estimating the state of health of the battery comprises: measuring a voltage and current of a battery in use to periodically generate a voltage value and a current value; using an adaptive filter to periodically update a G parameter value and an H parameter value in real time from the voltage value and the current value, said parameters indicating the present state of the battery; and using an initial value and a final value of the G parameter that is preset and a present value of the G parameter to estimate the state of health of the battery in real time. The G parameter is a parameter that represents the sensitivity of the voltage to changes in the current of the battery, and the H parameter is a parameter that represents an effective potential determined by the local equilibrium potential distribution and resistance distribution inside the battery.

Abstract: Provided is a battery state estimation method. The battery state estimation method comprises: a step for periodically measuring the voltage and current of a battery in use to generate a voltage value and a current value; a step for using an adaptive filter to generate a G parameter value and an H parameter value in real time from the voltage value and the current value, said parameters indicating the present state of the battery; and a step for using the G parameter value and the H parameter value to estimate the state of the battery in real time. The G parameter is a parameter that represents the sensitivity of the voltage to changes in the current of the battery, and the H parameter is a parameter that represents an effective potential determined by the local equilibrium potential distribution and resistance distribution inside the battery.

Abstract: A method of charging a battery, wherein the battery comprises a plurality of battery cells, includes charging the battery with a first voltage for a first time period, which charging is first charging, charging the battery with a second voltage for a second time period, which charging is second charging, and charging the battery with a third voltage for a third time period, which charging is third charging, wherein lengths of the first to third time periods are determined in correspondence with a magnitude of charging current of the battery.

Abstract: A secondary battery and a method of manufacturing the same are disclosed. In one aspect, the method includes preparing an electrode assembly comprising a positive electrode plate, a negative electrode plate, and a separator interposed therebetween. The method also includes freezing the electrode assembly after the electrode assembly is filled with an electrolyte solution, dipping the frozen electrode assembly in a liquid polymer material, retrieving the dipped electrode assembly from the liquid polymer material, and curing an external surface of the electrode assembly.

Abstract: A method of charging a battery, wherein the battery comprises a plurality of battery cells, includes charging the battery with a first voltage for a first time period, which charging is first charging, charging the battery with a second voltage for a second time period, which charging is second charging, and charging the battery with a third voltage for a third time period, which charging is third charging, wherein lengths of the first to third time periods are determined in correspondence with a magnitude of charging current of the battery.

Abstract: A negative electrode for a rechargeable lithium battery that includes a negative active material layer including a carbon-based material having a peak of about 20 degrees to 30 degrees at a (002) plane in an X-ray diffraction pattern using a CuK? ray, and an SEI (solid electrolyte interface) passivation film including at least one material selected from an organic material and an inorganic material and having an average thickness of about 10 nm to about 50 nm on the surface of the active material layer of the electrode.

Abstract: An electrode for a rechargeable lithium battery includes an electrode active material and a copolymer represented by where A is selected from —O—(CFRf3—CFRf4)—, —(CFRf4—CFRf5)— and combinations thereof, each of Rf1 through Rf5 is independently selected from fluorine, C1-C4 alkyls and C1-C4 fluorinated alkyls, and each of x and y is an integer ranging from 1 to 100,000.

Abstract: Embodiments of the present invention provide an accelerated lifetime estimation device for predicting the lifetime of a secondary battery, and a method thereof. The accelerated lifetime estimation device can accurately estimate a normal lifetime of the secondary battery while reducing an evaluation time period of the secondary battery.