Methods for on-line, high-accuracy estimation of battery state of power
US-9989595-B1 · Jun 5, 2018 · US
US2018136285A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2018136285-A1 |
| Application number | US-201715491519-A |
| Country | US |
| Kind code | A1 |
| Filing date | Apr 19, 2017 |
| Priority date | Nov 16, 2016 |
| Publication date | May 17, 2018 |
| Grant date | — |
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A method of estimating a state of a battery, the method includes actuating a controller to transformatively capture sensor data from a battery unit corresponding to an event associated with the battery unit; determine a state estimation model corresponding to the event among a plurality of state estimation models; input the transformed sensor data to the determined state estimation model; and estimate a state of the battery unit based on output information of the determined state estimation model.
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What is claimed is: 1 . A method of estimating a state of a battery, the method comprising: actuating a controller to transformatively capture sensor data from a battery unit corresponding to an event associated with the battery unit; determining a state estimation model corresponding to the event among a plurality of state estimation models; inputting the transformed sensor data to the determined state estimation model; and estimating a state of the battery unit based on output information of the determined state estimation model. 2 . The method of claim 1 , wherein the transformatively capturing comprises: extracting data from the sensor data based on a first time interval in response to the event being a discharging event associated with the battery unit; converting the extracted data to frequency domain data; filtering the frequency domain data; and converting the filtered frequency domain data to time domain data. 3 . The method of claim 2 , wherein the transformatively capturing further comprises: deleting data included in a length over a predetermined reference in response to a length of the time domain data exceeding the predetermined reference. 4 . The method of claim 2 , further comprising: acquiring a parameter of a state estimation model corresponding to the discharging event; and applying the parameter to the state estimation model corresponding to the discharging event. 5 . The method of claim 1 , wherein the transformatively capturing comprises: extracting data from the sensor data based on a second time interval in response to the event being a charging event associated with the battery unit. 6 . The method of claim 5 , further comprising: acquiring a parameter of a state estimation model corresponding to the charging event; and applying the parameter to the state estimation model corresponding to the charging event. 7 . The method of claim 1 , wherein the plurality of state estimation models comprise a first state estimation model exclusively configured to estimate the state of the battery unit during charging of the battery unit and a second state estimation model exclusively configured to estimate the state of the battery unit during discharging of the battery unit. 8 . A method of training a battery state estimation model, the method comprising: classifying sensor data of a battery unit of an event associated with the battery unit; actuating a controller to transformatively process the sensor data based on the classified sensor data; inputting the processed sensor data to a state estimation model corresponding to the event; and training the state estimation model corresponding to the event in response to the input. 9 . The method of claim 8 , wherein the transformative processing comprises: extracting data from the classified sensor data based on a first time interval in response to the event being a discharging event associated with the battery unit; converting the extracted data to frequency domain data; filtering the frequency domain data; and converting the filtered frequency domain data to time domain data. 10 . The method of claim 9 , wherein the performing of the transformative processing further comprises: deleting data included in a length over a predetermined reference in response to a length of the time domain data exceeding the predetermined reference. 11 . The method of claim 9 , wherein the inputting comprises inputting the time domain data to a state estimation model corresponding to the discharging event. 12 . The method of claim 8 , wherein the transformative processing comprises: extracting data from the sensor data based on a second time interval in response to the event being a charging event associated with the battery unit. 13 . The method of claim 12 , wherein the inputting comprises: inputting the extracted data to a state estimation model corresponding to the charging event. 14 . An apparatus for estimating a state of a battery, the apparatus comprising: a communicator configured to receive sensor data of a battery unit; and a controller operably coupled to the communicator, the controller configured: to perform transformative processing corresponding to an event associated with the battery unit on sensor data of the battery unit, to determine a state estimation model corresponding to the event among a plurality of state estimation models, to input the processed sensor data to the determined state estimation model, and to estimate a state of the battery unit based on output information of the determined state estimation model. 15 . The apparatus of claim 14 , wherein the controller is further configured: to extract data from the sensor data based on a first time interval in response to the event being a discharging event associated with the battery unit, to convert the extracted data to frequency domain data, to filter the frequency domain data, and to convert the filtered frequency domain data to time domain data. 16 . The apparatus of claim 15 , wherein the controller is further configured to delete data included in a length over a predetermined reference in response to a length of the time domain data exceeding the predetermined reference. 17 . The apparatus of claim 15 , wherein the controller is further configured to acquire a parameter of a state estimation model corresponding to the discharging event, and to apply the parameter to the state estimation model corresponding to the discharging event. 18 . The apparatus of claim 14 , wherein the controller is further configured to extract data from the sensor data based on a second time interval in response to the event being a charging event associated with the battery unit. 19 . The apparatus of claim 18 , wherein the controller is further configured to acquire a parameter of a state estimation model corresponding to the charging event, and to apply the parameter to the state estimation model corresponding to the charging event. 20 . The apparatus of claim 14 , wherein the plurality of state estimation models comprise a first state estimation model exclusively configured to estimate the state of the battery unit during charging of the battery unit and a second state estimation model exclusively configured to estimate the state of the battery unit during discharging of the battery unit.
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