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公开(公告)号：US20240170770A1
公开(公告)日：2024-05-23
申请号：US18206988
申请日：2023-06-07
发明人： Hoimin Kwon , Youngsuk Cho , Suhyun Kim , Kyounghan Ryu , Yeongho Lee , Jinyoung Park , Yooil Lee , Minsoo Kim
IPC分类号： H01M12/08 , H01M8/04082 , H01M8/04119 , H01M8/04276 , H01M8/04492
CPC分类号： H01M12/08 , H01M8/04119 , H01M8/04201 , H01M8/04276 , H01M8/04492
摘要： A power supply apparatus includes: an air supply part provided to supply air; a dehumidification part configured to remove moisture in the air supplied from the air supply part; an oxygen concentration part including a first oxygen concentration member, a second oxygen concentration member, and a vacuum pump configured to separate and concentrate oxygen from the air; a battery part including a lithium-air battery and configured to be supplied with the concentrated oxygen from the oxygen concentration part; and a controller. The controller is configured to, in response to discharging the lithium-air battery, generate the concentrated oxygen to be supplied to the lithium-air battery by driving one of the first oxygen concentration member or the second oxygen concentration member and regenerate the other of the first oxygen concentration member or the second oxygen concentration member by driving the vacuum pump while the concentrated oxygen is generated.
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2.发明公开公开(公告)号：US20240204269A1
公开(公告)日：2024-06-20
申请号：US18332216
申请日：2023-06-09
发明人： Hoimin Kwon , Youngsuk Cho , Suhyun Kim , Kyounghan Ryu , Yeongho Lee , Jinyoung Park , Yooil Lee , Minsoo Kim
IPC分类号： H01M10/42 , G01R31/36 , G01R31/367 , G01R31/378
CPC分类号： H01M10/4285 , G01R31/3644 , G01R31/367 , G01R31/378 , H01M12/08
摘要： An apparatus for diagnosing a fault for a lithium-air battery based power supply device includes a data collection part configured to collect data by measuring operational state changes occurring in the power supply device components for each type of fault, a training part configured to train a neural network model using the collected data to classify the type of fault, and a fault diagnosis part configured to diagnose the type of fault by inputting residual changes of each component during operation of the power supply device as input values for the trained neural network model.
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