US 12,449,447 B2
Battery fire prevention and diagnosis system
Hyang Eun Jo, Tongyeong-si (KR); Hwang Dong Seo, Gimhae-si (KR); and Jae Ryong Jung, Gimhae-si (KR)
Assigned to HYOSUNG HEAVY INDUSTRIES CORPORATION, Seoul (KR)
Appl. No. 18/010,519
Filed by HYOSUNG HEAVY INDUSTRIES CORPORATION, Seoul (KR)
PCT Filed Jul. 11, 2022, PCT No. PCT/KR2022/010061
§ 371(c)(1), (2) Date Dec. 15, 2022,
PCT Pub. No. WO2023/003244, PCT Pub. Date Jan. 26, 2023.
Claims priority of application No. 10-2021-0094146 (KR), filed on Jul. 19, 2021.
Prior Publication US 2023/0341442 A1, Oct. 26, 2023
Int. Cl. G01R 19/00 (2006.01); G01R 29/08 (2006.01); G01R 31/367 (2019.01); G01R 31/392 (2019.01)
CPC G01R 19/0053 (2013.01) [G01R 29/0807 (2013.01); G01R 31/367 (2019.01); G01R 31/392 (2019.01)] 3 Claims
OG exemplary drawing
 
1. A battery fire prevention and diagnosis system for a battery system including one or more modules, each of the one or more modules having one or more battery cells, comprising:
a frequency sensor configured to measure a radiated electromagnetic wave signal and an internal discharge of the one or more cells;
a data acquiring unit configured to receive the radiated electromagnetic wave signal measured from the frequency sensor;
a noise/defect cause database including:
on-site noise data constructed by measuring noise at a site currently in operation, and
defect cause data obtained by simulating battery cell swelling caused by overheating or overcharging due to internal defects of the battery system, wherein the defect cause data includes an internal discharge signal of the one or more battery cells occurring before a protective system operates following the swelling of the one or more battery cell; and
a diagnosis unit configured to:
remove the noise from the radiated electromagnetic wave signal after comparing the radiated electromagnetic wave signal with the on-site noise data;
extract at least one of a pulse size, a wave, and a frequency or any combination thereof from the noise removed radiated electromagnetic wave signal; and
determine an abnormality of the battery system and a cause of one or more of the internal defects thereof based on the radiated electromagnetic wave signal acquired from the data acquiring unit and the noise/defect cause database including the on-site noise data and the defect cause data,
wherein the battery system is equipped in an energy storage system (ESS).