TY - GEN
T1 - Connection Failure Detection for Lithium-ion Batteries Based on DBSCAN-Projection Method
AU - TANG, Xiaopeng
AU - YAO, Ke
AU - LIU, Boyang
AU - GAO, Furong
N1 - We would like to thank Kaori Ikegaya for correcting the language problems. This work is supported partly by the National Natural Science Foundation of China (61433005), partly by Guangdong Scientific and Technological Project (2017B010120002), partly by Guangzhou Scientific and Technological Project (201807010089) and partly by Hong Kong Research Grant Council (16207717).
PY - 2019
Y1 - 2019
N2 - This paper presents a connection failure detection for a Lithium-ion battery pack when no external vibrations exist. First, the gradient correction method is employed to identify the overall ohmic resistance, which is the summation of the internal and external (contact) resistance. Second, the battery state of health (SOH) is estimated with incremental capacity analysis (ICA) - based method. Third, Density-Based Spatial Clustering of Applications with Noise (DBSCAN) method is applied to diagnose the connection failure by matching the calculated resistance with the estimated SOH. Finally, a linear projection is applied to reduce the method sensitivity to the testing conditions such as different state of charge (SOC). Experiments show that the proposed method can identify the location of the connection failure well in real time.
AB - This paper presents a connection failure detection for a Lithium-ion battery pack when no external vibrations exist. First, the gradient correction method is employed to identify the overall ohmic resistance, which is the summation of the internal and external (contact) resistance. Second, the battery state of health (SOH) is estimated with incremental capacity analysis (ICA) - based method. Third, Density-Based Spatial Clustering of Applications with Noise (DBSCAN) method is applied to diagnose the connection failure by matching the calculated resistance with the estimated SOH. Finally, a linear projection is applied to reduce the method sensitivity to the testing conditions such as different state of charge (SOC). Experiments show that the proposed method can identify the location of the connection failure well in real time.
KW - Lithium-ion batteries
KW - connection failure
KW - DBSCAN
KW - state of health estimation
KW - gradient correction
U2 - 10.12783/dteees/iceee2019/31808
DO - 10.12783/dteees/iceee2019/31808
M3 - Conference paper (refereed)
SN - 9781605956411
T3 - DEStech Transactions on Environment, Energy and Earth Sciences
SP - 203
EP - 206
BT - Proceeding of the 3rd Joint International Conference on Energy, Ecology and Environment (ICEEE 2019) and Electrical Intelligent Vehicles (ICEIV 2019)
PB - Destech Publications, Inc
T2 - The 3rd Joint International Conference on Energy, Ecology and Environment and Electrical Intelligent Vehicles
Y2 - 23 July 2019 through 27 July 2019
ER -
