TY - GEN
T1 - Improved Impedance Measurements for Electric Vehicles with Reconfigurable Battery Systems
AU - Liebhart, Bernhard
AU - Diehl, Simon
AU - Schmid, Michael
AU - Endisch, Christian
AU - Kennel, Ralph
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/5/24
Y1 - 2021/5/24
N2 - Embedding impedance spectroscopy into onboard applications such as electric vehicles increases the diagnostic capabilities of battery management systems largely. A novel approach is presented and experimentally investigated throughout this work, whereby the load current excitation injected by the electric powertrain is pulsed by transistors. With a reconfigurable battery system, this form of active impedance spectroscopy can be used without further hardware. To obtain high-quality impedance data, a broadband data processing algorithm in the frequency domain is employed that deals inherently with both pulsing and non-pulsing data. An experimental setup is constructed to evaluate the proposed methods under real world conditions and the measurement results are in great accordance with laboratory reference measurements. Finally, a linear regression model acts as filter to suppress outliers, smooth the impedance spectra and thus describe the time-varying impedance of each cell.
AB - Embedding impedance spectroscopy into onboard applications such as electric vehicles increases the diagnostic capabilities of battery management systems largely. A novel approach is presented and experimentally investigated throughout this work, whereby the load current excitation injected by the electric powertrain is pulsed by transistors. With a reconfigurable battery system, this form of active impedance spectroscopy can be used without further hardware. To obtain high-quality impedance data, a broadband data processing algorithm in the frequency domain is employed that deals inherently with both pulsing and non-pulsing data. An experimental setup is constructed to evaluate the proposed methods under real world conditions and the measurement results are in great accordance with laboratory reference measurements. Finally, a linear regression model acts as filter to suppress outliers, smooth the impedance spectra and thus describe the time-varying impedance of each cell.
KW - Artificial Neural Network
KW - Impedance Spectroscopy
KW - Power MOSFET
KW - Reconfigurable Battery System
UR - http://www.scopus.com/inward/record.url?scp=85114212405&partnerID=8YFLogxK
U2 - 10.1109/ECCE-Asia49820.2021.9479060
DO - 10.1109/ECCE-Asia49820.2021.9479060
M3 - Conference contribution
AN - SCOPUS:85114212405
T3 - Proceedings of the Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021
SP - 1736
EP - 1742
BT - Proceedings of the Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 12th IEEE Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021
Y2 - 24 May 2021 through 27 May 2021
ER -