TY - GEN
T1 - Cloud-connected battery management for decision making on second-life of electric vehicle batteries
AU - Baumann, Michael
AU - Rohr, Stephan
AU - Lienkamp, Markus
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/5/21
Y1 - 2018/5/21
N2 - The Second-Life use of retired electric vehicles' (EV) batteries in stationary storage systems can not only help to reduce the CO2 footprint of EVs but also generate a significant residual value before recycling. However, the nowadays repurposing process from vehicle batteries to Second-Life storage systems is characterized by time and cost intensive process steps like disassembly to module level and manual state of health (SOH) measurements with costly test equipment. Therefore, the aim of this paper is to introduce a novel cloud-connected battery management approach to estimate the residual value of vehicle batteries in respect to various potential Second-Life applications. Based on measurement data acquired by the battery management system (BMS) during regular vehicle operation, the state of the vehicle battery is continuously updated in the form of an electric-Thermal system model on a server backend. In combination with an empirical aging model, the degradation behaviour for different Second-Life scenarios' load cycles can be predicted and thus the residual value calculated. Besides the introduction of the overall concept, the focus of this paper lies on the electric-Thermal modelling approach as well as the algorithms used for dynamic electric parameter estimation.
AB - The Second-Life use of retired electric vehicles' (EV) batteries in stationary storage systems can not only help to reduce the CO2 footprint of EVs but also generate a significant residual value before recycling. However, the nowadays repurposing process from vehicle batteries to Second-Life storage systems is characterized by time and cost intensive process steps like disassembly to module level and manual state of health (SOH) measurements with costly test equipment. Therefore, the aim of this paper is to introduce a novel cloud-connected battery management approach to estimate the residual value of vehicle batteries in respect to various potential Second-Life applications. Based on measurement data acquired by the battery management system (BMS) during regular vehicle operation, the state of the vehicle battery is continuously updated in the form of an electric-Thermal system model on a server backend. In combination with an empirical aging model, the degradation behaviour for different Second-Life scenarios' load cycles can be predicted and thus the residual value calculated. Besides the introduction of the overall concept, the focus of this paper lies on the electric-Thermal modelling approach as well as the algorithms used for dynamic electric parameter estimation.
KW - Battery
KW - Battery Management System
KW - Electric Vehicle
KW - End of Life
KW - Equivalent Circuit Model
KW - Second-Life
UR - http://www.scopus.com/inward/record.url?scp=85048526707&partnerID=8YFLogxK
U2 - 10.1109/EVER.2018.8362355
DO - 10.1109/EVER.2018.8362355
M3 - Conference contribution
AN - SCOPUS:85048526707
T3 - 2018 13th International Conference on Ecological Vehicles and Renewable Energies, EVER 2018
SP - 1
EP - 6
BT - 2018 13th International Conference on Ecological Vehicles and Renewable Energies, EVER 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 13th International Conference on Ecological Vehicles and Renewable Energies, EVER 2018
Y2 - 10 April 2018 through 12 April 2018
ER -
