Lecture
Can fusing Li-ion cell impedance in BMS algorithms lead to further optimization of next generation EV battery system?
- at -
- ICM Saal 2
- Language: English
- Type: Lecture
Lecture description
In addition to the costs, range anxiety and fast-charging capability, the safety of Li-ion batteries (LIBs) is most important. In
the proposed conference contribution, we introduce the practical application use cases of Electrochemical Impedance
Spectroscopy (EIS) in electric vehicles (EVs) and how EIS can further complement the current BMS data driven algorithms,
enabling better use of the existing LIB by fully understanding its limits. Such sensor fusion data coupled with physical,
machine learning, and AI algorithms can further accelerate acceptance of EVs without compromising battery health and
safety
the proposed conference contribution, we introduce the practical application use cases of Electrochemical Impedance
Spectroscopy (EIS) in electric vehicles (EVs) and how EIS can further complement the current BMS data driven algorithms,
enabling better use of the existing LIB by fully understanding its limits. Such sensor fusion data coupled with physical,
machine learning, and AI algorithms can further accelerate acceptance of EVs without compromising battery health and
safety
All lectures within this session
- -Standard BMS Platform
- Automotive
- -Can fusing Li-ion cell impedance in BMS algorithms lead to further optimization of next generation EV battery system?
- Automotive
- -BMS Podiums Discussion
- Automotive