2021.11.25 Workshop: Cloud- and AI-based battery SoH estimation in various applications

Presenters: Lithium Balance/Xolta, Aalborg University, IVI Fraunhofer Institute, Blue Ocean Robotics

Date and time: Thursday 25th of November 2021 at 10:00 AM – 14:00 PM (CET)

Venue: A. C. Meyers Vænge 15, 2450 Copenhagen, room: 2.2.040A (Aalborg University Copenhagen)
(or virtual participation possible via MS Teams. Online participants will receive an email with link a few days before the workshop)

Language: English.

Price: Free participation

Registration deadline: Monday 22nd of November at 18:00 (CET).

Maximum number attendees (with physical presence): 22

Agenda:

  1. 10:00 – 10:50: Introduction to the Cloud BMS project and battery state estimation:
    (Presenter: Lithium Balance/XOLTA)
    o Short overview of the project
    o Importance of the battery state estimation
    o Methods of the battery state estimation
    o IoT, Big Data based battery state estimation
    o Question & Answer session
  2. 10:50 – 11:40: Battery state of health (SoH) estimation and remaining useful lifetime (RUL) prediction in stationary application: an example for BESSs:
    (Presenter: IVI Fraunhofer Institute)
    o BESS’s field data collection, and monitoring
    o Analysis of the results
    o SoH estimation and RuL prediction
    o Question & Answer session
  3. 11:40 – 12:20: Lunch break:
  4. 12:20 – 13:10: Machine learning – based SoH estimation of forklift-used batteries:
    (Presenter: Aalborg University)
    o Accelerated lifetime testing of battery cells based on forklift mission profile
    o SoH estimation of battery cells using multiple linear regression
    o SoH estimation of forklift batteries based on Transfer Learning (TL)
    o Alghortim validation and conclusions
    o Question & Answer session
  5. 13:10 – 14:00: Example of the cost reduction for the robot application:
    (Presenter: Blue Ocean Robotics)
    o Robot case story
    o Robot batteries: challenges
    o Potential of the battery cost ownership reduction based on the Cloud BMS findings (design and operation)
    o Question & Answer session

Registration

For registration, please fill out the form below and pres ‘Tilmeld’. Some of the fields of the form are mandatory, and the registration cannot be finalized unless those fields have been completed. When the form has been completed sucessfully, you should be able to see the following message:

Registration is no longer possible as the deadline has been exceeded.

Erik Schaltz

Erik Schaltz received the MSc and PhD degrees in electrical engineering from the Department of Energy, Aalborg University, Aalborg, Denmark, in 2005 and 2010, respectively. From 2009 to 2012, he has been an Assistant Professor and since 2012, he has been an Associate Professor. Both positions also at the Department of Energy, Aalborg University. At the Department, he is the leader of the research group in E-mobility and Drives and the vice leader of the Batteries research group. He is a guest and associate editor in several journals related to batteries and e-mobility and he is also a board member of the Danish Battery Society. His research interests include the usage of power electronics, electric machines, fuel cells, batteries, ultracapacitors, etc. as power train in various applications like electric vehicles, industrial machinery, and heavy-duty systems. In addition, he is also focused on battery state-estimation, management (electric and thermal), and modelling (electric, thermal, and lifetime) of battery cells and packs.

Permanent link to this article: http://batteriselskab.dk/arrangementer/praesentationer/2021-11-25-workshop-cloud-and-ai-based-battery-soh-estimation-in-various-applications.htm