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: 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: Please fill out the form below.

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

Maximum number attendees (with physical presence): 22


  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

Workshop signup 20211125

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