Project Details

Description

This project will contribute to the wider use of renewable energy in the energy system as both longer and precisely known battery lifetimes will help the introduction of batteries in:
• Stationary battery energy storage (BES) systems to form a buffer between the supply and demand of fluctuating energy sources like e.g. wind, solar;
• Vehicles, where batteries will allow (green) electricity to replace unsustainable and fossil-fuel based oil as energy source. The battery demonstration cases in the project will focus on high-end industrial vehicles like the rapidly growing robot market where Danish industry has a strong position.

The project will develop dedicated hardware and software for cloud-based BMS demonstrations and future commercialization. The general advantages of the cloud-based BMS will be demonstrated on different battery applications including forklifts, robots and stationary BES system utilizing both new (1st life) and used (2nd life) batteries.
The cost reduction potential of the cloud BMS technology will be quantified in the design and demonstration of a new robot generation. The project ambition is to demonstrate that the effective battery cost of the new generation of robots using Cloud BMS is reduced by 50% compared to the previous generation.
AcronymCloud BMS
StatusFinished
Effective start/end date01/01/201830/09/2020

Funding

  • EUDP: DKK8,274,722.00

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  • Research Output

    • 2 Article in proceeding
    • 1 Journal article

    A Time-Varying Log-linear Model for Predicting the Resistance of Lithium-ion Batteries

    Vilsen, S. B., Sui, X. & Stroe, D-I., 2020, (Accepted/In press) IPEMC 2020-ECCE Asia .

    Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

    Open Access
    File
  • 13 Downloads (Pure)
    Open Access
    File
  • 5 Downloads (Pure)

    Predicting Lithium-ion Battery Resistance Degradation using a Log-Linear Model

    Vilsen, S. B., Kær, S. K. & Stroe, D-I., Sep 2019, Proceedings of 2019 IEEE Energy Conversion Congress and Exposition (ECCE). IEEE Press, p. 1136-1143 8 p. 8912770. (IEEE Energy Conversion Congress and Exposition).

    Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

    Open Access
    File
  • 11 Downloads (Pure)