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Markus Eider, M.Sc.

Research

  • Research project SmiLE

Research focus

  • Recommender systems
  • Decision support systems
  • Machine learning
  • Electric mobility

Teaching

  • Fundamentals of Computer Science (Bachelor Applied Computer Science / Interactive Systems)
  • Introduction to Programming (Bachelor Applied Computer Science / Interactive Systems)
  • Advanced Machine Learning (Master Artificial Intelligence and Data Science, summer semester 2022)

Blended learning: SMART vhb

  • Project employee in the course Java Programming (Prof. Dr. Andreas Berl)

Academic Staff

Research project “SmiLE”

DEGG's 2.28

0991/3615-633

0991/3615-297


consulting time

Consultation hours by appointment via email


Sortierung:
Beitrag (Sammelband oder Tagungsband)

  • Nicki Bodenschatz
  • Markus Eider
  • Andreas Berl

Challenges and requirements of electric vehicle fleet charging at company parking sites

pg. 623-628.

  • (2021)

DOI: 10.1109/ACIT52158.2021.9548563

The uprising number of electric vehicles on company parking sites creates a variety of challenges, in terms of scheduling charging processes. In uncoordinated charging, peaks loads can occur that harm the low voltage grid and make the company pay a higher electricity bill. Further, some vehicles may not be charged enough to be used for service appointments at customer homes. In a first step, this paper highlights the individual problems in detail that can appear in a company parking scenario. Next, it is shown that charging scheduling in a company case is not trivial. Finally, requirements to a software-based solution of the challenges are derived from the individual problems.
  • Angewandte Informatik
  • MOBIL