IEEE VTS Motor Vehicles Challenge 2023: A Multi-physical Benchmark Problem for Next Generation Energy Management Algorithms
The competitors are invited to develop the energy management algorithm (EMA) for the vehicle (cf. Figure 1). The EMA determines the operating conditions for the two energy storage devices and the three electric motors; minimization of the energy consumption and battery degradation are some of the main goals of the EMA.
Dear competitors,
we are happy to announce that the team
EDLab Sharks team from University of Padova won this year’s edition of the IEEE VTS Motor Vehicles Challange 2023.
2nd place: Ricercatori Polimi TEAM 2 from Politecnico di Milano
3rd place: NDS strategy 1 from Politecnico di Milano
Congratulations!
All rankings and details on the assessment process can be found here.
Many thanks to all competitors and their valuable input during the development process of the challenge.
We are looking forward to meet you in person at the IEEE VPPC 2023 in Milan!
Please refer to the change log.
Latest: 17th of Feb. 2023 - Final Release (i.a. 30 s preview horizon).
Remarks:
- Please take notice of the discussion board, with a lot of solved Q&A.
- Moreover, it is worthwhile to have a look at the solved issues section.
- How to get ready in MATLAB/Simulink, please refer to installation readme.
- For additional information please view presentation slides of the paper *.pdf.
- The submitted version of the publication, incl. fixed errata can be found in our elib repository.
- For information on the given tracks, please refer to tracks readme.
In Figure 1 the MVC 2023 challenge model and it's components are shown.
The competitors are invited to develop the top red block, the energy management algorithm (EMA).
Figure 1: Block diagram of the MVC 2023 benchmark problem.
Brembeck, J.; de Castro, R.; Tobolar, J. & Ebrahimi, I. IEEE VTS Motor Vehicles Challenge 2023: A Multi-physical Benchmark Problem for Next Generation Energy Management Algorithms 19th IEEE Vehicle Power and Propulsion Conference (VPPC), 2022
Link to reference *.bib file.
Copyright © 2022-2023 DLR & UCM. The code is released under the CC BY-NC 4.0 license. Link to short summary of CC BY-NC 4.0 license. For attribution see also license file.