Prediction-Based Fast Simulation with a Lightweight Solver for EV Batteries

Donggu Kyung, Inwhee Joe

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we propose a fast simulation method using a lightweight solver for EV batteries. In CPS, the simulation time should be reduced for real-time simulation by minimizing the overhead. In order to reduce the simulation time, the number of simulation steps needs to be decreased by a variable step size. To control the step size, a lightweight solver is introduced to predict the event as soon as possible before actual simulation. Through the prediction, a large step size can be used if there is no event, while a small step size can be used if there is an event. The simulation results show that our prediction-based method reduces the simulation time significantly, compared to the conventional non-prediction-based method.

Original languageEnglish
Title of host publicationIntelligent Systems Applications in Software Engineering - Proceedings of 3rd Computational Methods in Systems and Software, CoMeSySo 2019
EditorsRadek Silhavy, Petr Silhavy, Zdenka Prokopova
PublisherSpringer
Pages385-392
Number of pages8
ISBN (Print)9783030303280
DOIs
StatePublished - 2019 Jan 1
Event3rd Computational Methods in Systems and Software, CoMeSySo 2019 - Zlin, Czech Republic
Duration: 2019 Sep 102019 Sep 12

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1046
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference3rd Computational Methods in Systems and Software, CoMeSySo 2019
CountryCzech Republic
CityZlin
Period19/09/1019/09/12

Keywords

  • CPS
  • EV battery
  • FMI
  • Fast simulation
  • Lightweight solver

Cite this

Kyung, D., & Joe, I. (2019). Prediction-Based Fast Simulation with a Lightweight Solver for EV Batteries. In R. Silhavy, P. Silhavy, & Z. Prokopova (Eds.), Intelligent Systems Applications in Software Engineering - Proceedings of 3rd Computational Methods in Systems and Software, CoMeSySo 2019 (pp. 385-392). (Advances in Intelligent Systems and Computing; Vol. 1046). Springer. https://doi.org/10.1007/978-3-030-30329-7_34