Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

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

Authors
Kyung, DongguJoe, Inwhee
Issue Date
Sep-2019
Publisher
Springer
Keywords
CPS; EV battery; Fast simulation; FMI; Lightweight solver
Citation
Advances in Intelligent Systems and Computing, v.1046, pp.385 - 392
Indexed
SCOPUS
Journal Title
Advances in Intelligent Systems and Computing
Volume
1046
Start Page
385
End Page
392
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/147167
DOI
10.1007/978-3-030-30329-7_34
ISSN
2194-5357
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.
Files in This Item
Go to Link
Appears in
Collections
서울 공과대학 > 서울 컴퓨터소프트웨어학부 > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Joe, Inwhee photo

Joe, Inwhee
COLLEGE OF ENGINEERING (SCHOOL OF COMPUTER SCIENCE)
Read more

Altmetrics

Total Views & Downloads

BROWSE