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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
Pages
8
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
1860-0794
2194-5365
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.
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서울 공과대학 > 서울 컴퓨터소프트웨어학부 > 1. Journal Articles

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