Prediction-Based Fast Simulation with a Lightweight Solver for EV Batteries
- Authors
- Kyung, Donggu; Joe, 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.
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