期刊
IFAC PAPERSONLINE
卷 49, 期 11, 页码 48-53出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.ifacol.2016.08.008
关键词
Battery Modelling; Parametrisation; Identification; Algorithm; Electric Vehicle
资金
- EPSRC [EP/L505286/1] Funding Source: UKRI
This study is focused on fast low-fidelity battery modelling for online applications. Because the battery parameters change due to variations of battery's states, the model may need to be updated during operation. This can be achieved through the use of an online parameter identification technique, making use of online current-voltage measurements. The parametrisation algorithm's speed is a crucial issue in such applications. This paper describes a study exploring the trade-offs between speed and accuracy, considering equivalent circuit models with different levels of complexity and different parameter-fitting algorithms. A visual investigation of the battery parametrisation problem is also proposed by obtaining battery model identification surfaces which help us to avoid unnecessary complexities. Three standard fitting algorithms are used to parametrise battery models using current-voltage measurements. For each level of complexity; the algorithms performances arc evaluated using experimental data from a small NiMH battery pack. An application-oriented view on this trade-offs is discussed which demonstrates that the final target of the battery parametrisation problem can significantly affect the choice of the fitting algorithm and battery model structure. (C) 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据