Estimation of Best Linear Approximation from Varying Operating Conditions for the Identification of a Li-ion Battery Model

被引：3
|
作者：
Relan, Rishi [1 ]
Tiels, Koen [1 ]
Timmermans, Jean-Marc [2 ]
Schoukens, Johan [1 ]
机构：
[1] Vrije Univ Brussel, Dept ELEC, B-1050 Brussels, Belgium
[2] Vrije Univ Brussel, Dept ETEC MOBI, B-1050 Brussels, Belgium
来源：
IFAC PAPERSONLINE | 2017年 / 50卷 / 01期
关键词：
System identification; Multiple experiments; Nonlinear models; Li-ion battery; Best linear approximation; SYSTEM-IDENTIFICATION; ELECTRIC-VEHICLES; NONLINEAR DISTORTIONS; MANAGEMENT;
D O I：
10.1016/j.ifacol.2017.08.867
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The short term dynamic response of the battery varies with varying operating conditions. Hence, even before proceeding towards the modelling step, it is important to fully characterise and understand the dynamic behaviour of the battery at varying operating conditions. In this paper, a data-driven methodology for characterising the battery's short term electrical response at varying operating conditions e.g. at different levels of SoC and different temperature levels is discussed. Furthermore, a novel way to estimate the best linear approximation from the data acquired at these operating conditions with varying levels of noise and nonlinear distortions is proposed. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
引用
收藏
页码：4739 / 4744
页数：6
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