返回
Bandwidth based electrical-analogue battery modeling for battery modules
DOI:10.1016/j.jpowsour.2012.07.006.png)
摘要
En 中文
A technique for building a high fidelity electrical-analogue battery model by identifying the model parameters at the module level, as opposed to the cell level, is proposed in this paper. The battery model, which is represented by electrical circuit components, can be easily integrated into popular simulation environments for system level design and predictive analysis. A novel bandwidth based time-domain procedure is introduced for identifying the model parameters by selective assignment of the limited bandwidth of the battery model approximation according to the natural bandwidth of the system that uses the battery. The aim of this paper is to provide an accurate off-line electrical-analogue battery model for simulation of larger systems containing large-format batteries, as opposed to a detailed electrochemical model suitable for simulation of internal battery processes. The proposed procedure has been experimentally verified on a 6.8 Ah Ultralife UBBL10 Li-ion battery module which is a microcosm for a modern large-format battery pack. A maximum 0.25% error was observed during a performance test with arbitrary but bandwidth-limited charging and discharging intervals characteristic of a typical battery application. (C) 2012 Elsevier B.V. All rights reserved.
Keyword:
Batteries
Parameter identification
Electrical model
Lithium-ion
State of charge
Bandwidth
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
7.9
论文数:
3.7W
被引数:
15.0W
机构
引用论文
Computational battery dynamics (CBD) - electrochemical/thermal coupled modeling and multi-scale modeling计算电池动力学 (CBD) -电化学/热耦合建模和多尺度建模
Rapid test and non-linear model characterisation of solid-state lithium-ion batteries固态锂离子电池的快速测试和非线性模型表征
The novel state of charge estimation method for lithium battery using sliding mode observer基于滑模观测器的锂电池荷电状态估计新方法
Accurate electrical battery model capable of predicting, runtime and I-V performance能够预测、运行时间和i-v性能的精确电池模型
Battery, Ultracapacitor, Fuel Cell, and Hybrid Energy Storage Systems for Electric, Hybrid Electric, Fuel Cell, and Plug-In Hybrid Electric Vehicles: State of the Art用于电动,混合动力电动,燃料电池和插电式混合动力电动汽车的电池,超级电容器,燃料电池和混合动力储能系统: 最新技术

