[1]黄玉莎,陈玉珊,秦琳琳,等.基于 CARMA 模型的动力电池荷电状态估计[J].控制与信息技术,2020,(02):36.[doi:10.13889/j.issn.2096-5427.2020.01.400]
 HUANG Yusha,CHEN Yushan,QIN Linlin,et al.Charge State Estimation of Power Battery Based on CARMA Model[J].High Power Converter Technology,2020,(02):36.[doi:10.13889/j.issn.2096-5427.2020.01.400]
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基于 CARMA 模型的动力电池荷电状态估计()
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《控制与信息技术》[ISSN:2095-3631/CN:43-1486/U]

卷:
期数:
2020年02期
页码:
36
栏目:
电力与传动控制
出版日期:
2020-04-05

文章信息/Info

Title:
Charge State Estimation of Power Battery Based on CARMA Model
文章编号:
2096-5427(2020)02-0036-05
作者:
黄玉莎陈玉珊秦琳琳石  春吴  刚
(中国科学技术大学 信息科学技术学院,安徽 合肥 230026)
Author(s):
HUANG Yusha CHEN Yushan QIN Linlin SHI Chun WU Gang
( School of Information Science and Technology, University of Science and Technology of China, Hefei, Anhui 230026, China )
关键词:
荷电状态受控自回归滑动平均模型动力电池SOC 估计
Keywords:
SOC(state of charge) CARMA(controlled auto-regressive moving average) power battery SOC estimation
分类号:
TM911;U46
DOI:
10.13889/j.issn.2096-5427.2020.01.400
文献标志码:
A
摘要:
为完善电动汽车电池管理系统的主要功能,实现对电池准确建模及荷电状态 (state of charge,SOC) 的准确估计,文章基于二阶 RC 等效电路建立了一种受控自回归滑动平均模型 (controlled auto-regressive moving average,CARMA),推导得到电池开路电压 (open circuit voltage,OCV) 的最优估计,并结合分段建立的电池 OCV SOC 模型实现电池 SOC 估计,从而实现了电池模型参数在线实时辨识以及 SOC 实时估计,解决了因初值设定不合理而影响SOC估计准确度的问题。仿真结果表明:在美国联邦城市运行工况下,SOC估计误差的绝对值不超过2.39%,实现了较为准确的 SOC 估计。
Abstract:
In order to perfect main functions of electric vehicle battery management system, this paper aims to realize accurate battery modeling and state of charge(SOC) estimation. In this paper, based on the second-order RC equivalent circuit model, a controlled auto regressive moving average (CARMA) of the battery was established. The optimal estimation of open circuit voltage (OCV) is derived from the CARMA model, and battery SOC estimation is realised by OCV-SOC segmentation model. The method realizes online real-time identification of battery model parameters and real-time SOC estimation, which solves the problem of unreasonable initial value setting that affects the accuracy of SOC estimation. Simulation results show that under the operating conditions of the federal city in the United States, the absolute value of the SOC estimation error does not exceed 2.39%, and a more accurate SOC estimation is achieved.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2019-11-22
作者简介:黄玉莎(1996—),女,硕士研究生,研究方向为电池建模与估计。
更新日期/Last Update: 2020-05-08