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文章摘要
基于自恢复效应电池放电模型及其应用研究
Research on the Dynamic Self-recovery Eeffect Battery Model and its Application.
Received:December 15, 2013  Revised:July 01, 2014
DOI:
中文关键词: 动态电池模型  微电网  荷电状态  在线动态分析
英文关键词: dynamic battery model  micro-grid  State of charge  Online dynamic analysis
基金项目:
Author NameAffiliationE-mail
Zhang Peng* Zhongyuan University of Technology zhangpengbbc@163.com 
He-Fan-lin ZhongYuan University of Technology  
Wang Xiao-lei Zhongyuan University of Technology  
Xiao Jun-ming Zhongyuan University of Technology  
FAN Fu-ling Zhongyuan University of Technology  
CHANG Jing Zhongyuan University of Technology  
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中文摘要:
      现有电池SOC预测方法,大都基于开路电压、开路电流等外电路或者测量电源内阻的方法,而没有考虑到电源的内在特性,尤其没有考虑电池的自恢复效应的影响,且大都采用恒压、恒流放电的工作模式,难以实现对电池SOC的动态预测。针对电池SOC预测方法的缺点,提出了一种包含有电池自恢复效应的电池SOC动态预测方法:提出一款包含有电池自恢复效应的动态电池模型,基于此电池模型提出了计及电池自恢复效应的动态放电模型,并论述了此放电模型与自恢复效应的关系,仿真结果表明,本预测方法具有较高的预测精度,且可实现动态预测。
英文摘要:
      The existing the battery SOC forecast method, largely based on the open-circuit voltage, open circuit current external circuit or method of measuring the power of internal resistance without taking into account the inherent characteristics of the power supply, in particular, did not consider the battery self-recovery effect, and is mostly used constant pressure or a constant current discharge mode of operation, difficult to achieve a dynamic prediction of the battery SOC. For battery SOC detection method has the disadvantage, the paper presents a battery self-recovery effect of battery SOC dynamic detection and prediction methods: proposed a dynamic battery model contains a battery of self-recovery effect contains the battery, this battery-based model dynamic discharge model of self-recovery effect, and prove that the effect of the discharge model with self-recovery relationship, the simulation results show that the prediction method has higher prediction accuracy, and dynamic forecast.
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