Optimizing Current Profiles for Efficient Online Estimation of Battery Equivalent Circuit Model Parameters Based on Cramer-Rao Lower Bound

被引:7
|
作者
Pillai, Prarthana [1 ]
Sundaresan, Sneha [1 ]
Pattipati, Krishna R. [2 ]
Balasingam, Balakumar [1 ]
机构
[1] Univ Windsor, Dept Elect & Comp Engn, Windsor, ON N9B 3P4, Canada
[2] Univ Connecticut, Dept Elect & Comp Engn, Storrs, CT 06269 USA
基金
加拿大自然科学与工程研究理事会;
关键词
battery management system; battery equivalent circuit model; least squares estimation; battery internal resistance; Cramer-Rao lower bound; OF-CHARGE ESTIMATION; PREDICTION;
D O I
10.3390/en15228441
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Battery management systems (BMS) are important for ensuring the safety, efficiency and reliability of a battery pack. Estimating the internal equivalent circuit model (ECM) parameters of a battery, such as the internal open circuit voltage, battery resistance and relaxation parameters, is a crucial requirement in BMSs. Numerous approaches to estimating ECM parameters have been reported in the literature. However, existing approaches consider ECM identification as a joint estimation problem that estimates the state of charge together with the ECM parameters. In this paper, an approach is presented to decouple the problem into ECM identification alone. Using the proposed approach, the internal open circuit voltage and the ECM parameters can be estimated without requiring the knowledge of the state of charge of the battery. The proposed approach is applied to estimate the open circuit voltage and internal resistance of a battery.
引用
收藏
页数:21
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