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西北工业大学 国内
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Lithium polymer battery state-of-charge estimation based on adaptive unscented kalman filter and support vector machine
Jinhao Meng,
Guangzhao Luo
, Fei Gao
自动化学院
Northwestern Polytechnical University Xian
Université de technologie de Belfort Montbéliard
科研成果
:
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同行评审
317
引用 (Scopus)
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探究 'Lithium polymer battery state-of-charge estimation based on adaptive unscented kalman filter and support vector machine' 的科研主题。它们共同构成独一无二的指纹。
分类
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按字母排序
Engineering
Battery Model
33%
Estimation Result
16%
Experimental Result
16%
Kalman Filter
100%
Least Square
66%
Limited Number
16%
Lithium Battery State-of-Charge
16%
Measurement Equation
16%
Moving Window
33%
State of Charge
100%
Support Vector Machine
100%
Chemical Engineering
Support Vector Machine
100%