Multi-innovation adaptive Kalman filter algorithm for estimating the SOC of lithium-ion batteries based on singular value decomposition and Schmidt orthogonal transformation

The state of charge (SOC) of lithium battery is a key parameter for effective management of battery management systems (BMS). To address the problems of low precision, complex computation and poor robustness of traditional charging state estimation methods, an enhanced algorithm based on Unscented K...

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Veröffentlicht in:	Energy (Oxford) 2024-12, Vol.312, p.133597, Article 133597
Hauptverfasser:	Xiao, Jie, Xiong, Yonglian, Zhu, Yucheng, Zhang, Chao, Yi, Ting, Qian, Xing, Fan, Yongsheng, Hou, Quanhui
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptive unscented Kalman filter algorithms energy lithium batteries Lithium-ion battery Multi-innovation noise control Schmidt orthogonal transform Singular value decomposition State of charge
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