State of health estimation for lithium-ion batteries using recurrent neural networks with gated recurrent unit

Shaoyu Zhang; Chunhui Wu; Wenyuan Xiong

doi:10.3788/IRLA20200339

Journals >Infrared and Laser Engineering >Volume 50 >Issue 2 >Page 20200339 > Article

Infrared and Laser Engineering
Vol. 50, Issue 2, 20200339 (2021)

State of health estimation for lithium-ion batteries using recurrent neural networks with gated recurrent unit

Shaoyu Zhang¹, Chunhui Wu², and Wenyuan Xiong¹

Author Affiliations

¹Center of Experimental Teaching, Guangdong University of Finance, Guangzhou 510091, China

²School of Internet Finance and Information Engineering, Guangdong University of Finance, Guangzhou 510091, China

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DOI: 10.3788/IRLA20200339 Cite this Article

Shaoyu Zhang, Chunhui Wu, Wenyuan Xiong. State of health estimation for lithium-ion batteries using recurrent neural networks with gated recurrent unit[J]. Infrared and Laser Engineering, 2021, 50(2): 20200339 Copy Citation Text

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References

[7] H Chaoui, C C Ibe-Ekeocha. State of charge and state of health estimation for lithium batteries using recurrent neural networks. IEEE Transactions on Vehicular Technology, 66, 8773-8783(2017).

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