PREDICTION OF REMAINING USEFUL LIFE OF LITHIUM-ION BATTERIES BASED ON PCA-GPR

He Bingchen; Yang Xueming; Wang Jinsong; Zhu Xu; Hu Zongjie; Liu Qiang

doi:10.19912/j.0254-0096.tynxb.2022-0422

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Acta Energiae Solaris Sinica ›› 2022, Vol. 43 ›› Issue (5) : 484-491. DOI: 10.19912/j.0254-0096.tynxb.2022-0422

PREDICTION OF REMAINING USEFUL LIFE OF LITHIUM-ION BATTERIES BASED ON PCA-GPR

He Bingchen¹, Yang Xueming¹, Wang Jinsong², Zhu Xu¹, Hu Zongjie¹, Liu Qiang¹

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Abstract

A health indicator （HI） is extracted from the voltage-capacity curve during the charging process, which is highly correlated with the battery life. Then a PCA-GPR based prediction model for the remaining useful life of lithium-ion batteries is proposed by using principal component analysis （PCA） to analyze and downscale the multidimensional factors affecting the battery life, combined with gaussian processes regression （GPR） machine learning method. Finally, the remaining lifetime prediction of lithium-ion battery is performed and compared with PCA-BP neural network and PCA-Support vector machine （SVM） models. The results show that the HI and prediction model proposed in this paper can effectively improve the prediction accuracy of the remaining useful life of lithium-ion batteries. Among the compared prediction models, the PCA-GPR model optimized by Bayesian optimizer exhibits the best prediction performance.

Key words

lithium-ion battery / remaining useful life prediction / health indicator / principal component analysis / Gaussian regression process

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He Bingchen, Yang Xueming, Wang Jinsong, Zhu Xu, Hu Zongjie, Liu Qiang. PREDICTION OF REMAINING USEFUL LIFE OF LITHIUM-ION BATTERIES BASED ON PCA-GPR[J]. Acta Energiae Solaris Sinica. 2022, 43(5): 484-491 https://doi.org/10.19912/j.0254-0096.tynxb.2022-0422

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