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    Lifetime Prediction of LiFePO4 Batteries Using Multilayer Classical-Quantum Hybrid Classifier

    Muhammad Haris1,*, Muhammad Noman Hasan1 , Abdul Basit2, Shiyin Qin1

    Journal of Quantum Computing, Vol.3, No.3, pp. 89-95, 2021, DOI:10.32604/jqc.2021.016390

    Abstract This article presents a multilayer hybrid classical-quantum classifier for predicting the lifetime of LiFePO4 batteries using early degradation data. The multilayer approach uses multiple variational quantum circuits in cascade, which allows more parameters to be used as weights in a single run hence increasing accuracy and provides faster cost function convergence for the optimizer. The proposed classifier predicts with an accuracy of 92.8% using data of the first four cycles. The effectiveness of the hybrid classifier is also presented by validating the performance using untrained data with an accuracy of 84%. We also demonstrate that the proposed classifier outperforms traditional… More >

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