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Bo Sun

affiliation not provided to SSRN

SCHOLARLY PAPERS

6

DOWNLOADS

509

TOTAL CITATIONS

2

Scholarly Papers (6)

A Cnn-Sam-Lstm Hybrid Neural Network for Multi-State Estimation of Lithium-Ion Batteries Under Dynamical Operating Conditions

Number of pages: 32 Posted: 06 Nov 2023
affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, Beihang University (BUAA) and affiliation not provided to SSRN
Downloads 123 (607,238)

Abstract:

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Lithium-ion battery, State of charge, State of energy, state of health, Multi-state estimate.

A Cnn-Sam-Lstm Hybrid Neural Network for Multi-State Estimation of Lithium-Ion Batteries Under Dynamical Operating Conditions

Number of pages: 22 Posted: 14 Oct 2023
affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, Beihang University (BUAA), affiliation not provided to SSRN and affiliation not provided to SSRN
Downloads 51 (1,083,731)
Citation 1

Abstract:

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Lithium-ion battery, State of charge, State of energy, State of health, Multi-state estimate.

2.

Adaptive Evolution Enhanced Physics-Informed Neural Networks for Time-Variant Health Prognosis of Lithium-Ion Batteries

Number of pages: 28 Posted: 05 Oct 2022
affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, Beihang University (BUAA), affiliation not provided to SSRN, affiliation not provided to SSRN and Beihang University (BUAA)
Downloads 152 (488,442)

Abstract:

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Physics-informed neural networks, Health prognosis, Adaptive evolution, Lithium-ion battery, Long short-term memory, Kullback-Leibler divergence

3.

An Adaptive Semi-Supervised Self-Learning Method for Online State Of Health Estimation of Lithium-Ion Batteries

Number of pages: 27 Posted: 28 Sep 2023
affiliation not provided to SSRN, Beihang University (BUAA), affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN and affiliation not provided to SSRN
Downloads 67 (916,100)
Citation 1

Abstract:

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Lithium-ion battery, state of health estimation, Online unlabeled data, Semi-supervised learning, Dynamic conditions

4.

A Cnn-Sam-Lstm Hybrid Neural Network for Multi-State Estimation of Lithium-Ion Batteries

Number of pages: 21 Posted: 16 Sep 2023
affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, Beihang University (BUAA) and affiliation not provided to SSRN
Downloads 64 (933,592)

Abstract:

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Lithium-ion battery, State of charge, State of energy, State of health, Multi-state estimate.

5.

Cumulative Damage Simulation-Based Online Wear Failure Uncertainty Quantitative Modeling for Shaft Products

Number of pages: 12 Posted: 01 Oct 2024
affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, China North Vehicle Research Institute and China North Vehicle Research Institute
Downloads 30 (1,318,317)

Abstract:

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Shaft products, Cumulative damage simulation, PINN, uncertainty quantification, Digital twin

6.

Cumulative Damage Simulation-Based and Intelligent Response Surface Online Wear Failure Uncertainty Quantitative Assessment for Shaft Products

Number of pages: 20 Posted: 17 May 2025
affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, Beihang University (BUAA), affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, China North Vehicle Research Institute and China North Vehicle Research Institute
Downloads 22 (1,424,331)

Abstract:

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Shaft products, digital twin, Cumulative damage simulation, Intelligent response surface, uncertainty quantification