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Battery health monitoring using machine learning /

TextPublisher: USPCAS-E, NUST, Islamabad : 2019Description: 70 pSubject(s): MS-EEP Thesis MS ThesisDDC classification: 621.3 Summary: TH-145

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Item type	Current location	Home library	Call number	Status	Date due	Barcode	Item holds
Thesis	US-Pakistan Center for Advanced Studies in Energy (USPCAS-E)	US-Pakistan Center for Advanced Studies in Energy (USPCAS-E)	621.3 SHE (Browse shelf)	Available		CAS-ETH0000145

Total holds: 0

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Previous	621.3 SHA Investigation on Structural, Optical, and Ectrical Properties of Erbium Oxide-based Composites for Photocatalysis /	621.3 SHA Feasible Selection of Candidate Wind Farms’ Capacity for Generation Expansion Planning /	621.3 SHA Improvement of Electrochemical Properties of Layered Cathode Materials for Sodium-ion Batteries /	621.3 SHE Battery health monitoring using machine learning /	621.3 SOH A hybrid design of integrated silicon (Si) solar cell with guided mode resonance filter (GMRF) /	621.3 SOP Net Zero Onsite Energy Homes: opportunities and Challenges /	621.3 SUL Multi-Objective Optimization Based Approach for Optimal Allocation of Distributed Generation Considering Techno-Economic and Environmental Indices /	Next

TH-145

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