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Fault detection and failure assessment of lithium-ion battery through AC impedance spectroscopy and machine learning : a thesis report

By: Vyas, Mayank (2016REN9058)Contributor(s): Pareek, Kapil [Supvr.]Material type: Text

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TextPublication details: Jaipur Centre for Energy and Environment, MNIT 2021 Description: ix,209p. +1 CDSubject(s): Energy and Environment | Fault detection and failure assessmentDDC classification: 628

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Item type	Current library	Call number	Status	Date due	Barcode
Thesis	Malaviya National Institute of Technology Reference	628 (Browse shelf(Opens below))	Not for loan		TH00648

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Previous	628 Predictive analytics and machine learning for mitigating unintentional islanding in solar P V distributed generation systems : a thesis report	628 Studies on solid state anaerobic digestion of agrictultural stubble and its simultaneous treatment for improved methanogensis : a thesis report	628 Quantification of occupant's adaptive actions for improving the indoor environment quality in buildings : a thesis report	628 Fault detection and failure assessment of lithium-ion battery through AC impedance spectroscopy and machine learning : a thesis report	628 Performance evaluation of photovoltaic double skin facade with forced ventilation : a thesis report	628 Operational flexibility enhancement in low-carbon power systems : a thesis report	628 Modelling operational aspects in long-term power generation planning with high RE pentration : a thesis report	Next

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