Hybrid physics-informed neural networks for lithium-ion battery modeling and prognosis
Indexed from repository: NASA Technical Reports Server
(
ntrs.nasa.gov)
Document Information
| Document Title | Hybrid physics-informed neural networks for lithium-ion battery modeling and prognosis |
|---|---|
| Author / Organization | Renato G. Nascimento, Matteo Corbetta, Chetan S. Kulkarni, Felipe A.C. Viana |
| Subject & Discipline | ACCEPTED_MANUSCRIPT |
| Categories | Aerospace & Aviation |
| Publication Year | 2026 |
| License / Rights | Public Domain / NASA STI Open Access |
| Resource Verification | Listed PDF (Verification Pending) |
| Original Host Website |
NASA Technical Reports Server
(ntrs.nasa.gov)
|
| File Format | application/pdf (Portable Document Format) |
| Language | EN |
| Catalog ID | DOC-32104 |
| Original Source Link | Visit Source Page on ntrs.nasa.gov » |