Electric vehicle intelligent monitoring and analysis for battery
| dc.contributor.author | Saxena, A. | |
| dc.contributor.author | Binod, S. | |
| dc.contributor.author | Maurya, S. | |
| dc.contributor.author | Kapoor, O. | |
| dc.contributor.author | Singh, U. | |
| dc.contributor.author | Kumar, R. | |
| dc.contributor.author | Sharma, A.K. | |
| dc.date.accessioned | 2026-02-06T06:33:37Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | This article shows the intelligent monitoring of electric vehicle for battery energy management with soft computing techniques. Thereafter different soft computing techniques like fuzzy logic controller, energy hub method, dynamic programming, DRL method, model predictive control was proposed to get the best results for the performance of EV and it is observed that fuzzy logic controller gives the best results as compared to other techniques vehicle for battery energy management. © 2024 Author(s). | |
| dc.identifier.citation | AIP Conference Proceedings, 2024, Vol.2816, 1, p. - | |
| dc.identifier.issn | 0094243X | |
| dc.identifier.uri | https://doi.org/10.1063/5.0177453 | |
| dc.identifier.uri | https://idr.nitk.ac.in/handle/123456789/28756 | |
| dc.publisher | American Institute of Physics | |
| dc.subject | DRL | |
| dc.subject | DYNAMIC | |
| dc.subject | FUZZY LOGIC CONTROL | |
| dc.subject | PREDICTIVE | |
| dc.title | Electric vehicle intelligent monitoring and analysis for battery |