AI-Enabled Cyber Physical System And Battery Life Estimation For Smart Grid Applications
| dc.contributor.author | N.k A.P.; Kumar A.; Chitransh V.; Singh R.K.; Lal V.N.; Singh S.K. | |
| dc.date.accessioned | 2025-05-23T11:17:04Z | |
| dc.description.abstract | In this paper, the development of an efficient three- layer Cyber Physical System (CPS) using a multi-output power electronic interface integrated with IoT-enabled modules and AI- based algorithms is presented. The power electronic interface layer of the proposed CPS eliminates the need of bulky electrolytic capacitors and reduces the switching loss. This layer facilitates DC to DC and DC to three-phase AC power conversion for battery charging and smart-grid applications respectively. AI-based algorithms are utilized for accurately predicting the Remaining Useful Life (RUL) of batteries. The performance of the proposed CPS is validated through simulation and experimental measurement results using a 700 W prototype system. The measurement results show that the proposed CPS enables real-time monitoring, accurate prediction of RUL, predictive maintenance decisions, data analytics, and optimized power flow. © 2023 IEEE. | |
| dc.identifier.doi | https://doi.org/10.1109/IECON51785.2023.10312224 | |
| dc.identifier.uri | http://172.23.0.11:4000/handle/123456789/6965 | |
| dc.relation.ispartofseries | IECON Proceedings (Industrial Electronics Conference) | |
| dc.title | AI-Enabled Cyber Physical System And Battery Life Estimation For Smart Grid Applications |