Deepak Kumar

7 ta ish

Delhi Technological University

1. A Novel Approach for State of Health Estimation of Lithium-Ion Batteries Based on Improved PSO Neural Network Model

   Rashid Nasimov, Deepak Kumar, M. Rizwan +3

   MaqolaOAOchiq kirishAdvanced Battery Technologies ResearchProcesses20248 iqtibos

   ABIABI:AkademIndex/2026.other.103998

2. Advanced Intelligent approach for state of charge estimation of lithium-ion battery

   Deepak Kumar, M. Rizwan, Amrish K. Panwar

   Maqola20233 iqtibos

   ABIABI:AkademIndex/2026.other.222068

3. Advanced Intelligent Hybrid Approach for State of Charge Estimation of Li-Ion Batteries in Electric Vehicles under Various Drive Cycles

   Deepak Kumar, M. Rizwan, Amrish K. Panwar

   Maqola20233 iqtibos

   ABIABI:AkademIndex/2026.other.222069

4. New Filter-based Supervised Learning Approach for State of Charge Estimation of Li-Ion Battery for EV Applications

   M. Rizwan, Deepak Kumar, Amrish K. Panwar

   Maqola20233 iqtibos

   ABIABI:AkademIndex/2026.other.222072

5. Exploration of grown cobalt-doped zinc oxide nanoparticles and photodegradation of industrial dye

   Deepak Kumar, Mrityunjay Kumar Singh, Mohan Singh Mehata

   Maqola20222 iqtibos

   ABIABI:AkademIndex/2026.other.222047

6. Robust state of health estimation of commercial lithium-ion batteries based on enhanced hybrid machine learning model for electrified transportation

   Deepak Kumar, M. Rizwan, Amrish K. Panwar

   MaqolaAdvanced Battery Technologies ResearchElectrical Engineering20240 iqtibos

   ABIABI:AkademIndex/2024.article.000969

7. Artificial Intelligence Approaches for SOH Estimation in Lithium‐Ion Batteries: A Comprehensive Review of Progress, Critical Evaluations, Challenges, and Toward Future Outlooks

   Deepak Kumar, Rashid Nasimov, Akshat Singh +3

   MaqolaOAOchiq kirishAdvanced Battery Technologies ResearchApplied Computational Intelligence and Soft Computing20250 iqtibos

   ABIABI:AkademIndex/2025.article.000845