Rizwan, M.

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

Kumar, D., Rizwan, M., & Panwar, A. K. (2023) · Energy Sources, Part A: Recovery, Utilization, and Environmental Effects

Battery Modeling and ManagementAdvancements in Battery Materials

Cited by 23

Towards Green AI: A Novel Hybrid Filter Based AI Approach for Energy Efficient State of Charge and Energy Estimation in Li-Ion Batteries Under Various Drive Cycles

Kumar, D., Rizwan, M., & Panwar, A. K. (2025) · IEEE Transactions on Industry Applications

Battery Modeling and ManagementElectric and Hybrid Vehicle Technologies

Cited by 11

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

Kumar, D., Rizwan, M., & Panwar, A. K. (2023) · 2023 IEEE International Conference on Power Electronics, Smart Grid, and Renewable Energy (PESGRE)

Battery Modeling and ManagementAdvancements in Battery Materials

Cited by 9

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

Kumar, D., Nasimov, R., Singh, A., Jha, A., Jha, A., & Rizwan, M. (2025) · Applied Computational Intelligence and Soft Computing

Battery Modeling and ManagementAdvancements in Battery Materials

Cited by 8

Towards Green AI: Energy-Efficient State of Health Estimation and Degradation Analysis of Commercial Lithium-Ion Batteries Based on Deep Learning and Filter Technique Approach

Kumar, D., Ahmed, M., Jamil, M., Rizwan, M., & Panwar, A. K. (2026) · IEEE Transactions on Industry Applications

Battery Modeling and ManagementAdvancements in Battery Materials

Cited by 3