Control Engineer, Wabtec Corporation, United States
Kiran Bhaskar is a dynamic researcher and engineer with a focus on energy storage and battery health monitoring systems. Currently a Controls Engineer at Wabtec Corporation in Erie, Pennsylvania, he is developing advanced State of Charge (SoC) and State of Health (SoH) estimation techniques for locomotive battery packs. He completed his Ph.D. in Mechanical Engineering from The Pennsylvania State University with a remarkable GPA of 3.98/4, where he also earned his MS in the same field. Kiran holds a B.Tech (Hons) in Mechanical Engineering from the Indian Institute of Technology (IIT) Madras and an M.Tech in Thermal Engineering. He has a strong background in battery modeling, fault diagnosis, and anomaly detection. Throughout his career, Kiran has applied his expertise in various industries, including energy systems, automotive, and logistics. He has won multiple awards for his research and is a leading expert in the field of battery health management. 🔋⚙️
Profile
Education
Kiran Bhaskar is currently pursuing his Ph.D. and MS in Mechanical Engineering at The Pennsylvania State University (2019-2024), maintaining an impressive GPA of 3.98/4. Before this, he earned a B.Tech (Hons) in Mechanical Engineering with a Minor in Operations Research from the prestigious Indian Institute of Technology (IIT) Madras (2013-2018). At IIT Madras, Kiran also completed an M.Tech in Thermal Engineering with a GPA of 8.7/10. He further broadened his academic experience during a semester abroad at the Czech Technical University in Prague (2017), achieving a GPA of 9.56/10. Kiran’s academic journey has been distinguished by excellence in research and practical application, particularly in the areas of battery systems, thermal engineering, and energy management. He has demonstrated remarkable skills in both theoretical modeling and experimental validation across a range of advanced engineering topics. 🎓📚
Awards and Honors
Kiran Bhaskar has received numerous prestigious accolades throughout his academic and professional career. Most notably, he was awarded the Thomas and June Beaver Award (2024) for outstanding industrially-sponsored research at The Pennsylvania State University. He was recognized as an ASME Dynamic Systems and Control Division Rising Star at the 2023 Modeling, Estimation, and Control Conference. He has also been a finalist for multiple Energy Systems Best Paper Awards at the 2024 Modeling, Estimation, and Control Conference and the American Control Conference. Kiran’s poster presentations have earned him first runner-up honors at IndustryXchange 2022 and 2023 in the “Digital Connectivity” and “Technologies for the Built Environment” sessions. His academic performance was acknowledged with the Prime Minister’s Scholarship and securing a 99.86 percentile rank in the IIT-JEE Advanced Entrance Examination. His contributions to battery health and anomaly detection continue to be recognized in both industry and academia. 🏆📜
Research Focus
Kiran Bhaskar’s research focuses primarily on advanced energy systems, specifically lithium-ion battery health management, fault diagnosis, and optimization. His doctoral work has contributed significantly to the modeling of battery performance degradation, particularly the aging and heterogeneity-induced capacity loss in parallel-connected cells. Kiran has developed innovative techniques for detecting anomalies, including using Principal Component Analysis (PCA) for fault detection and sensor signal reconstruction. His work also includes the development of state estimation methods for monitoring battery State of Charge (SoC), State of Health (SoH), and energy management in large battery packs. In addition, Kiran has made strides in post-damage short circuit detection and the development of model-based internal short circuit detection algorithms. His research bridges theoretical concepts with practical applications, enhancing energy efficiency and safety in battery-powered systems, including locomotives and electric vehicles. He continues to push the boundaries of control systems and battery diagnostics. 🔋🔧💡
Publications
- Data-driven thermal anomaly detection in large battery packs – K. Bhaskar et al. (2023) 🛠️📊
- State of Charge and State of Health estimation in large lithium-ion battery packs – K. Bhaskar et al. (2023) 🔋💡
- Detecting synthetic anomalies using median-based residuals in lithium-ion cell groups – K. Bhaskar et al. (2022) 📉⚠️
- Detection of engine knock using speed oscillations in a single-cylinder spark-ignition engine – K. Bhaskar et al. (2019) 🔧🚗
- Heterogeneity-induced power and capacity loss in parallel-connected cells – K. Bhaskar et al. (2024) ⚡🔋
- Short Circuit Estimation in Lithium-Ion Batteries Using Moving Horizon Estimation – J. Moon, K. Bhaskar et al. (2024) ⚡🔍
- Post-Damage Short Circuit Detection in Lithium-ion Batteries – K. Bhaskar et al. (2024) ⚡🔎
- Faulty sensor signal reconstruction in Li-ion battery packs – K. Bhaskar et al. (2024) 🛠️💻
- Anomaly diagnosis and health monitoring of lithium-ion battery packs – K. Bhaskar (2024) 🧐