Ashraf Shanaq
Ph.D. Candidate · Electrical & Computer Engineering
Oakland University
Ashraf Shanaq is a Ph.D. candidate in Electrical and Computer Engineering at Oakland University. His doctoral research focuses on reliable hybrid nonlinear dual-time-constant modeling of lithium iron phosphate (LiFePO₄) batteries, with particular emphasis on parameter identification, state-of-charge estimation, hysteresis characterization, and measurement uncertainty management. His research combines dynamic system modeling, optimization, signal processing, and computational techniques to improve battery model accuracy and reliability. His broader research interests include intelligent control systems, embedded systems, artificial intelligence, autonomous vehicles, and advanced battery management systems.
Research & Publications
One verified publication is listed below; this is not a complete bibliography.
Enhance Parameter Identification Accuracy for State-of-Charge Optimization in Lithium-Ion Batteries
Plain-language summary: This study combines battery modeling, hybrid optimization and adaptive parameter identification to improve estimates of how much charge remains in lithium-ion batteries. The authors report lower estimation errors than the comparison methods under the conditions studied.
Summary based on the publisher’s abstract; not a full-paper review.
View Publication ↗Start here · New researcher guide
Suggested first step: Read the model and parameter-identification method, then identify the datasets, baseline methods and error measures needed to reproduce one comparison. Check newer literature before proposing an extension.
Future work named in the abstract: Computational optimization, scalability and applicability across different battery chemistries.
ICCC reading suggestion based on the abstract; feasibility and reproducibility have not been verified.