Hicham Megnafi

INESC TEC, University of Abou Bekr Belkaïd

Papers

Total Citations

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About

Hicham Megnafi is a researcher specializing in battery management systems, energy optimization, and mobile robotics, with a particular focus on developing intelligent algorithms for accurate battery state estimation. His work addresses a critical challenge in autonomous robotics: ensuring reliable and efficient energy management for mobile platforms that depend entirely on onboard battery power. Megnafi's most notable contributions center on the application of advanced filtering techniques to battery monitoring. His pioneering work on Battery Management Systems (BMS) using Extended Kalman Filter (EKF) approaches has provided more accurate and computationally feasible methods for estimating battery State of Charge (SOC) in mobile robots, moving beyond conventional techniques such as Open Circuit Voltage and Coulomb Counting. His development of the Dual Coulomb Counting Extended Kalman Filter (DCC-EKF) represents a particularly innovative hybrid methodology, combining classical counting approaches with probabilistic estimation to enhance precision in real-world conditions. With a combined citation count of 22 across his key publications, all produced in 2021, Megnafi has quickly established relevance within the robotics and energy management communities. His embedded systems perspective makes his research especially practical, offering implementable solutions for engineers designing next-generation autonomous mobile robots.