Ghofrane Benarfa

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About

Ghofrane Benarfa is a researcher at the forefront of intelligent energy management and autonomous mobile robotics, with a particular focus on fuel cell and battery-powered systems. Her work addresses critical challenges in industrial automation, specifically the operational efficiency and energy sustainability of autonomous forklifts and mobile robots. Benarfa’s major contributions include the development of an online health-aware energy management strategy for fuel cell hybrid robots, which optimizes performance under startup–shutdown conditions—a key innovation for extending system lifespan and reliability. This work has garnered significant attention, accumulating 7 citations since its 2024 publication. Additionally, she has pioneered the use of machine learning to predict charging queue waiting times for electric autonomous forklifts, a solution that tackles the persistent issues of short battery autonomy and prolonged charging periods. Her 2022 paper on this topic, with 3 citations, demonstrates her early impact in applying predictive analytics to industrial logistics. Benarfa’s research is notable for bridging real-time energy optimization with data-driven operational planning, offering practical advancements for autonomous systems in warehouses and factories. Her work is essential reading for students and researchers interested in the intersection of energy management, machine learning, and robotics.