Max Robotics — Global Service Robot Directory + US Certification

About

Daniel Hissel is a leading figure in the field of prognostics and health management (PHM), with a particular focus on fuel cell systems and energy conversion technologies. His most influential work, the highly cited 2015 review "Particle filter-based prognostics: Review, discussion and perspectives" (335 citations), has become a cornerstone reference for researchers developing advanced remaining useful life prediction methods. Hissel's major contributions lie in bridging the gap between theoretical estimation algorithms and practical industrial applications, especially for proton exchange membrane fuel cells (PEMFC). He has pioneered the use of particle filters to model degradation in complex electrochemical systems, enabling more accurate and robust predictions of system failure. Beyond prognostics, his research spans multi-physics modeling, fault diagnosis, and control strategies for hybrid energy systems. Hissel's work has had a profound impact on improving the reliability and lifespan of fuel cell technologies, with his citation record reflecting his role as a key architect in the PHM community. His contributions are essential reading for anyone working on condition-based maintenance or durability in energy systems.