Abstract

Proton exchange membrane (PEM) fuel cells represent a promising solution for a sustainable hydrogen-based mobility. Due to remaining challenges regarding costs and durability of PEM fuel cell systems, market activation programs as a precursor to market introduction are still required to accelerate the broad commercialization of PEM fuel cell systems in transportation applications. The recent shift by some original equipment manufacturers (OEMs) from passenger car (PC) and light-duty vehicle (LDV) applications to heavy-duty vehicle (HDV) applications is accompanied by higher lifetime and system power requirements that necessitate modified design and development approaches. Design-based approaches to increase the lifetime of PEM fuel cells usually concentrate on the use of advanced materials and the design of durable fuel cell stacks. Operation-based approaches aim to mitigate degradation through the development of advanced control strategies. However, the initial design of a PEM fuel cell system as well as the calibration of its control strategy to achieve a long service life is inevitably associated with a high degree of uncertainty. In addition, often challenging time-to-market specifications result in insufficient time for extensive durability testing, necessitating the use of accelerated stress tests (AST). Results of ASTs usually deviate to a greater or lesser extent from realistic driving conditions and exacerbate the issue of uncertainty regarding durability in field operation. Therefore, the coordinated development and deployment of on-board strategies for condition assessment, lifetime prediction and degradation mitigation are of huge importance to meet the high lifetime requirements in HDV applications.With this in mind, this paper presents an on-board Prescriptive Lifetime Management system that enables optimization-based post-prognostic decision-making to extend the service life of PEM fuel cell systems while considering the need to maximize system performance and efficiency. Based on the current state of the art, the requirements of the Prescriptive Lifetime Management are defined and its conceptual design as well as modeling and simulation framework are described.

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