Enhanced Kalman Filter-Based Identification of a Fuel Cell Circuit Model in Impedance Spectroscopy Tests

Flammia, Danilo; Guarino, Alessio; Petrone, G.; Zamboni, Walter

doi:10.1007/978-3-030-56970-9_10

Cited by 1 publication

(2 citation statements)

References 8 publications

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“…The fuel cell stacks are physically connected in parallel, but are in series from the reliability point of view, that is the system is considered as failed as soon as one stack is failed; The fuel cell stacks in the network system are identical, and the output power density of each stack ranges from the minimal output power density L min to the maximum output power density L max ; The values of the fuel cell overall resistances are considered to be measurable whenever necessary, in the sense that a monitoring system and algorithm (e.g. a Kalman filter 26,39 ) are assumed to be available to deliver the estimated values of the resistances.…”

Section: Post-prognostics Decision-makingmentioning

confidence: 99%

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Post-prognostics decision-making strategy for load allocation on a stochastically deteriorating multi-stack fuel cell system

Zuo

Cadet

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part O:

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This work proposes a load allocation decision strategy based on deterioration prognostics information for multi-stack fuel cell systems. The fuel cell deterioration is characterized by the overall resistance value, as it carries the key aging information of a fuel cell. The fuel cell deterioration dynamics is then modeled as an increasing stochastic process whose trend is a function of the fuel cell output power. Combining system deterioration and fuel cell consumption, a multi-objective optimization (MOO) based decision-making strategy is proposed to manage the operation of a multi-stack fuel cell system. Based on this algorithm, the optimal operating power load is computed for each stack. Finally, the performance of the proposed approach is compared to the case without post-prognostics decision for a three-stack fuel cell system. The simulation results show that the proposed post-prognostics decision-making strategy can manage fuel cell system operating in real time by scheduling the optimal load allocation among stacks.

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Section: Post-prognostics Decision-makingmentioning

confidence: 99%

“…The values of the fuel cell overall resistances are considered to be measurable whenever necessary, in the sense that a monitoring system and algorithm (e.g. a Kalman filter 26,39 ) are assumed to be available to deliver the estimated values of the resistances.…”

Section: Post-prognostics Decision-makingmentioning

confidence: 99%

Post-prognostics decision-making strategy for load allocation on a stochastically deteriorating multi-stack fuel cell system

Zuo

Cadet

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part O:

View full text Add to dashboard Cite

show abstract

Enhanced Kalman Filter-Based Identification of a Fuel Cell Circuit Model in Impedance Spectroscopy Tests

Cited by 1 publication

References 8 publications

Post-prognostics decision-making strategy for load allocation on a stochastically deteriorating multi-stack fuel cell system

Post-prognostics decision-making strategy for load allocation on a stochastically deteriorating multi-stack fuel cell system

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