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This paper addresses the critical need for improving fuel cell electric vehicles (FCEVs) reliability to promote their commercialization. A physics-based observer that combines an Extended Kalman Filter (EKF) with a Sequential Probability Ratio Test (SPRT) has been employed to address two major failure modes in FCEV stacks: flooding and reduction of Electrochemical Active Surface Area (ECSA). Furthermore, the observer estimates the hidden states of a standard automotive airpath system to enable state-feedback control. Therefore, the proposed observer is a novel approach which holistically tackles three coupled problems (i.e., flooding, ECSA loss, and airpath state estimation) which are typically addressed individually. Additionally, the observer is computationally affordable and relies solely on typical vehicle sensors. The observer performance has been validated through simulations, testing various dynamic scenarios in the presence of flooding, ECSA loss failures, and sensors uncertainty. The estimation errors have been confined within a 3% error band for all test cases while the health indicators coherently responded in the presence of faults. • Electrochemical Active Surface Area (ECSA) tracking via parameters estimation. • Single observer supports flooding and ECSA loss detection, and state-feedback control. • Mean value plant model implementation with faults simulation capability. • Flooding detection through Sequential Probability Ratio Test algorithm. [Display omitted] [ABSTRACT FROM AUTHOR]

The fuel cell airpath multivariable control problem of optimally coordinating the electric compressor motor and the back-pressure valve to achieve efficient and safe conditions, for both steady state and transient operation, has not been completely addressed in the literature. This paper proposes a nonlinear model predictive control strategy, implemented via the Garrett Motion proprietary NMPC toolbox, to regulate the oxygen stoichiometry and the cathode pressure of an automotive fuel cell airpath system, while avoiding compressor surge and air starvation. The controller set-points are optimized, using the nonlinear model, to achieve the maximum system power as a function of the operating stack condition. The effectiveness and robustness of the proposed control strategy have been validated by means of a simulated World harmonized Light-duty vehicles Test Cycle (WLTC), under both state feedback and model parameters uncertainties. [Display omitted] • MPC ensures compressor surge and oxygen starvation avoidance under severe dynamic scenarios. • Controller robustness assessed via a WLTC regulatory cycle under noisy and uncertain conditions. • Fuel efficiency is not significantly sensitive with respect to different controller calibrations. [ABSTRACT FROM AUTHOR]

• A new hybrid condition-/age-based maintenance policy is proposed for deteriorating units whose observed degradation paths are simultaneously affected by temporal variability, unit to unit variability, and measurement error. • The proposed maintenance policy uses in a combined manner a perfect and an imperfect measurement procedure. • The actual (hidden) degradation phenomenon process is described by using a gamma process with random effect. • The measurement error is modeled as a non-Gaussian random variable that depends in stochastic sense on the measured degradation level. • A comparative study with other maintenance policies is developed to demonstrate the utility of the proposed approach in terms of long-run average maintenance cost rate. In this paper, a hybrid condition-/age-based maintenance policy is proposed for deteriorating units whose observed degradation paths are affected by temporal variability, unit to unit variability, and measurement error. The hidden degradation process is described by using a gamma model with random effect. The measurement error is modeled as a non-Gaussian random variable. Units are assumed to fail when their degradation level exceeds a given threshold. The suggested maintenance policy consists in using the information obtained at a predetermined inspection time to decide whether to immediately replace the unit or to postpone its replacement to a successive predetermined time. The inspection involves measuring the degradation level of the unit. It is supposed that an imperfect procedure is firstly adopted, which provides a perturbed measurement of the true degradation level. However, it is also supposed that a more expensive perfect measurement procedure can be optionally used, depending on the result provided by the imperfect one. The proposed maintenance policy is applied to a real-world inspired case of a pipeline. The performances of the policy are measured in terms of the long-run average maintenance cost rate. Obtained results demonstrate the affordability and utility of the proposed approach. [ABSTRACT FROM AUTHOR]