This paper introduces a model predictive control (MPC) strategy for solid oxide fuel cell (SOFC) systems, introducing thermal stress-aware power modulation. The proposed MPC approach incorporates a temperature rate-of-change constraint to manage local temporal and spatial temperature gradients in the SOFC during transient power modulation. The study evaluates the sensitivity and effectiveness of the temperature rate-of-change constraint under four different constraint parameter sets, spanning a range from fast to slow power modulation. A one-dimensional spatially discretised SOFC model is employed in the simulations to assess the resulting local temperature gradients. The results of this paper indicate that the proposed MPC strategy enhances transient power tracking performance compared to the conventional approach of using an electrical current rate-of-change constraint with 1%–17%, without a significant increase in the local temporal and spatial temperature gradients in the SOFC.

This paper presents a novel scheduling approach for inland waterway transport (IWT) vessels that must pass through multi-chamber locks. A switching max-plus linear (SMPL) model is built to determine, for each vessel, the most appropriate route, the arrival times at relevant waypoints as well as at the destination, the relative order in which it moves through the network with respect to other vessels, its assignment to certain lock chambers together with other vessels, and its position inside each chamber. The SMPL constraints are translated to mixed integer linear programming (MILP) constraints for the optimization problem to be solvable, and objectives minimizing arrival times or arrival time offsets are defined. The proposed approach is tested on a multi-lock waterway, and its performance is compared to the current state of practice using relevant key performance indicators (KPIs), which allows to demonstrate the superior performance of the proposed approach.

This paper considers the presence of movable bridges in inland waterway transport, and presents a control framework for the joint dynamic coordination of bridge operations and autonomous vessel navigation to minimize waiting times of vessels at bridges. Simultaneous evolution of bridge occupancy and vessel position is captured by a control-oriented model that incorporates qualitative behavior in the form of propositional logic expressions. A model predictive control (MPC) strategy is designed considering adaptable bridge opening regimes to exploit vessel passage demand, and operational preferences of both vessel skippers and bridge operators are taken into account to reach fair trade-off decisions. A realistic case study pertaining to the Rhine-Alpine corridor is used to demonstrate the effectiveness of the approach. Appropriate key performance indicators (KPIs) are defined and employed for a quantitative comparison with a mixed-integer programming (MIP) strategy with fixed opening regimes. Furthermore, sensitivity to the main MPC parameters is examined by carrying out extensive testing to assess the effect of each design parameter on the solution.