In the mobility industry, the fuel cell technology combined with batteries allows to overcome some of the main pain points of battery electric vehicles (BEVs), namely the high recharging time and the high battery mass for applications requiring high amount of energy to fulfill their missions (e.g., bus and heavy-duty vehicles).
A fuel cell electric vehicle (FCEV) powertrain relies on a fuel cell system mainly to fulfill the stationary power demand and on a battery to provide power with higher dynamics and to recover braking energy. The entire powertrain requires an advanced control system to define the power split between fuel cell and batteries, while fulfilling all component and system level constraints.
The purpose of this paper is to present a Model Predictive Controller (MPC) for the optimal operations of a fuel cell / battery hybrid powertrain applied to a city bus. The proposed real-time MPC strategy has been designed to optimize the trade-off among hydrogen consumption, battery state of charge (SOC) dynamics, fuel cells and battery power smoothness, while guaranteeing the fulfilment of all the required constraints.
A high-fidelity simulation plant, modelled in GT-SUITE, has been used to verify the effectiveness of the proposed strategy. A comparison analysis with a rule-based strategy is also provided. Simulation results confirms that the proposed MPC strategy can guarantee a smooth use of the fuel cell module, while satisfying the power needs of the propulsion system. The control system is also able to obtain better energy recovery performance during braking phases, while allowing self-sustainability of the battery SOC. The next steps will include the deployment and validation on a real powertrain in a test bench located in Turin (Italy).