Model Predictive Control for power management in hybrid fuel cell vehicles

Fuel Cell Hybrid Electric Vehicles (FCHEV) are being investigated in many research and development programs motivated by the urgent need for more fuel-efficient vehicles that produce fewer harmful emissions. Hybridization can greatly benefit fuel cell technology. There are many potential ad vantages such as the improvement of transient power demand, the ability of regenerative braking and the opportunities for optimization of the vehicle efficiency. The coordination among the various power sources requires a high level of control in the vehicle. This work presents a control system that fulfils the power demanded by the electric motor making use of two power sources: a primary source (fuel cell) and a battery pack. Both power sources, independently or together, supply power to the vehicle in order to satisfy driver's demand. The real-time control computes the power distribution between the primary energy source and its associated Energy Storage System (ESS) to optimize the global hydrogen consumption while maintaining drivability. The coordination between the various power sources requires a high level of control in the vehicle. Model Predictive Control (MPC) is used in order to minimize the overall energy use in the presence of several constraints that appear due to drivability requirements and the characteristic of the components. The proposed control strategy has been tested on a simulated model of a SUV (Sport Utility Vehicle), showing that a good control strategy can fulfil the power requested by the driver with the minimum fuel consumption.