KEYWORDS: Optimized power management strategies, Fuel-cell electric vehicle, Multi-criteria function, Hydrogen consumption, Aging. ABSTRACT: Hybrid fuel cell powertrain system is a promising approach to comply with the needs of a large range of applications – from light commercial vehicles to heavy duty trucks, even trains. A multi fuel cell stack configuration, in combination with a battery, opens the way to an optimization of the system energy management. Thanks to an adapted power split between the fuel cell system and the battery, a suitable control would reduce powertrain aging (fuel cell and battery). This is one of the goals of the ECH2 collaborative project, targeting an increase in system reliability and performance over time, and a reduced total cost of ownership of Fuel Cell Electric Vehicles (FCEV). In this paper we propose a methodology to study the impact of optimal control on the consumption and aging of a Fuel Cell Electrical Vehicle (FCEV) architecture. The optimal control problem is formulated with a combined cost function of consumption, battery aging and fuel cell aging criteria. The solution of this problem is applied on a simplified model of electrical parts coupled with the degradation models respectively of battery capacity and fuel cell voltage that are defined as aging indicators. We also describe the elements of a more detailed multi-physics model that will be used in the validation phases of the control strategy. We made a sensitivity study of the multi-criteria function by adding weighting parameters where we show that reducing fuel cell voltage losses is proportional to minimizing consumption but opposite to reducing battery capacity losses, we also show that the dependency between these three criteria vary along the components' lifetime. These studies allowed to find the link between the selection of the weighting parameters in a multi-criteria cost function and the consumption/aging rates. An application of a generic backward dynamic programming algorithm on a heavy-duty truck is proposed to illustrate the methodology.
Mr. Chouaib Afri, Advanced Control Systems Engineer, Vitesco Technologies