This paper addresses the design of an energy management strategy (EMS) for a multi-stack fuel cell system (MFCS). In this regard, firstly, two power allocation strategies, namely Daisy Chain and Equal Distribution have been developed and compared in characteristics terms. Subsequently, a novel adaptive strategy is proposed to split the power between the fuel cells and the battery by utilizing the demanded power, state of charge (SOC) of the battery, maximum power and efficiency point of each fuel cell. In a MFCS, each fuel cell shows variable performances in different operating conditions depending on its specific ageing, material, and external factors. The purpose of this study is to ensure an equal level of degradation for each fuel cell and to make them operate in an efficient zone, with the assistance of an online identification method as well as an adaptive power strategy. Simulations have been conducted in Matlab-Simulink environment. In this work, a mechanistic fuel cell model is employed to imitate the behaviour of a real MFCS and a semi-empirical model, coupled with an adaptive recursive least square (ARLS) to predict the maximum power (MP) and maximum efficiency (ME). The results of the proposed strategy show noticeable improvements in the fuel economy.

Energy management strategy, Model identification, Multi-stack, PEM fuel cell
19th IEEE International Conference on Industrial Technology, ICIT 2018
Department of Electronics

Macias, A. (Alvaro), Kandidayeni, M. (Mohsen), Boulon, L. (Loic), & Chaoui, H. (2018). A novel online energy management strategy for multi fuel cell systems. In Proceedings of the IEEE International Conference on Industrial Technology (pp. 2043–2048). doi:10.1109/ICIT.2018.8352503