Real-time optimization strategy for fuel cell hybrid power sources with load- following control of the fuel or air flow

摘要

This paper analyses two Real-Time Optimization (RTO) strategies for Proton Exchange Membrane Fuel Cell (PEMFC) system which is used as main energy source for Fuel Cell Hybrid Power Source (FCHPS) of the FC vehicle (FCV). In this study the optimization function was defined as mix of the FC net power and the Fuel Consumption Efficiency by using two weighting coefficients. The Global Extremum Seeking (GES) algorithm is proposed here as RTO method for multimodal optimization surfaces having many peaks on the plateau around the optimal point that is the Global Maximum Point (GMP). One of the fueling rates is Load-Following (LF) controlled in order to adapt the FC net power to load demand and assure the charge-sustaining mode for the battery. The GES algorithm will establish the optimal duty cycle for the Boost converter, so the proposed strategies will be called the Boost-GES-RTO strategies with Air-LF and Fuel-LF, respectively. The Static Feed Forward (sFF) control strategy will be used as reference for constant and variable load profile. The gaps in performance indicators were estimated for both Boost-GES-RTO strategies. For example, the gaps in FC system efficiency and fuel economy could be up to 1.61% and 1421pm, and 2.65 and 1141pm for the Boost-GES-RTO strategies with Air-LF and Fuel-LF. The performance of Boost-GES-RTO strategies was also shown by estimating the fuel economy for 6 kW FCHPS under variable load profile.