Optimized power management based on adaptive-PMP algorithm for a stationary PEM fuel cell/battery hybrid system

This research develops an efficient and robust polymer electrolyte membrane (PEM) fuel cell/battery hybrid operating system. The entire system possesses its own rapid dynamic response benefited from hybrid connection and power split characteristics due to DC/DC buck-boost converter. An indispensable energy management system (EMS) plays a significant role in achieving optimal fuel economy and in a promising running stability. EMS as an indispensable part plays a significant role in achieving optimal fuel economy and promising operation stability. This study aims to develop an adaptive supervisory EMS that comprises computer-aided engineering tools to monitor, control, and optimize the performance of the hybrid power system. A stationary fuel cell/battery hybrid operating system is optimized using adaptive-Pontryagin's minimum principle (A-PMP). The proposed algorithm depends on the adaptation of the control parameter (i.e., fuel cell output power) from the state of charge (SOC) and load power feedback. The integrated model simulated in a Matlab/Simulink environment includes the fuel cell, battery, DC/DC converter, and power requirements models by analyzing the three different load profiles. Real-time experiments are performed to verify the effectiveness of EMS after analyzing the simulated operating principle and control scheme.