Robust fuzzy model predictive control for energy management systems in fuel cell vehicles. (May 2020)

• Record Type: Journal Article
• Authors: Shen, Di; Lim, Cheng-Chew; Shi, Peng
• Is Part Of: Control engineering practice. Volume 98(2020)
• Publication Date: 2020-05
• Subjects: Energy management -- Hybrid vehicle -- Fuzzy control -- Model predictive control -- Fuel cell -- Electric vehicle; Automatic control -- Periodicals; 629.89
• DOI: 10.1016/j.conengprac.2020.104364
• Languages: English
• ISSNs: 0967-0661

Abstract

Abstract: Fuel cell vehicle combines the benefits of fuel cell stack and energy storage system to achieve fuel economy and zero-emission. The energy management system is vital to the hybrid vehicle systems since it regulates power flow from the fuel cell stack and energy storage system. In this paper, we design an energy management scheme in fuel cell vehicle systems. By using optimal control principle, we aim to reduce hydrogen consumption while maintaining battery state of charge under practical operating constraints and uncertain future power demand. The Fuzzy modelling approach is employed to describe the nonlinear power plant and a robust model predictive based control is designed to achieve the desired system performance. Moreover, traffic condition is incorporated into the energy management controller design to further improve the system performance. The effectiveness and advantages of the proposed control scheme are illustrated by a simulator developed based on real-world experimental data.