A comparative study of power allocation strategies used in fuel cell and ultracapacitor hybrid systems. (15th December 2019)

• Record Type: Journal Article
• Authors: Wang, Yujie; Sun, Zhendong; Li, Xiyun; Yang, Xiaoyu; Chen, Zonghai
• Is Part Of: Energy. Volume 189(2019)
• Publication Date: 2019-12-15
• Subjects: Power allocation strategy -- System modeling -- Dynamic programming -- Rule-based strategy; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2019.116142
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: The proton exchange membrane fuel cell is a good candidate for the future green transportation. In the vehicle applications, the fuel cell systems are always grouped with other energy storage devices such as the lithium-ion batteries and ultracapacitors in order to enhance their dynamic performance. The energy management strategy, especially the power allocation strategy plays an important role in the energy management system of the vehicles. This paper presents a comparative study of the power allocation strategies used in different hybrid structures. First, a framework of the fuel cell and ultracapacitors hybrid system is established considering the models of the ultracapacitor, fuel cells, and vehicle dynamics. Then the suboptimal on-line power allocation strategies based on classical cybernetics and rules are presented. The off-line dynamic program algorithm is employed as an optimal solution in order to compare with the proposed suboptimal on-line power allocation strategies. After that, simulations are put forward to compare the performance of the presented power allocation strategies. Finally, experimental studies are conducted to compare the fuel economy and the dynamic property of different hybrid structures using a semi-physical experimental platform. Compared with the fuel cell and batteries hybrid structure, the fuel economy of the fuel cell and ultracapacitors hybrid structure has improved by 21.03%–26.70% under the PID-based power allocation strategy, and improved by 21.86%–30.48% under the rule-based power allocation strategy. The results indicate that the proposed rule-based strategy can achieve a near optimal performance compared with the dynamic programming algorithm and is easily applied online. Highlights: The framework of a fuel cell and ultracapacitors hybrid system is established. The PID and rule-based power allocation strategies are proposed. The dynamic programming algorithm is presented as an optimal solution. Simulations and experimental studies are compared under different road maps. The fuel economy and performance are compared with different hybrid structures.