Energy management and optimization of PEMFC/battery mobile robot based on hybrid rule strategy and AMPSO

Xueqin Lü,, Yinbo Wu, Jie Lian and Yangyang Zhang

Renewable Energy, 2021, vol. 171, issue C, 881-901

Abstract: Due to the flexibility of seam tracking robot in special environment, independent power supply with different characteristics is adopted. Power allocation of hybrid power system composed of proton exchange membrane fuel cell and lithium battery is mainly researched. According to the requirements of economy and safety, hybrid rule fuzzy state machine control is designed to realize the optimal operation and fast response of power supply system. On the basis of energy allocation, further reduction of hydrogen consumption and power fluctuation is considered, which improves the power supply scheme. The sensitivity analysis method is used to screen the optimization variables, which reduces the complexity of the strategy; in addition, an adaptive mutation particle swarm optimization is studied to optimize the strategy, which combines the mutation idea, adaptively changes the weight and learning factor, and realizes the minimization of power fluctuation and equivalent hydrogen consumption. The results show that the stability of fuel cell and the rationality of lithium battery charging and discharging are greatly improved, and the fuel economy and service life of hybrid power system are improved.

Keywords: PEMFC/LIB hybrid power system; Energy management; Hybrid rule fuzzy state machine; Adaptive mutation particle swarm optimization; Power fluctuation; Energy consumption minimization (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148121003141
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:171:y:2021:i:c:p:881-901

DOI: 10.1016/j.renene.2021.02.135

Access Statistics for this article

Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides

More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().