Fuzzy logic simulator for energy management algorithms testing

2014 ◽  
Author(s):  
L. Ciabattoni ◽  
M. Grisostomi ◽  
G. Ippoliti ◽  
S. Longhi ◽  
A. Bonci
Keyword(s):  
Fuzzy Logic ◽  
Energy Management ◽  
Management Algorithms

scholarly journals Experts versus Algorithms? Optimized Fuzzy Logic Energy Management of Autonomous PV Hybrid Systems with Battery and H2 Storage

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1777
Author(s):  
Lisa Gerlach ◽  
Thilo Bocklisch
Keyword(s):  
Fuzzy Logic ◽  
Energy Management ◽  
Fuzzy Logic Controller ◽  
Expert Knowledge ◽  
Large Power ◽  
Hybrid Energy ◽  
Knowledge Based ◽  
Long Term Storage ◽  
Fuzzy Logic Approach

Off-grid applications based on intermittent solar power benefit greatly from hybrid energy storage systems consisting of a battery short-term and a hydrogen long-term storage path. An intelligent energy management is required to balance short-, intermediate- and long-term fluctuations in electricity demand and supply, while maximizing system efficiency and minimizing component stress. An energy management was developed that combines the benefits of an expert-knowledge based fuzzy logic approach with a metaheuristic particle swarm optimization. Unlike in most existing work, interpretability of the optimized fuzzy logic controller is maintained, allowing the expert to evaluate and adjust it if deemed necessary. The energy management was tested with 65 1-year household load datasets. It was shown that the expert tuned controller is more robust to changes in load pattern then the optimized controller. However, simple readjustments restore robustness, while largely retaining the benefits achieved through optimization. Nevertheless, it was demonstrated that there is no one-size-fits-all tuning. Especially, large power peaks on the demand-side require overly conservative tunings. This is not desirable in situations where such peaks can be avoided through other means.

An idea for students project work: Energy management in hybridization of energy sources for transportation application

2018 ◽  
Vol 57 (3) ◽  
pp. 253-271 ◽  
Author(s):  
A Geetha ◽  
C Subramani
Keyword(s):  
Fuzzy Logic ◽  
Energy Storage ◽  
Electric Vehicle ◽  
Energy Management ◽  
Storage Systems ◽  
Project Work ◽  
Specific Power ◽  
Energy Sources ◽  
Energy Storage Systems ◽  
Time Problem

The study of electric vehicle and its energy sources are being incorporated in undergraduate and postgraduate syllabuses. This article discusses the basic concepts and design of energy storage systems for electricity based transpiration application. The content of this work elaborates the importance of energy storage systems in electric vehicle and hybridization of energy storage systems i.e. battery and ultracapacitor, which seems to be a promising topic among the final-year project students as well as an emerging research topic among the research scholars worldwide. Hence, this article is prepared in order to trigger those students’ knowledge in multisourced electric vehicle in depth. This study highly focuses on fuzzy logic-based energy sources power split strategy for a multisourced electric vehicle to enhance a better sharing of energy across the multisources with distinct characteristics like high specific power (ultracapacitor) and high specific energy (battery). In general, fuzzy logic controller best suits for a complicated real-time problem. Further it does not require a priori knowledge of a vehicle driving pattern over a time. Hence, the proposed control strategy can provide a satisfactory improvement in vehicle efficiency, assured reduction in stress factor, and energy consumption rate and reduced ultracapacitor sources state of charge difference in all different hybridization topologies. Thus, this paper can help students working on energy management problems of hybridization of energy sources.

scholarly journals Energy Management of Parallel-Connected Cells in Electric Vehicles Based on Fuzzy Logic Control

Energies ◽  
2017 ◽  
Vol 10 (3) ◽  
pp. 404 ◽  
Author(s):  
Chuanxue Song ◽  
Yulong Shao ◽  
Shixin Song ◽  
Cheng Chang ◽  
Fang Zhou ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Energy Management ◽  
Electric Vehicles ◽  
Fuzzy Logic Control ◽  
Logic Control
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