Renewable Energy Global Innovations features: Insight into stall delay and computation of 3D sectional aerofoil characteristics of NREL phase VI wind turbine using inverse BEM and improvement in BEM analysis accounting for stall delay effect

Significance Statement

Various aerodynamic load computation approaches for undertaking the aeroelastic analysis of wind turbines has been developed. Blade Element Momentum, for instance, is applied frequently owing to its fast and simple nature. This method provides the loads along the blade span, torque and the amount of power generated by the turbine from the wind speed, aerofoil attributes and blade geometry. Wind turbine blades are designed with aerofoil cross sections; therefore, the Blade Element Method demands aerofoil characteristics as a function of the angle of attack in order to calculate the forces.

Real time flow over the turbine are in axial and radial directions. However, only axial flow is taken into consideration when using 2D aerofoil characteristics while radial flow is normally neglected. This creates high discrepancies of the computed aerofoil characteristics and forces of the CFD or Experiment analysis with the values calculated from the Blade Element Momentum code implementing the 2D aerofoil attributes. This unpleasant agreement is due to stall delay and is evident in most stall-regulated turbines.

Professor E.Y.K. Ng and his PhD student Ijaz Fazil at Nanyang Technological University in Singapore discussed the aerofoil characteristics as well as its various extrapolation methods for an array of angles of attack. They conducted Unsteady RANS (URANS) CFD analysis on two-bladed NREL Phase VI wind turbine and the measurements were compared with the experimental outcomes of the NREL/NASA test for confirmation. Their research work is now published in Energy.

The NREL phase VI rotor adopted for in their study was a two blade stall regulated wind turbine and the blades were tapered and twisted. The rotational speed was 72rpm for all wind speeds.. They conducted the URANS analysis for different inlet wind speeds by implementing the sliding mesh approach. The authors measured pressure at 18 radial locations including the five radial locations considered in experimental measurements.

There was a rise in the lift coefficient along the blade span when compared to the 2-dimensional aerofoil attributes for the same angle of attack owing to the span wise flow. This is the stall delay. This effect if effective at inboard sections and it reduces gradually towards the blades’ tips. Apparently, there is no clear explanation for stall delay but the authors believed that when stall occurred, separated flow on the suction side of the blade, appeared to rotate along with the blade, and experienced centrifugal force. The centrifugal force caused the separated flow to move in a radial manner towards the tip. This span wise flow also permitted Coriolis force to act towards the trailing edge, and therefore, resulted in stall delay.

The research team also discussed in their paper the reasons for the over prediction of the Blade Element Momentum analysis on using existing stall delay correction models. The Blade Element Momentum with or without the stall delay models couldn’t predict the correction distribution of aerofoil characteristics along the span of the blade in order to contemplate the impact of the stall delay.

The study proposed the use of the 3D aerofoil characteristics which is computed using Inverse BEM method in the Blade Element Momentum to take care of the stall delay. A good agreement with the aerofoil characteristics distribution along the span of the blade was realized in the current method.

The comparison of extracted CL (at 18 locations) from CFD analysis using inverse BEM and Distribution of CL along the blade span from BEM analysis on using existing stall delay models.

Comparison of extracted CL (at 18 locations) from CFD analysis using inverse BEM and distribution of CL along the blade span from proposed BEM analysis.

About The Author

Ijaz Fazil received his Bachelor of Engineering in Mechanical Engineering from Anna University, India in 2008. He has scored 93.94 percentile in GATE 2008. He received his Master of Science in Mechanical Engineering from National University of Singapore, Singapore in 2010. He commenced his Ph.D. study on Computational Fluid Dynamics (CFD) analysis of rotor and wake aerodynamics of wind turbine at Nanyang Technological University, Singapore, in August 2011. To date, he has presented 3 conference papers and has 1 journal publication. His research interests are –CFD, Wind Turbine Aerodynamics, Building Physics, Thermal Comfort and Fire Modelling. LinkedIn profile.

About The Author

EYK Ng obtained his Ph.D at Cambridge Univ. and a faculty in NTU. He is the Editor-in-Chief for the ISI Journal of Mechanics in Medicine and Biology for dissemination of original research in all fields of mechanics in medicine and biology since 2000;

He is the Founding Editor-in-Chief for the ISI indexed Journal of Medical Imaging and Health Informatics. His main area of research is human physiology, biomedical engg; computational fluid dynamics and numerical heat transfer. Ng has had more than 275 ISI journal articles and 100 conference papers and 13+1 books published including “Compressor Instability with Integral Methods” (2007); “Cardiac Pumping and Perfusion Engineering” (2007); “Imaging and Modelling of Human Eye” (2008); “Distributed Diagnosis and Home Healthcare, D2H2 v.1 and 3” (2009, 2012); “Performance Evaluation in Breast Imaging, Tumor Detection and Analysis” (2010); “Computational Analysis of Human eye with Applications” (2011); “Multimodality Breast Cancer Imaging” (2013); “Human eye imaging and modeling,” “Image Analysis and Modeling in Ophthalmology,” “Ophthalmology Imaging and Applications” (2013, 2014), “Bio-inspired Surfaces and Applications” (2016); “Computation and Mathematical Methods in Cardiovascular Physiology” by WSPC (2017, in-press) and “Application of Infrared to Biomedical Sciences” (2017). He is an invited keynotes speaker for more than 15 international scientific confs./workshops. 15 of his papers have been adopted as references in Singapore Standard (SS 582: 2013) and ISO/IEC 80601-2-59:2008.

He is also presently serving as panel member for the Biomedical Standards Committee, Singapore. The co-inventor of three USA patents on multiple analytical software classifier programs to identify the different stages of breast cancer development using thermal data with Cyrcadia Health, Inc. system, he further explores the use of IR in the field of ophthalmology for early detection of health abnormality.  Here is his publication list  and CV . 

Reference

Ijaz Fazil Syed Ahmed Kabir, E.Y.K. Ng. Insight into stall delay and computation of 3D sectional aerofoil characteristics of NREL phase VI wind turbine using inverse BEM and improvement in BEM analysis accounting for stall delay effect. Energy, volume 120 (2017), pages 518-536.

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Renewable Energy Global Innovations features: On-board capacity estimation of lithium iron phosphate batteries by means of half-cell curves

Significance Statement

Battery management systems face usually different challenging tasks. One of the most important concerns the on-board evaluation of the total battery capacity in electric and hybrid electric vehicles. This is due to the fact that the battery capacity has to be computed without necessarily discharging the battery entirely starting from a fully charged state. In fact, during the vehicle operations, the discharge process is mainly carried out in a dynamic condition under variable current rates and temperature. Selecting a method to be used in this process has poised a challenge mainly for lithium iron phosphate cells.

In a recent paper published in Journal of Power Sources, Andrea Marongiu and colleagues estimated lithium iron phosphate batteries capacity by means of half-cell curves. Their research mainly focused on developing a new approach that is based on the detection of the actual degradation mechanisms by collecting plateau information.

First, a model was developed and introduced which described the characteristics of the electrode voltage curves of the lithium iron phosphate cells and the impact of aging on the full cell voltage. A description of the main degradation mechanisms that can occur during the lifetime of the lithium iron phosphate cell and a model capable of describing the effects of degradation on the electrode and on the full cell voltage curves were presented. The research team then introduced a new battery management system structure with an implemented algorithm for on-board capacity estimation.

The results reported in the work show that not all the information from the voltage plateaus has to be collected at the same time although the collection phases have to be over short duration intervals. The new introduced algorithm is simple to parametrize, since only the characteristics of the cell in a fresh state are needed, in terms of stoichiometry and half-cell voltage curves. Eventually, both during charge and discharge the algorithm is able to correctly track the actual battery capacity with an error of approximately 1%. Also, the new proposed BMS structure is designed in a way that part of the novel methodology can run offline (not-real time). This means that the approach can be implemented in cheap microcontrollers, as it does not need to be executed in real time.

The method presented in this paper is valid for lithium iron phosphate /G cells, primarily due to the need of collecting data of plateaus, which is one of the main features of this type of cells. Nevertheless, the proposed model and the approach shown in the literature have a general formulation, which demonstrate the benefit of the tracked aging information for different lithium-ion technologies and additional application scopes.

About The Author

Andrea Marongiu received his master degree in Electrical Engineering from the Cagliari University, Italy, in 2010. In March 2011 he joined the Institute for Power Electronics and Electrical Drives (ISEA) at the RWTH Aachen University, Germany, as a research associate and PhD student.

His areas of interest were lithium-ion batteries with special focus on lithium iron phosphate-based cells, EV batteries and the related on board Battery Management System. From August 2016 to February 2017 he worked as Lead Engineer Battery Algorithm at National Electric Vehicle Sweden AB in Sweden. Since March 2017 he works as battery expert at IK4-CIDETEC in Spain, in the field of hybrid system for automotive applications.

About The Author

Dirk Uwe Sauer currently holds the title of professor for electrochemical energy conversion and storage systems at the Institute for Power Electronics and Electrical Drives (ISEA) & Institute for Power Generation and Storage Systems (PGS) at E.ON ERC RWTH Aachen University as well as Principle Investigator at Helmholtz Institute Münster Ionics in Energy Storage.

Originally, professor Sauer studied physics at University of Darmstadt, Germany, and upon graduating in 1994 became a scientist, project coordinator and head of group at Fraunhofer Institute for Solar Energy Systems ISE in Freiburg until 2003. While at the Fraunhofer Institute for Solar Energy Systems ISE, Professor Sauer headed the groups for storage systems, the interdisciplinary team for off-grid and remote power supply-systems, and was the managing director of the club for rural electrification. In 2003, he was appointed as junior professor at RWTH Aachen University, in 2009 he was appointed as professor, and in 2012 he was appointed as full professor for electrochemical energy conversion and storage systems at RWTH Aachen University. In 2010, he became a founding partner of P3 Energy & Storage, and in 2015 he became a founding partner of both BatterieIngenieure GmbH as well as eBusplan GmbH. Together with Prof. Martin Winter he is chairman of the conference “Kraftwerk Batterie / Advanced Battery Power”.

About The Author

Nsombo Nlandi has studied computer science at the RWTH Aachen University in Germany and received his master degree in 2009. In 2013 he got his second master degree in electrical engineering at the University of Hagen, Germany. From 2009 to 2016 he worked as researcher associate at the Institute for Power Electronics and Electrical Drives (ISEA), where he pursued his PhD. His research interests were mainly focused on software for battery diagnostic, namely the development of intelligent Battery Management Systems (BMS). Since August 2016 he has joined National Electric Vehicle Sweden AB (Sweden) as Lead Engineer for Embedded Systems.

About The Author

Yao RONG was born in Nanjing, China. He received his bachelor degree in Electrical Power Engineering and Automation from the Shanghai Jiao Tong University in 2007. Afterwards he studied at the RWTH Aachen University the master course of Electrical Power Engineering. During this period he wrote his master thesis at the Institute for Power Electronics and Electrical Drives (ISEA), working meanwhile a student assistant. He obtained his master degree in 2014. In 2015 he joined Jiangsu Marathon Investment Management Co., Ltd In China, where he works currently as chief research officer.

References

Andrea Marongiu^1,3, Nsombo Nlandi^1,3, Yao Rong^1,3, Dirk Uwe Sauer^1,2,3. On-board capacity estimation of lithium iron phosphate batteries by means of half-cell curves.  Journal of Power Sources volume 324 (2016) pages 158-169.

Show Affiliations

1. Electrochemical Energy Conversion and Storage Systems Group, Institute for Power Electronics and Electrical Drives (ISEA), RWTH Aachen University, Jägerstrasse 17/19, D-52066 Aachen, Germany
2. Institute for Power Generation and Storage Systems (PGS), E.ON ERC, RWTH Aachen University, Mathieustrasse, D-52074 Aachen, Germany
3. Jülich Aachen Research Alliance, JARA-Energy, Germany

 

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