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Modeling and Analysis of a fuzzy Type MPPT algorithm 20

Modeling and Analysis of a Fuzzy Type MPPT Algorithm

19th International Conference on Electrical Drives and Power Electronics (EDPE) / 9th Joint Slovakian-Croatian Conference

作者： Corcau, Jenica Ileana Dinca, Liviu Univ Craiova Dept Elect Energet & Aerosp Engn Craiova Romania

ISBN: (纸本)9781728103891

This paper presents a study on a MPPT (maximum power point tracker) which uses fuzzy control algorithm. Many algorithms were developed in the past few years to control the power obtained from a solar panel and optimize the panel performances in a large domain of functioning parameters. fuzzy logic algorithms have the advantage they do not need a mathematical model for the solar panel in order to implement the controller. A fuzzy controller for a solar panel is obtained, implemented in MATLAB/SIMPOWERSYS and its functioning is studied by numerical simulations. Good results were obtained, power consumed by the load being very close to maximum power solar panel can achieve. That means this type of MPPT keeps the solar panel very close to the optimum functioning point.

关键词： MPPT solar panel fuzzy logic algorithm mathematical model

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M5P model tree based fast fuzzy maximum power point tracker

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SOLAR ENERGY 2018年 163卷 405-424页

作者： Blaifi, Sid-ali Moulahoum, Samir Benkercha, Rabah Taghezouit, Bilal Saim, Abdelhakim Univ Medea Res Lab Elect Engn & Automat LREA Medea Algeria CDER Ctr Dev Energies Renouvelables Algiers Algeria Univ Sci & Technol Houari Boumediene Fac Elect & Comp Sci Algiers Algeria

In spite of the many research contributions that have been introduced in the recent literature, maximum power point trackers (MPPT) still carry important issues related to convergence speed, computation load, accuracy, ease of implementation, and so on. The fuzzy logic based MPPT presents high steady-state performances in terms of speed of convergence and accuracy. However, the complexity of implementation is the first drawback of this MPPT type especially for embedded systems. In addition, fuzzy algorithms show relatively a large computation time compared to most of conventional MPPTs. In this way, the aim of this paper is to benefit from fuzzy logic advantages along with M5P model tree based modeling. Indeed, a new fast MPPT algorithm is established by modeling the fuzzy logic algorithm using M5P model tree that translates the model on simple if-then instructions. The new model has been trained based on simulation based dataset recorded for 500 W/m(2) irradiation. The obtained model presents a good agreement with the fuzzy algorithm even for different irradiations and weather conditions. Furthermore, the developed algorithm shows improved performances compared to P&O and InCon algorithms. Moreover, satisfactory results have been obtained when the new algorithm has been subjected to one-day profile of real measurement.

关键词： Photovoltaic module Maximum power point tracker M5P model tree fuzzy logic algorithm

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Study of Aircraft Icing Warning algorithm Based on Millimeter Wave Radar

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Journal of Meteorological Research 2017年第6期31卷 1034-1044页

作者： Jinhu WANG Junxiang GE Qilin ZHANG Pan FAN Ming WEI Xiangchao LI Collaborative Innovation Center on Forecast and Evaluation of MeteorologicalDisasters/Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration Nanjing University of Information Science&TechnologyNanjing 210044 Key Laboratory of Meteorological Disaster of Ministry of Education Nanjing University of Information Science&TechnologyNanjing 210044 Jiangsu Key Laboratory of Meteorological Observation and Information Processing Nanjing University of Information Science&TechnologyNanjing 210044 National Demonstration Center for Experimental Atmospheric Science and Environmental Meteorology Education Nanjing University of information Science&TechnologyNanjing 210044

In order to avoid accidents due to aircraft icing, an algorithm for identifying supercooled water was studied. Specifically, a threshold method based on millimeter wave radar, lidar, and radiosonde was used to retrieve the coverage area of supercooled water and a fuzzy logic algorithm was used to classify the observed meteorological targets. The macrophysical characteristics of supercooled water could be accurately identified by combing the threshold method with the fuzzy logic algorithm. In order to acquire microphysical characteristics of supercooled water in a mixed phase, the unimodal spectral distribution of supercooled water was extracted from a bimodal or trimodal spectral distribution of a mixed phase cloud, which was then used to retrieve the effective radius and liquid water content of supercooled water by using an empirical formula. These retrieved macro- and micro-physical characteristics of supercooled water can be used to guide aircrafts during takeoff, flight, and landing to avoid dangerous areas.

关键词： supercooled water aircraft icing millimeter wave radar threshold method fuzzy logic algorithm power spectral density

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Optimal μ-Estimation-Based Regenerative Braking Strategy for an AWD HEV

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IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION 2017年第1期3卷 249-258页

作者： Paul, Deepak Velenis, Efstathios Cao, Dongpu Dobo, Tamas Cranfield Univ Ctr Automot Engn Sch Transportat & Management Cranfield MK43 0AL Beds England Jaguar Land Rover Ltd Coventry CV4 4LF W Midlands England

Braking force distribution (BFD) for electrified vehicles with the aim of maximizing energy regeneration has been a challenging research topic, due to the complex operating conditions and tradeoff among different vehicle performance measures. It is known that the level of tire-road friction has a significant impact on the braking force boundaries that define the locking conditions of front and rear wheels, and therefore, on the allowable set of BFD's where the vehicle's stability and controllability are maintained. However, previously developed BFD strategies for regenerative braking have not considered the changing boundaries of braking limits due to varying tireroad friction levels and introduce conservative BFD constraints to ensure stability and controllability. This paper proposes a BFD strategy for an all-wheel-drive electrified vehicle with a single electric motor, based on the estimation of the tire-road friction coefficient (mu) using a fuzzy logic estimation approach. The proposed strategy takes into consideration the motor efficiency and available speed reduction ratios in order to find the optimal BFD, which maximizes the regenerative power during braking, for a given vehicle speed and deceleration demand. Simulation analyses demonstrate the effectiveness of the proposed tireroad friction estimation-based BFD optimization strategy that significantly improves braking energy recovery. Preliminary test results with a prototype vehicle provide additional validation of the benefits of the proposed method.

关键词： Braking force distribution (BFD) electrified vehicles fuzzy logic algorithm regenerative braking tire-road friction estimation

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The fuzzy logic Method to Efficiently Optimize Electricity Consumption in Individual Housing

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ENERGIES 2017年第11期10卷 1701页

作者： Bissey, Sebastien Jacques, Sebastien Le Bunetel, Jean-Charles Univ Tours Res Grp Mat Microelect Acoust & Nanotechnol F-37000 Tours France

Electricity demand shifting and reduction still raise a huge interest for end-users at the household level, especially because of the ongoing design of a dynamic pricing approach. In particular, end-users must act as the starting point for decreasing their consumption during peak hours to prevent the need to extend the grid and thus save considerable costs. This article points out the relevance of a fuzzy logic algorithm to efficiently predict short term load consumption (STLC). This approach is the cornerstone of a new home energy management (HEM) algorithm which is able to optimize the cost of electricity consumption, while smoothing the peak demand. The fuzzy logic modeling involves a strong reliance on a complete database of real consumption data from many instrumented show houses. The proposed HEM algorithm enables any end-user to manage his electricity consumption with a high degree of flexibility and transparency, and "reshape" the load profile. For example, this can be mainly achieved using smart control of a storage system coupled with remote management of the electric appliances. The simulation results demonstrate that an accurate prediction of STLC gives the possibility of achieving optimal planning and operation of the HEM system.

关键词： demand side management electricity consumption prediction and management fuzzy logic algorithm individual housing

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Terrain classification using intelligent tire

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JOURNAL OF TERRAMECHANICS 2017年 71卷 15-24页

作者： Khaleghian, Seyedmeysam Taheri, Saied Virginia Tech Dept Biomed Engn & Mech Blacksburg VA 24061 USA Virginia Tech Ctr Tire Res CenTiRe Blacksburg VA 24061 USA

A wheeled ground robot was designed and built for better understanding of the challenges involved in utilization of accelerometer based intelligent tires for mobility improvements. Since robot traction forces depend on the surface type and the friction associated with the tire-road interaction, the measured acceleration signals were used for terrain classification and surface characterization. To accomplish this, the robot was instrumented with appropriate sensors (a tri-axial accelerometer attached to the tire innerliner, a single axis accelerometer attached to the robot chassis and wheel speed sensors) and a data acquisition system. Wheel slip was measured accurately using encoders attached to driven and non-driven wheels. A fuzzy logic algorithm was developed and used for terrain classification. This algorithm uses the power of the acceleration signal and wheel slip ratio as inputs and classifies all different surfaces into four main categories;asphalt, concrete, grass, and sand. The performance of the algorithm was evaluated using experimental data and good agreements were observed between the surface types and estimated ones. (C) 2017 ISTVS. Published by Elsevier Ltd. All rights reserved.

关键词： Wheeled ground robot Intelligent tire Terrain classification fuzzy logic algorithm

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Study on deep-learning-based identification of hydrometeors observed by dual polarization Doppler weather radars

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EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING 2017年第1期2017卷 1页

作者： Wang, Haijiang Ran, Yuanbo Deng, Yangyang Wang, Xu Chengdu Univ Informat Technol Coll Elect Engn Chengdu 610225 Sichuan Peoples R China CMA Key Lab Atmospher Sounding Chengdu 610225 Sichuan Peoples R China

Hydrometeor classification for dual polarization Doppler weather radar echo is a procedure that identifies hydrometeor types based on the scattering properties of precipitation particles to polarized electromagnetic waves. The difference in shape, size, or spatial orientation among different types of hydrometeor will produce different scattering characteristics for the electromagnetic waves in a certain polarization state. Moreover, the polarimetric measurements, which are calculated from the radar data and closely associated with these characteristics, are also different. The comprehensive utilization of these polarimetric measurements can effectively improve the identification accuracy of the phase of various hydrometeors. In this paper, a new identification method of the hydrometeor type based on deep learning (DL) and fuzzy logic algorithm is proposed: firstly, the feature extraction method based on deep learning is used for training the correlation among multiple parameters and extracting the relatively independent features. Secondly, the Softmax classifier is applied to classify the precipitation patterns, including rain, snow, and hail, and it is based on the features extracted by deep learning algorithm. Finally, the fuzzy logic algorithm is adopted to identify the hydrometeor types in various precipitation patterns. In order to test the accuracy of the classification results, the hydrometeor classifier has been applied to a stratiform cloud precipitation process, and it is found that the classification results agree well with the other polarimetric products.

关键词： Hydrometeor Polarimetric measurements Deep learning Feature fuzzy logic algorithm

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Hybrid evolutionary algorithm based fuzzy logic controller for automatic generation control of power systems with governor dead band non-linearity

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COGENT ENGINEERING 2016年第1期3卷 Article: 1161286页

作者： Singh, Omveer Nasiruddin, Ibraheem Maharishi Markandeshwar Univ Dept Elect Engn Ambala Haryana India Quassim Univ Dept Elect Engn Buraydah Saudi Arabia

A new intelligent Automatic Generation Control (AGC) scheme based on Evolutionary algorithms (EAs) and fuzzy logic concept is developed for a multi-area power system. EAs i.e. Genetic algorithm-Simulated Annealing (GA-SA) are used to optimize the gains of fuzzy logic algorithm (FLA)-based AGC regulators for interconnected power systems. The multi-area power system model has three different types of plants i.e. reheat, non-reheat and hydro, and are interconnected via Extra High Voltage Alternate Current transmission links. The dynamic model of the system is developed considering one of the most important Governor Dead Band (GDB) non-linearity. The designed AGC regulators are implemented in the wake of 1% load perturbation in one of the control areas and the dynamic response plots are obtained for various system states. The investigations carried out in the study reveal that the system dynamic performance with hybrid GA-SA-tuned fuzzy technique (GASATF)-based AGC controller is appreciably superior as compared to that of integral and FLA-based AGC controllers. It is also observed that the incorporation of GDB non-linearity in the system dynamic model has resulted in degraded system dynamic performance.

关键词： automatic generation control governor dead band non-linearity fuzzy logic algorithm evolutionary algorithms

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Research on Design of Early-warning Explosion-proof Monitoring System for Coal Mine Based on ZigBee

Research on Design of Early-warning Explosion-proof Monitori...

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2017 International Conference on Computer, Electronics and Communication Engineering(CECE2017)

作者： A-long YU Jin-qiao DAI Hua-jun SUN School of Physics and Electronic Electrical Engineering Huaiyin Normal University

An early-warning and explosion-proof monitoring system for coal mine environment is designed based on Zig Bee, in view of the underground special environment. The underground system, with CC2530 + CC2401 chip as the core of ZigB ee node, realizes communication with upper computer through CAN bus by the central controller. Upper computer uses the Labview software to program and realize real-time display of the coal mine parameters including CH, CO, O concentration, temperature and humidity and personnel coordinates. The early warning technology based on fuzzy logic algorithm, explosion-proof technology based on physical isolation are adopted to this system. A kind of RSSI weighted centroid algorithm mixed with LQI was put forward. Experiment proved that this system runs stably, improving the personnel positioning accuracy and has a good prospect of application.

关键词： ZigBee CC2530 CAN fuzzy logic algorithm Explosion-proof LQI

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A novel fuzzy logic-based image steganography method to ensure medical data security

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COMPUTERS IN BIOLOGY AND MEDICINE 2015年 67卷 172-183页

作者： Karalcis, R. Guler, J. Capraz, I. Bilir, E. Cumhuriyet Univ Fac Tech Educ Dept Elect & Comp Educ Sivas Turkey Gazi Univ Fac Tech Educ Dept Elect & Comp Educ TR-06500 Ankara Turkey Gazi Univ Fac Med Dept Neurol TR-06500 Ankara Turkey

This study aims to secure medical data by combining them into one file format using steganographic methods. The electroencephalogram (EEG) is selected as hidden data, and magnetic resonance (MR) images are also used as the cover image. In addition to the EEG, the message is composed of the doctor's comments and patient information in the file header of images. Two new image steganography methods that are based on fuzzy-logic and similarity are proposed to select the non-sequential least significant bits (LSB) of image pixels. The similarity values of the gray levels in the pixels are used to hide the message. The message is secured to prevent attacks by using lossless compression and symmetric encryption algorithms. The performance of stego image quality is measured by mean square of error (MSE), peak signal-to-noise ratio (PSNR), structural similarity measure (SSIM), universal quality index (UQI), and correlation coefficient (R). According to the obtained result, the proposed method ensures the confidentiality of the patient information, and increases data repository and transmission capacity of both MR images and EEG signals. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Medical image steganography Medical data security fuzzy logic algorithm Similarity based algorithm Least significant bit

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