Simulation of the proposed combined Fuzzy Logic Control for Maximum Power Point Tracking and Battery Charge Regulation used in CubeSat

• Autorzy: Seddjar Abderrahmane , Kerrouche Kamel Djamel Eddine , Wang Lina

Identyfikatory

DOI

10.24425/aee.2020.133916

• Języki publikacji: EN

Abstrakty

EN

One of the most critical systems of any satellite is the Electrical Power System (EPS) and without any available energy, the satellite would simply stop to function. Therefore, the presented research within this paper investigates the areas relating to the satellite EPS with the main focus towards the CubeSat platform. In this paper, an appropriate EPS architecture with the suitable control policy for CubeSat missions is proposed. The suggested control strategy combines two methods, the Maximum Power Point Tracking (MPPT) and the Battery Charge Regulation (BCR), in one power converter circuit, in order to extract the maximum power of the Photovoltaic (PV) system and regulate the battery voltage from overcharging. This proposed combined control technique is using a Fuzzy Logic Control (FLC) strategy serving two main purposes, the MPPT and BCR. Without an additional battery charger circuit and without switching technique between the two controllers, there are no switching losses and the efficiency of the charging characteristic can be increased by selecting this proposed combined FLC. By testing a space-based PV model with the proposed EPS architecture, some simulation results are compared to demonstrate the superiority of the proposed control strategy over the conventional strategies such as Perturb and Observe (P&O) and FLC with a Proportional Integral Derivative (PID) controller.

Słowa kluczowe

EN

combined Fuzzy Logic Control; Electrical Power System; photovoltaic system; Maximum Power Point Tracking; Battery Charge Regulation; Perturb and Observe; CubeSat

• Wydawca: Polish Academy of Sciences, Committee on Electrical Engineering
• Czasopismo: Archives of Electrical Engineering
• Rocznik: 2020
• Tom: Vol. 69, nr 3
• Strony: 521--543
• Opis fizyczny: Bibliogr. 49 poz., rys., tab., wz.

Twórcy

autor

Seddjar Abderrahmane

• Algerian Space Agency, Satellites Development Center PO Box 4065, Ibn Rochd USTO, Bir El Djir, Oran, Algeria

autor

Kerrouche Kamel Djamel Eddine

• Algerian Space Agency, Satellites Development Center PO Box 4065, Ibn Rochd USTO, Bir El Djir, Oran, Algeria

autor

Wang Lina

• School of Automation on Science and Electrical Engineering Beihang University, Beijing 100191, China

Bibliografia

• [1] Poghosyan A., Golkar A., CubeSat evolution: Analyzing CubeSat capabilities for conducting science missions, Progress in Aerospace Sciences, vol. 88, pp. 59–83 (2017).
• [2] Fritz B.A., Stephan A.W., Walker P.W., Brown C.M., Nicholas A.C., Dymond K.F., Budzien S.A., Marquis P.J., Finne T.T., Wolfram K.D., Ultraviolet beam splitter characterization for use in a CubeSat optical system, Journal of Applied Remote Sensing, vol. 13, no. 3, p. 032503 (2019).
• [3] Garcia R.F., Sibbing Z.R., Van Camp A., Can We Estimate Air Density of the Thermosphere with CubeSats?, Journal of Spacecraft and Rockets, pp. 1–8 (2019).
• [4] Song S., Kim H., Chang Y.-K., Design and Implementation of 3U CubeSat Platform Architecture, International Journal of Aerospace Engineering, vol. 1, pp. 1–17 (2018), DOI: 10.1155/2018/2079219.
• [5] https://www.endurosat.com/cubesat-store/all-cubesat-modules/1-5u-cubesat-platform/, accessed 2019.
• [6] Xu D., Zhang D., Power Electronics Systems in Satellites, Control of Power Electronic Converters and Systems, edited by: Elsevier (2018).
• [7] Kerrouche K., Wang L., Aoudeche A., Low-Cost EPS for nanosatellites constellation of belt and road countries, Fourth IAA Conference on Dynamics and Control of Space Systems, DyCoSS (2018).
• [8] Peng L., Jun Z., Xiaozhou Y., Luping C., Design and validation of modular MPPT electric power system for multi-U CubeSat, 2017 3rd IEEE International Conference on Control Science and Systems Engineering (ICCSSE), pp. 374–377 (2017).
• [9] Ahmed J., Salam Z., A modified P&O maximum power point tracking method with reduced steady-state oscillation and improved tracking efficiency, IEEE Transactions on Sustainable Energy, vol. 7, no. 4, pp. 1506–1515 (2016).
• [10] Ballaji A., Divakar B., Hediyal N., Mandi R.P., Swamy K.N., Energy Efficient Perturb and Observe Maximum Power Point Algorithm with Moving Average Filter for Photovoltaic Systems, International Journal of Renewable Energy Research, vol. 9, no. 1 (2019).
• [11] Belkaid A., Colak I., Kayisli K., Implementation of a modified P&O-MPPT algorithm adapted for varying solar radiation conditions, Electrical Engineering, vol. 99, no. 3, pp. 839–846 (2017).
• [12] Gopal Y., Kumar K., Birla D., Lalwani M., Banes and boons of perturb and observe, incremental conductance and modified regula falsi methods for sustainable PV energy generation, Journal of Power Technologies, vol. 97, no. 1, pp. 35–43 (2017).
• [13] Isaloo B.A., Amiri P., Improved variable step size incremental conductance MPPT method with high convergence speed for PV systems, Journal of Engineering Science and Technology, vol. 11, no. 4, pp. 516–528 (2016).
• [14] Loukriz A., Haddadi M., Messalti S., Simulation and experimental design of a new advanced variable step size Incremental Conductance MPPT algorithm for PV systems, ISA transactions, vol. 62, pp. 30–38 (2016).
• [15] Zakzouk N.E., Elsaharty M.A., Abdelsalam A.K., Helal A.A., Williams B.W., Improved performance low-cost incremental conductance PV MPPT technique, IET Renewable Power Generation, vol. 10, no. 4, pp. 561–574 (2016).
• [16] Bartczak M., Partial Shading Detection in Solar System Using Single Short Pulse of Load, Metrology and Measurement Systems, vol. 24, no. 1, pp. 193–199 (2017).
• [17] Bendib B., Krim F., Belmili H., Almi M., Boulouma S., Advanced Fuzzy MPPT Controller for a stand-alone PV system, Energy Procedia, vol. 50, pp. 383–392 (2014).
• [18] Samal S., Barik P.K., Sahu S.K., Extraction of maximum power from a solar PV system using fuzzy controller based MPPT technique, 2018 Technologies for Smart-City Energy Security and Power (ICSESP), pp. 1–6 (2018).
• [19] Jasim A., Shepetov Y., Maximum Power Point Tracking for Satellite Solar Power Load Matching under Different Light Panels, Current Journal of Applied Science and Technology, pp. 1–14 (2017).
• [20] Talha A., Boumaaraf H., Bouhali O., Evaluation of maximum power point tracking methods for photovoltaic systems, Archives of Control Sciences, vol. 21, no. 2, pp. 151–165 (2011).
• [21] Cardozo D.O., Pardo M., Algarín C.R., Fuzzy Logic Controller for Maximum Power Point Tracking Based on Voltage Error Measurement in Isolated Photovoltaic Systems, 2018 IEEE ANDESCON, pp. 1–6 (2018).
• [22] Wang Y., Yang Y., Fang G., Zhang B., Wen H., Tang H., Fu L., Chen X., An Advanced Maximum Power Point Tracking Method for Photovoltaic Systems by Using Variable Universe Fuzzy Logic Control Considering Temperature Variability, Electronics, vol. 7, no. 12, p. 355 (2018).
• [23] Yilmaz U., Kircay A., Borekci S., PV system fuzzy logic MPPT method and PI control as a charge controller, Renewable and Sustainable Energy Reviews, vol. 81, pp. 994–1001 (2018).
• [24] Mlakić D., Nikolovski S., ANFIS as a method for determinating MPPT in the photovoltaic system simulated in MATLAB/Simulink, 2016 39th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), pp. 1082–1086 (2016).
• [25] Della Krachai S., Stambouli A.B., Della Krachai M., Bekhti M., Experimental investigation of artificial intelligence applied in MPPT techniques, International Journal of Power Electronics and Drive Systems, vol. 10, no. 4, p. 2138 (2019).
• [26] Hassan S., Li H., Kamal T., Arifoğlu U., Mumtaz S., Khan L., Neuro-Fuzzy wavelet based adaptive MPPT algorithm for photovoltaic systems, Energies, vol. 10, no. 3, p. 394 (2017).
• [27] Bahri O., Talbi E.-G., Amor N.B., A generic fuzzy approach for multi-objective optimization under uncertainty, Swarm and Evolutionary Computation, vol. 40, pp. 166–183 (2018).
• [28] Seddjar A., Berrached N., A Fuzzy Approach for a Hybrid Multi-Mobile Robot Control Architecture to Maintain a Specific Formation During Navigation, International Review of Automatic Control (IREACO), vol. 8, no. 1, pp. 63–71 (2015).
• [29] Shiau J.-K., Wei Y.-C., Lee M.-Y., Fuzzy controller for a voltage-regulated solar-powered MPPT system for hybrid power system applications, Energies, vol. 8, no. 5, pp. 3292–3312 (2015).
• [30] Neji B., Hamrouni C., Alimi A.M., Nakajima H., Alim A.R., Hierarchical Fuzzy-Logic-Based Electrical Power Subsystem for Pico Satellite ERPSat-1, IEEE Systems Journal, vol. 9, no. 2, pp. 474-486 (2013).
• [31] Naick K., Chatterjee K., Chatterjee T., Fuzzy logic controller based maximum power point tracking technique for different configurations of partially shaded photovoltaic system, Archives of Electrical Engineering (2018).
• [32] Bhat Nempu P., Sabhahit Jayalakshmi N., A new power management strategy for PV-FC-based autonomous DC microgrid, Archives of Electrical Engineering, vol. 67, no. 4 (2018).
• [33] Drir N., Barazane L., Loudini M., Optimizing the operation of a photovoltaic generator by a genetically tuned fuzzy controller, Archives of Control Sciences, vol. 23, no. 2, pp. 145–167 (2013).
• [34] Krause F.C., Loveland J.A., Smart M.C., Brandon E.J., Bugga R.V., Implementation of commercial Li-ion cells on the MarCO deep space CubeSats, Journal of Power Sources, vol. 449, p. 227544 (2020).
• [35] Sanchez-Sanjuan S., Gonzalez-Llorente J., Hurtado-Velasco R., Comparison of the incident solar energy and battery storage in a 3U CubeSat satellite for different orientation scenarios, Journal of Aerospace Technology and Management, vol. 8, no. 1, pp. 91–102 (2016).
• [36] Gonzalez-Llorente J., Lidtke A.A., Hurtado R., Okuyama K.-I., Single-Bus and Dual-Bus Architectures of Electrical Power Systems for Small Spacecraft, Journal of Aerospace Technology and Management, vol. 11 (2019).
• [37] Bogaraj T., Kanakaraj J., Chelladurai J., Modeling and simulation of stand-alone hybrid power system with fuzzy MPPT for remote load application, Archives of Electrical Engineering, vol. 64, no. 3, pp. 487–504 (2015).
• [38] Shah M., Juneja A., Bhattacharya S., Dean A.G., High frequency GaN device-enabled CubeSat EPS with real-time scheduling, 2012 IEEE Energy Conversion Congress and Exposition (ECCE), pp. 2934–2941 (2012).
• [39] Mojallizadeh M.R., Karimi B., Nonlinear control of a satellite electrical power system based on the sliding mode control, ISRN Aerospace Engineering, vol. 2013 (2013).
• [40] Villalva M.G., Gazoli J.R., Ruppert Filho E., Comprehensive approach to modeling and simulation of photovoltaic arrays, IEEE Transactions on Power Electronics, vol. 24, no. 5, pp. 1198–1208 (2009).
• [41] Rekioua D., Matagne E., Optimization of photovoltaic power systems: modelization, simulation and control, Springer Science and Business Media (2012), DOI: 10.1007/978-1-4471-2403-0.
• [42] Initiative N.C.L., CubeSat 101: Basic Concepts and Processes for First-Time CubeSat Developers, San Luis Obispo, USA (2017).
• [43] Dadios E., Fuzzy Logic: Controls, Concepts, Theories and Applications, BoD–Books on Demand (2012).
• [44] Rahim R., Comparative Analysis of Membership Function on Mamdani Fuzzy Inference System for Decision Making, Journal of Physics Conference Series, vol. 930 (2017).
• [45] Iancu I., A Mamdani type fuzzy logic controller, Fuzzy Logic-Controls, Concepts, Theories and Applications, edited by: IntechOpen (2012), DOI: 10.5772/36321.
• [46] GmbH A.S.S.P., 28% Triple Junction GaAs Solar Cell Type: TJ Solar Cell 3G28C, edited (2016).
• [47] Mohan N., Power electronics: a first course, Wiley (2011).
• [48] Motahhir S., El Ghzizal A., Sebti S., Derouich A., MIL and SIL and PIL tests for MPPT algorithm, Cogent Engineering, vol. 4, no. 1, p. 1378475 (2017).
• [49] Erickson R.W., Maksimovic D., Fundamentals of power electronics, Springer Science and Business Media (2007).

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).