Implementation of a modified incremental conductance MPPT algorithm with direct control based on a fuzzy duty cycle change estimator using dSPACE Tawfik Radjai a,⇑ , Lazhar Rahmani a , Saad Mekhilef b , Jean Paul Gaubert c a Universite ´ Se ´tif 1, Faculte ´ de Technologie, De ´partement d’e ´lectrotechnique, laboratoire d’automatique (LAS), Algeria b University of Malaya, Faculty of Engineering, Department of Electrical Engineering, Malaysia c Universite ´ de Poitiers, Laboratoire d’Informatique et d’Automatique pour les Syste `mes (LIAS), France Received 8 January 2014; received in revised form 9 September 2014; accepted 10 September 2014 Communicated by: Associate Editor Arturo Morales-Acevedo Abstract Maximum power point tracking (MPPT) is a necessary function in all photovoltaic (PV) systems. The classic incremental conductance (IC) MPPT algorithm is widely used in the literature. However, when large changes occur in the irradiance, the performance of this algorithm is degraded. To eliminate all of the disadvantages of the classic IC algorithm, we developed a new IC controller based on a fuzzy duty cycle change estimator with direct control. A fuzzy logic estimator (FLE) is used to estimate the new duty cycle used to track the PV array maximum power point. Compared with the fixed step IC MPPT method with direct control, the proposed algorithm reaches the MPP more accurately and faster during dynamic and steady-state conditions. A controlled Cuk DC–DC converter was implemented and connected to a SunTech STP085B PV panel to verify the accuracy of the proposed method. Matlab/Simulink was used for the simulation studies. Additionally, the algorithms were digitally implemented on the dSPACE ACE1104 platform. The results obtained confirm the advantages of the proposed algorithm. Ó 2014 Elsevier Ltd. All rights reserved. Keywords: Photovoltaic; Fuzzy logic estimator; MPPT; Incremental conductance; Cuk; Fixed step 1. Introduction The petroleum crisis and the increasing demand for energy, coupled with the possibility of the reduced supply of conventional fuels, has motivated progress in renewable energy research and applications. Among renewable energy sources, solar energy is currently considered to be the most useful natural energy source because it is abundant, clean and distributed over the earth. Solar energy is a primary factor in all other processes of energy production on earth (de Brito et al., 2013). Despite these advantages, the efficiency of solar energy conversion is currently low, and the initial cost for its implementation is still considered high (de Brito et al., 2013; Fairley, 2011). The efficiency of solar cells depends on many factors, such as the temperature, insulation, the spectral character- istics of the sunlight and the presence of dirt and shadows (Bratcu et al., 2011; Jain and Agarwal, 2007; Ji et al., 2011). Rapidly changing atmospheric conditions can reduce the photovoltaic (PV) array output power. http://dx.doi.org/10.1016/j.solener.2014.09.014 0038-092X/Ó 2014 Elsevier Ltd. All rights reserved. ⇑ Corresponding author. E-mail addresses: r_toufik@yahoo.fr (T. Radjai), lazhar_rah@yahoo. fr (L. Rahmani), saad@um.edu.my (S. Mekhilef), jean.paul.gaubert@ univ-poitiers.fr (J.P. Gaubert). www.elsevier.com/locate/solener Available online at www.sciencedirect.com ScienceDirect Solar Energy 110 (2014) 325–337