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this paper presents fuzzy output tracking control of switching photovoltaic (PV) DC-DC converters. The proposed control ensures good performances and overall large-signal stability of the system over the whole operating space. To do this, we present a model of PV system and a state space model for DC-DC boost converter. Then, we introduce an added integral state of the output tracking error. The resulting augmented system is converted into a Takagi sugeno fuzzy model (TSFM). The Parallel distributed compensation (PDC) concept is employed to design the state-feedback based control law whereby the control gains are fined using the linear quadratic regulator (LQR) technique. Finally, the design procedures are applied to a dynamics model of typical PV power control system using a DC-DC boost converter to illustrate the effectiveness of the proposed control techniques.

In this paper, multi-criteria and hierarchical energy management system (EMS) for a light solar vehicle (LSV) is investigated. This vehicle uses of a lithium-ion battery (bat), a supercapacitor (SC), a photovoltaic (PV) generator and a propulsion system. The proposed management strategy aims to enhance power sharing between multiple sources with different characteristics, and to optimize power trajectory in order to avoid the energy losses in the DC/DC converters. For this sake, the developed strategy is based on five modes switching process. The proposed EMS consists of three hierarchical levels. The high level defines dynamically mode operation according to system situation and management strategy (decision strategy). It employs the state of charge of the battery (SOCbat), the state of charge of SC (SOCsc), the PV power (Ppv) and the load power (Pload) as a four-information sensor to distinguish different modes and determine the mode selected. While the medium level, integrates an algorithm to compute the reference power for the SC and the battery at each instant and according to selected mode. The low level plays an interface between EMS and DC/DC converters. It is composed from the proportional integral (PI) controllers which provide a pulse width modulation (PWM) signal to DC/DC converters. It is noteworthy here that the fuzzy logic (FL) technology is used to implement the suggested EMS. The obtained results of various simulations demonstrate the effectiveness and reliability of the proposed strategy.

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