Output Voltage Control Analysis of Three-Level Boost DC-DC Converters

In this paper, an optimized maximum power point tracking (MPPT) control for a standalone photovoltaic (PV) system using a three-level boost (TLB) converter is introduced. The proposed MPPT method is based on an intelligent perturb and observe algorithm using the artificial neural network (ANN-P&O) to reduce the oscillations at the maximum power point (MPP). In advance, The ANN provides the values of the voltage and the current at the MPP for any solar irradiance and cell temperature. Based on the provided voltage and current, the P&O algorithm generates the optimal duty cycle of the TLB converter to perfectly track the MPP of the PV generator for different values of cell temperature and sunlight irradiance. Besides, a proportional-integral (PI) controller is added to ensure the TLB capacitor voltage balance. The established ANN-P&O approach is validated in Matlab/Simulink and compared to the conventional P&O algorithm under various scenarios: (i) irradiance variations, (ii) temperature variations, and (iii) load variations.

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“…e converter frequency is noted as f; d 1 (d 2 ) is the S 1 (S 2 ) duty cycle. e switches command signals are delayed by a half-period [23].…”

Section: Three-level Boost Convertermentioning

confidence: 99%

Intelligent Perturb and Observe Based MPPT Approach Using Multilevel DC-DC Converter to Improve PV Production System

Ayad

Elwarraki

Baghdadi

2021

Journal of Electrical and Computer Engineering

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“…A fuzzy logic controller of a DC voltage control has been addressed in [17], [18], [19], and [20]. In [21], an optimized controller for a boost converter based on the PSO algorithm has been pro-posed.…”

Section: Introductionmentioning

confidence: 99%

Optimized Nonlinear Integral Backstepping Controller for DC–DC Three-Level Boost Converters

et al. 2023

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Multi-level DC-DC converters have been widely used in automotive and other high-power applications. Thus, the control of these multi-level converters is an emerging thematic in power electronics to ensure their proper functioning. This paper provides a novel nonlinear control of a DC-DC three level boost converter (T-LBC) based on a backstepping (BS) technique with an integral action and is optimized using genetic algorithms (GA). Firstly, the average state model of the T-LBC is described. Then, this model is used to design an integral BS controller; nevertheless, the controller parameters are often determined manually, which may degrade the control quality. A genetic algorithm-based optimization method is applied to establish the best controller gains and improve the proposed controller efficiency. The asymptotic stability converter is verified using the Lyapunov method criteria. In order to validate the introduced controller under different scenarios, the Matlab/Simulink environment is used. In addition, it is compared with different controllers such as conventional backstepping, fuzzy logic, and proportional-integral-derivate (PID) controllers under varying references to highlight its performance further. Finally, the designed controller is verified experimentally by implementing it using a dSPACE 1104 control board. The simulation and experimental results show that the optimized integral BS controller presents the best performances in terms of settling time, overshoot and steady-state error.INDEX TERMS Three level boost DC-DC converter, nonlinear control, integral backstepping, genetic algorithms, tuning.MOHAMED BAGHDADI received the B.S. degree in industrial informatics and electronics from Mohammed First University, Oujda, Morocco, in 2015, and the M.S. degree in electrical engineering from Cadi Ayyad University, Marrakesh, Morocco, in 2017, he is currently pursuing the Ph.D. degree in electrical engineering and energy efficiency with the Electrical Systems, Energy Efficiency and Telecommunications Laboratory. His research interests include semiconductor device models, digital signal processing chips, design, control, modeling and simulation of semiconductor device, and hardware in the loop strategy.

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