Improvement of the Standard Perturb & Observe MPPT control strategy by the proposed Fuzzy Logic Mechanism for a Cascade Regulation of a PMSM-based PV pumping system

Fuzzy control of permanent magnet synchronous motor for new energy vehicle based on MFO algorithm

“…Analyzed from the perspective of environmental protection, the application of new energy vehicles helps to reduce the dependence on traditional energy sources and reduce environmental pollution. The application of Synchronous Motor with Permanent Magnets can further improve the energy-saving effect of new energy vehicles [9][10] and realize a more environmentally friendly driving style. From the safety point of view, precise control of new energy vehicles can be achieved through control, improving driving safety and stability.…”

Improved P&O-MPPT strategy based on new design of small-signal model used for voltage regulation of solar

“…This last one must be converted to a pulse width modulation (PWM) signal for real time implementation [2,4]. According to several previous works [5][6][7][8][9][10], the P&O algorithm that is implemented directly in the MPPT control strategy remains the most widely used algorithm for extracting the maximum power from PV panels. The corresponding optimal duty cycle control is computed from the simultaneous evaluation of two electrical variables PV voltage and PV power.…”

“…It is important to note that choosing a small fixed step size results in a significant deceleration of the convergence speed that is required to track the desired MPP, especially in steady state [10]. Unfortunately, this results in a slowing down of the power response, and therefore a destabilization of the solar energy conversion process, which in turn leads to a malfunction of the electrical load [8].…”

“…To overcome this shortcoming, the standard P&O-MPPT control strategy must contain a variable step size instead of a fixed one. Among many scholars who have recently contributed to improving the performance of standard P&O-MPPT control strategies [5][6][7][8][9][10], Paul et al, (2015) proposed the modified P&O-MPPT control based on artificial neural network (ANN). This last was previously optimized by genetic algorithm (GA) where the PI controller provides the trigger signal to the DC-DC boost converter.…”

“…Furthermore, Taibi et al, (2022) introduced the FLC mechanism to automatically update the existing duty cycle control. Unfortunately, the main drawback of these strategies lies in the design of the fuzzy rules, which requires a lot of experience in the FLC field [10]. Parallelly, Kollimalla and Mishra, (2014) developed the modified P&O-MPPT control strategy to regulate the current of the solar PV generator using the reference PV current perturbation.…”