New approach for improving the performance of dual axis solar tracker with auto cleaning system

Although significant efforts have been made to enhance industrial air conditioning systems, there are still efficiency and transient response issues in vehicle air conditioning systems using IPMSM compressors. This paper focuses on the neural network compensator-based control in an interior permanent-magnet synchronous motor (IPMSM) to address the occurrence of reduced power copper loss efficiency and degraded velocity response in the motor system when confronted with periodic dynamic disturbances of step signals. This paper encompasses two main objectives: the first objective is to introduce a neural network (NN) compensator to improve the power copper loss efficiency. The NN compensator is developed using the velocity loop and current loop control model equation of an IPMSM, and trained to implement optimal compensation control based on the back propagation algorithm. The second objective is to optimize the dynamic performance of velocity response compared to the traditional maximum torque per ampere (MTPA) current control method under step disturbance and dynamic control conditions by building an experimental system for validation, incorporating both hardware and simulation. Another significant advantage is the low computational load introduced by the neural network compensator, rendering it well-suited for implementation within low-order DSP systems. The results indicate that the neural network compensator surpasses conventional MTPA control method in both simulation and hardware-based implementations concerning power copper loss and velocity response in an IPMSM control system.

Neural Network Compensator-Based Control for Enhancing IPMSM Dynamics and Copper Loss Efficiency for Air Compressor

In this work, the system of a boost converter coupled with a solar cell as a power source is studied. The study is approached from the local stability analysis of the three differential equations that model the system. Then the energy shaping control based on passivity is applied to determine the global stability of the system. Using this control, the mathematical model is studied and the simulation results are compared with those obtained experimentally. 

Efecto de un control basado en pasividad en un sistema celda-convertidor

The linear increase in the growth of the population demands a requisite for energy resources. Knowing the loathsome truth that non-renewable sources will ultimately exhaust, the significance of renewable sources cannot be undervalued. Considering various factors, many work areas are reliant upon fossil fuels for the generation of electricity. The use of fossil fuels will increase the quality of power production but will drain one day, and industries must change to renewable sources. The earliest system that strikes a chord with regard to renewable energy is the photovoltaic (PV) energy system. In this specific circumstance, interest in solar systems is expanding step by step, and its installations are becoming broad. The implementation of the solar water pumping method used for irrigation purposes using a Zeta converter was best suited for small and minor farmers, but still, the efficiency of the system can be upgraded with the use of filters. The vantage of the ZETA converter has less result voltage ripple and smooth water pumping application. The PV-based system has reached the point where it is used in Electric vehicles by enhancing the standard operating condition of the converter under the steady and dynamic behavior of a PV system. Eventually, it can be worked considerably under minimum solar irradiance. Maximum power point tracking (MPPT) of the signal had dominant performance in a zeta converter circuit while sign levels ripple current, and voltage on the output side was compact.

Design and Implementation of Modified Zeta Converter for Solar Water Pumping Application

Os conversores boost são amplamente utilizados para elevar a tensão de saída a um nível superior à tensão de entrada de diversos sistemas. Esses conversores são comumente utilizados em baterias para automóveis elétricos, frenagem regenerativa de motores de corrente contínua, quadrirrotores, carregadores solares, amplificadores de áudio de potência e diversos outros dispositivos. Para tal, este dispositivo armazena energia no campo magnético de um indutor e, em seguida, transfere essa energia para um capacitor de tal forma que a tensão do capacitor pode aumentar além da tensão da fonte que forneceu energia ao indutor. Porém, para obter uma tensão desejada na saída, é fundamental utilizar um controlador confiável para realizar a regulação desse sistema. Este artigo apresenta a modelagem matemática, projeto de dimensionamento de acordo com especificações estabelecidas e controle preditivo de um conversor boost. A estratégia de controle utilizada para regular a tensão deste conversor é um controlador deadbeat, o qual possui uma estrutura simples, porém provê rápida resposta ao sistema em malha fechada. Os resultados de simulação numérica demonstram a superioridade do controlador preditivo em relação a um controlador proporcional-integral-derivativo. 

Modelagem matemática, projeto e controle preditivo de um conversor boost

Speed Control of PMSM Using Modified Particle Swarm Optimization Technique Based on Inertia Weight Updating Mechanism

This paper proposes an AI approach to enhance the PMSM drive systems through an ANN based speed controller. Due to its great efficiency and precise control capabilities, PMSM drives are broadly used in industrial applications. However, achieving optimal speed control remains a challenging task, especially under varying operating conditions and disturbances. To address this, the proposed ANN-based speed controller utilizes to approximate the complex nonlinear relationship between motor torque and control input. Through adaptive learning, the controller effectively adapts to changing system dynamics, uncertainties, and disturbances, resulting in improved speed tracking accuracy, disturbance rejection, and robustness. Simulation results shows the better performance of the ANN controller compared to conventional techniques, making it a promising solution for enhancing PMSM drive system performance in various industrial applications. 

Dynamic Analysis of Vector Controlled PMSM with Constant Torque Angle Control Strategy Using Artificial Neural Network

This paper presents the design, simulation and fabrication of single-ended primary-inductance converter (SEPIC) model and analyzes the results of implementation of zero-voltage and zero-current switching (ZV-ZCS). ZV-ZCS SEPIC converter has been simulated in MATLAB in buck as well as boost mode. A fabricated model of the SEPIC converter has been designed to be operated in ZV-ZCS mode. This converter has been designed with an aim of reducing power losses during switching of higher frequency devices, such that the overall efficiency of the system can be improved.

Design of PWM Triggered SEPIC Converter Using Zero-Voltage Zero-Current Switching

ABSTRACT The most admired alternative to conventional energy sources is solar energy. In north-eastern regions of India, where availability of sun is unpredictable but irradiance level is high, special observation is needed to upgrade the solar collection systems. The main objective of the research work is to develop a renewable system, which can extract maximum voltage using dual axis movable surface and design a cascaded converter, which can further increase the voltage while maintaining high efficiency. The output of the smart independent self-regulating solar panel hardware model proposed in this paper is fed into a DC–DC cascaded Boost-SEPIC system for renewable-based applications. The newly created renewable system is built to move the panel so that the most voltage is extracted. The DC–DC cascaded converter receives power from the solar panel’s output. To assess the system’s effectiveness and voltage gain, a thorough circuit analysis is carried out. The converter is tested using various duty cycles. With a 50% duty ratio and 90% efficiency, the suggested converter produces a 40 V DC output from a 20 V DC input voltage from a solar panel. Results from an experimental prototype are used to verify the converter’s viability.

/pdf/design-of-smart-autonomous-solar-panel-with-cascaded-sepic-14u73wg9.pdf

Design of smart autonomous solar panel with cascaded SEPIC-boost converter for high voltage renewable applications

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Papers

Speed Control of PMSM Using Modified Particle Swarm Optimization Technique Based on Inertia Weight Updating Mechanism

Dynamic Analysis of Vector Controlled PMSM with Constant Torque Angle Control Strategy Using Artificial Neural Network

Design of PWM Triggered SEPIC Converter Using Zero-Voltage Zero-Current Switching

Design of smart autonomous solar panel with cascaded SEPIC-boost converter for high voltage renewable applications