Experimental Investigation of Performance Characteristics for Savonius-Style VAWTs: A Comparative Study

Savonius-style wind turbines are mainly gauged by two types of coefficients namely: (i) coefficient of power (CP) and (ii) coefficient of torques (CT). Coefficient of power is defined as the ratio of power generated by the turbine to the total power available to the turbine from the free-flowing wind. This is synonymous to the operational efficiency of the wind turbine. Coefficient of torque reflects the torque generating ability of the turbine. In this manuscript, experiments have been performed using three different types of rotor profiles for Savonius-style wind turbines (SSWTs) namely, classical SSWT, Benesh type SSWT and elliptical shaped SSWT using oriented jets. Using deflector plates the orientation of jets have been varied from 20° to 70°. Addition of deflector plates to the wind turbines, assists in maximizing the utilization of wind energy. Experiments have been performed in the laminar air flow. Mechanical loads have been used to study Coefficient of performance (CP) and coefficient of torque (CT) as a function of tip speed ratio (TSRs). The velocity of the wind is adjusted by varying the rheostat that controls the AC motor for the wind tunnel systems. Experimental results indicated that optimum performance could be achieved from all three types of SSWT variants at TSR ∼ 0.70. Out of the three designs studied in this manuscript, elliptic shaped SWT yielded best coefficient of performance equal to 0.39 at TSR = 0.70.

Parameter identification of permanent magnet synchronous AC motor based on spectral method

This paper establishes a mathematical model with random terms for a permanent magnet synchronous AC motor, which is a nonlinear system using d - axis current, q - axis current and the rotor electric angular speed as state variables. The numerical solution obtained by the Euler-Maruyama method is used as the measurement data. Aiming at the parameter identification of the system, a step-by-step identification method based on the spectral method discretize the system first and then using the least squares is proposed. This method is used to identify multiple parameters of the motor in the same model. In step-by-step identification, firstly by fixing the motor speed, the system is transformed into a linear system, which is used to estimate the resistance, inductance and flux linkage. After that, the speed is not fixed, for the electrical parameters are known, we can identify damping and inertia by using mechanical equations. Finally, the experimental results show that the relative errors of the parameters identified by the proposed method are smaller, which shows the effectiveness of this method for multi-parameter identification.

Performance and Energy Consumption of Paddle Wheel Aerator Driven by Brushless DC Motor and AC Motor: A Preliminary Study

Energy demand for paddle wheel aerator in a shrimp pond is high and brings to second highest cost of operational behind feed supply. Most of wheel aerators are driven by electric motors than diesel engines as their easy operations. The electric motors need high electrical energy to drive wheel aerators along day and night. The common type of motor used is Alternating Current (AC) or induction motor, however Brushless Direct Current (BLDC) motor has potential electrical energy saving which need to be explored. This study objectives to find out performance of BLDC and AC motor as paddle wheel aerator driver. The motor’s performances were compared in term of operation of paddle wheel at various static loads. Both motor also challenged by On/Off running every 5 minutes, the treatment goal was to determine their reliability. Parameters observed included consumption of power, wheel rotary, torque, and efficiency, motor temperature as well. Results showed energy consumption of BLDC motor 51% lower than AC motor, and BLDC motor attained 89.99% of maximum efficiency while AC motor efficiency had 73.16%, however rotary wheel and torque both of them were similar. The On/Off treatment caused rising temperature of AC motor but did not affect the temperature of BLDC motor. Therefore, applied BLDC motor as paddle wheel aerator driver could be alternative way to reduce energy consumption without reducing its performance.

Overview of AC Motor Sensorless Algorithms: a Unified Perspective

This paper reviews sensorless algorithms for both induction motors and permanent magnet motors using the active flux model, such that any design applicable for non-salient pole ac motors can also be included in the review framework. The proposed review framework classifies all sensorless algorithms following a five-layer hierarchy abbreviated as O-I-M-A-I, resulting in four main categories as i) inherently sensorless position estimation, ii) non-inherently sensorless position estimation, iii) post-position-estimation speed estimation, and iv) speed estimation for indirect field orientation. Various ac motor models are derived by assuming a constant active flux amplitude, based on which seven generic sensorless algorithms are summarized in a tutorial. Recommendations are made for sensorless drive designers to begin with inherently sensorless method such that the two-way coupling between position estimation and speed estimation is avoided. Finally, classical induction motor model results from time-varying active flux amplitude and slip relation, for which a state transformation is recommended for achieving global stability.<br>

Overview of AC Motor Sensorless Algorithms: a Unified Perspective

This paper reviews sensorless algorithms for both induction motors and permanent magnet motors using the active flux model, such that any design applicable for non-salient pole ac motors can also be included in the review framework. The proposed review framework classifies all sensorless algorithms following a five-layer hierarchy abbreviated as O-I-M-A-I, resulting in four main categories as i) inherently sensorless position estimation, ii) non-inherently sensorless position estimation, iii) post-position-estimation speed estimation, and iv) speed estimation for indirect field orientation. Various ac motor models are derived by assuming a constant active flux amplitude, based on which seven generic sensorless algorithms are summarized in a tutorial. Recommendations are made for sensorless drive designers to begin with inherently sensorless method such that the two-way coupling between position estimation and speed estimation is avoided. Finally, classical induction motor model results from time-varying active flux amplitude and slip relation, for which a state transformation is recommended for achieving global stability.<br>

Proposed Commutation Method for Performance Improvement of Brushless DC Motor

This study focused on the efficiency improvement and acoustic noise reduction of brushless DC (BLDC) motors by reducing current harmonics using a novel BLDC commutation method. To achieve these goals, we designed an improved 150° commutation method for a three-phase permanent magnet BLDC motor that can improve the current waveform. Although the 120° commutation method is generally employed for BLDC motors, an improved 150° commutation method is introduced to operate the BLDC with increased efficiency and acoustic noise similar to a brushless AC motor. This study investigated the attributes of various commutation methods, both theoretically and experimentally, to determine the optimal commutation method. The results of this study indicate that the improved 150° commutation method is optimal in terms of harmonic attributes and reduced torque ripple, allowing it to improve motor efficiency and reduce acoustic noise.

ML models for real-time hybrid systems

A correct system design can be systematically obtained from a specification model of a real-time system that integrates hybrid measurements In a realistic industrial environment, this has been carried out through complete Matlab / Simulink / Stateflow models. However, there is a widespread interest in carrying out that modeling resorting to Machine Learning models, which can be understood as Automated Machine Learning for Real-time systems that present some degree of hybridation. An AC motor controller which must be able to maintain a constant air flow through a filter is one of these systems. The article also discusses a practical application of the method for implementing a closed loop control system to show how the proposed procedure can be applied to derive complete hybrid system designs with ANN.