Search results

This study aims to simulate and test the performance of a transmitting and receiving capacitive micro-machined ultrasonic transducer (CMUT). Aimed at detecting demand of the CMUT, a matched integrated adjustment circuit was designed through analyzing processing methods of transducer’s weak echo signal.

Based on the analysis of CMUT array structure and work principle, the CMUT units are designed and the dynamic performance analysis of SIMULINK is given according to the demand of underwater detecting. A transceiver isolation circuit is used to make transmission mode and receiving mode separate. A detection circuit is designed based on the transimpedance amplifier to achieve extraction of high-frequency and weak signal.

Through experimentation, the effectiveness of the CMUT performance simulation and the transceiver integrated adjustment circuit were verified. In addition, the test showed that CMUT with 400 kHz frequency has wider bandwidth and better dynamic characteristics than other similar transducers.

This paper provides a theoretical basis and design reference for the development and application of CMUT technology.

This paper aims to present a new master’s programme for promoting energy access and energy efficiency in Southern Africa.

A transdisciplinary approach called “participatory integrated assessment of energy systems” (PARTICIPIA) was used for the development of the curriculum. This approach is based on the two emerging fields of “multi-scale integrated assessment” and “science for governance”, which bring innovative concepts and methods.

The application of the PARTICIPIA methodology to three case studies reveals that the proposed transdisciplinary approach could support energy and development policies in the region. The implementation of the PARTICIPIA curriculum in three higher education institutions reveals its ability to respond to the needs of specific contexts and its connection with existing higher education programmes.

Considering energy issues from a transdisciplinary approach in higher education is absolutely critical because such a holistic view cannot be achieved through engineering curricula. Deliberate and greater efforts should be made to integrate methods from “multi-scale integrated assessment” and “science for governance” in higher education curricula to train a new breed of modern-day energy planners in charge of coming up with solutions that are shared by all relevant stakeholders.

This paper presents an innovative higher education curriculum in terms of the attention given to energy access and energy efficiency that affect the southern Africa region and the nature of the methodology adopted to face these issues.

The purpose of this paper is to demonstrate the effectiveness of Six Sigma as an innovative tool in software design optimization. The problem of reducing simulation time for characterizing a type of DC motor is studied in this paper. The case study illustrates how Six Sigma tools such as the design of experiments (DOE) method can be used to improve a simulation process.

A first‐principle model for the motor is used for simulation in MATLAB^®. Each parameter in the model is assumed to have a known distribution. Using the random number generator in MATLAB^®, Monte Carlo analysis is conducted. To reduce simulation time, several factors in the simulation process are identified. A two‐level full factorial DOE matrix is constructed. The Monte Carlo analysis is carried out for each of the parameter set in the DOE matrix. Based on the simulation results and the DOE analysis, the Simulink model is identified as the main contributor to the computational time of the simulation. Several steps are taken to reduce the computational time related to the Simulink model. The improved model requires only one‐fourth of the original computational time.

The paper illustrates that Six Sigma tools can be applied to algorithm and software‐development process for optimization purpose. Statistical analysis can be conducted in the simulation environment to provide valuable information.

As an example, the improved simulation process is used to derive statistical information related to the speed vs torque curve and response time as part of the motor characteristics. The findings suggest that with an optimized simulation model, large amount of statistical analyses can be conducted in the simulation environment to provide practical information. This approach can be effectively used in early stage of product design, e.g. during the feasibility study.

In industry, most of the DOE are conducted using real‐test data. It is usually time consuming and cost inefficient. This paper combines mathematical modelling and statistical analysis to optimize a simulation model using DOE. The novel approach used in this paper can be applied in many other software optimization problems. It is expected that this approach will broaden the application of Six Sigma in industry.

The purpose of this paper is to obtain an accurate methodology for modelling and analysis of the permanent magnet synchronous generator connected to power electronic components.

This paper presents the methodology of the co-simulation of a permanent magnet synchronous generator. It combines Simulink, Maxwell and Simplorer software to demonstrate the electrical machine behaviour connected with the power electronics’ circuit. The finite element analysis performed on the designed machine exhibit a more accurate behaviour over simplified Simulink models. Results between both simulation and co-simulation are compared to measurements.

The co-simulation approach offers a more accurate depiction of the machine behaviour and its interaction with the non-linear circuits.

This paper focuses on the interior permanent magnet type of PMSG and its interaction with a passive rectifier (nonlinear circuit).

The advanced capabilities of the co-simulation method allow to analyse more variations (geometry, materials, etc.), and its interaction with non-linear circuits, than previous simulation techniques.

The co-simulation as a tool for analysis and design of systems interconnected with unconventional and conventional electrical machines and prototypes, and the comparison of the obtained results with classical analysis and design methods, against measurements obtained from the prototype.

The purpose of this research is to develop new techniques for component physical modeling for the dynamic simulation of integrated power systems.

A FE‐based phase variable model is proposed so as to achieve fast and accurate simulation. Such a model is established based on the nonlinear transient FE analysis, in order to take into consideration the harmonic effects due to the nonlinear magnetization property, magnetic circuit geometry as well as other design variations.

In the FE‐based phase variable model, the inductances are described as functions of the phase angle and the magnitude of winding currents, the rotor position and other operational parameters. They are obtained from the transient FE solutions, stored in tables, and retrieved during the simulation. The FE‐based phase variable model is implemented in Simulink in two ways. The first is the equation‐based block and the second is the circuit component‐based block. The FE‐based phase variable models of various electrical components in the power system were studied. This includes various types of rotating machines and transformers. Examination and application examples show the correctness and effectiveness of the proposed operational modeling procedures.

The developed FE‐based physical phase variable model is as accurate as the full FE model with much faster simulation speed. It will benefit the dynamic simulation of integrated power system. This combination of physical modeling and integrated dynamic simulation is original and represents an added value to the state‐of‐the‐art in this field.

The purpose of this paper is to analyze the performance of LCLC resonant converter (RC) with proportional integral controller and fuzzy gain scheduled proportional integral controller.

The drawbacks of series RC and parallel resonant converter (PRC) are explained using relevant references in Section 1 of this paper. The necessity of RCs and the merits of zero voltage and zero current switching are given in the Section 2. In Section 3, the modeling of LCLC RC using state space technique is done. In Section 4, the open loop analysis and performance evaluation of proportional integral controller, fuzzy gain scheduled proportional controller using MATLAB Simulink is obtained. The hardware specification is given and experimental results are taken for LCLC RC. In Section 5, conclusion of study is given.

The LCLC RC overcomes the drawbacks of series and PRC. The fuzzy gain scheduled proportional integral controller is suitable for load variations in RC.

The output of the converter is not affected with the load variations since the controller suggested in the paper works for load changes and can be a solution for load parameter deviation applications. Also performance of the RC is improved by the fast response of the proposed controller.

The brushless direct current motor (BLDCM) is widely accepted and adopted by many industries instead of direct current motors due to high reliability during operation. Brushless direct current (BLDC) has outstanding efficiency as losses that arise out of voltage drops at brushes and friction losses are eliminated. The main factor that affects the performance is temperature introduced in the internal copper core windings. The control of motor speed generates high temperature in BLDC operation. The high temperature is due to presence of ripples in the operational current. The purpose is to present an effective controlling mechanism for speed management and to improve the performance of BLDCM to activate effective management of speed.

The purpose is to present an optimal algorithm based on modified moth-flame optimization algorithm over recurrent neural network (MMFO-RNN) for speed management to improve the performance. The core objective of the presented work is to achieve improvement in performance without affecting the design of the system with no additional circuitry. The management of speed in BLDCM has been achieved through reduction or minimization of ripples encircled with torque of the motor. The implementation ends in two stages, namely, controlling the loop of torque and controlling the loop of speed. The MMFO-RNN starts with error optimization, which arises from both the loops, and most effective values have been achieved through MMFO-RNN protocol.

The parameters are enriched with Multi Resolution Proportional Integral and Derivative (MRPID) controller operation to achieve minimal ripples for the torque of BLDC and manage the speed of the motor. The performance is increased by adopting this technique approximately 12% in comparison with the existing methodology, which is the main contributions of the presented work. The outcomes are analyzed with the existing methodologies through MATLAB Simulink tool, and the comparative analyses suggest that better performance of the proposed system produces over existing techniques, and proto type model is developed and cross verifies the proposed system.

The MMFO-RNN starts with error optimization, which arises from both the loops, and most effective values have been achieved through MMFO-RNN protocol. The parameters are enriched with MRPID controller operation to achieve nil or minimal ripples and to encircle the torque of Brushless Direct Current and manage the speed.

The purpose of this study is to find the suitable trajectory path of the Numerical model of the Quadcopter. Quadcopters are widely used in various applications due to their compact size and ease of assembly. Because they are quite unstable, autonomous control systems would be used to overcome this problem. Modelling autonomous control is predominant as the research scope faces challenges because of its highly non-linear, multivariable system with 6 degree of freedom.

Quadcopters with antonym systems can operate in an unknown environment by overcoming unexpected disturbances. The first objective when designing such a system is to design an accurate mathematical model to describe the dynamics of the system. Newton’s law of motion was used to build the mathematical model of the system.

Establishment of the mathematical model and the physics behind a four propeller drone for the frame TAROT 650 carbon was done. Simulink model was developed based on the mathematical model for simulating the complete dynamics of the drone as well as location and gusts were included to check the stability.

The control response of the system was simulated numerically results are discussed. The trajectory path was found. The phases with their own parameters can be used to implement the mathematical model for another type of quadcopter model and achieve quick development.

The purpose of this study was to build and develop mathematical models correlating ambient conditions and electrical energy to the coefficient of performance (COP) of an air-source heat pump (ASHP) water heater. This study also aimed to design a simulation application to compute the COP under different heating up scenarios, and to calculate the mean significant difference under the specified scenarios by using a statistical method.

A data acquisition system was designed with respect to the required sensors and data loggers on the basis of the experimental setup. The two critical scenarios (with hot water draws and without hot water draws) during the heating up cycles were analyzed. Both mathematical models and the simulation application were developed using the analyzed data.

The predictors showed a direct linear relationship to the COP under the no successive hot water draws scenario, while they exhibited a linear relationship with a negative gradient to the COP under the simultaneous draws scenario. Both scenarios showed the ambient conditions to be the primary factor, and the weight of importance of the contribution to the COP was five times more in the scenario of simultaneous hot water draws than in the other scenario. The average COP of the ASHP water heater was better during a heating cycle with simultaneous hot water draws but demonstrated no mean significant difference from the other scenario.

There was a need to include other prediction parameters such as air speed, difference in condenser temperature and difference in compressor temperature, which could help improve model accuracy. However, these were excluded because of insufficient funding for the purchase of additional temperature sensors and an air speed transducer.

The research was conducted in a normal middle-income family home, and all the results were obtained from the collected data from the data acquisition system. Moreover, the experiment was very feasible because the conduction of the study did not interfere with the activities of the house, as occupants were able to carry out their activities as usual.

This paper attempts to justify the system efficiency under different heating up scenarios. Based on the mathematical model, the performance of the system could be determined all year round and the payback period could be easily evaluated. Finally, from the study, homeowners could see the value of the efficiency of the technology, as they could easily compute its performance on the basis of the ambient conditions at their location.

This is the first research on the mathematical modeling of the COP of an ASHP water heater using ambient conditions and electrical energy as the predictors and by using surface fitting multi-linear regression. Further, the novelty is the design of the simulation application for a Simulink environment to compute the performance from real-time data.

This paper aims to introduce the usage of sensitivity analysis (SA) for the problem of faults identification in three-phase induction motors (IMs). These motors are susceptible to different kinds of faults that should be detected in a proper time to keep the systems working in a safety environment.

One of the effective approaches for faults identifications, which is presented in the literature, is a model-based strategy. This strategy mainly depends on using a software model to make an identification decision. Therefore, this work intends to examine the model sensitivity towards variables’ variation. The SA toolbox of Matlab R2017b package is used for this purpose since the Matlab software is a well-known environment, and it is easy for a nonstatistical person to deal with it. As a study case, open-circuit and stator inter-turn faults in the stator windings of a three-phase IM have been chosen.

The results show that the model-based strategy is considerably speed up by up to 30% when neglecting the trivial model’s parameters with the same accurate identification decision as compared with the results of this strategy without using the SA.

The novelty of this work is summarized in devoting the usage of SA in the field of faults identification to enhance the speed of final decision.