vol. 4 núm. 1 (2023): transactions on energy systems and engineering applications

Editor-in-Chief Andres Marrugo discusses the role of Large Language Models, like ChatGPT, in academic publishing, highlighting some practical applications, potential pitfalls, and the ethical considerations required for their responsible use in academia.

The proposed fuel cell-based ultra-voltage gain boost converter offers an alternative to transformer-based topologies for achieving high voltage gain. While transformers can achieve high voltage gains, they come with drawbacks such as high cost, design complexity, and increased weight. In this article, a switched inductor circuit is introduced as an alternative solution to achieve high voltage gain. This circuit enhances overall system performance by reducing size, weight, and cost. Operating in a transformer-less topology, the converter boosts voltage levels while ensuring low voltage stress on the switching devices. The suggested design enables larger voltage gain values even at low duty ratios. The output of the fundamental boost converter serves as the input for the switched inductor circuit, effectively boosting the voltage level and supplying more voltage to the output side. This converter is particularly suitable for applications requiring ultra-voltage gain in electric vehicles, which offer reduced pollution compared to internal combustion engines. Moreover, the utilization of this topology reduces space requirements. The article presents a thorough investigation of the steady state operation in continuous conduction mode, and theoretical verification and MATLAB simulations demonstrate the performance and operation of the proposed converter.

In this work, we propose to use an optimal multiband filter with least mean square algorithm to design a signal conditioning module for denoising Electrocardiogram (ECG) signals contaminated with predominant noises. The module is implemented on a Field Programmable Gate Array (FPGA) hardware. The experimental results of the proposed module are investigated and compared using an ECGID database available on Physionet. Quantitative and qualitative analysis is performed using Signal to Noise Ratio (SNR), Mean Square Error (MSE), and quality indexes to assess the effectiveness of the module. The average values of SNR are 10.90124, and MSE is 0.001761, indicating the successful elimination of noises in the filtered ECG signal using the proposed module. The signal quality indexes also demonstrate that the relevant information for diagnosing cardiac functionality is preserved. Furthermore, the performance of the designed module is tested on ECG signals obtained from electrodes placed on the human body. The Spartan 3s500efg320-5 FPGA device is employed to implement the filter design module using the partial serial architecture.

This paper is concerned with the economic generation dispatch problem. It is a well-known fact that practical aspects of power plant equipment, as well as the objectives to be met, may result in a nonconvex, nondifferentiable model that poses difficulties to conventional mathematical programming methods. This paper proposes the use of metaheuristic Teaching-Learning-Based Optimization to overcome such difficulties. This metaheuristic is well known for requiring a few parameters and, most importantly, it does not require the tuning of problem-dependent parameters. The algorithm proposed in this work is parameter-free; that is, the few parameters required by the Teaching-Learning-Based Optimization method are set automatically based on the power system’s data. In addition, the handling of constraints, such as generators’ prohibited zones and the generator-load-loss power balance, is performed in a very efficient way. Simulation results are shown for power systems containing 3 to 40 generation units, and the results provided by the proposed method are shown and discussed based on comparisons with other metaheuristics and a mathematical programming technique.

This paper presents the application of higher-grade magnetic material for performance improvement of interior permanent magnet synchronous motors (IPMSM) for high-speed applications. The efficiency and weight of the motor are important performance parameters for high-speed applications. Efficiency improvement with simultaneous weight reduction is the key design issue for many specific applications. The main contribution of this work is to explore the possibility of using high-grade magnetic material for efficiency improvement with a simultaneous weight reduction of IPMSM motors. Three different standard rating motors were designed with the usual M19 material, and their performance was estimated. Finite element modelling and simulation was carried out to validate the initial design. For performance comparison, initial designs were regarded as reference designs. Design improvement was carried out with the application of high-grade magnetic material Hiperco 50A and its influence on the performance of IPMSM motors was analyzed. Three different standard ratings motors were considered in this work to analyze the effect of material in a wide range. Improved design was also validated with finite element modelling and simulation. It was observed that the efficiency is effectively improved with weight reduction using Hiperco 50A material in all three standard-rating IPMSM motors.

This paper presents a control scheme for DC-DC buck converters operating in Continuous Conduction Mode (CCM) that achieves fast and accurate regulation of the output voltage while reducing the computational burden on the control system. The study investigates the boundary-based control scheme for a buck converter and models the converter circuit as a Switched Dynamical System (SDS) using hybrid automaton due to its continuous and discrete states. The boundaries of these states are determined to enable the implementation of a fixed-frequency Pulse-Width Modulation (PWM) control scheme. The proposed control scheme was evaluated through simulation with variations in input voltage, load, and reference voltage. It was further analyzed for model mismatch due to parametric variations and parasitic parameters, which demonstrated its effectiveness and robustness under various operating conditions. The SDS approach for controlling the buck converter is simple, requires minimal mathematical calculations, and is free from modeling errors. The output voltage was stable under regulatory and servo problems, as well as sinusoidal input testing. The proposed scheme was compared with other conventional schemes and found superior in terms of steady-state and dynamic response. Additionally, integral compensation was introduced to counter parasitic parameters, which was found to be effective.