Percorrer por autor "Nascimento, Cecilia Pagnozzi do"
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- Active material cost optimization for three-phase induction motors of 2 and 4 polesPublication . Nascimento, Cecilia Pagnozzi do; Ferreira, Ângela P.; Bazzo, Thiago de Paula MachadoThis work was developed in collaboration with WEGeuro Portugal. It presents the optimization of 8 high-voltage induction motors, with the objective of reducing the active material costs of these machines. WEGeuro has been manufacturing high-performance motors for decades. The opportunity to reduce the motor costs was well appreciated, and the following work was originated. Reducing the motor cost increases the company’s profit and competition in the market, whereas keeping its well-known high-quality standard. The optimization was based on modifying specific design parameters of the motors with WEGeuro's internal analytical optimization software. Among the available algorithms, the one chosen was the Nelder-Mead Simplex. The process began with individual optimizations for each motor; then, the optimizations were performed collectively to create a default design for motors with the same number of poles and further reduce their final costs. The dimensions of the slots, the core length, and the stator windings were the main design variables changed during the optimization process because the active materials of the motor (aluminum, copper, and steel) are more influenced by these parameters. Regarding the constraints, the starting current, the efficiency, and the maximum magnetic induction were the most important in the analyses. The results of the analytical software were later verified using the finite element method in Ansys Maxwell software. The saturation phenomena and the harmonics were also analyzed. At the end, the active material costs of the motors had a significant reduction, respecting the imposed constraints and manufacturing limits. As an additional result, the efficiency of the machines was improved and, in most cases, the harmonic content was mitigated.
- Optimization approaches in electric machine design: insights from a bibliometric analysisPublication . Nascimento, Cecilia Pagnozzi do; Silvério, Ana Cristina; Baptista, Bruno; Carvalho, José Augusto; Bazzo, Thiago; Ferreira, Ângela P.Optimizing the design of electric machines is a complex task due to the large number of interrelated geometric and physical parameters that influence performance, efficiency, cost, and sustainability. Numerous deterministic and stochastic optimization techniques have been developed to address these challenges, each presenting distinct advantages and limitations. Deterministic approaches, though computationally efficient, often converge to local minima, while stochastic methods provide broader search capabilities at the expense of higher computational effort. Despite the growing application of optimization in electric machine design, a comprehensive bibliometric overview of this research area is lacking. This study aims to fill that gap by conducting a bibliometric analysis of optimization methods applied to electric machine design. Using data retrieved from the Web of Science (WoS) and analyzed through co-citation mapping with VOSviewer, 246 relevant articles were examined, resulting in a focused sample of 73 key studies. The analysis identifies the most frequently optimized machine types, the main optimization objectives, and the predominant methodologies employed in recent years. By addressing these dimensions, this work provides a conceptual reference framework to guide both academic researchers and industry professionals in selecting appropriate optimization strategies. The results also highlight emerging trends and future research opportunities, contributing to a deeper understanding of the evolution and intellectual structure of optimization in electric machine design.