Dc-to-Dc converter power-train optimization for maximum efficiency

Wilson, Thomas G.; Whelan, Edward W.; Rodriguez, Robert; Dishman, John M.

doi:10.1109/pesc.1981.7083637

Cited by 4 publications

(2 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Particular focus was given to trade-off between efficiency and weight, as the switching frequency of the converter was varied between 30 and 120 kHz. Despite, the frequency was varied up to 2 MHz; the simple loss models used are inaccurate at the high end of the frequency range in Wilson et al (1983). In order to obtain a practical converter optimization approach suitable for industrial applications, several improvements to the previous researches were developed in Ridley et al (1990).…”

Section: Power Converter Design Optimizationmentioning

confidence: 99%

Bi-objective sizing optimization of power converter using genetic algorithms

Mejbri

Ammous

Abid

et al. 2013

COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering

View full text Add to dashboard Cite

Purpose -This paper aims to focus on the trade-off between losses and converter cost. Design/methodology/approach -The continual development of power electronic converters, for a wide range of applications such as renewable energy systems (interfacing photovoltaic panels via power converters), is characterized by the requirements for higher efficiency and lower production costs. To achieve such challenging objectives, a computer-aided design optimization based on genetic algorithms is developed in Matlab environment. The elitist non-dominated sorting genetic algorithm is used to perform search and optimization, whereas averaged models are used to estimate power losses in different semiconductors devices. The design problem requires minimizing the losses and cost of the boost converter under electrical constraints. The optimization variables are, as for them, the switching frequency, the boost inductor, the DC capacitor and the types of semiconductor devices (IGBT and MOSFET). It should be pointed out that boost topology is considered in this paper but the proposed methodology is easily applicable to other topologies. Findings -The results show that such design methodology for DC-DC converters presents several advantages. In particular, it proposes to the designer a set of solutions -as an alternative of a single one -so that the authors can choose a posteriori the adequate solution for the application under consideration. This then allows the possibility of finding the best design among all the available choices. Furthermore, the design values for the selected solution were obtainable components. Originality/value -The authors focus on the general aspect of the discrete optimization approach proposed here. It can also be used by power electronics designers with the help of additional constraints in accordance with their specific applications. Furthermore, the use of such non-ideal average models with the multi-objective optimization is the original contribution of the paper and it has not been suggested so far.

show abstract

Section: Power Converter Design Optimizationmentioning

confidence: 99%

Bi-objective sizing optimization of power converter using genetic algorithms

Mejbri

Ammous

Abid

et al. 2013

COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering

View full text Add to dashboard Cite

show abstract

“…In some traditional methods, mathematical approximations are used to find the analytical expression of optimal designs. For example, the numerical methods include an additional interactive function and an augmented Lagrangian function in the analytical equations to optimize the design accuracy of a switching regulator [5], [6], [7]. Using this method, the converter design can be only optimized for the desired performance and the optimal design parameters are bounded.…”

Section: Introductionmentioning

confidence: 99%

Artificial Neural Networks-Based Multi-Objective Design Methodology for Wide-Bandgap Power Electronics Converters

Rajamony

Wang

Calderon-Lopez

et al. 2022

IEEE Open J. Power Electron.

View full text Add to dashboard Cite

Design methodology of power electronics converters is critical to fully explore the potential of wide-bandgap power semiconductors at the converter level. However, existing design methods largely rely on complex mathematical models which significantly increases the computational time, complexity and further leads to problems including poor constraint handling capabilities, inaccurate design, difficult parameter tuning and inadequate problem dimension. These all could generate suboptimal designs that make the whole design process meaningless. To overcome the aforementioned problems, in this paper, an artificial neural network (ANN)-based multi-objective design approach is proposed, which offers significant advantages in reducing the repetitive usage of complex mathematical models and hence the computational time of design. The computational time was reduced by up to around 78% and 67% compared to the numerical modeling and geometric program (GP) methods as validated through a hardware design process. The proposed method was implemented in MATLAB/Simulink to design a 1kW single-phase inverter, resulting in a design with an optimized efficiency (98.4%) and power density (4.57kW/dm 3 ). The accuracy of the design is verified through experimental prototyping and the measured efficiency and power density are 98.02% and 4.54kW/dm 3 , respectively, so the errors of efficiency and power density are both less than 1%.

show abstract

Practical nonlinear design optimization tool for power converter components

Ridley

Lee

1987

1987 IEEE Power Electronics Specialists Conference

View full text Add to dashboard Cite

Dc-to-Dc converter power-train optimization for maximum efficiency

Cited by 4 publications

References 6 publications

Bi-objective sizing optimization of power converter using genetic algorithms

Bi-objective sizing optimization of power converter using genetic algorithms

Artificial Neural Networks-Based Multi-Objective Design Methodology for Wide-Bandgap Power Electronics Converters

Practical nonlinear design optimization tool for power converter components

Contact Info

Product

Resources

About