scholarly journals Optimized Multiport DC/DC Converter for Vehicle Drivetrains: Topology and Design Optimization

2018 ◽  
Vol 8 (8) ◽  
pp. 1351 ◽  
Author(s):  
Duong Tran ◽  
Sajib Chakraborty ◽  
Yuanfeng Lan ◽  
Joeri Van Mierlo ◽  
Omar Hegazy
Keyword(s):  
Integrated Design ◽  
Optimization Method ◽  
Input Current ◽  
Optimized Design ◽  
Multiple Sources ◽  
Weight Losses ◽  
Multi Objective Genetic Algorithm ◽  
Reduce Development Time ◽  
Bandgap Semiconductors ◽  
Current Ripples

DC/DC Multiport Converters (MPC) are gaining interest in the hybrid electric drivetrains (i.e., vehicles or machines), where multiple sources are combined to enhance their capabilities and performances in terms of efficiency, integrated design and reliability. This hybridization will lead to more complexity and high development/design time. Therefore, a proper design approach is needed to optimize the design of the MPC as well as its performance and to reduce development time. In this research article, a new design methodology based on a Multi-Objective Genetic Algorithm (MOGA) for non-isolated interleaved MPCs is developed to minimize the weight, losses and input current ripples that have a significant impact on the lifetime of the energy sources. The inductor parameters obtained from the optimization framework is verified by the Finite Element Method (FEM) COMSOL software, which shows that inductor weight of optimized design is lower than that of the conventional design. The comparison of input current ripples and losses distribution between optimized and conventional designs are also analyzed in detailed, which validates the perspective of the proposed optimization method, taking into account emerging technologies such as wide bandgap semiconductors (SiC, GaN).

scholarly journals Optimized Design of a Sonar Transmitter for the High-Power Control of Multichannel Acoustic Transducers

Electronics ◽  
2021 ◽  
Vol 10 (21) ◽  
pp. 2682
Author(s):  
Byung-Hwa Lee ◽  
Ji-Eun Baek ◽  
Dong-Wook Kim ◽  
Jeong-Min Lee ◽  
Jae-Yoon Sim
Keyword(s):  
Control Method ◽  
Special Functions ◽  
Fitness Function ◽  
Integrated Design ◽  
Optimization Method ◽  
Current Control ◽  
Experimental Result ◽  
Optimized Design ◽  
Constant Power ◽  
Acoustic Transducers

For driving multichannel underwater acoustic transducers, the integrated design of the transmitter based on the analysis of the widely distributed impedance should be considered. Previous studies focused on either the matching circuit or the fast resonant tracking control. This paper proposes the design and control methods of a sonar transmitter based on the analysis of the impedance distribution. For the transmitter design, the optimization method based on the particle swarm optimization (PSO) algorithm is proposed for estimating the equivalent and matching circuit parameters. The equivalent circuits of the transducer are more precisely designed by using the measured data in both air and water. The fitness function proposed in the matching includes special functions, such as the limitation and parasitic inductances. A comparison of the experimental and simulation results shows that the optimized matching design improved the power factor, and was similar to the experimental result. For the transmitter control, the constant power and voltage control (CPVC) and instant voltage and current control (IVCC) methods are proposed for the variable impedance load. The impedance variation range affects the rated power and rated voltage of the transmitter, and the rating range determines the initial modulation index (MI) of the pulse-width modulation (PWM) control. To verify the control method, an experimental setup including the multichannel acoustic transducers was established. As a result, the constant power and constant voltage were verified with the proposed control, and the instant voltage and current control also worked in the event that the instant voltage or current exceed their threshold values.

scholarly journals Efficient Multi-Objective CFD-Based Optimization Method for a Scroll Distributor

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 377
Author(s):  
Damian Obidowski ◽  
Mateusz Stajuda ◽  
Krzysztof Sobczak
Keyword(s):  
Energy Savings ◽  
Axisymmetric Flow ◽  
Geometry Optimization ◽  
Optimization Method ◽  
Problem Size ◽  
Computational Point ◽  
Multi Objective ◽  
Flow Problems ◽  
Multi Objective Genetic Algorithm ◽  
Separation Zones

An efficient approach to the geometry optimization problem of a non-axisymmetric flow channel is discussed. The method combines geometrical transformation with a computational fluid dynamics solver, a multi-objective genetic algorithm, and a response surface. This approach, through geometrical modifications and simplifications allows transforming a non-axisymmetric problem into the axisymmetric one in some specific devices i.e., a scroll distributor or a volute. It results in a significant decrease in the problem size, as only the flow in a quasi-2D section of the channel is solved. A significantly broader design space is covered in a much shorter time than in the standard method, and the optimization of large flow problems is feasible with desktop-class computers. One computational point is obtained approximately eight times faster than in full geometry computations. The method was applied to a scroll distributor. For the case under analysis, it was possible to increase flow uniformity, eradicate separation zones, and increase the overall efficiency, which was followed by energy savings of 16% for the scroll. The results indicate that this method can be successfully applied for the optimization of similar problems.

A New PWM Strategy to Reduce the Inverter Input Current Ripples

2009 ◽  
Vol 24 (1) ◽  
pp. 172-180 ◽  
Author(s):  
J. Hobraiche ◽  
J.-P. Vilain ◽  
P. Macret ◽  
N. Patin
Keyword(s):  
Input Current ◽  
Current Ripples

Large-scale three-dimensional anisotropic topology optimization of variable-axial lightweight composite structures

2021 ◽  
pp. 1-15
Author(s):  
Yuqing Zhou ◽  
Tsuyoshi Nomura ◽  
Enpei Zhao ◽  
Kazuhiro Saitou
Keyword(s):  
Topology Optimization ◽  
Composite Structures ◽  
Large Scale ◽  
Volume Fraction ◽  
Three Dimensional ◽  
Optimization Method ◽  
Optimized Design ◽  
Adaptive Meshing ◽  
Design Synthesis ◽  
Fiber Placement

Abstract Variable-axial fiber-reinforced composites allow for local customization of fiber orientation and thicknesses. Despite their significant potential for performance improvement over the conventional multiaxial composites and metals, they pose challenges in design optimization due to the vastly increased design freedom in material orientations. This paper presents an anisotropic topology optimization method for designing large-scale, 3D variable-axial lightweight composite structures subject to multiple load cases. The computational challenges associated with large-scale 3D anisotropic topology optimization with extremely low volume fraction are addressed by a tensor-based representation of 3D orientation that would avoid the 2π periodicity of angular representations such as Euler angles, and an adaptive meshing scheme, which, in conjunction with PDE regularization of the density variables, refines the mesh where structural members appear and coarsens where there is void. The proposed method is applied to designing a heavy-duty drone frame subject to complex multi-loading conditions. Finally, the manufacturability gaps between the optimized design and the fabrication-ready design for Tailored Fiber Placement (TFP) is discussed, which motivates future work toward a fully-automated design synthesis.

Comparison of a Thermoacoustic Refrigerator Stack Performance: Mylar Spiral, Celcor Substrates and 3D Printed Stacks

2019 ◽  
Vol 27 (03) ◽  
pp. 1950021
Author(s):  
N. A. Zolpakar ◽  
N. Mohd-Ghazali
Keyword(s):  
Optimal Design ◽  
Temperature Difference ◽  
Cooling System ◽  
Coefficient Of Performance ◽  
Design Parameters ◽  
Optimized Design ◽  
Multi Objective Genetic Algorithm ◽  
Potential Alternative ◽  
3D Printed ◽  
Thermoacoustic Refrigeration

Although the thermoacoustic refrigeration (TAR) system has been recognized as a potential alternative environmentally cooling system, the low coefficient of performance (COP) has yet to make it marketable. One major factor contributing towards the low COP is the fabrication method applied to the stack component which is the most important component in the TAR. In this paper, comparison of the performance of a (i) 3D printed stack, (ii) a hand fabricated Mylar stack and (iii) an off-the-shelf Celcor substrates stack has been done; these being based on optimized design parameters using Multi-Objective Genetic Algorithm (MOGA). The performance is determined from the temperature attained at the cold end of the stack and the temperature difference across the stack. Experimental results showed that the 3D printed stack has the best performance by achieving a temperature, [Formula: see text]C at the cold end and a temperature difference of [Formula: see text]C across the stack, about 60% of the designed temperature difference even though the fabricated 3D printed stack deviated from the optimal design due to fabrication constraint as compared to that of the Mylar stack which was closer to the optimal design. This 3D printing of the stack promises a big potential in the improvement of the TAR performance because of the consistency achievable with the precise dimensions of the stack.

A Community Detection Method Based on Multi-Objective Optimization Method

2014 ◽  
Vol 571-572 ◽  
pp. 177-182 ◽  
Author(s):  
Lu Wang ◽  
Yong Quan Liang ◽  
Qi Jia Tian ◽  
Jie Yang ◽  
Chao Song ◽  
...  
Keyword(s):  
Community Detection ◽  
Detection Method ◽  
Optimization Method ◽  
Research Area ◽  
Multi Objective ◽  
Detection Algorithms ◽  
Multi Objective Genetic Algorithm ◽  
Community Fitness ◽  
Active Research ◽  
Active Research Area

Community detection in complex network has been an active research area in data mining and machine learning. This paper proposed a community detection method based on multi-objective evolutionary algorithm, named CDMOEA, which tries to find the Pareto front by maximize two objectives, community score and community fitness. Fast and Elitist Multi-objective Genetic Algorithm is used to attained a set of optimal solutions, and then use Modularity function to choose the best one from them. The locus based adjacency representation is used to realize genetic representation, which ensures the effective connections of the nodes in the network during the process of population Initialization and other genetic operator. Uniform crossover is introduced to ensure population’s diversity. We compared it with some popular community detection algorithms in computer generated network and real world networks. Experiment results show that it is more efficient in community detection.

Solid Mechanics Based Design and Optimization for Support Structure Generation in Stereolithography Based Additive Manufacturing

2015 ◽  
Author(s):  
Guanglei Zhao ◽  
Chi Zhou ◽  
Sonjoy Das
Keyword(s):  
Additive Manufacturing ◽  
Solid Mechanics ◽  
Search Algorithm ◽  
Pso Algorithm ◽  
Optimization Method ◽  
Optimized Design ◽  
Support Structures ◽  
Support Structure ◽  
Element Analysis ◽  
Structure Generation

Support structures are typically required to hold parts in place in various additive manufacturing processes. Design of support structure includes identifying both anchor locations and geometries. Extensive work has been done to optimize the anchor locations to reliably keep part in position, and minimize the contacting area as well as the total volume of the support structures. However, relatively few studies have been focused on the mechanical property analysis of the structure. In this paper, we proposed a novel design optimization method to identify the anchor geometry based on solid mechanics theory. Finite element analysis method is utilized to study the stress distribution on both the support structure and main part. Particle Swarm Optimization (PSO) algorithm with a novel constraining handling strategy is employed to optimize the design model. A gradient descent local search algorithm is utilized to quickly locate the global solution in the vicinity explored by PSO. The developed optimization framework is deployed on a bottom-up projection based Stereolithography process. The experimental results show that the optimized design can efficiently reduce the material used on support structure and marks left on the part.

Optimization Study of a Hybrid Solar Air Conditioner

2013 ◽  
Author(s):  
Ali Al-Alili ◽  
Yunho Hwang ◽  
Reinhard Radermacher
Keyword(s):  
Genetic Algorithm ◽  
Optimization Problems ◽  
Global Optimum ◽  
Optimized Design ◽  
Air Conditioner ◽  
Air Conditioners ◽  
Multi Objective Genetic Algorithm ◽  
Design Variables ◽  
Optimization Study ◽  
Systems Simulation

In order for the solar air conditioners (A/Cs) to become a real alternative to the conventional systems, their performance and total cost has to be optimized. In this study, an innovative hybrid solar A/C was simulated using the transient systems simulation (TRNSYS) program, which was coupled with MATLAB in order to carry out the optimization study. Two optimization problems were formulated with the following design variables: collector area, collector mass flow rate, storage tank volume, and number of batteries. The Genetic Algorithm (GA) was selected to find the global optimum design for the lowest electrical consumption. To optimize the two objective functions simultaneously, a Multi-Objective Genetic Algorithm (MOGA) was used to find the Pareto front within the design variables’ bounds while satisfying the constraints. The optimized design was also compared to a standard vapor compression cycle. The results show that coupling TRNSYS and MATLAB expands TRNSYS optimization capability in solving more complicated optimization problems.

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