Multi-objective optimization of an Interior PM motor for a high-performance drive

Author(s):  
Nicola Bianchi ◽  
Dario Durello ◽  
Emanuele Fornasiero
2020 ◽  
Vol 13 (1) ◽  
pp. 317-317
Author(s):  
Rui Sun ◽  
Jie Guo ◽  
Qiang Wu ◽  
Zhuohan Zhang ◽  
Wenyan Yang ◽  
...  

Correction for ‘A multi-objective optimization-based layer-by-layer blade-coating approach for organic solar cells: rational control of vertical stratification for high performance’ by Rui Sun et al., Energy Environ. Sci., 2019, 12, 3118–3132.


2012 ◽  
Vol 166-169 ◽  
pp. 548-552
Author(s):  
Xian Jie Wang ◽  
Xun An Zhang ◽  
Yeda Lian

Structure optimization seeks to achieve the best performance for a structure while satisfying various constrains such as a given probability. In the traditional mathematical model of structure optimization, the goal and the restraint functions are given without considering the randomness of the structural system. In this paper, the random loads and strength are described by probability method, the structure reliability is considered as objective function. Using the genetic algorithm, the mega-sub controlled structural systems is multi-objective optimization designed based on the structure reliability under random excitation, combined with the probability density evolution method for evaluation of extreme value distribution. A low-cost and high-performance structure is getting.


2021 ◽  
Vol 35 (11) ◽  
pp. 1441-1442
Author(s):  
Sawyer Campbell ◽  
Yuhao Wu ◽  
Eric Whiting ◽  
Lei Kang ◽  
Pingjuan Werner ◽  
...  

Metasurfaces offer the potential to realize large SWaP (size, weight, and power) reduction over conventional optical elements for their ability to achieve comparable functionalities in ultrathin geometries. Moreover, metasurfaces designed with phase change materials offer the potential to go beyond what is achievable by conventional optics by enabling multiple functionalities in a single reconfigurable meta-device. However, designing a single metasurface geometry that simultaneously achieves multiple desired functionalities while meeting all bandwidth requirements and fabrication constraints is a very challenging problem. Fortunately, this challenge can be overcome by the use of state-of-the-art multi-objective optimization algorithms which are well-suited for the inverse-design of multifunctional meta-devices.


Author(s):  
Ayyoub Mehdizadeh Momen ◽  
Omar Abdelaziz ◽  
Kyle Gluesenkamp ◽  
Edward Vineyard ◽  
Michael Benedict

While there have been extensive studies on thermofluid characteristics of different magnetocaloric refrigeration systems, a conclusive optimization study using non-dimensional parameters which can be applied to a generic system has not been reported yet. In this study, a numerical model has been developed for optimization of active magnetic refrigerator (AMR). This model is computationally efficient and robust, making it appropriate for running the thousands of simulations required for parametric study and optimization. The governing equations have been non-dimensionalized and numerically solved using finite difference method. A parametric study on a wide range of non-dimensional numbers has been performed. While the goal of AMR systems is to improve the performance of competitive parameters including COP, cooling capacity and temperature span, new parameters called “AMR performance index-1” have been introduced in order to perform multi objective optimization and simultaneously exploit all these parameters. The multi-objective optimization is carried out for a wide range of the non-dimensional parameters. The results of this study will provide general guidelines for designing high performance AMR systems.


2019 ◽  
Vol 12 (10) ◽  
pp. 3118-3132 ◽  
Author(s):  
Rui Sun ◽  
Jie Guo ◽  
Qiang Wu ◽  
Zhuohan Zhang ◽  
Wenyan Yang ◽  
...  

This article analyzes and discusses a multi-objective optimization-based layer-by-layer blade-coating approach, which provides a new technology choice for large-scale manufacturing of organic solar cells.


Information ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 398
Author(s):  
Hejun Xuan ◽  
Lidan Lin ◽  
Lanlan Qiao ◽  
Yang Zhou

Manycast routing and spectrum assignment (RSA) in elastic optical networks (EONs) has become a hot research field. In this paper, the mathematical model and high efficient algorithm to solve this challenging problem in EONs is investigated. First, a multi-objective optimization model, which minimizes network power consumption, the total occupied spectrum, and the maximum index of used frequency spectrum, is established. To handle this multi-objective optimization model, we integrate these three objectives into one by using a weighted sum strategy. To make the population distributed on the search domain uniformly, a uniform design method was developed. Based on this, an improved grey wolf optimization method (IGWO), which was inspired by PSO (Particle Swarm Optimization, PSO) and DE (Differential Evolution, DE), is proposed to solve the maximum model efficiently. To demonstrate high performance of the designed algorithm, a series of experiments are conducted using several different experimental scenes. Experimental results indicate that the proposed algorithm can obtain better results than the compared algorithm.


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