scholarly journals Minimum Set of Rotor Parameters for Synchronous Reluctance Machine and Improved Optimization Convergence via Forced Rotor Barrier Feasibility

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2744
Author(s):  
Branko Ban ◽  
Stjepan Stipetic ◽  
Tino Jercic
Keyword(s):  
Differential Evolution Algorithm ◽  
Optimization Procedure ◽  
Permanent Magnet Machines ◽  
The Novel ◽  
Geometric Complexity ◽  
Torque Density ◽  
Reluctance Machine ◽  
Evolution Algorithm ◽  
Lower Torque ◽  
Modern Machine

Although rare earth materials are the critical component in high torque density permanent magnet machines, their use has historically been a commercial risk. The alternatives that have been in the recent industry focus are synchronous reluctance machines (SyRM). They have lower torque density but also relatively low material cost and higher overload capability. Multi-layer IPM and SyRM machines have significant geometric complexity, resulting in a high number of parameters. Considering that modern machine design requires the use of optimization algorithms with computational load proportional to the number of parameters, the whole design process can take several days. This paper presents novel SyRM parameterization with reduced number of parameters. Furthermore, the paper introduces the novel forced feasibility concept, applied on rotor barrier parameters, resulting in improved optimization convergence with overall optimization time reduced by 12.3%. Proposed approaches were demonstrated using optimization procedure based on the existing differential evolution algorithm (DE) framework.

scholarly journals Comparative stable walking gait optimization for small-sized biped robot using meta-heuristic optimization algorithms

2018 ◽  
Vol 40 (4) ◽  
pp. 407-424
Author(s):  
Tran Thien Huan ◽  
Ho Pham Huy Anh
Keyword(s):  
Humanoid Robot ◽  
Differential Evolution Algorithm ◽  
Biped Robot ◽  
The Novel ◽  
Biped Robots ◽  
Walking Gait ◽  
Gait Parameters ◽  
Lift Height ◽  
Evolution Algorithm ◽  
Gait Optimization

This paper proposes a new way to optimize the biped walking gait design for biped robots that permits stable and robust stepping with pre-set foot lifting magnitude. The new meta-heuristic CFO-Central Force Optimization algorithm is initiatively applied to optimize the biped gait parameters as to ensure to keep biped robot walking robustly and steadily. The efficiency of the proposed method is compared with the GA-Genetic Algorithm, PSO-Particle Swarm Optimization and Modified Differential Evolution algorithm (MDE). The simulated and experimental results carried on the prototype small-sized humanoid robot demonstrate that the novel meta-heuristic CFO algorithm offers an efficient and stable walking gait for biped robots with respect to a pre-set of foot-lift height value.

scholarly journals Formulation and Solution of an Inverse Reliability Problem to Simulate the Dynamic Behavior of COVID-19 Pandemic

2021 ◽  
Vol 22 (1) ◽  
pp. 91-107
Author(s):  
F. S. Lobato ◽  
G. M. Platt ◽  
G. B. Libotte ◽  
A. J. Silva Neto
Keyword(s):  
Dynamic Behavior ◽  
Differential Evolution Algorithm ◽  
Iteration Process ◽  
Real Data ◽  
The Novel ◽  
Design Variables ◽  
Different Types ◽  
Evolution Algorithm ◽  
Novel Coronavirus ◽  
Optimization Loop

Different types of mathematical models have been used to predict the dynamic behavior of the novel coronavirus (COVID-19). Many of them involve the formulation and solution of inverse problems. This kind of problem is generally carried out by considering the model, the vector of design variables, and system parameters as deterministic values. In this contribution, a methodology based on a double loop iteration process and devoted to evaluate the influence of uncertainties on inverse problem is evaluated. The inner optimization loop is used to find the solution associated with the highest probability value, and the outer loop is the regular optimization loop used to determine the vector of design variables. For this task, we use an inverse reliability approach and Differential Evolution algorithm. For illustration purposes, the proposed methodology is applied to estimate the parameters of SIRD (Susceptible-Infectious-Recovery-Dead) model associated with dynamic behavior of COVID-19 pandemic considering real data from China's epidemic and uncertainties in the basic reproduction number (R0). The obtained results demonstrate, as expected, that the increase of reliability implies the increase of the objective function value.

scholarly journals Optimization Methodology of PMSM Cooled by External Convection in Aircraft Propulsion

Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 3975
Author(s):  
Luigi Pio Di Noia ◽  
Luigi Piegari ◽  
Renato Rizzo
Keyword(s):  
Electric Propulsion ◽  
Differential Evolution Algorithm ◽  
Optimization Procedure ◽  
Permanent Magnet Motors ◽  
Aircraft Emissions ◽  
Element Analysis ◽  
Electrical Drives ◽  
Evolution Algorithm ◽  
Optimization Methodology ◽  
Aircraft Propulsion

Nowadays, the reduction of aircraft emissions is one of the industrial targets with a horizon time until 2050. The recent progresses in electrical drives give the opportunity to modify the aircraft propulsion based on thermal engine or gas turbine to a hybrid/full electric one. Some problems must be solved: weight, reliability, and the choice of the best configuration for the electric propulsion. One of the most important aspects to solve is the thermal behavior of power converters and electric motors. This paper proposes an optimization procedure for the design of surface permanent magnet motors used for the aircraft propulsion: the aim of the paper is to investigate the possibility of cooling the motor with only the air flow due to the aircraft speed. The optimization procedure has been solved with the integration of analytical model and finite element analysis and using a differential evolution algorithm.

Study of the Influence of the Underflow Diameter on the Separation Process of an Optimized Hydrocyclone for Concentration Purposes

2017 ◽  
Vol 899 ◽  
pp. 136-141 ◽  
Author(s):  
S.M. Gonçalves ◽  
Yanne Novais Kyriakidis ◽  
Luiz Gustavo Martins Vieira ◽  
Marcos Antonio de Souza Barrozo
Keyword(s):  
Laboratory Experiments ◽  
Differential Evolution Algorithm ◽  
Optimization Procedure ◽  
Separation Process ◽  
Total Efficiency ◽  
Cfd Simulations ◽  
Evolution Algorithm ◽  
Filtration Effect ◽  
Solid Liquid ◽  
Solid Liquid Separation

Hydrocyclones are equipment typically used in solid-liquid separation. Such equipment can be used with the purpose of classifying particles or concentrating suspensions. In this context, a new filtering hydrocyclone was conceived through Surface Response and Differential Evolution Algorithm techniques in order to optimize the Euler’s number. Based on this optimized geometry, the aim of the present paper was to verify the influence of the underflow diameter on the overall separation process at 147 kPa on the same optimized hydrocyclone geometry, but without the filtration effect, by performing laboratory experiments and CFD simulations using the commercial software Fluent®. The results showed that the use of the smallest underflow diameter increased up to 44% (v/v) the concentration of the underflow stream, compared to the suspension initially fed, with an Euler’s number of 862. Despite a small decrease (14%) in the total efficiency and an increase from 12.01 to 16.05 of the reduced cut size diameter, compared to the underflow diameter originally used in the optimization procedure, the benefits of recovering liquid by reducing the underflow diameter outweigh these disadvantages.

scholarly journals Color Image Quantization Algorithm Based on Self-Adaptive Differential Evolution

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Qinghua Su ◽  
Zhongbo Hu
Keyword(s):  
Differential Evolution ◽  
Color Image ◽  
Differential Evolution Algorithm ◽  
Optimization Methods ◽  
Particle Swarm Algorithm ◽  
The Novel ◽  
Image Quantization ◽  
Adaptive Differential Evolution ◽  
Evolution Algorithm ◽  
Self Adaptive

Differential evolution algorithm (DE) is one of the novel stochastic optimization methods. It has a better performance in the problem of the color image quantization, but it is difficult to set the parameters of DE for users. This paper proposes a color image quantization algorithm based on self-adaptive DE. In the proposed algorithm, a self-adaptive mechanic is used to automatically adjust the parameters of DE during the evolution, and a mixed mechanic of DE andK-means is applied to strengthen the local search. The numerical experimental results, on a set of commonly used test images, show that the proposed algorithm is a practicable quantization method and is more competitive thanK-means and particle swarm algorithm (PSO) for the color image quantization.

Solving Problems in Chaos Control though an Differential Evolution Algorithm with Region Zooming

2011 ◽  
Vol 110-116 ◽  
pp. 5048-5056 ◽  
Author(s):  
Fei Gao ◽  
Yi Bo Qi ◽  
Qiang Yin ◽  
Jia Qing Xiao
Keyword(s):  
Differential Evolution ◽  
Chaos Control ◽  
Uniform Design ◽  
Differential Evolution Algorithm ◽  
Initial Population ◽  
The Novel ◽  
Objective Functions ◽  
Unstable Periodic Orbits ◽  
Evolution Algorithm ◽  
Best Parameters

In this paper, a novel scheme is propose to solve the problems in chaos control via a nonnegative multi–modal nonlinear optimization, which finds the unstable periodic orbits and best parameters of chaos system such that the objective function is minimized. The novel scheme embeds with a differential evolution algorithm consisting of techniques in three aspects: uniform design to the initial population, deflection and stretching to the objective functions, and the region zooming self–adaptively, which result in a much more effective searching mechanism with fine equilibrium between exploitation and exploration. To exhibit the new scheme’s performance, the experiments done to Hénon, Chen and Lü system are given, and the simulations done show that the method has better adaptability, dependability and robustness.

scholarly journals Electromagnetic Performance of the Novel Hybrid-Pole Permanent Magnet Machines for High Peak Torque Density

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 220384-220393
Author(s):  
Yu-Xi Liu ◽  
Ji-Wei Cao ◽  
Qin-He Gao ◽  
Zhi-Hao Liu ◽  
Ya-Chao Lu ◽  
...  
Keyword(s):  
Permanent Magnet ◽  
Peak Torque ◽  
High Peak ◽  
Permanent Magnet Machines ◽  
The Novel ◽  
Torque Density ◽  
Electromagnetic Performance

Differential Evolution Algorithm In Models Of Technical Optimization

2021 ◽  
Author(s):  
Roman Knobloch ◽  
Jaroslav Mlynek
Keyword(s):  
Differential Evolution ◽  
Cost Function ◽  
Optimization Algorithms ◽  
Differential Evolution Algorithm ◽  
Gradient Methods ◽  
Optimization Procedure ◽  
Acceptable Solution ◽  
Optimization Task ◽  
Evolution Algorithm ◽  
The Cost

At present, evolutionary optimization algorithms are increasingly used in the development of new technological processes. Evolutionary algorithms often allow the optimization procedure to be performed even in cases where classical optimization algorithms fail (e.g. gradient methods) and where an acceptable solution is sufficient to solve the optimization task. The article focuses on possibilities of using a differential evolution algorithm in the optimization process. This algorithm is often referred to in the literature as a global optimization procedure. However, we show by means of a practical example that the convergence of the classic differential algorithm to the global extreme is not generally assured and is largely dependent on the specific cost function. To remove this weakness, we designed a modified version of the differential evolution algorithm. The improved version, named the modified differential evolution algorithm, is described in the article. It is possible to prove asymptotic convergence to the global minimum of the cost function for the modified version of the algorithm.

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