scholarly journals A Multi-Objective Design Optimization for a Permanent Magnet Synchronous Machine with Hairpin Winding Intended for Transport Applications

Electronics ◽  
2021 ◽  
Vol 10 (24) ◽  
pp. 3162
Author(s):  
Mohammad Soltani ◽  
Stefano Nuzzo ◽  
Davide Barater ◽  
Giovanni Franceschini
Keyword(s):  
Design Optimization ◽  
Power Density ◽  
Electric Propulsion ◽  
Heat Dissipation ◽  
Proximity Effects ◽  
Electrical Machine ◽  
Potential Candidate ◽  
Electric Drives ◽  
Multi Objective ◽  
Good Heat

Nowadays, interest in electric propulsion is increasing due to the need to decarbonize society. Electric drives and their components play a key role in this electrification trend. The electrical machine, in particular, is seeing an ever-increasing development and extensive research is currently being dedicated to the improvement of its efficiency and torque/power density. Among the winding methods, hairpin technologies are gaining extensive attention due to their inherently high slot fill factor, good heat dissipation, strong rigidity, and short end-winding length. These features make hairpin windings a potential candidate for some traction applications which require high power and/or torque densities. However, they also have some drawbacks, such as high losses at high frequency operations due to skin and proximity effects. In this paper, a multi-objective design optimization is proposed aiming to provide a fast and useful tool to enhance the exploitation of the hairpin technology in electrical machines. Efficiency and volume power density are considered as main design objectives. Analytical and finite element evaluations are performed to support the proposed methodology.

Integrated Design and Multi-Objective Optimization of a Single Stage Heat-Pump Turbocompressor

2013 ◽  
Author(s):  
J. Schiffmann
Keyword(s):  
Design Optimization ◽  
High Efficiency ◽  
Integrated Design ◽  
Heat Pumps ◽  
Small Scale ◽  
Multi Objective Optimization ◽  
Design Constraints ◽  
Multi Objective ◽  
Wide Range ◽  
Standard Design

Small scale turbomachines in domestic heat pumps reach high efficiency and provide oil-free solutions which improve heat-exchanger performance and offer major advantages in the design of advanced thermodynamic cycles. An appropriate turbocompressor for domestic air based heat pumps requires the ability to operate on a wide range of inlet pressure, pressure ratios and mass flows, confronting the designer with the necessity to compromise between range and efficiency. Further the design of small-scale direct driven turbomachines is a complex and interdisciplinary task. Textbook design procedures propose to split such systems into subcomponents and to design and optimize each element individually. This common procedure, however, tends to neglect the interactions between the different components leading to suboptimal solutions. The authors propose an approach based on the integrated philosophy for designing and optimizing gas bearing supported, direct driven turbocompressors for applications with challenging requirements with regards to operation range and efficiency. Using previously validated reduced order models for the different components an integrated model of the compressor is implemented and the optimum system found via multi-objective optimization. It is shown that compared to standard design procedure the integrated approach yields an increase of the seasonal compressor efficiency of more than 12 points. Further a design optimization based sensitivity analysis allows to investigate the influence of design constraints determined prior to optimization such as impeller surface roughness, rotor material and impeller force. A relaxation of these constrains yields additional room for improvement. Reduced impeller force improves efficiency due to a smaller thrust bearing mainly, whereas a lighter rotor material improves rotordynamic performance. A hydraulically smoother impeller surface improves the overall efficiency considerably by reducing aerodynamic losses. A combination of the relaxation of the 3 design constraints yields an additional improvement of 6 points compared to the original optimization process. The integrated design and optimization procedure implemented in the case of a complex design problem thus clearly shows its advantages compared to traditional design methods by allowing a truly exhaustive search for optimum solutions throughout the complete design space. It can be used for both design optimization and for design analysis.

scholarly journals Reliability-Oriented Design of Inverter-Fed Low-Voltage Electrical Machines: Potential Solutions

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4144
Author(s):  
Yatai Ji ◽  
Paolo Giangrande ◽  
Vincenzo Madonna ◽  
Weiduo Zhao ◽  
Michael Galea
Keyword(s):  
Power Density ◽  
High Speed ◽  
High Performance ◽  
Low Voltage ◽  
Electrical Machines ◽  
Design Stage ◽  
Switching Frequency ◽  
Special Focus ◽  
Electrical Machine ◽  
Engineering Approach

Transportation electrification has kept pushing low-voltage inverter-fed electrical machines to reach a higher power density while guaranteeing appropriate reliability levels. Methods commonly adopted to boost power density (i.e., higher current density, faster switching frequency for high speed, and higher DC link voltage) will unavoidably increase the stress to the insulation system which leads to a decrease in reliability. Thus, a trade-off is required between power density and reliability during the machine design. Currently, it is a challenging task to evaluate reliability during the design stage and the over-engineering approach is applied. To solve this problem, physics of failure (POF) is introduced and its feasibility for electrical machine (EM) design is discussed through reviewing past work on insulation investigation. Then the special focus is given to partial discharge (PD) whose occurrence means the end-of-life of low-voltage EMs. The PD-free design methodology based on understanding the physics of PD is presented to substitute the over-engineering approach. Finally, a comprehensive reliability-oriented design (ROD) approach adopting POF and PD-free design strategy is given as a potential solution for reliable and high-performance inverter-fed low-voltage EM design.

scholarly journals Multi-Objective Multidisciplinary Design Optimization of a Robotic Fish System

2021 ◽  
Vol 9 (5) ◽  
pp. 478
Author(s):  
Hao Chen ◽  
Weikun Li ◽  
Weicheng Cui ◽  
Ping Yang ◽  
Linke Chen
Keyword(s):  
Design Optimization ◽  
Optimization Algorithm ◽  
Multidisciplinary Design Optimization ◽  
Robotic Fish ◽  
Multidisciplinary Design ◽  
Optimization Approach ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Cfd Method ◽  
The Individual

Biomimetic robotic fish systems have attracted huge attention due to the advantages of flexibility and adaptability. They are typically complex systems that involve many disciplines. The design of robotic fish is a multi-objective multidisciplinary design optimization problem. However, the research on the design optimization of robotic fish is rare. In this paper, by combining an efficient multidisciplinary design optimization approach and a novel multi-objective optimization algorithm, a multi-objective multidisciplinary design optimization (MMDO) strategy named IDF-DMOEOA is proposed for the conceptual design of a three-joint robotic fish system. In the proposed IDF-DMOEOA strategy, the individual discipline feasible (IDF) approach is adopted. A novel multi-objective optimization algorithm, disruption-based multi-objective equilibrium optimization algorithm (DMOEOA), is utilized as the optimizer. The proposed MMDO strategy is first applied to the design optimization of the robotic fish system, and the robotic fish system is decomposed into four disciplines: hydrodynamics, propulsion, weight and equilibrium, and energy. The computational fluid dynamics (CFD) method is employed to predict the robotic fish’s hydrodynamics characteristics, and the backpropagation neural network is adopted as the surrogate model to reduce the CFD method’s computational expense. The optimization results indicate that the optimized robotic fish shows better performance than the initial design, proving the proposed IDF-DMOEOA strategy’s effectiveness.

Application of Multi-Objective Genetic Algorithm (MOGA) for Design Optimization of Valve Timing at Various Engine Speeds

2011 ◽  
Vol 264-265 ◽  
pp. 1719-1724 ◽  
Author(s):  
A.K.M. Mohiuddin ◽  
Md. Ataur Rahman ◽  
Yap Haw Shin
Keyword(s):  
Genetic Algorithm ◽  
Design Optimization ◽  
Robust Design Optimization ◽  
Primary Concern ◽  
Variable Valve Timing ◽  
Valve Timing ◽  
Engine Valve ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Variable Valve

This paper aims to demonstrate the effectiveness of Multi-Objective Genetic Algorithm Optimization and its practical application on the automobile engine valve timing where the variation of performance parameters required for finest tuning to obtain the optimal engine performances. The primary concern is to acquire the clear picture of the implementation of Multi-Objective Genetic Algorithm and the essential of variable valve timing effects on the engine performances in various engine speeds. Majority of the research works in this project were in CAE software environment and method to implement optimization to 1D engine simulation. The paper conducts robust design optimization of CAMPRO 1.6L (S4PH) engine valve timing at various engine speeds using multiobjective genetic algorithm (MOGA) for the future variable valve timing (VVT) system research and development. This paper involves engine modelling in 1D software simulation environment, GT-Power. The GT-Power model is run simultaneously with mode Frontier to perform multiobjective optimization.

Sign in / Sign up

Export Citation Format

Share Document