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Reliability Based Multi-Objective De...

Vadamodala, Lavanya.

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Reliability Based Multi-Objective Design Optimization for Switched Reluctance Machines.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Reliability Based Multi-Objective Design Optimization for Switched Reluctance Machines./
作者:	Vadamodala, Lavanya.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:	203 p.
附註:	Source: Dissertations Abstracts International, Volume: 82-12, Section: B.
Contained By:	Dissertations Abstracts International82-12B.
標題:	Electromagnetics. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28642906
ISBN:	9798516072949

Reliability Based Multi-Objective Design Optimization for Switched Reluctance Machines.
Vadamodala, Lavanya.

Reliability Based Multi-Objective Design Optimization for Switched Reluctance Machines. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 203 p.

Source: Dissertations Abstracts International, Volume: 82-12, Section: B.

Thesis (Ph.D.)--The University of Akron, 2021.

This item must not be sold to any third party vendors.

In this thesis, a numerical model is developed for estimating the reliability of a Switched Reluctance Machine (SRM), and is then used in its design optimization. SRM design optimization is performed using the multi-objective surrogate optimization method. The multi-objective surrogate optimization method is chosen because of its ability to find a global solution within a given number of function evaluations. In this study, optimization considers reliability as one of the objectives or constraints to obtain an optimal design with high reliability. The optimum design should operate for the target lifetime (20000 hours) before maintenance or complete replacement. Since optimization using 2D FEA is slow, a modified analytical model is developed to more quickly obtain a suitable design. This model predicts flux linkage and torque for a given phase current and rotor position with minimum error. Tapering in the stator and rotor poles is introduced in addition to traditional rectangular poles to reduce the error in predicting flux linkage and torque at unaligned and partially aligned positions. An improved BH curve model with a knee adjustment factor is used to predict the magnetic characteristics of steel used in the machine. Assumptions and detailed derivation of models to estimate flux linkage, co-energy, and torque are included. Reliability is defined as the probability of a component or system operating for a given time. The probability of a component to operate is calculated based on its failure rate. The failure rate of the machine is obtained as the combination of the machine's base failure rate and the failure rate of the windings, rotor, and shaft. The reliability of the machine is obtained using state transition diagrams associated with the Markov model under normal and fault conditions. Along with the machine's reliability, Mean Time to Failure (MTTF) is also predicted for all operating conditions. Using the developed analytical and reliability models for SRM, optimization is performed in two stages. In first stage, sensitivity analysis is performed using the Taguchi methodology, where the sensitivity of objectives to change in each independent variable is calculated. Based on this, sensitive and non-sensitive variables are identified. In second stage, optimization using the multi-objective surrogate optimization method is carried out. Both single and double-level optimization methods are performed to look at the advantages and disadvantages of the optimization methods and optimum designs obtained based on the number of iterations and design performance. In this thesis, the reliability models are developed for a 32 kW SRM. This machine's target application is Front End Motor Generator (FEMG) to drive engine accessories in an electric truck. The optimum design obtained for the 32 kW SRM is verified with Finite Element Analysis (FEA), and the prototype is built. The performance of the machine is validated using experimental results from the testing of the prototype. The failure factor and MTTF are calculated using measurements. It was found that there is good agreement between predictions from simulation and experimental measurements.

ISBN: 9798516072949Subjects--Topical Terms:

3173223
Electromagnetics.
Subjects--Index Terms:

Reliability

Reliability Based Multi-Objective Design Optimization for Switched Reluctance Machines.
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