1,720,994 research outputs found
Structural Design Evaluation of Integrated Rotor Hub and Shaft for a High-Speed Surface Mounted Radial Flux Permanent Magnet Synchronous Motor
No full textIncreasing the reliability and power density of a surface-mounted permanent magnet synchronous machine (SPMSM) is crucial due to the broader applications in the automotive and aerospace sectors. Concerns with such machines are that the overall rotating assembly experiences significant mechanical loads due to the rapid rotational speeds, making it exceptionally challenging to design the structural integrity of these components. This study's main objective is to offer a scientific justification for designing an integrated rotor hub and shaft through efficient Finite Element Modeling (FEM) and integration strategies to maximize the rotating assembly durability of a 150kW radial flux SPMSM spinning at 20,000 rpm. The optimization of integrated topology is evaluated based on a multiphysics platform, along with studies conducted on motor assembly eigen frequency. The integrated approach combining the shaft and rotor hub made of AISI 4340 solely saves 1.84kg, removing the necessity of standard components such as balancing end clamp plates, locknuts, and washers. Lower masses are proportional to lower centrifugal forces, reducing radial stress and promoting component/assembly stiffness
Rotor Durability Optimization by Means of Finite Element Multiphysics Analysis for High-Speed Surface Permanent Magnet Electric Machines
No full textTransport electrification is pushing the automotive and aerospace industries to enhance the power density of their powertrains further and further. One of the technologies currently pursued by some companies is high-speed electric motors. For instance, the new Model S Plaid motor by Tesla has a carbon-fiber wrapped IPM (Interior Permanent Magnet) rotor which can exceed 20,000rpm. The SPX88-120 made by Helix company shows a power density of about 18kW/kg at 50,000rpm. However, such high rotating speeds result is huge mechanical stresses in the entire rotating assembly, thus making the structural design of these parts extremely challenging. The primary goal of this paper is to provide a scientific rationale for the effective Finite Element Modeling (FEM) and integration strategies to maximize the rotating assembly durability of a 150kW radial flux SPMSM (surface-mounted permanent magnet synchronous motor) considered as a case-study. A non-linear simulation requires the input of a stress-strain curve and modified power law hardening study is conducted. The secondary goal of the paper is to analyze the thermal stress risers for multiphysics optimization of components. An analytical methodology to estimate the fatigue life for fully reverse cyclic loading is expressed. An extensive study on the eigen mode shape and frequency was performed to understand the dominant frequency of the system. A comparative performance study is conducted on shaft critical speeds, modal analysis, and stiffness interaction between components. Multiphysics optimization of topology is undertaken, the principal stresses in significant load-bearing components are reduced by 10 to 33%
Generalized Analytical Solution for N-Segment Axial Flux Halbach Arrays
No full textA generalized analytical solution for the 3-dimensional flux density field of an axial flux cylindrical Halbach Array is developed, based on existing work for 4-segment Halbach arrays. It is designed to reduce time, expense and knowledge associated with the traditional method of performing finite element analysis (FEA) to characterize such an array. It is applicable to the following applications: magnetic bearings, gears, couplings, generators and motors for electric vehicles. Halbach arrays of 4, 6 and 8-segment configurations are analyzed using the improved analytical method, then validated using FEA. The analytical equation is used to perform a sensitivity analysis on the 8-segment array
Multi-stress lifetime model of the winding insulation of electrical machines
No full textIn this paper, a novel multi-stress model which estimates the lifetime of the winding insulation relative to its duty cycle is proposed and investigated. With an adequate implementation of this model, then an electrical machine can be designed not only in terms of its performance requirements, but also considering the associated reliability and lifetime aspects. The determination of the model parameters is based on the results of accelerated thermo-mechanical ageing tests
A Low-Power Sigma-Delta Modulator for Healthcare and Medical Diagnostic Applications
Full text linkThis paper presents a switched-capacitor Sigma-Delta modulator designed in 90-nm CMOS technology, operating at 1.2-V supply voltage. The modulator targets healthcare and medical diagnostic applications where the readout of small-bandwidth signals is required. The design of the proposed A/D converter was optimized to achieve the minimum power consumption and area. A remarkable performance improvement is obtained through the integration of a low-noise amplifier with modified Miller compensation and rail-to-rail output stage. The manuscript also presents a set of design equations, from the small-signal analysis of the amplifier, for an easy design of the modulator in different technology nodes. The Sigma-Delta converter achieves a measured 96-dB dynamic range, over a 250-Hz signal bandwidth, with an oversampling ratio of 500. The power consumption is 30 μW, with a silicon area of 0.39 mm2
Bearing Current Modelling and Investigation in Axial Flux Permanent Magnet Synchronous Motors for Aerospace Applications
No full textThis paper investigates the bearing current issue of the Axial Flux Permanent Magnet Synchronous Motors (AFPMSM) used in aerospace. The case-study examined in this work is an eVTOL propulsion motor. The paper focuses on calculating the various parasitic components that relate to the bearing current phenomena in the AFPMSM. The simulation work presented in this paper provides a good understanding of the bearing current phenomenon and the sensitivity of the different parameters on the bearing current. According to the authors' best knowledge, this is the first time investigating the bearing current problem in AFPMSM. The paper also proposes a model for the bearing current simulation in this machine. Once the importance of the problem had been assessed, the bearing current possibility and the different solutions to overcome this problem have been investigated. The study also shows the pros and cons of each of these suggested solutions from the electrical point of view
Stability and performance analysis of a voltage controlled resistor circuit for wide band-gap device gate drivers
No full textWide band-gap devices are making inroads in the power converters scenario, and specific circuits to drive these components are actively under development. The purpose of this paper is to analyze, from the stability and dynamic performance point of view, a Voltage Controlled Power Resistor (VCPR), that can be used to control the gate resistance of the device driver with values over a continuous range. Parametric analysis, SPICE simulations and experimental outcomes are presented, in order to determine circuit characteristics. Results show that the proposed topology is stable under a wide range of electric parameters, and suggest that the circuit bandwidth can be tuned in order to benefit from the VCPR in a wide band-gap device gate driver
Estimation of equivalent thermal conductivity of impregnated slots in electric machines using Artificial Neural Network Surrogate Model
No full textThe accurate prediction of temperature within the slot of an electric motor stands as a crucial yet intricate task. It presents a challenge due to its computational demands, particularly when numerous iterations are requisite to identify the optimal configuration for a specific application. In response to this challenge, our study delves into the utilization of an Artificial Neural Network (ANN) as a tool to predict thermal conductivity within the motor slot with a high degree of accuracy. Our approach involves training the ANN using data derived from Finite Element Analysis (FEA)-based numerical simulations, which provide a robust foundation for modeling the thermal behavior of the motor slot. By harnessing the power of machine learning techniques embedded within the ANN, we aim to achieve a more efficient and effective means of temperature prediction compared to conventional methods. One of the key advantages of our proposed model is its ability to adapt and learn from complex and nonlinear relationships inherent in thermal conductivity estimation. This adaptability is especially beneficial in scenarios where traditional analytical models, as commonly found in existing literature, may fall short in capturing the intricacies of thermal behavior within the motor slot. Through rigorous testing and comparison with established analytical models, we demonstrate the superiority of our ANN-based approach in terms of accuracy and reliability. Our findings not only contribute to advancing the field of thermal management in electric motors but also highlight the potential of Artificial Neural Networks as a powerful tool for predictive modeling in complex engineering systems
Accurate Modeling of Ultra Low-Power Σ∆ Modulator
No full textThis paper presents a behavioural model suitable
for the simulation of low-power Sigma-Delta Modulators. Second-
order effects affecting the settling behaviour of the switched-
capacitor integrator was included, leading to improved accuracy.
Due to the oversampling mode of the converter, transistor-level
simulations are extremely time consuming. Accurate behavioural
models are thus mandatory in the first design phase of the
modulator, in particular when the involved analog blocks must
be optimized for minimum power consumption at some converter
resolution
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