Sensitivity Analysis of Manufacturing Tolerances in Permanent Magnet Synchronous Machines With Stator Segmentation

Kolb, Johann; Hameyer, Kay

doi:10.1109/tec.2020.3017279

Cited by 17 publications

(16 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The sensitivity analysis method is applied to study the mean torque produced by a PMSM dedicated to automotive traction, and also the most significant electromagnetic contributions responsible for its noise emissions at low speed. Therefore, this study supplements the rare studies of electric motor NVH sensitivity to dispersions performed in [2,9], with new results showing the effect of several geometric and control parameter variations in their design space and in their tolerance intervals on the prevailing NVH criteria of the considered motor. These results show that specific attention should be paid to robustness when dealing with the design of silent electric motors, because their NVH indicators can be very sensitive to slight parameter dispersions.…”

Section: Introductionmentioning

confidence: 62%

“…For this problem, this complete sensitivity estimation could not have been obtained using the existing sensitivity analysis methods. By employing methods from [2,[4][5][6][7][8][9], the effect of tolerances could have been estimated for a given design, but the dependence of this effect on the considered design would not have been brought to light, and some potential robustness issues could have been missed. Using global sensitivity analysis methods applying parameter variations which are large with respect to the tolerance interval spans, such as those used in [17,18], the high sensitivity of some criteria to parameter variations in their tolerance intervals would not have been raised: a good example is the parameter R HPM , which has a moderate effect on torque engine order 48 for large variations, but whose deviations can be very influent on this criterion for some designs and should therefore be considered in a robust design or optimisation approach to avoid robustness issues.…”

Section: Discussionmentioning

confidence: 99%

“…On the other hand, the sensitivity analyses of manufacturing tolerance, such as those performed by Kolb et al. in [2], usually only evaluate their effect for a fixed design. A global overview of the effect of parameter deviations on the criteria of interest for the entire design space is preferable before running a robust design or optimisation approach.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Two‐level global sensitivity analysis of the excitation contributions leading to acoustic noise in an electric motor for the purpose of robust optimisation

Jeannerot

Ouisse

Lanfranchi

et al. 2021

IET Electric Power Appl

View full text Add to dashboard Cite

This study presents a sensitivity analysis methodology used for electric motor design. This innovative approach evaluates both global effects of parameter variations in their design range and of parameter deviations in their tolerance intervals on design objectives. For the purpose of robust optimisation, this method helps to select the most influent design parameters and uncertain parameters, which are not necessarily the same. Suitable for any design approach, this method is particularly useful in dealing with objectives defined by non-linear and non-regular functions, such as electric motor acoustic criteria. In this study, the method is applied to the sensitivity evaluation of electromagnetic tangential excitations responsible for acoustic emissions in an electric motor. The sensitivity of output mean torque is also investigated. The sensitivity analysis shows that acoustic criteria appear generally more sensitive to parameter deviations than mean torque. Parameter deviations can be even more influent on acoustic criteria than larger parameter variations in their design range. As can be expected from the sensitivity results, the study eventually shows that the acoustic optimisation of the electric motor faces robustness issues.

show abstract

Section: Introductionmentioning

confidence: 62%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Two‐level global sensitivity analysis of the excitation contributions leading to acoustic noise in an electric motor for the purpose of robust optimisation

Jeannerot

Ouisse

Lanfranchi

et al. 2021

IET Electric Power Appl

View full text Add to dashboard Cite

show abstract

“…The weighted sum approach also proves to significantly increase the yield estimate ỸMC of the optimization problem in Eq. (22)(23)(24)(25)(26)(27)(28). The weight w is varied from 1 × 10 −3 to 5 × 10 −3 in four steps.…”

Section: Optimization Resultsmentioning

confidence: 99%

Multi-Objective Yield Optimization for Electrical Machines using Machine Learning

Huber¹,

Fuhrländer²,

Schöps³

2022

Preprint

View full text Add to dashboard Cite

This work deals with the design optimization of electrical machines under the consideration of manufacturing uncertainties. In order to efficiently quantify the uncertainty, blackbox machine learning methods are employed. A multiobjective optimization problem is formulated, maximizing simultaneously the reliability, i.e., the yield, and further performance objectives, e.g., the costs. A permanent magnet synchronous machine is modeled and simulated in commercial finite element simulation software. Four approaches for solving the multiobjective optimization problem are described and numerically compared, namely: ε-constraint scalarization, weighted sum scalarization, a multi-start weighted sum approach and a genetic algorithm.

show abstract

“…With the introduction of the stator segmentation, many advantages can be achieved, such as better cooling, which is achieved with axial segmentation, reduced weight of the machine by removing some sections of the stator, simplified winding process by allowing better automatization techniques, ability to use different materials (e.g. oriented steel) and increased slot copper fill factor (Aggarwal et al , 2020; Kolb and Hameyer, 2020; Rens et al , 2016; Yuan et al , 2014; Balluff et al , 2018; Shen et al , 2016; Camilleri and Mcculloch, 2021). By increasing the slot copper fill factor, the power density and efficiency can be increased due to the higher magneto-motive force (MMF).…”

Section: Introductionmentioning

confidence: 99%

Influence of stator segmentation on iron losses in PMSMs for traction applications

Garmut

Petrun

2022

COMPEL

View full text Add to dashboard Cite

Purpose This paper presents a comparative study of different stator-segmentation topologies of a permanent magnet synchronous machine (PMSM) used in traction drives and their effect on iron losses. Using stator segmentation allows one to achieve more significant copper fill factors, resulting in increased power densities and efficiencies. The segmentation of the stators creates additional air gaps and changes the soft magnetic material’s material properties due to the cut edge effect. The aim of this paper is to present an in-depth analysis of the influence of stator segmentation on iron losses. The main goal was to compare various segmentation methods under equal excitation conditions in terms of their influence on iron loss. Design/methodology/approach A transient finite element method analysis combined with an extended iron-loss model was used to evaluate discussed effects on the stator’s iron losses. The workflow to obtain a homogenized airgap length accounting for cut edge effects was established. Findings The paper concludes that the segmentation in most cases slightly decreases the iron losses in the stator because of the overall reduced magnetic flux density B due to the additional air gaps in the magnetic circuit. An increase of the individual components, as well as total power loss, was observed in the Pole Chain segmentation design. In general, segmentation did not change the total iron losses significantly. However, different segmentation methods resulted in the different distortion of the magnetic field and, consequently, in different iron loss compositions. The analysed segmentation methods exhibited different iron loss behaviour with respect to the operation points of the machine. The final finding is that analysed stator segmentations had a negligible influence on the total iron loss. Therefore, applying segmentation is an adequate measure to improve PMSMs as it enables, e.g. increase of the winding fill factor or simplifying the assembly processes, etc. Originality/value The influence of stator segmentation on iron losses was analysed. An in-depth evaluation was performed to determine how the discussed changes influence the individual iron loss components. A workflow was developed to achieve a computationally cheap homogenized model.

show abstract

Sensitivity Analysis of Manufacturing Tolerances in Permanent Magnet Synchronous Machines With Stator Segmentation

Cited by 17 publications

References 34 publications

Two‐level global sensitivity analysis of the excitation contributions leading to acoustic noise in an electric motor for the purpose of robust optimisation

Two‐level global sensitivity analysis of the excitation contributions leading to acoustic noise in an electric motor for the purpose of robust optimisation

Multi-Objective Yield Optimization for Electrical Machines using Machine Learning

Influence of stator segmentation on iron losses in PMSMs for traction applications

Contact Info

Product

Resources

About