Comparative study of the Tesla Model S and Audi e-Tron Induction Motors

Thomas, Robin; Husson, Hugo; Garbuio, Lauric; Gerbaud, Laurent

doi:10.1109/elma52514.2021.9503055

Cited by 26 publications

(6 citation statements)

References 8 publications

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“…One route that could be adopted to enhance the representation of AC loss variability at higher temperatures within the SSM is to calibrate the SSM at multiple operating frequencies and temperatures. As the available stators consisted of thicker laminations than those considered by Thomas et al [19], there is the potential for higher core losses to be present, leading to disagreement between the FEA and the experimental results.…”

Section: Discussionmentioning

confidence: 92%

“…Combined, the magnitude of strand and bundle losses within a stator winding are often defined using the 'AC loss factor' K AC , which represents the ratio of the AC to DC ohmic power loss at a given frequency and temperature. Whilst core losses can also be significant at high AC excitation frequencies, in modern electric vehicle traction motors core losses are a small proportion of the total machine loss when compared to winding copper losses due to the use of advanced electrical steels and thin laminations [19], [20].…”

Section: Experimental Ac Loss Estimationmentioning

confidence: 99%

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Designing for Conductor Lay and AC Loss Variability in Multistrand Stator Windings

Hoole

Mellor

Simpson

2023

IEEE Trans. on Ind. Applicat.

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Vehicle electrification places significant pressures on electric machine design due to the need for increased power densities and mass production. These two requirements couple when designing multistrand stator windings, which exhibit significant AC loss variability as a result of the random nature of the conductor lay within the stator slot caused by automated insert winding. This paper presents two prediction methods for AC loss variability to be deployed at the winding design stage. The first consists of an analytical approach, whilst the second constructs a 2D finite element analysis geometry that captures conductor lay characteristics. Comparison of predictions from both approaches to experimental AC loss measurements established that the proposed models capture the experimentally observed AC loss variability characteristics and that the analytical method is suitable for early design stages whilst the finite element approach should be adopted once the winding configuration is finalised.

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Section: Discussionmentioning

confidence: 92%

Section: Experimental Ac Loss Estimationmentioning

confidence: 99%

Designing for Conductor Lay and AC Loss Variability in Multistrand Stator Windings

Hoole

Mellor

Simpson

2023

IEEE Trans. on Ind. Applicat.

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“…This review discusses low-cost PMSM material and PM topology. In [21,22,23] non-magnet low-cost induction motor, both stator and rotor material losses are high which decreases the efficiency and fault tolerance. Which are the main drawback of this EV drive system.…”

Section: B Motivation Of Researchmentioning

confidence: 99%

Critical Aspects of Electric Motor Drive Controllers and Mitigation of Torque Ripple—Review

et al. 2022

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Electric vehicles (EVs) are playing a vital role in sustainable transportation. It is estimated that by 2030, Battery EVs will become mainstream for passenger car transportation. Even though EVs are gaining interest in sustainable transportation, the future of EV power transmission is facing vital concerns and open research challenges. Considering the case of torque ripple mitigation and improved reliability control techniques in motors, many motor drive control algorithms fail to provide efficient control. To efficiently address this issue, control techniques such as Field Orientation Control (FOC), Direct Torque Control (DTC), Model Predictive Control (MPC), Sliding Mode Control (SMC), and Intelligent Control (IC) techniques are used in the motor drive control algorithms. This literature survey exclusively compares the various advanced control techniques for conventionally used EV motors such as Permanent Magnet Synchronous Motor (PMSM), Brushless Direct Current Motor (BLDC), Switched Reluctance Motor (SRM), and Induction Motors (IM). Furthermore, this paper discusses the EV-motors history, types of EVmotors, EV-motor drives powertrain mathematical modelling, and design procedure of EV-motors. The hardware results have also been compared with different control techniques for BLDC and SRM hub motors. Future direction towards the design of EV by critical selection of motors and their control techniques to minimize the torque ripple and other research opportunities to enhance the performance of EVs are also presented.

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“…There is a growing interest in employing highperformance electric motors such as induction motors in electric vehicles (EVs) applications due to their lower cost; robust structure; wider operating speed range; and higher reliability [1]. These motors can serve as a practical solution for small and regular EVs, such as electric micro cars and three-wheelers, utilizing small traction electric motors (e-motors) with power ratings between 7 to 15 kW [2] and Audi e-tron 140 kW [3]. However, induction motors have lower power and torque density and efficiency as compared to permanent magnet synchronous motors [4].…”

Section: Introductionmentioning

confidence: 99%

Magnetic Field-Based Induction Machine Modeling Incorporating Space and Time Harmonic Effects

Guruwatta Vidanalage,

Lombardi,

Tjong

et al. 2024

IEEE Access

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Integration of the impacts of time and space harmonics simultaneously during the design stages of inverter-fed induction machines (IMs) is crucial for the accurate calculation of electromagnetic torque (EM) and ripples. Traditional magnetic field-based models offer an analytical approach for determining the EM torque in IMs by calculating inductances. However, by assuming infinite core permeabilities, these models neglect the impact of the core magnetomotive force (MMF) drops due to the difficulties in accurately calculating these drops and the impracticality of isolating the contribution from each phase, which is essential for inductances calculations. These factors contribute to deficiencies in this modeling approach, which become more noticeable when the combined impacts of time and space harmonics on MMF drop calculations are also disregarded. Therefore, this paper introduces a novel magnetic-field-based model to predict the torque and torque ripples of inverter-fed induction motors by addressing the above limitations. This involves modifying the turns and winding function, and calculating the core MMF drops based on the timely variation of non-sinusoidal core flux densities, considering their major and minor flux-density loop effects. Consequently, the associated energy is used to calculate the net available energy, thereby enhancing torque calculations. Compared to the experimental results obtained from an 11kW prototyped induction motor, the proposed model exhibits notable enhancements, achieving average accuracies of 96.4% for average torque and 94.51% for torque ripples, in contrast to the respective traditional model accuracies, 81.1% and 45.1%.

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Comparative study of the Tesla Model S and Audi e-Tron Induction Motors

Cited by 26 publications

References 8 publications

Designing for Conductor Lay and AC Loss Variability in Multistrand Stator Windings

Designing for Conductor Lay and AC Loss Variability in Multistrand Stator Windings

Critical Aspects of Electric Motor Drive Controllers and Mitigation of Torque Ripple—Review

Magnetic Field-Based Induction Machine Modeling Incorporating Space and Time Harmonic Effects

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