Power Losses in Outside-Spin Brushless D.C. Motor

Andrada, P.; Burgués, Marcel Torrent; Benavides, Josep Ignasi Perat; Molina, Balduino Blanqué

doi:10.24084/repqj02.320

Cited by 15 publications

(9 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The second term represents the friction losses in radial shaft seals and is an empiric first-order approximation on manufacturer data, where S is the amount of seals in the drivetrain. The third term models the windage losses for an outer rotor machine [15] where D is the outside rotor diameter Fig. 1.…”

Section: Mechanical Lossesmentioning

confidence: 99%

Displacement of the maximum power point caused by losses in wind turbine systems

et al. 2016

View full text Add to dashboard Cite

Keywords:Wind energy Maximum power point tracking Modeling of losses Power coefficient Energy yield a b s t r a c tThe energy yield of wind turbines is to a large extent determined by the performance of the Maximum Power Point Tracking (MPPT) algorithm. Conventionally, they are programmed to maximize the turbines power coefficient. However, due to losses in the generator and converter, the true optimal operating point of the system shifts. This effect is often overlooked, which results in a decreased energy yield. Therefore, in this paper, the wind turbine system is modeled including the dominant loss components to investigate this effect in detail. By simulations and experiments on a wind turbine emulator, it is shown that the location of the maximum power point is significantly affected for low wind speeds. For high wind speeds, the effect is less pronounced. The parameter of interest is the increase in yearly energy output with respect to the classical MPPT method, which is calculated in this paper by including a Rayleigh wind speed distribution. For typical average wind speeds, the energy yield can increase with 1 e2%. There is no cost associated with operating the turbine in the overall MPP, making it worthwhile to include this effect. The findings are implemented in an MPPT algorithm to validate the increased performance in a dynamic situation.

show abstract

Section: Mechanical Lossesmentioning

confidence: 99%

Displacement of the maximum power point caused by losses in wind turbine systems

et al. 2016

View full text Add to dashboard Cite

show abstract

“…An explicit description of the determination process of the power losses equations based on the barycenter method is reported in [6]. The expressions for these power losses are based on the equations provided in [4], [8], [9] and reformulated afterwards in connection to the barycenter method in order to calculate them for each region as follows:  Mechanical losses [4], [8] due to friction phenomena :…”

Section: B)mentioning

confidence: 99%

“…with the friction coefficient (N.m/rad), the number of points in the region, Ω the corresponding rotational speed (rad/s) of the region in cause, and 〈•〉 denotes the mean value in the region.  Copper losses [8] caused by the induced currents in the stator windings : 4 (3) where represents the phase resistance (ohm) and , the phase current (A) of the barycenter for the considered region.  Iron losses [8] based on the magnetic properties of the materials :…”

Section: B)mentioning

confidence: 99%

Design of a brushless DC permanent-magnet generator for use in micro-wind turbine applications

Laczko

Brisset

Radulescu

2018

JAE

View full text Add to dashboard Cite

This paper deals with the optimal design of a direct-driven brushless DC permanent-magnet (BLDCPM) generator over a long-term wind speed cycle operation. Such a large wind speed profile causes long processing time in the search of the optimal solution, therefore a simplification method of the profile based on an original barycenter method is proposed and applied to the power losses computation of the wind energy system. As a result, the optimization methodology relies on two modeling levels different in simulation time and approach and is based on a constrained mono-objective problem with adequate optimization strategy and algorithm that aims at reducing the global system power losses for the given wind speed profile while finding the optimal geometrical and electrical features of the BLDCPM wind generator.

show abstract

“…The mechanical losses PMech is manly caused by friction losses in bearings can be determined using the following equation (36) 23 , where nbear. is the number of bearings, W is the motor weight, and Nr is the motor rotational speed.…”

Section: Mechanical Lossesmentioning

confidence: 99%

A Parametric Environment for Weight and Sizing Prediction of Motor/Generator for Hybrid Electric Propulsion

Miyairi¹,

Perullo²,

Mavris³

2015

51st AIAA/SAE/ASEE Joint Propulsion Conference

View full text Add to dashboard Cite

In response to the growing aviation fuel demands and environmental concerns, NASA has set aggressive goals for individual aircraft to improve environmental performance for three technology generations (N+1, N+2, and N+3). After setting these goals, numerous advanced concept aircrafts have been proposed in an effort to accomplish these requirements. One of these projects which helps to meet the N+3 is the Subsonic Ultra Green Aircraft Research (SUGAR) project. Through the SUGAR, the team concluded that hybrid electric propulsion concept ("hFan" proposed by General Electric) has a potential to meet the N+3 requirements. One of the key components in the design of this new architecture is an electric motor which is embedded within the engine. At the conceptual design phase, high-fidelity engine weight and size prediction including new architecture is crucial to design aircraft. In this study, a Switched Reluctance Motor (SRM) is selected as a primary application because the SRM has several advantages for aircraft engine component. The goal of this research is to create the SRM weight and sizing prediction models based on a semi-empirical approach within the Numerical Propulsion System Simulation (NPSS) and Weight Analysis for Turbine Engines(WATE++) environment. The primary benefit of utilizing NPSS/WATE++ for the SRM weight and sizing estimation is that the maximum and minimum size of the SRM can be determined by engine operating condition and component dimensions. Modeling approach and features are described and several engine case studies are carried out to validate the motor weight and sizing model for four types of motor configurations. Based on the results of the model, the yielded values such as motor outer diameter, power output, and efficiency are only slightly different than that of the hFan's target.Nomenclature SUGAR = Subsonic Ultra Green Aircraft Research SRM = Switched Reluctance Motor NPSS = Numerical Propulsion System Simulation WATE++ = Weight Analysis for Turbine Engines Pd = power output, hp Nr = motor rotation speed, rpm D s = motor stator diameter, m D r = motor rotor diameter, m D shaft = motor shaft diameter, m L stk = axial length of the stator pole, m D LPT hub diameter = LPT hub diameter, m D LP shaft diameter = LP shaft diameter, m β s = stator pole arc, rad β r = rotor pole arc, rad t s = stator pole-width, m t r = rotor pole-width, m g = airgap length, m L e = overall length, m d s = stator slot depth, m d r = rotor slot depth, m y s = stator yoke thickness, m y r = rotor yoke thickness, m A s = specific electric loading, Amp-con/m B = specific magnetic loading, T Downloaded by CARLETON UNIVERSITY LIBRARY on August 2, 2015 | http://arc.aiaa.org |

show abstract

Power Losses in Outside-Spin Brushless D.C. Motor

Cited by 15 publications

References 4 publications

Displacement of the maximum power point caused by losses in wind turbine systems

Displacement of the maximum power point caused by losses in wind turbine systems

Design of a brushless DC permanent-magnet generator for use in micro-wind turbine applications

A Parametric Environment for Weight and Sizing Prediction of Motor/Generator for Hybrid Electric Propulsion

Contact Info

Product

Resources

About