The AdvancedMachines Library: Loss Models for Electric Machines

Haumer, Anton; Kral, Christian; Kapeller, H.; Bauml, T.; Gragger, Johannes V.

doi:10.3384/ecp09430103

Cited by 11 publications

(13 citation statements)

References 3 publications

(3 reference statements)

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“…The evaluation of the motor drive losses using these equations was performed by Modelica Associations [49], Table 2 Power loss model of an industrial robot motor drive [48,49] IR motor drive losses Explanation Core losses Core losses or iron losses occur due to the magnetization process of the core material (hysteresis) and due to the eddy current effect in that process. Generally, this loss contributes about 20-25 % of the total motor losses.…”

Section: Power Losses In the Ir Modelmentioning

confidence: 99%

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Reducing the energy consumption of industrial robots in manufacturing systems

Paryanto

Brossog

Bornschlegl

et al. 2015

Int J Adv Manuf Technol

151

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Reducing the energy consumption of industrial robots (IR) that are used in manufacturing systems has become a main focus in the development of green production systems. This is due to the reality that almost all automated manufacturing processes are using IR as the main component. Thus, reducing the energy consumption of IR will automatically reduce operating costs and CO 2 emissions. Therefore, a method for reducing the energy consumption of IR in manufacturing systems is desired. Firstly, this paper presents a literature survey of the research in energy consumption analysis of IR that is used in manufacturing processes. The survey found that current research in this field is focused on the development of simulation models of IR that are able to be used to predict its energy consumption. Secondly, a modular model to analyze power consumption and dynamic behavior of IR is developed. Afterward, an experimental investigation is carried out to validate and estimate the accuracy of the model developed. The investigation shows that the developed modular model can be conveniently used to optimize the industrial robot's operating parameters, which are commonly needed for production planning and at the process optimization stage. In addition, the investigation shows that the process constraints, environment layout, productivity requirement, Paryanto ( ) · M. Brossog · J. Franke as well as the robot payload and operating speed are the key factors that must be considered for optimizing the productivity and efficiency of IR.

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Section: Power Losses In the Ir Modelmentioning

confidence: 99%

“…Due to the priority task and limitation of the Modelica language, only power losses in the IR body mechanism Fig. 5 Speed of the asynchronous induction machine, simulation results compared with actual measurements [49] and power losses in the IR motor drive are modeled in the IR simulation model.…”

Section: Stator and Rotor Lossesmentioning

confidence: 99%

Reducing the energy consumption of industrial robots in manufacturing systems

Paryanto

Brossog

Bornschlegl

et al. 2015

Int J Adv Manuf Technol

151

View full text Add to dashboard Cite

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“…The mechanical flanges, the thermal connector as well as the temperature sensors and angle sensor outputs are the same for all wrapper models of permanent magnet synchronous machines. Both the quasi static and the transient machine models take losses into account: temperature dependent copper loss, (eddy current) core loss, friction loss, stray load loss and PM loss -see [4,5]. All these losses are dissipated either to an internal thermal ambient with fixed operational temperature, or exchanged with an external thermal model through the thermal port.…”

Section: Machines and Sensorsmentioning

confidence: 99%

The New EDrives Library: A Modular Tool for Engineering of Electric Drives

Haumer

Kral²

2014

Linköping Electronic Conference Proceedings

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Simulation is an indispensable tool for the engineering of systems containing electric drives. Depending on the design phase and the engineering task different levels of modeling details are required: proof of concept, investigation of energy and power consumption, design of control, etc. The new EDrives library provides three levels of abstraction for inverters: quasi static (neglecting electrical transients), averaging (neglecting switching effects) and switching-for serving different demands. The inverters can feed the machine models of the Modelica Standard Library: Modelica.Magnetic.FundamentalWave and the new Modelica.Magnetic.QuasiStatic.FundamentalWave. The EDrives library copes with arbitrary phase numbers and can be easily extended to develop new control algorithms. In this publication the structure of the library and the implemented control principles are presented. Furthermore, examples comparing the three different levels of abstraction are included.

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“…Each loss model takes a consistent power balance into account, such that all dissipated losses are always considered in a respective thermal connector. The loss models have been presented and validated against measurements in Haumer et al (2009). For the mechanical components actio et reactio applies.…”

Section: Electric Machine Componentsmentioning

confidence: 99%