Comparison of Optimized Pulse Patterns with Direct Model Predictive Control Using Co-Simulation

Schulte, Christoph; Peter, Klaus; Leuer, Michael; Böcker, Joachim

doi:10.1049/cp.2016.0331

Cited by 2 publications

(2 citation statements)

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“…Hence, there is actually a thermal sweet spot at which the total motor losses are minimal [134] [135]. One might want to control the motor temperature to this sweet spot, e.g., by manipulating the active motor cooling or by changing inverter pulse patterns to pursue certain loss distributions within the motor [136]. In this respect, temperature monitoring is a central task of the drive control software.…”

Section: Derating Safety Margins and Estimation Accuracymentioning

confidence: 99%

Thermal Monitoring of Electric Motors: State-of-the-Art Review and Future Challenges

Wallscheid

2021

IEEE Open J. Ind. Applicat.

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Temperature sensing in electric motors is an important task to ensure component protection against excessive heat while maximizing the power and torque capabilities. In order to optimize the dynamic performance limits of a motor during online operation, important motor temperatures must be known in real time. Since temperature measurements are associated with costs and integration efforts, model-based estimation methods became highly relevant. In recent years, many promising contributions have been made to this field leading to a vast literature basis. This paper organizes the literary landscape and gives a bird's-eye overview of the three most important estimation classes: Indirect methods, which track temperature-sensitive electrical motor parameters, and direct methods, namely lumped-parameter thermal networks as well as supervised machine learning. Practical limitations as well as special challenges of the respective methods are emphasized throughout the text. The aim of the paper is therefore to facilitate the entry for interested researchers and engineers in this field as well as to stimulate new research impulses. Hence, open problems as well as future research questions are addressed at the end of this review.

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Section: Derating Safety Margins and Estimation Accuracymentioning

confidence: 99%

Thermal Monitoring of Electric Motors: State-of-the-Art Review and Future Challenges

Wallscheid

2021

IEEE Open J. Ind. Applicat.

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“…Recently, predictive model-based control (PMC) has been suggested as robust control strategy by [17][18][19] to regulate the AC voltage constant and mitigate harmonics at the PCC. This concept based on prediction current and voltage control techniques for VSI connected to LRC filter is also suggested in [20][21][22][23].…”

Section: Introductionmentioning

confidence: 99%

Improved predictive current model control based on adaptive PR controller for standalone system based DG set

Ikaouassen¹,

Raddaoui²,

Rezkallah³

et al. 2020

IJECE

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This paper investigates an improved current predictive model control (PCMC) strategy with a prediction horizon of one sampling time for voltage regulation in standalone system based on diesel engine driven fixed speed of a synchronous generator. An adaptive PR controller with anti-windup scheme is employed to achieve high performance regulation without saturation issues. In addition, new method to obtain the optimal parameters of the adaptive PR controller to achieve high performance during the transition and in steady state is provided. To balance the power at the point of common coupling (PCC) as well as to feed a clean power to the connected loads, a three-phase voltage source inverter (VSI) with LRC filter is controlled using the developed improved PCMC strategy, where the output filter current is controlled using the predicting of the system behaviour model in the future step, at each sampling prediction time. The performances of the proposed configuration and the improved control strategy are verified using Matlab/Simulink interface.

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Comparison of Optimized Pulse Patterns with Direct Model Predictive Control Using Co-Simulation

Cited by 2 publications

References 0 publications

Thermal Monitoring of Electric Motors: State-of-the-Art Review and Future Challenges

Thermal Monitoring of Electric Motors: State-of-the-Art Review and Future Challenges

Improved predictive current model control based on adaptive PR controller for standalone system based DG set

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