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Real-Time Loss Minimizing Control of Induction Machines for Dynamic Load Profiles Under Deadbeat-Direct Torque and Flux Control
- Source :
- IEEE Transactions on Industry Applications. 57:3754-3762
- Publication Year :
- 2021
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2021.
-
Abstract
- This paper develops a real-time loss minimizing control technique on induction machines for dynamic load profiles. Steady-state loss minimization has been well addressed in the literature. However, when the steady-state optimal stator flux linkage is applied to highly dynamic load profiles, more losses are induced during transients due to the slow rotor flux dynamics. Several heuristic methods have been developed for real-time loss reduction, but they are not designed for minimum losses. Loss-minimizing flux trajectories have been generated by dynamic programming but require prior information of load profiles. In this paper, a real-time loss minimizing control technique is developed for applications without prior information of load profiles. It resembles the loss-minimizing stator flux trajectory generated by a modified dynamic programming method, which generates the best practical solution for unknown load profiles. The steady-state optimal solution for the stator flux linkage is derived based on the induction machine loss model. Both simulation and experimental results demonstrate the energy saving capability of the proposed method.
- Subjects :
- Steady state (electronics)
Computer science
Heuristic (computer science)
Stator
05 social sciences
020207 software engineering
02 engineering and technology
Optimal control
Flux linkage
Industrial and Manufacturing Engineering
Dynamic load testing
law.invention
Dynamic programming
Control and Systems Engineering
law
Control theory
0202 electrical engineering, electronic engineering, information engineering
Trajectory
Torque
0501 psychology and cognitive sciences
Electrical and Electronic Engineering
Reduction (mathematics)
050107 human factors
Subjects
Details
- ISSN :
- 19399367 and 00939994
- Volume :
- 57
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Industry Applications
- Accession number :
- edsair.doi.dedup.....fae9745a4ba330e54d30bc8d452ac6cc
- Full Text :
- https://doi.org/10.1109/tia.2021.3076417