Self-optimizing and model-adaptive control of electrical drive systems with predictive planning of pulse patterns
Final Report Abstract
Electric drives perform a wide variety of tasks and are an essential component of modern industrial society. Usually, the drives are operated in closed-loop control mode, where, in addition to fulfilling the control objective, secondary aspects such as loss-reduced operation, maximum voltage utilization and high control dynamics are increasingly desired or required by the operators. In order to achieve these goals, a consistent concept of self-optimizing and model-adaptive control of synchronous machines has been investigated in this project. The concept can be divided into two stages. In the first stage, the electrical model of a highly utilized synchronous machine with cross-saturation effects is identified during online operation. Here, a modulator-free model predictive current control is used. The resulting natural excitation due to switching-frequency current ripple is advantageous for the identification of the motor. The prediction model required for the control is continuously estimated by the recursive least squares method. Physical parameters such as differential inductances and flux linkages can be continuously adapted and stored in tables. In a second step, a modulator-based model predictive flux control method is developed. By using a modulator, current distortion and thus losses can be reduced. Using the identified machine model from the first stage, the flux con-troller is able to reach operating points for given reference torques in minimum time. Furthermore, torque and current limits are taken into account as state constraints, preventing transient overcurrents and torque overshoots and undershoots. In addition, the entire modulation range of the inverter, from linear modulation to overmodulation, including six-step operation, is continuously utilized to its maximum. This results in an approximately 10% increase in drive power at high speeds compared to linear modulation. To ensure consistently high control quality and accuracy, the (nonlinear) flux linkage tables are continuously adapted during operation at sufficiently high speeds to compensate for temperature and aging effects. Since the presented two-stage concept requires minimal prior knowledge of the electric drive and a low number of tuning parameters, an electric drive system can be commissioned and operated without exten-sive expert knowledge. The proposed concept has been simulated and validated by extensive experimental investigations with a highly utilized interior permanent magnet synchronous motor.
Publications
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Torque Characteristics of a Per-manent Magnet Motor: 74 Million Samples for Data Driven Learning.
A. Brosch; O. Wallscheid & J. Böcker
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Data-Driven Recursive Least Squares Estimation for Model Predictive Current Control of Permanent Magnet Synchronous Motors. IEEE Transactions on Power Electronics, 36(2), 2179-2190.
Brosch, Anian; Hanke, Soren; Wallscheid, Oliver & Bocker, Joachim
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Model Predictive Control of Permanent Magnet Synchronous Motors in the Overmodulation Region Including Six-Step Operation. IEEE Open Journal of Industry Applications, 2, 47-63.
Brosch, Anian; Wallscheid, Oliver & Bocker, Joachim
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Torque and Inductances Estimation for Finite Model Predictive Control of Highly Utilized Permanent Magnet Synchronous Motors. IEEE Transactions on Industrial Informatics, 17(12), 8080-8091.
Brosch, Anian; Wallscheid, Oliver & Bocker, Joachim
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Long-Term Memory Recursive Least Squares Online Identification of Highly Utilized Permanent Magnet Synchronous Motors for Finite-Control-Set Model Predictive Control. IEEE Transactions on Power Electronics, 38(2), 1451-1467.
Brosch, Anian; Wallscheid, Oliver & Bocker, Joachim
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Model Predictive Torque Control for Permanent-Magnet Synchronous Motors Using a Stator-Fixed Harmonic Flux Reference Generator in the Entire Modulation Range. IEEE Transactions on Power Electronics, 38(4), 4391-4404.
Brosch, Anian; Wallscheid, Oliver & Bocker, Joachim
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Time-Optimal Model Predictive Control of Permanent Magnet Synchronous Motors Considering Current and Torque Constraints. IEEE Transactions on Power Electronics, 38(7), 7945-7957.
Brosch, Anian; Wallscheid, Oliver & Böcker, Joachim
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Time-Optimal Model Predictive Control of Permanent Magnet Synchronous Motors in the Whole Speed and Modulation Range Considering Current and Torque Constraints. Institute of Electrical and Electronics Engineers (IEEE).
Brosch, Anian; Wallscheid, Oliver & Böcker, Joachim
