Browsing by Author "Hinkkanen, Marko, Prof., Aalto University, Department of Electrical Engineering, Finland"

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  • Control Aspects for Energy-Efficient and Sensorless AC Motor Drives
    (2015) Qu, Zengcai
     School of Electrical Engineering | Doctoral dissertation (article-based)
    This research proposes control methods for improving the energy efficiency and stability of sensorless AC motor drives. The study focuses on induction motors (IMs) and synchronous reluctance motors (SyRMs). Loss-minimizing methods are developed for both IM and SyRM drives. The loss-minimizing control applies dynamic space-vector motor models which take into account hysteresis losses and eddy-current losses as well as the magnetic saturation. The minimum points of the loss function are numerically searched in order to calculate the efficiency-optimal control variable. Magnetic saturation effects can affect the energy optimization more significantly than core-loss parameters. Additionally, flux-angle and rotor-angle estimation methods in sensorless drives are also sensitive to inductance parameters. A saturation model was proposed for SyRMs using explicit power functions. The proposed model takes into account cross saturation and fulfills the reciprocity condition. In order to improve the stability of the sensorless IM drives, especially at low speeds, a gain scheduling method was proposed for a full-order flux observer. The observer gains are selected as functions of the rotor speed estimate in order to improve the damping and robustness of the closed-loop system. The observer is augmented with a stator-resistance adaptation scheme in the low-speed region. In high-speed applications with limited sampling frequency, dynamic performance of the discrete-time approximation of a continuous-time controller can dramatically decrease, and can, in the worst case, even become unstable. A discrete-time current controller was proposed for SyRMs. The current controller is designed based on the exact discrete-time motor model that includes the effects of the zero-order hold and delays. The dynamic performance and robustness are improved, especially at low sampling to fundamental frequency ratios.
  • Dynamic induction machine models including magnetic saturation and iron losses
    (2013) Ranta, Mikaela
     School of Electrical Engineering | Doctoral dissertation (article-based)
    Dynamic induction machine models are used as the basis for the design and implementation of control algorithms. Costs can be reduced by applying speed-sensorless control, and advanced control strategies open up for the possibility of using an induction machine in demanding applications. However, a reliable and good control performance requires more detailed induction machine models. This thesis deals with models including the magnetic saturation and iron losses. A small-signal model, which includes the saturation due to variations in the main flux magnitude and the load torque, is used to analyze the transient behavior of the machine. Due to the magnetic saturation, the inductances vary as a function of the operating point, and the machine appears to be salient in transients. Based on the model, an identification method for the leakage inductance is proposed. The identification is based on signal injection and can be performed as the machine is running under different load conditions. A model for the skin effect of the rotor bars can be used in combination with the leakage inductance identification in the case of an induction machine equipped with deep rotor bars. The magnetizing curve can be modeled using a simple power function. An adaptive identification method is developed for the identification of magnetizing curve parameters. Identification of the leakage inductance prior to the magnetizing curve identification improves the results in case a no-load condition cannot be reached. The stator hysteresis and eddy current losses are modeled using a nonlinear resistance. The resistance is not dependent on any frequency, and is thus defined also during transients. The resistance model is experimentally investigated both for the case of an induction machine and a nonlinear inductor. The iron loss model is used in a loss-minimizing control algorithm for the induction machine.
  • Identification and Speed Control Design of Resonating Mechanical Systems in Electric Drives
    (2014) Saarakkala, Seppo
     School of Electrical Engineering | Doctoral dissertation (article-based)
    Ac electrical machines supplied with a frequency converter have been increasingly selected for torque actuators in modern motion control applications. These applications often contain several moving or rotating masses connected together with mechanical transmission components. This configuration results in mechanical resonances and, if the speed-feedback loop is delayed, instability can even occur. To overcome the resonance problems, several speed control methods and different tuning approaches have been proposed: They range from the gain decreasing of a simple proportional integral (PI) controller to the use of complex nonlinear controllers. This dissertation provides methods to analytically tune the speed controller of electrical drives. The tuning rules are given for both a rigid single-mass system and a resonating two-mass system. The speed controller is designed to give both the robust regulation performance as well as accurate reference tracking. The controller gains are always parametrized in the parameters of the mechanical system and in some design specifications, which results in the possibility of applying gain scheduling if required. The dissertation demonstrates on an experimental level that an effective and robust classical speed controller can be designed for both the rigid single-mass system as well as the resonating two-mass system. However, the controlled mechanical-system model must be known and the controller must be tuned using the known model. Finding a suitable mechanical model and its parameters may sometimes be problematic. Not all of parameters are always available or else the datasheet values may not be accurate. To overcome the problems of finding the mechanical parameters, this dissertation provides methods to identify the mechanical load and its parameters. The identification can be done both in the open-loop and closed-loop operations and it is based on using discrete-time polynomial models instead of frequency-domain methods. The experiments established that the polynomial-model based, discrete-time method is a better choice, than the frequency-response-based method. This is mainly because of the absence of the time domain to the frequency domain conversion, which adds an additional computational burden and numerical inaccuracy to the identification method. The experiments further demonstrate that the proposed identification method can be successfully applied both in the open-loop and in the closed-loop configurations.