Self-Learning MTPA Control of Interior Permanent-Magnet Synchronous Machine Drives Based on Virtual Signal Injection

This paper describes a simple but effective novel self-learning maximum torque per ampere (MTPA) control scheme for interior permanent-magnet synchronous machine (IPMSM) drives to achieve fast dynamic response in tracking the MTPA points without accurate prior knowledge of machine parameters. The proposed self-learning control (SLC) scheme generates the optimal d-axis current command for MTPA operation after training. Virtual signal injection control (VSIC), which has been recently developed as a novel parameter-independent MTPA points tracking scheme, is utilized to train the SLC and compensate the error of the SLC during its operation. In this way, the proposed SLC can achieve the MTPA operation accurately with fast response and the online training of the SLC will not affect MTPA operation of IPMSM drives. The proposed control scheme is verified by simulations and experiments under various operation conditions on a prototype IPMSM drive system

An Accurate Virtual Signal Injection Control of MTPA for IPMSM with Fast Dynamic Response

A maximum torque per ampere (MTPA) control based on virtual signal injection for interior permanent magnet synchronous motor (IPMSM) with fast dynamic response is proposed in this paper. A small square wave signal is mathematically injected into current angle for accurately tracking MTPA points. The extracted derivative of elctromagnetic torque is utilized to compensate the initially set current angle to the real MTPA operation current angle. Due to the absence of bandpass and lowpass filters which are essential in the sinusoidal injected signal scheme, this method shows good dynamic response. By incorporating a modified equation for the torque after signal injection, the steady-state accuracy is also enhanced. The d- and q-axes current references are obtained through the current vector magnitude and optimal current angle instead of using the torque equation with nominal motor parameters, which guarantees the accuracy of the output torque. The proposed scheme is parameter independent and no real signal is injected to the current or voltage command. Thus, the problems of high-frequency signal injection method are avoided. A prototype is set up and experiments are carried out to verify effectiveness and robustness of the proposed control scheme

Self-Adaptive High-Frequency Injection Based Sensorless Control for Interior Permanent Magnet Synchronous Motor Drives

open5openKumar, Piyush; Bottesi, Omar; Calligaro, Sandro; Alberti, Luigi; Petrella, RobertoKumar, Piyush; Bottesi, Omar; Calligaro, Sandro; Alberti, Luigi; Petrella, Robert

Self-adaptive high-frequency injection based sensorless control for interior permanent magnet synchronous motor drives \u2020

Abstract: An auto-tuning and self-adaptation procedure for High Frequency Injection (HFI) based position and speed estimation algorithms in Interior Permanent Magnet Synchronous Motor (IPMSM) drives is proposed in this paper. Analytical developments show that, using conventional approaches, the dynamics of the high-frequency tracking loop varies with differential inductances, which in turn depend on the machine operating point. On-line estimation and adaptation of the small signal gain of the loop is proposed here, allowing accurate auto-tuning of the sensorless control scheme which does not rely on a priori knowledge of the machine parameters. On-line adaptation of Phase-Locked Loop (PLL) gains and of the injected voltage magnitude is also possible, leading to important advantages from the performance, loss and acoustic point of view. The theoretical basis of the method has been introduced first and the main concept demonstrated by means of simulations. Implementation has been carried out using the hardware of a commercial industrial drive and two Interior Permanent Magnet Synchronous Motors, namely a prototype and an off-the-shelf machine. Experimental tests demonstrate the feasibility and effectiveness of the proposal

Adaptive Torque Estimation for an IPMSM with Cross-Coupling and Parameter Variations

This paper presents a new adaptive torque estimation algorithm for an interior permanent magnet synchronous motor (IPMSM) with parameter variations and cross-coupling between d- and q-axis dynamics. All cross-coupled, time-varying, or uncertain terms that are not part of the nominal flux equations are included in two equivalent mutual inductances, which are described using the equivalent d- and q-axis back electromotive forces (EMFs). The proposed algorithm estimates the equivalent d- and q-axis back EMFs in a recursive and stability-guaranteed manner, in order to compute the equivalent mutual inductances between the d- and q-axes. Then, it provides a more accurate and adaptive torque equation by adding the correction terms obtained from the computed equivalent mutual inductances. Simulations and experiments demonstrate that torque estimation errors are remarkably reduced by capturing and compensating for the inherent cross-coupling effects and parameter variations adaptively, using the proposed algorithm.111Ysciescopu

Direct Torque Control for Silicon Carbide Motor Drives

Direct torque control (DTC) is an extensively used control method for motor drives due to its unique advantages, e.g., the fast dynamic response and the robustness against motor parameters variations, uncertainties, and external disturbances. Using higher switching frequency is generally required by DTC to reduce the torque ripples and decrease stator current total harmonic distortion (THD), which however can lower the drive efficiency. Through the use of the emerging silicon carbide (SiC) devices, which have lower switching losses compared to their silicon counterparts, it is feasible to achieve high efficiency and low torque ripple simultaneously for DTC drives. To overcome the above challenges, a SiC T-type neutral point clamped (NPC) inverter is studied in this work to significantly reduce the torque and flux ripples which also effectively reduce the stator current ripples, while retaining the fast-dynamic response as the conventional DTC. The unbalanced DC-link is an intrinsic issue of the T-type inverter, which may also lead to higher torque ripple. To address this issue, a novel DTC algorithm, which only utilizes the real voltage space vectors and the virtual space vectors (VSVs) that do not contribute to the neutral point current, is proposed to achieve inherent dc-link capacitor voltage balancing without using any DC-link voltage controls or additional DC-link capacitor voltages and/or neutral point current sensors. Both dynamic performance and efficiency are critical for the interior permanent-magnet (IPM) motor drives for transportation applications. It is critical to determine the optimal reference stator flux linkage to improve the efficiency further of DTC drives and maintain the stability of the drive system, which usually obtained by tuning offline and storing in a look-up table or calculated online using machine models and parameters. In this work, the relationship between the stator flux linkage and the magnitude of stator current is analyzed mathematically. Then, based on this relationship, a perturb and observe (P&O) method is proposed to determine the optimal flux for the motor which does not need any prior knowledge of the machine parameters and offline tuning. However, due to the fixed amplitude of the injected signal the P&O algorithm suffers from large oscillations at the steady state conditions. To mitigate the drawback of the P&O method, an adaptive high frequency signal injection based extremum seeking control (ESC) algorithm is proposed to determine the optimal reference flux in real-time, leading to a maximum torque per ampere (MTPA) like approach for DTC drives. The stability analysis and key parameters selection for the proposed ESC algorithm are studied. The proposed method can effectively reduce the motor copper loss and at the same time eliminate the time consuming offline tuning effort. Furthermore, since the ESC is a model-free approach, it is robust against motor parameters variations, which is desirable for IPM motors

Virtual Signal Injection-Based Direct Flux Vector Control of IPMSM Drives

This paper describes a novel virtual signal injection-based direct flux vector control for the maximum torque per ampere (MTPA) operation of the interior permanent magnet synchronous motor (IPMSM) in the constant torque region. The proposed method virtually injects a small high-frequency current angle signal for tracking the optimal flux amplitude of the MTPA operation. This control scheme is not affected by the accuracy of the flux observer and is independent of machine parameters in tracking the MTPA points and will not cause additional iron loss, copper loss, and torque ripple as a result of real signal injection. Moreover, by employing a bandpass filter with a narrow frequency range the proposed control scheme is also robust to current and voltage harmonics, and load torque disturbances. The proposed method is verified by simulations and experiments under various operating conditions on a prototype IPMSM drive system

Advances in Rotating Electric Machines

It is difficult to imagine a modern society without rotating electric machines. Their use has been increasing not only in the traditional fields of application but also in more contemporary fields, including renewable energy conversion systems, electric aircraft, aerospace, electric vehicles, unmanned propulsion systems, robotics, etc. This has contributed to advances in the materials, design methodologies, modeling tools, and manufacturing processes of current electric machines, which are characterized by high compactness, low weight, high power density, high torque density, and high reliability. On the other hand, the growing use of electric machines and drives in more critical applications has pushed forward the research in the area of condition monitoring and fault tolerance, leading to the development of more reliable diagnostic techniques and more fault-tolerant machines. This book presents and disseminates the most recent advances related to the theory, design, modeling, application, control, and condition monitoring of all types of rotating electric machines

Active thermal management for Interior Permanent Magnet Synchronous Machine (IPMSM) drives based on model predictive control

This paper proposes an active thermal management scheme for Interior Permanent Magnet Synchronous Machine (IPMSM) drives based on the model predictive control concept. The proposed control scheme can adaptively set torque limit based on the thermal state of the machine to limit the machine winding and end-winding temperatures. The proposed control scheme is assessed by experiments on a laboratory machine drive system and simulated for traction drives over Worldwide Harmonized Light-duty Test Cycle (WLTC). Compared with conventional traction control scheme, the proposed scheme can effectively reduce peak temperature and hence thermal stress of the machine for improving its lifetime

Online Control of IPMSM Drives for Traction Applications Considering Machine Parameter and Inverter Nonlinearities

In this paper, an online control method of interior permanent magnet synchronous machine (IPMSM) drives for traction applications considering machine parameter and inverter nonlinearities is presented. It is shown that the conventional technique using parameter information instantly extracted from premeasured parameter look-up tables (LUTs) only determines the local maximum torque per ampere (MTPA) operating point associated with this specific parameter information without evaluating the global MTPA achievement. Therefore, global MTPA operation may not be achieved for conventional online control IPMSM drives with extreme nonlinear machine parameters (e.g., short-period overload operations). Thus, a model-based correction method using stator flux adjustment is proposed for an online quasiglobal MTPA achievement. It is also proven that in the flux-weakening (FW) region, due to the inverter nonlinearities, a lower than expected maximum achievable torque for a demanded speed and a higher than expected current magnitude for a demanded torque may be obtained. Hence, an inverter nonlinearity compensation (INC) method exploiting the voltage feedback (FB) loop is introduced and its advantages over the conventional INC scheme are demonstrated. The proposed online control method is validated via measurements on a 10-kW IPMSM