Self-learning Direct Flux Vector Control of Interior Permanent Magnet Machine Drives

This paper proposes a novel self-learning control scheme for interior permanent magnet synchronous machine (IPMSM) drives to achieve maximum torque per ampere (MTPA) operation in constant torque region and voltage constraint maximum torque per ampere (VCMTPA) operation in field weakening region. The proposed self-learning control scheme (SLC) is based on the newly reported virtual signal injection aided direct flux vector control. However, other searching based optimal control schemes in the flux-torque (f-t) reference frame are also possible. Initially the reference flux amplitudes for MTPA operations are tracked by virtual signal injection and the data are used by the proposed self-learning control scheme to train the reference flux map online. After training, the proposed control scheme generates the optimal reference flux amplitude with fast dynamic response. The proposed control scheme can achieve MTPA or VCMTPA control fast and accurately without accurate prior knowledge of machine parameters and can adapt to machine parameter changes during operation. The proposed control scheme is verified by experiments under various operation conditions on a prototype 10 kW IPMSM drive

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

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

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

Commutation Angle Maps Evaluation for Magnet Arrangements of Interior Permanent Magnet Synchronous Machines in Electric Vehicles

© 2021 IEEE. This is the accepted manuscript version of a conference paper which has been published in final form at 10.1109/SEST50973.2021.9543397The commutation angle, γ , of an interior permanent magnet synchronous motor's (IPMSM) vector diagram, plays an important role in compensating the back electromotive force; both under load phase current variations and/or when an extended speed range, being near the constant power range, is required by the application. This commutation angle is defined as the angle between the fundamental of the phase current and the fundamental of the back-emf. It can be utilized to provide a compensating effect in IPMSMs. This is due to the reluctance torque component being dependent on the phase current before the extended speed range. A real-time maximum torque per current and voltage strategy is employed to find the trajectory and optimum commutation angles, γ , where the level of accuracy depends on the application and available computational speed. A magnet volume reduction is proposed in this paper to minimize the permanent magnet mass to motor torque density, whilst maintaining the phase current below its maximum rated value. A mapping of γ allows the determination of the optimum angles as shown in this paper. The 3rd generation Toyota Prius IPMSM is considered the reference motor, where only the rotor configuration is altered to allow for an individual assessment. The electric vehicle's performance during acceleration and deceleration using various IPMSM rotor configurations is evaluated for a given four-wheel-drive vehicle. The powertrain uses two single-gear onboard, under standard drive cycles.Peer reviewe

MTPA control of IPMSM drives based on virtual signal injection considering machine parameter variations

Due to parameter variations with stator currents, the derivatives of machine parameters with respect to current angle or d-axis current are not zero. However, these derivative terms are ignored by most of mathematical model based efficiency optimized control schemes. Therefore, even though the accurate machine parameters are known, these control schemes cannot calculate the accurate efficiency optimized operation points. In this paper, the influence of these derivative terms on maximum torque per ampere (MTPA) control is analyzed and a method to take into account these derivative terms for MTPA operation is proposed based on the recently reported virtual signal injection control (VSIC) method for interior permanent magnet synchronous machine (IPMSM) drives. The proposed control method is demonstrated by both simulations and experiments under various operating conditions on prototype IPMSM drive systems

Squirrel cage induction motor scalar control constant V/F analysis

In constant V/f control technique it is assume that the stator resistance and leakage inductance drops are negligible, especially at high speed and small load. In other words, the back emf is comparatively large at high speed and hence these voltage drops can be neglected. By maintaining constant V/f, constant Eg/f and hence constant air-gap flux is assumed. This assumption is however invalid at low speeds since a significant voltage drop appears across the stator impedance. The terminal voltage, V no longer approximates ag. By using MATLAB Simulink, the open-loop constant V/f is simulated. It is shown that the performance of the drive deteriorates at low speeds. The improvement in the performance by applying voltage boost is shown and discussed

Mathematical Approaches to Modeling, Optimally Designing, and Controlling Electric Machine

Optimal performance of the electric machine/drive system is mandatory to improve the energy consumption and reliability. To achieve this goal, mathematical models of the electric machine/drive system are necessary. Hence, this motivated the editors to instigate the Special Issue “Mathematical Approaches to Modeling, Optimally Designing, and Controlling Electric Machine”, aiming to collect novel publications that push the state-of-the art towards optimal performance for the electric machine/drive system. Seventeen papers have been published in this Special Issue. The published papers focus on several aspects of the electric machine/drive system with respect to the mathematical modelling. Novel optimization methods, control approaches, and comparative analysis for electric drive system based on various electric machines were discussed in the published papers

A Novel Multi-Criteria Local Latin Hypercube Refinement System for Commutation Angle Improvement in IPMSMs

The commutation angle, γ, of an interior permanent magnet synchronous motor's (IPMSM) vector diagram, plays an important role in compensating the back electromotive force (back-EMF); both under phase current variations and an extended speed range, is required by the application. This commutation angle is defined as the angle between the fundamental of the motor phase current and the fundamental of the back-EMF. It can be utilised to provide a compensating effect in IPMSMs. This is due to the reluctance torque component being dependent on the commutation angle of the phase current even before entering the extended speed range. A real-time maximum torque per current and voltage strategy is demonstrated to find the trajectory and optimum commutation angles, γ, where the level of accuracy depends on the application and available computational speed. A magnet volume reduction using a novel multi-criteria local Latin hypercube refinement (MLHR) sampling system is also presented to improve the optimisation process. The proposed new technique minimises the magnet mass to motor torque density whilst maintaining a similar phase current level. A mapping of γ allows the determination of the optimum angles, as shown in this paper. The 3rd generation Toyota Prius IPMSM is considered as the reference motor, where the rotor configuration is altered to allow for an individual assessment.</p