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This study proposes an on-line minimum loss (ML) control strategy that considers the iron and copper losses of an interior permanent magnet synchronous motor in torque-controlled applications. The proposed ML control strategy utilizes a constrained optimization problem to satisfy torque reference tracking and loss minimization. An equivalent iron loss resistance circuit is adopted for the loss minimization. To solve the optimization problem, the Lagrange multiplier method is applied through a numerical analysis algorithm. The resulting solution provides the optimal current reference for every sampling instant. The Lagrange multiplier method needs parameters such as magnetic flux linkages, dynamic inductances, and iron loss resistance. Fundamental magnetic flux linkages are estimated using a flux observer, and the dynamic inductances are estimated with high-frequency voltage signal injection. The proposed iron loss resistance estimator estimates the equivalent iron resistance without any preliminary experiments. DC input power is measured using a current sensor for the accurate on-line estimation of iron loss resistance. To analyze the effectiveness of ML control compared with conventional maximum torque per ampere control, finite element analysis is used. The feasibility of the proposed ML control strategy is verified through simulation and experiments. [ABSTRACT FROM AUTHOR]

Improvement of the low-speed sensorless position control for an interior permanent magnet synchronous motor (IPMSM), which drives a horizontal axis washing machine drum, extended-flux (EF) model-based PI observer (PIO) system is proposed. This control is designed to estimate the derivatives of the EF components, which are voltage components, from which the rotor position information is extracted. Motor parameters change during the operation because of the load and temperature, and those changes affect the performance of sensorless IPMSM drive, especially at low-speed operation. For satisfactory low-speed operation, observer gains should be carefully selected to reduce the influence of measurement noise and un-modeled dynamics. Linear quadratic (LQR) control method is used to calculate the optimal coefficients of a PIO to improve low-speed performance. The PI observer is chosen for its capability to decouple modeling uncertainties and measurement noise. The effectiveness of the proposed sensorless method is verified by the simulation on MATLAB/Simulink and experimental results in a 900W IPMSM drive for washing machine. The proposed estimator achieves stable operation at 87 rpm 100% and 45 rpm 25% load torque conditions. It has a much better dynamic performance and improved capability and is robust for speed and torque variations in the system. [ABSTRACT FROM AUTHOR]

To realize the smooth transition from the partial flux weakening zone I (FW-I Zone) to the deep flux weakening zone II (FW-II Zone) and avoid the current loop saturation during the deep flux weakening control for an interior permanent magnet synchronous motor, a novel deep flux weakening control strategy with variable direct axis (d-axis) current limitation (VDL-FWC) is proposed. In the framework of the traditional voltage closed-loop feedback regulation flux weakening control (FB-FWC) strategy, the d-axis flux weakening current is limited by the maximum torque per voltage, which is quickly obtained through a parabolic approximation that varies with the quadrature axis (q-axis) current. Therefore, when the d-axis weakening current exceeds its limitation, a closed-loop voltage feedback proportional-integral controller is used to adjust the q-axis current increment, which transfers the exceeding d-axis current to the q-axis current to prevent voltage saturation. This process helps the current loop avoid becoming out of control. The proposed deep flux weakening control strategy is compared with the FB-FWC strategy and flux weakening control strategy with a fixed direct d-axis current limitation (FDL-FWC). Studies show that the proposed strategy is effective and has a higher load capacity in the deep flux weakening zone. [ABSTRACT FROM AUTHOR]

Sensorless schemes are mainly used in fault-tolerant control of interior permanent magnet synchronous motor (IPMSM) drives. Traditional sensorless methods with injection of high-frequency (HF) carrier signals into the stationary reference frame have a stable performance. However, phase shifts caused by conventional high-pass filters (HPFs) decrease the estimation accuracy. Besides, the demodulation process is usually complicated, which increases the difficulty of application. To solve these problems, this study presents an HF-induced current direct demodulation method. Rotor position angle can be solved from the sampled currents at adjacent moments without demodulation signals. Therefore, the errors related to filters in the rotor position estimation are eliminated. Besides, the efficiency of the demodulation algorithm is improved. Furthermore, an online compensation method for cross-saturation effect is proposed. Experimental results verify that the proposed strategy can obtain an accurate rotor position with good steady-state and dynamic performance. [ABSTRACT FROM AUTHOR]

Pulsating high-frequency voltage injection is an effective method for estimating the initial rotor position for interior permanent magnet synchronous motors (IPMSMs). This method is based on the magnetic saliency of a motor rather than a back-electromotive-force (back-EMF) model. In addition, it is feasible when the motor is static or in low-speed operations. However, accurate estimation of the rotor position is realized on the assumption that the direct-axis and quadrature-axis of the motor are completely decoupled, which is not always satisfied. Then, the mutual inductance between the two axes introduces a theoretical error into the rotor position estimation. In this paper, the theoretical error of the rotor position estimation caused by mutual inductance is deduced. An improved initial rotor position estimation method is proposed to eliminate harmonic theoretical errors by injecting high-frequency voltage in the decoupling coordinate system. Finally, the effectiveness of this method is verified by experimental results. [ABSTRACT FROM AUTHOR]

This paper proposes a high-frequency (HF) square wave voltage signal injection strategy for interior permanent magnet synchronous motor (IPMSM) maximum torque per ampere (MTPA) drives. Unlike previous methods, this strategy injects a square wave HF signal into the voltage directly regardless of the current loop bandwidth limitations. In addition, the injected frequency can surpass the cut-off frequency of the current loop. Therefore, the disturbance caused by the injected signal can be reduced. The process of MTPA operating point adjustment only needs to sample and analyze the current amplitude without additional digital filters. Thus, the dynamic response promotes, and avoids the extra hardware and calculation burden. To decrease the convergence time when the load changes rapidly, an equivalent mathematical model of an IPMSM is employed to provide prior current references. Both simulation and experimental results confirm the validity and feasibility of the proposed strategy. [ABSTRACT FROM AUTHOR]

Light electric vehicles (LEVs) are usually used as neighborhood electric vehicles (NEVs) for the second vehicle or car-sharing service. For LEVs, it is important to reduce energy consumption to have greater mileage at the same battery capacity. One of the direct ways to decrease energy consumption is the efficiency improvement of the traction motor, which is the main propulsion system. Also, the weight reduction of the traction motor can be a solution to energy usage mitigation. This paper suggested the design process of a traction motor for LEV considering material properties to minimizing the energy consumption of the vehicle. During the design process, vehicle simulation was adopted to calculate energy consumption. In addition, traction motor and battery which are the key components of LEV were mathematically modeled and used in the simulation. Using them, energy consumption was estimated within the change of stack length of the traction motor for some drive cycles. Finally, from these simulations, optimum power density is determined which minimizes energy consumption. [ABSTRACT FROM AUTHOR]

This paper presents a nonlinear state observer model for sensorless speed control of an interior permanent magnet synchronous motor (IPMSM) drive. First, an augmented state space model of the IPMSM and the system uncertainty dynamics is obtained in the d − q synchronously rotating reference frame. Then, the proposed nonlinear state estimator based on an extended Luenberger observer is constructed by using rotor position, rotor speed, q-axis stator current, and system uncertainty vector as the state variables. Hence, the estimated system parameter uncertainties can be used to dramatically improve the performance of the speed controller without any additional observer. The stability of the proposed observer at low and high speed is asymptotically guaranteed by Lyapunov stability analysis. In addition, the proposed model is simple to carry out, so it does not require a complex calculation. Simulation results obtained via a Matlab/Simulink software indicate that the proposed observer model can assure an excellent state estimation over a wide speed range even when the rotor speed or load torque changes abruptly as well as the difference in the initial values of real and estimated rotor position. [ABSTRACT FROM AUTHOR]

A nonlinear observer for a class of nonlinear interconnected systems is introduced. The proposed methodology facilitates the observer design for nonlinear systems. Sufficient conditions criteria are derived to ensure asymptotical convergence of the proposed observer. The convergence of the proposed observer is studied in both nominal and abnormal cases. The designed observer is applied for self-sensing control of interior permanent magnet synchronous machine (IPMSM) to estimate the rotor position, the rotor speed, the stator resistance, and the load torque. Performance of the proposed observer algorithm is evaluated through real-time experiments using an industrial benchmark. Two cases are employed to prove the performance capability of the proposed self-sensing control algorithm. The first case measures the performance under normal operating condition. The influence of parameter deviations on the proposed self-sensing control algorithm is discussed to prove the robustness of the proposed observer in the second case. The accuracy of the proposed self-sensing control algorithm is greater than 93 %. [ABSTRACT FROM AUTHOR]

This paper presents a nonlinear sliding mode control (SMC) scheme with a variable damping ratio for interior permanent magnet synchronous motors (IPMSMs). First, a nonlinear sliding surface whose parameters change continuously with time is designed. Actually, the proposed SMC has the ability to reduce the settling time without an overshoot by giving a low damping ratio at the initial time and a high damping ratio as the output reaches the desired setpoint. At the same time, it enables a fast convergence in finite time and eliminates the singularity problem with the upper bound of an uncertain term, which cannot be measured in practice, by using a simple adaptation law. To improve the efficiency of a system in the constant torque region, the control system incorporates the maximum torque per ampere (MTPA) algorithm. The stability of the nonlinear sliding surface is guaranteed by Lyapunov stability theory. Moreover, a simple sliding mode observer is used to estimate the load torque and system uncertainties. The effectiveness of the proposed nonlinear SMC scheme is verified using comparative experimental results of the linear SMC scheme when the speed reference and load torque change under system uncertainties. From these experimental results, the proposed nonlinear SMC method reveals a faster transient response, smaller steady-state speed error, and less sensitivity to system uncertainties than the linear SMC method. [ABSTRACT FROM AUTHOR]