Some Permanent Magnet Synchronous Motor (PMSM) Sensorless Control Methods based on Operation Speed Area

This paper compares some sensorless Permanent Magnet Synchronous Motor (PMSM) controls for driving an electric vehicle in terms of operating speed. Sensorless control is a type of control method in which sensors, such as speed and position sensors, are not used to measure controlled variables.  The controlled variable value is estimated from the stator current measurement. Sensorless control performance is not as good as a sensor-based system. This paper aims are to recommend a control method for the PMSM sensorless controls that would be used to drive an electric vehicle. The methods that we will discuss are divided into four categories based on the operation speed area.  They are a startup, low speed, high speed, and low and high-speed areas. The low and high-speed area will be divided into with and without switching.  If PMSM more work at high speed, the most speed area that is used, we prefer to choose the method that works at high speed, that is, the modification or combination of two or more conventional methods

Sensorless Rotor Position Estimation For Brushless DC Motors

Brushless DC motor speed is controlled by synchronizing the stator coil current with rotor position in order to acquire an accurate alignment of stator rotating field with rotor permanent-magnet field for efficient transfer of energy. In order to accomplish this goal, a motor shaft is instantly tracked by using rotating rotor position sensors such as Hall effect sensors, optical encoders or resolvers etc. Adding sensors to detect rotor position affects the overall reliability and mechanical robustness of the system. Therefore, a whole new trend of replacing position sensors with sensorless rotor position estimation techniques have a promising demand. Among the sensorless approaches, Back-EMF measurement and high frequency signal injection is the most common. Back-EMF is an electromotive force, directly proportional to the speed of rotor revolutions per second, the greater the speed motor acquires the greater the Back-EMF amplitude appears against the motion of rotation. However, the detected Back-EMF is zero at start-up and does not provide motor speed information at this instant. There-fore, Back-EMF based techniques are highly unfavourable for low speed application specially near zero. On the other hand, signal injection techniques are comparatively developed for low or near zero motor speed applications and they also can estimate the on-line motor parameters exploiting the identification theory on phase voltages and currents signals. The signal injection approach requires expensive additional hardware to inject high frequency signal. Since, motors are typically driven with pulse width modulation techniques, high frequency signals are naturally already present which can be used to detect position. This thesis presents rotor position estimation by measuring the voltage and current signals and also proposes an equivalent permanent-magnet synchronous motor model by fitting thedata to a position dependent circuit model

High-frequency issues using rotating voltage injections intended for position self-sensing

The rotor position is required in many control schemes in electrical drives. Replacing position sensors by machine self-sensing estimators increases reliability and reduces cost. Solutions based on tracking magnetic anisotropies through the monitoring of the incremental inductance variations are efficient at low-speed and standstill operations. This inductance can be estimated by measuring the response to the injection of high-frequency signals. In general however, the selection of the optimal frequency is not addressed thoroughly. In this paper, we propose discrete-time operations based on a rotating voltage injection at frequencies up to one third of the sampling frequency used by the digital controller. The impact on the rotation-drive, the computational requirement, the robustness and the effect of the resistance on the position estimation are analyzed regarding the signal frequency

Parameter estimation for condition monitoring of PMSM stator winding and rotor permanent magnets

Winding resistance and rotor flux linkage are important to controller design and condition monitoring of a surface-mounted permanent-magnet synchronous machine (PMSM) system. In this paper, an online method for simultaneously estimating the winding resistance and rotor flux linkage of a PMSM is proposed, which is suitable for application under constant load torque. It is based on a proposed full-rank reference/variable model. Under constant load torque, a short pulse of id 0 is transiently injected into the d-axis current, and two sets of machine rotor speeds, currents, and voltages corresponding to id = 0 and id 0 are then measured for estimation. Since the torque is kept almost constant during the transient injection, owing to the moment of system inertia and negligible reluctance torque, the variation of rotor flux linkage due to injected id 0 can be taken into account by using the equation of constant torque without measuring the load torque and is then associated with the two sets of machine equations for simultaneously estimating the winding resistance and rotor flux linkage. Furthermore, the proposed method does not need the values of the $dq$-axis inductances, while the influence from the nonideal voltage measurement, which will cause an ill-conditioned problem in the estimation, has been taken into account and solved by error analysis. This method is finally verified on two prototype PMSMs and shows good performance. © 1982-2012 IEEE

Comparative Study of Sensorless Control Methods of PMSM Drives

Recently, permanent magnet synchronous motors (PMSMs) are increasingly used in high performance variable speed drives of many industrial applications. This is because the PMSM has many features, like high efficiency, compactness, high torque to inertia ratio, rapid dynamic response, simple modeling and control, and maintenance-free operation. In most applications, the presence of such a position sensor presents several disadvantages, such as reduced reliability, susceptibility to noise, additional cost and weight and increased complexity of the drive system. For these reasons, the development of alternative indirect methods for speed and position control becomes an important research topic. Many advantages of sensorless control such as reduced hardware complexity, low cost, reduced size, cable elimination, increased noise immunity, increased reliability and decreased maintenance. The key problem in sensorless vector control of ac drives is the accurate dynamic estimation of the stator flux vector over a wide speed range using only terminal variables (currents and voltages). The difficulty comprises state estimation at very low speeds where the fundamental excitation is low and the observer performance tends to be poor. The reasons are the observer sensitivity to model parameter variations, unmodeled nonlinearities and disturbances, limited accuracy of acquisition signals, drifts, and dc offsets. Poor speed estimation at low speed is attributed to data acquisition errors, voltage distortion due the PWM inverter and stator resistance drop which degrading the performance of sensorless drive. Moreover, the noises of system and measurements are considered other main problems. This paper presents a comprehensive study of the different methods of speed and position estimations for sensorless PMSM drives. A deep insight of the advantages and disadvantages of each method is investigated. Furthermore, the difficulties faced sensorless PMSM drives at low speeds as well as the reasons are highly demonstrated. Keywords: permanent magnet, synchronous motor, sensorless control, speed estimation, position estimation, parameter adaptation

Low-cost, high-resolution, fault-robust position and speed estimation for PMSM drives operating in safety-critical systems

In this paper it is shown how to obtain a low-cost, high-resolution and fault-robust position sensing system for permanent magnet synchronous motor drives operating in safety-critical systems, by combining high-frequency signal injection with binary Hall-effect sensors. It is shown that the position error signal obtained via high-frequency signal injection can be merged easily into the quantization-harmonic-decoupling vector tracking observer used to process the Hall-effect sensor signals. The resulting algorithm provides accurate, high-resolution estimates of speed and position throughout the entire speed range; compared to state-of-the-art drives using Hall-effect sensors alone, the low speed performance is greatly improved in healthy conditions and also following position sensor faults. It is envisaged that such a sensing system can be successfully used in applications requiring IEC 61508 SIL 3 or ISO 26262 ASIL D compliance, due to its extremely high mean time to failure and to the very fast recovery of the drive following Hall-effect sensor faults at low speeds. Extensive simulation and experimental results are provided on a 3.7 kW permanent magnet drive

Advanced Modeling of Anisotropic Synchronous Machine Drives for Sensorless Control

Synchronous machines are extensively used for home appliances and industrial applications thanks to their fast dynamic response, good overload capability and high energy density. A precise knowledge of the rotor position is required to control efficiently this kind of motors. In most of the applications resolvers or absolute encoders are installed on the rotor shaft. The employment of position sensors leads to significant drawbacks such as the increased size and cost of the system and a lower reliability of the drive, caused by additional hardware and cabling. In sensorless drives motor position is estimated and employed in the machine control. Thus, no position sensor is required by the drive and all the drawbacks entailed by the sensor are eliminated. Moreover, the position estimation could be useful for redundancy in case of system failures. Therefore, position estimation techniques are object of great interest in the electric drives field. Position estimation techniques can be divided into two main categories: methods that are suitable for medium or high speed and techniques suitable for low speed or standstill operations. In the former group the motor position is estimated through a reconstruction of the permanent magnet flux or back electromotive force (back-EMF). In case of synchronous reluctance machines it is possible to reconstruct the extended active flux or back-EMF. Stator voltages and currents measurements are needed for these reconstruction methods. Since these signals amplitude is proportional to the rotor speed, position estimation can be successfully performed only for medium and high speed machine operations. In the low speed range, sensorless schemes exploit the rotor magnetic anisotropy. Thus, position can be estimated only for anisotropic motors, i.e. synchronous reluctance motors (SynRM), permanent magnet assisted synchronous reluctance motors (PMA-SynRM) and interior permanent magnet synchronous motors (IPMSM). The rotor anisotropy is recognized thanks to an high frequency voltage injection in the stator windings. Several injection techniques have been proposed, differing from the signal typology. In particular, high frequency sinusoidal or square-wave carriers are often applied. The position information is usually extracted from the current response through a heterodyning demodulation that entails the use of low pass filters in the position estimator, limiting its dynamic. The aim of the research was proposing a new algorithm to estimate the rotor position from the HF current response, getting rid of the demodulation and its weaknesses. Thus, the ellipse fitting technique has been proposed. Robustness against signal processing delay effects and a reduced number of required filters are the main advantages of this novel approach. The inverse problem related to the ellipse fitting is solved implementing a recursive least squares algorithm. The proposed ellipse fitting technique is not affected by signal processing delay effects, and it requires the tuning of only one parameter, called forgetting factor, making the studied method suitable for industrial application thanks to its minimal setup effort. Besides the ellipse fitting technique for rotor position estimation, two other topics have been studied: - Computation of self-sensing capabilities of synchronous machines. - Online incremental inductances identification for SynRM.Synchronous machines are extensively used for home appliances and industrial applications thanks to their fast dynamic response, good overload capability and high energy density. A precise knowledge of the rotor position is required to control efficiently this kind of motors. In most of the applications resolvers or absolute encoders are installed on the rotor shaft. The employment of position sensors leads to significant drawbacks such as the increased size and cost of the system and a lower reliability of the drive, caused by additional hardware and cabling. In sensorless drives motor position is estimated and employed in the machine control. Thus, no position sensor is required by the drive and all the drawbacks entailed by the sensor are eliminated. Moreover, the position estimation could be useful for redundancy in case of system failures. Therefore, position estimation techniques are object of great interest in the electric drives field. Position estimation techniques can be divided into two main categories: methods that are suitable for medium or high speed and techniques suitable for low speed or standstill operations. In the former group the motor position is estimated through a reconstruction of the permanent magnet flux or back electromotive force (back-EMF). In case of synchronous reluctance machines it is possible to reconstruct the extended active flux or back-EMF. Stator voltages and currents measurements are needed for these reconstruction methods. Since these signals amplitude is proportional to the rotor speed, position estimation can be successfully performed only for medium and high speed machine operations. In the low speed range, sensorless schemes exploit the rotor magnetic anisotropy. Thus, position can be estimated only for anisotropic motors, i.e. synchronous reluctance motors (SynRM), permanent magnet assisted synchronous reluctance motors (PMA-SynRM) and interior permanent magnet synchronous motors (IPMSM). The rotor anisotropy is recognized thanks to an high frequency voltage injection in the stator windings. Several injection techniques have been proposed, differing from the signal typology. In particular, high frequency sinusoidal or square-wave carriers are often applied. The position information is usually extracted from the current response through a heterodyning demodulation that entails the use of low pass filters in the position estimator, limiting its dynamic. The aim of the research was proposing a new algorithm to estimate the rotor position from the HF current response, getting rid of the demodulation and its weaknesses. Thus, the ellipse fitting technique has been proposed. Robustness against signal processing delay effects and a reduced number of required filters are the main advantages of this novel approach. The inverse problem related to the ellipse fitting is solved implementing a recursive least squares algorithm. The proposed ellipse fitting technique is not affected by signal processing delay effects, and it requires the tuning of only one parameter, called forgetting factor, making the studied method suitable for industrial application thanks to its minimal setup effort. Besides the ellipse fitting technique for rotor position estimation, two other topics have been studied: - Computation of self-sensing capabilities of synchronous machines. - Online incremental inductances identification for SynRM

Dual-rate modified stochastic gradient identification for permanent magnet synchronous motor

The high-performance application of high-power permanent magnet synchronous motor (PMSM) is increasing. This paper focuses on the parameter estimation of PMSM. A novel estimation algorithm for PMSM’s dual-rate sampled-data system has been developed. A polynomial transformation technique is employed to derive a mathematical model for PMSM’s dual-rate sampled-data system. The proposed modified stochastic gradient algorithm gets more excellent convergence performance for smaller index ε. Simulation and experimental results demonstrate the effectiveness and performance improvement of the proposed algorithm