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

A Sensorless Direct Torque Control Scheme Suitable for Electric Vehicles

International audienceIn this paper a sensorless control is proposed to increase the efficiency of a Direct Torque Control (DTC) of an induction motor propelling an Electric Vehicle (EV). The proposed scheme uses an adaptive flux and speed observer that is based on a full order model of the induction motor. Moreover, it is evaluated on an EV global model taking into account the vehicle dynamics. Simulations were first carried out on a test vehicle propelled by a 37-kW induction motor to evaluate the consistency and the performance of the proposed control approach. The commonly used European drive cycle ECE-15 is adopted for simulation. The obtained results seem to be very promising. Then, the proposed control approach was experimentally implemented, on a TMS320F240 DSP-based development board, and tested on 1-kW induction motor. Experimental results show that the proposed control scheme is effective in terms of speed and torque performances. Indeed, it allows speed and torque ripple minimization. Moreover, the obtained results show that the proposed sensorless DTC scheme for induction motors is a good candidate for EVs propulsion

Speed -Sensorless Estimation And Position Control Of Induction Motors For Motion Control Applications

Thesis (Ph.D.) University of Alaska Fairbanks, 2006High performance sensorless position control of induction motors (IMs) calls for estimation and control schemes which offer solutions to parameter uncertainties as well as to difficulties involved with accurate flux and velocity estimation at very low and zero speed. In this thesis, novel control and estimation methods have been developed to address these challenges. The proposed estimation algorithms are designed to minimize estimation error in both transient and steady-state over a wide velocity range, including very low and persistent zero speed operation. To this aim, initially single Extended Kalman Filter (EKF) algorithms are designed to estimate the flux, load torque, and velocity, as well as the rotor, Rr' or stator, Rs resistances. The temperature and frequency related variations of these parameters are well-known challenges in the estimation and control of IMs, and are subject to ongoing research. To further improve estimation and control performance in this thesis, a novel EKF approach is also developed which can achieve the simultaneous estimation of R r' and Rs for the first time in the sensorless IM control literature. The so-called Switching and Braided EKF algorithms are tested through experiments conducted under challenging parameter variations over a wide speed range, including under persistent operation at zero speed. Finally, in this thesis, a sensorless position control method is also designed using a new sliding mode controller (SMC) with reduced chattering. The results obtained with the proposed control and estimation schemes appear to be very compatible and many times superior to existing literature results for sensorless control of IMs in the very low and zero speed range. The developed estimation and control schemes could also be used with a variety of the sensorless speed and position control applications, which are challenged by a high number of parameter uncertainties

Sensorless And Independent Speed Control Of Dual-PMSM Drives Using Five-Leg Inverter (FLI)

This research aims to develop and implement a combined sensorless and independent speed control for dual-PMSM (Permanent Magnet Synchronous Motor) drives fed by a single Five-Leg Inverter (FLI). Dual-motor drives are widely used in high traction power industry such as propulsion system, aircraft, locomotive, Hybrid Electric Vehicle (HEV) and others. In general, dual-motor drives are designed to reduce size and cost with respect to single motor drives. However, dual-motor drives using a single three-leg inverter has its limitation in the case of operation at different operating conditions and independent speed control requirement. Recent research has shown that, dual motor drives can be independently controlled by using Five-Leg inverter (FLI). By employing this FLI topology, the dual-motor drives can be used for four-quadrant control, variable speed operation and load disturbance rejection. In other words, it can be operated for different applications. In the case of conventional dual-PMSM drives, the drives system still requires current sensors and voltage transducers for speed and rotor position estimation. In PMSM drives, the information of the feedback speed and rotor angular position is compulsory. Therefore, this research is trying to implement a combined sensorless and independent speed control for dual PMSM drives system and at the same time eliminating the usage of voltage transducers. This thesis investigates the behavior of sensorless and independent speed control for Dual-Permanent Magnet Synchronous Motor (PMSM) drives. Initially, a single PMSM drives is designed and simulated, followed by the development of Dual-PMSM drives model. The speed and current controllers are implemented in d-q rotor reference frame using Simulink/MATLAB and the switching signals are generated by the built-in function and dSPACE. Then, the sensorless drive system is developed based on adaptive speed and position estimator. The overall performance of the drives is investigated and evaluated in terms of speed responses overshoot under variation of speed reference and speed drop under load torque disturbances. The simulation results have proved that the performance characteristics of sensorless dual-PMSM are almost similar with system using sensor except during the start-up condition. The motor performance is degraded in terms of speed overshoot for small and medium speed reference or when the motor operates far from the designed operating condition (rated value). The proposed independent dual-PMSM drives fed by FLI have better load rejection capability compared with conventional dual-PMSM drives fed by single three-phase inverter. The experimental results of the drives under investigation have shown acceptable correlation between the theoretical and simulation

A PI/Backstepping Approach for Induction Motor Drives Robust Control

International audienceThis paper presents a robust control design procedure for induction motor drives in case of modeling errors and unknown load torque. The control law is based on the combination of nonlinear PI controllers and a backstepping methodology. More precisely, the controllers are determined by imposing flux-speed tracking in two steps and by using appropriate PI gains that are nonlinear functions of the system state. A comparative study between the proposed PI/Backstepping approach and the feedback linearizing control is made by realistic simulations including load torque changes, parameter variations and measurement noises. Flux-speed tracking results show the proposed method effectiveness in presence of strong disturbances

Development and Implementation of Some Controllers for Performance Enhancement and Effective Utilization of Induction Motor Drive

The technological development in the field of power electronics and DSP technology is rapidly changing the aspect of drive technology. Implementations of advanced control strategies like field oriented control, linearization control, etc. to AC drives with variable voltage, and variable frequency source is possible because of the advent of high modulating frequency PWM inverters. The modeling complexity in the drive system and the subsequent requirement for modern control algorithms are being easily taken care by high computational power, low-cost DSP controllers. The present work is directed to study, design, development, and implementation of various controllers and their comparative evaluations to identify the proper controller for high-performance induction motor (IM) drives. The dynamic modeling for decoupling control of IM is developed by making the flux and torque decoupled. The simulation is carried out in the stationary reference frame with linearized control based on state-space linearization technique. Further, comprehensive and systematic design procedures are derived to tune the PI controllers for both electrical and mechanical subsystems. However, the PI-controller performance is not satisfactory under various disturbances and system uncertainties. Also, precise mathematical model, gain values, and continuous tuning are required for the controller design to obtain high performance. Thus, to overcome these drawbacks, an adapted control strategy based on Adaptive Neuro-Fuzzy Inference System (ANFIS) based controller is developed and implemented in real-time to validate different control strategies. The superiority of the proposed controller is analyzed and is contrasted with the conventional PI controller-based linearized IM drive. The simplified neuro-fuzzy control (NFC) integrates the concept of fuzzy logic and neural network structure like conventional NFC, but it has the advantages of simplicity and improved computational efficiency over conventional NFC as the single input introduced here is an error instead of two inputs error and change in error as in conventional NFC. This structure makes the proposed NFC robust and simple as compared to conventional NFC and thus, can be easily applied to real-time industrial applications. The proposed system incorporated with different control methods is also validated with extensive experimental results using DSP2812. The effectiveness of the proposed method using feedback linearization of IM drive is investigated in simulation as well as in experiment with different working modes. It is evident from the comparative results that the system performance is not deteriorated using proposed simplified NFC as compared to the conventional NFC, rather it shows superior performance over PI-controller-based drive. A hybrid fuel cell (FC) supply system to deliver the power demanded by the feedback linearization (FBL) based IM drive is designed and implemented. The modified simple hybrid neuro-fuzzy sliding-mode control (NFSMC) incorporated with the intuitive FBL substantially reduces torque chattering and improves speed response, giving optimal drive performance under system uncertainties and disturbances. This novel technique also has the benefit of reduced computational burden over conventional NFSMC and thus, suitable for real-time industrial applications. The parameters of the modified NFC is tuned by an adaptive mechanism based on sliding-mode control (SMC). A FC stack with a dc/dc boost converter is considered here as a separate external source during interruption of main supply for maintaining the supply to the motor drive control through the inverter, thereby reducing the burden and average rating of the inverter. A rechargeable battery used as an energy storage supplements the FC during different operating conditions of the drive system. The effectiveness of the proposed method using FC-based linearized IM drive is investigated in simulation, and the efficacy of the proposed controller is validated in real-time. It is evident from the results that the system provides optimal dynamic performance in terms of ripples, overshoot, and settling time responses and is robust in terms of parameters variation and external load

Differential-Algebraic Approach to Speed and Parameter Estimation of the Induction Motor

This thesis considers a differential-algebraic approach to estimating the speed and rotor time constant of an induction motor using only the measured terminal voltages and currents. It is shown that the induction motor speed satisfies both a second-order and a third-order polynomial equation whose coefficients depend the stator voltages, stator currents, and their derivatives. Further, it is shown that as long as the stator electrical frequency is nonzero, the speed is uniquely determined by these polynomials. The speed so determined is then used to stabilize a dynamic (Luenberger type) observer to obtain a smoothed speed estimate. With full knowledge of the machine parameters and filtering of the sensor noise, simulations and experiments indicate that this estimator has the potential to provide low speed (including zero speed) control of an induction motor under full load. A differential-algebraic approach is also used to obtain an estimate of the rotor time constant of an induction motor, again using only the measured stator voltages and currents. Experimental results are presented to demonstrate the practical use of the identification method

Rotor speed estimation for indirect stator flux oriented induction motor drive based on MRAS scheme

In this paper, a conventional indirect stator flux oriented controlled (ISFOC) induction motor drive is presented. In order to eliminate the speed sensor, an adaptation algorithm for tuning the rotor speed is proposed. Based on the model reference adaptive system (MRAS) scheme, the rotor speed is tuned to obtain an exact ISFOC induction motor drive. The reference and adjustable models, developed in stationary stator reference frame, are used in the MRAS scheme to estimate induction rotor peed from measured terminal voltages and currents. The IP gains speed controller and PI gains current controller are calculated and tuned at each sampling time according to the new estimated rotor speed. The proposed algorithm has been tested by numerical simulation, showing the capability of driving active load; and stability is preserved. Experimental results obtained with a general-purpose 1-kW induction machine are presented showing the effectiveness of the proposed approach in terms of dynamic performance

Comparative Analysis of Estimation Techniques of SFOC Induction Motor for Electric Vehicles

International audienceThis paper presents system analysis, modeling and simulation of an electric vehicle with different sensorless control techniques. Indeed, sensorless control is considered to be a lower cost alternative than the position or speed encoder-based control of induction motors for an electric vehicle. Two popular sensorless control methods, namely, the Luenberger observer and the Kalman filter methods are compared regarding speed and torque control characteristics. They are also compared against the well-known model reference adaptive system. Simulations on a test vehicle propelled by 37-kW induction motor lead to very interesting comparison results

Data-driven online temperature compensation for robust field-oriented torque-controlled induction machines

Squirrel-cage induction machines (IMs) with indirect field-oriented control are widely used in industry and are frequently chosen for their accurate and dynamic torque control. During operation, however, temperature rises leading to changes in machine parameters. The rotor resistance, in particular, alters, affecting the accuracy of the torque control. The authors investigated the effect of a rotor resistance parameter mismatch in the control algorithm on the angular rotor flux misalignment and the subsequent deviation of stator currents and motor torque from their setpoints. Hence, an online, data-driven torque compensation to eliminate the temperature effect is proposed to enable robust torque-controlled IMs. A model-based analysis and experimental mapping of the temperature effect on motor torque is presented. A temperature-torque lookup-table is subsequently implemented within the control algorithm demonstrating the ability to reduce the detrimental effect of temperature on torque control. Experimental results on a 5.5 kW squirrel-cage induction motor show that the proposed data-driven online temperature compensation method is able to reduce torque mismatch when compared to having no temperature compensation. Up to 17% torque mismatch is reduced at nominal torque and even up to 23% at torque setpoints that are lower than 20% of the nominal torque. A limited torque error of <1% remains in a broad operating range