Nicola Bedetti

Self-Commissioning of Inverter Dead-Time Compensation by Multiple Linear Regression Based on a Physical Model

Dead-time and switch voltage drops represent the most important sources of distortion of the (average) output voltage in pulsewidth modulation inverters. Their effect is a function of the parameters of the drive system and of the operating conditions and is often intolerable in many drives applications, thus requiring a proper compensation strategy. Many techniques are implemented in industrial drives and reported in the literature, even very recently. Differently from standard approaches, the proposed methodology is based on a detailed physical model of the power converter (including output capacitance), described by a small set of parameters. A novel self-commissioning identification procedure is introduced, adopting multiple linear regression. The technique is tested on a commercial drive in comparison with state-of-the-art techniques. In addition, back electromotive force estimation improvements in a permanent-magnet synchronous motor sensorless drive system are shown to provide additional validation of the method.

Stand-Still Self-Identification of Flux Characteristics for Synchronous Reluctance Machines Using Novel Saturation Approximating Function and Multiple Linear Regression

Motor characterization has a fundamental role in dynamics, torque accuracy, and efficiency of vector controlled Synchronous Reluctance Machine (SynRM) drives. Control performances and robustness in the whole speed/torque range, including the flux-weakening region, and in sensorless operation strongly rely on the knowledge of machine flux versus current characteristics. A convenient flux saturation approximating function is proposed in this paper, together with an efficient parameters self-identification procedure. The adopted strategy is very simple and can be performed at stand-still by injecting a proper voltage stimulus (current control is not involved), and does not require any additional hardware (motor can be either connected or disconnected from mechanical load). Nevertheless, an excellent fitting for the flux curves on both axes is obtained, using reasonable memory and computational resources. These features make the technique very suitable to motor self-identification in industrial drives. Experimental results based on a commercial drive and two SynRMs are reported to demonstrate the effectiveness of the proposal. Extensions of the method to the evaluation of the whole flux map (including cross-saturation effects) or to interior permanent-magnet machines is also investigated and verified.

Accurate modeling, compensation and self-commissioning of inverter voltage distortion for high-performance motor drives

Dead-times, power devices voltage drops and total output capacitance represent the most important sources of distortion of the average output voltage in voltage-fed PWM inverters. Their effect is a function of actual parameters of the drive system and of the operating conditions, and is often intolerable in many drives applications, thus requiring a proper compensation strategy. Many techniques are implemented in industrial drives and reported in literature, even very recently. Necessary dead time between the two switches of each leg for sure represents the main cause of distortion and is therefore the most investigated topic in technical literature. Less often the compensation strategy is based on an actual model of the converter due to the increased complexity of the modeling task and consequently due to the difficulties in the compensation approach. The methodology considered in this paper belongs to this last class and is based on a detailed physical model of the power converter. A novel approach is presented to obtain a properly simplified model, thus allowing the derivation of a simple but effective compensation strategy. A novel self-commissioning identification of the compensation model parameters is proposed and its validity and effectiveness is verified on a commercial general purpose drive. Comparison with respect to standard compensation techniques is reported and demonstrates the superior characteristics of the proposal. Finally, dramatic performance improvements of a sensorless drive system are also shown to gain an additional validation of the method.

Analytical design of flux-weakening voltage regulation loop in IPMSM drives

Analytical design and adaptation of voltage regulation loop for flux-weakening control of Interior Permanent Magnet Synchronous Motor drives are addressed in this paper. Theoretical analysis of the overall dynamics of the loop has been carried out in recent papers, also taking into account non-linear effects and discrete-time implementation issues. A proper gain adaptation technique was proposed to provide a local linearization, aiming at maximization of the dynamical performance and maintain stability of the loop. Unfortunately no closed-form design method was provided due to the complexity of the transfer function and only graphical analysis of the loop function was shown. In this paper a novel simplified analysis is proposed, which allows analytical design of the regulator gains after the application of a real-time compensation of any non-linearity. Simulations validate the approach, and experimental tests show the feasibility of the technique on a standard drive hardware, leveraging its ease of implementation.

Stand-still self identification of flux characteristics for SynRM using novel saturation approximating function and multiple linear regression

Accuracy of motor characterization has a fundamental role in dynamics, torque accuracy and efficiency of vector controlled Synchronous Reluctance Motor (SynRM) drives. Control performances and robustness in the whole speed/torque range, including the flux-weakening region, and in sensorless operation strongly rely on the knowledge of machine flux vs. current characteristics. A convenient flux saturation approximating function is proposed in this paper, together with an efficient parameters self-identification procedure. The adopted strategy is very simple and can be performed at standstill by injecting a proper voltage stimulus (current control is not involved), and does not require any additional hardware (motor can be either connected or disconnected from mechanical load). Nevertheless an excellent fitting for the flux curves on both axes is obtained, using reasonable memory and computational resources. These features make the technique very suitable to motor identification in industrial drives. Experimental results based on a commercial drive and two SynRM machines are reported to demonstrate the effectiveness of the proposal. Extensions of the method to the evaluation of the whole flux map (including cross-saturation effects) or to interior permanent magnet machines is also investigated and verified.

A novel approach to the design of back-EMF observer based sensorless control of non-salient PMSM: Theoretical analysis and experimental investigations

A back-electromotive force (back-EMF) based sensorless technique for isotropic surface-mounted permanent magnet synchronous motor (SPMSM) drive systems is considered in this paper. Differently from the case of application-specific drives, in general-purpose ones tuning represents an important challenge, especially if low-speed operation or relatively fast dynamics is desired. The trade-off between dynamics and steady-state performances introduced by estimation noise, and in particular by inverter non-linearity, is discussed. The influence of the parameters in the speed and position estimation loop is characterized analytically and experimentally. As a result, a procedure for the design of each of the estimation processing blocks is derived, which is parametric on the desired speed regulation bandwidth, taken as an input from the application requirements. Finally, the stabilizing effect of a constant positive direct-axis current reference is demonstrated, which allows to obtain consistent improvements in control accuracy performances at low-speed, at the cost of very small additional losses.

Automatic MTPA tracking in IPMSM drives: Loop dynamics, design and auto-tuning

Maximum Torque Per Ampere (MTPA) based on motor parameters is a common approach to achieve high efficiency and torque density in Interior Permanent Magnet Synchronous Machine Drives (IPMSMs). However, uncertainty (e.g., due to identification errors, magnetic saturation, or temperature variation) results in undesired deviation from the optimal operating trajectory. To solve this problem, MTPA tracking methods have been proposed, which exploit signal injection to search the minimum current point for a certain load torque in a closed-loop fashion. Closed-form design of the MTPA tracking loop dynamics has never been addressed in past literature and represents the main topic of this paper. A recent and efficient tracking method has been considered for the analysis and case study, i.e., [14]. Nonlinear small-signal gain of the loop can be calculated in closed form, leading to two valuable results. Dynamics can be programmed by optimal design of the tracking regulator, and online adaptation can be applied, making the designed MTPA tracking dynamics invariant with the operating point. A straightforward and effective solution is proposed for the regulator design, which allows us to obtain the desired bandwidth and first-order tracking response in the whole range of operation, being also suitable for auto-tuning and online adaptation. The method has been studied analytically and in simulation, also considering the influence of noise and parametric uncertainties. Finally the technique has been implemented on the hardware of a commercial industrial drive, proving the effectiveness of the proposal. The concepts described in this paper, design approach and adaptation strategy, analyzed here for the first time, are general and can be applied to any control scheme implementing closed-loop MTPA tracking.

Automatic MTPA Tracking in IPMSM Drives: Loop Dynamics, Design and Auto-Tuning

In the control of Interior Permanent Magnet Synchronous Machines (IPMSMs), Maximum Torque Per Ampere (MTPA) based on motor parameters is a common approach to achieve high efficiency and torque density. Parametric uncertainty (e.g. due to identification errors, magnetic saturation or temperature variation) results in undesired deviation from the optimal operating trajectory. To solve this problem, MTPA tracking methods have been proposed, which exploit signal injection to search the minimum current point for a certain load torque, in a closed-loop fashion. For one of these methods, [13], stability of the non-linear dynamics was analyzed, and an upper bound for the convergence time was found, but no explicit method was proposed for the design of the tracking regulator. In this paper this last topic is addressed. By introducing some approximations, the linearized system is calculated and a loop transfer function obtained, which is invariant with the operating point. Thus, by means of a very simple design rule (i.e. suitable for auto-tuning), the MTPA tracking regulator gains can be designed in order to obtain the desired bandwidth. The method has been studied analytically and in simulation, also considering the influence of noise and parametric uncertainties. Finally the technique has been implemented on the hardware of a commercial industrial drive, proving the effectiveness of the proposal.

Self-commissioning of inverter dead-time compensation by multiple linear regression based on a physical model

Dead-times and switch voltage drops represent the most important sources of distortion of the (average) output voltage in PWM inverters. Their effect is a function of the parameters of the drive system and of the operating conditions, and is often intolerable in many drives applications, thus requiring a proper compensation strategy. Many techniques are implemented in industrial drives and reported in literature, even very recently. Differently from standard approaches the proposed methodology is based on a detailed physical model of the power converter (including output capacitance), described by a small set of parameters. A novel self-commissioning identification procedure is proposed, adopting Multiple Linear Regression. The technique is tested on a commercial drive in comparison to state-of-the-art techniques. Also back-EMF estimation improvements in a PMSM sensorless drive system are shown to provide additional validation of the method.

Self-adaptation of MTPA tracking controller for IPMSM and SynRM drives based on on-line estimation of loop gain

Maximum Torque Per Ampere (MTPA) tracking techniques for the control of Interior Permanent Magnet Synchronous Machines (IPMSMs) and Synchronous Reluctance Machine (SynRMs) drives were introduced in the last decade, with the aim of overcoming the dependence on motor parameter knowledge accuracy. In fact, uncertainty due to identification errors, magnetic saturation or temperature variation results in undesired deviation from the optimal MTPA trajectory. A recent paper [14] addressed gain adaptation and closed-form design of the loop controller gain for the MTPA tracking method proposed in [11]. However, since adaptation was based on motor parameters, at least a coarse knowledge of them was required. Moreover, relatively intensive calculation resources had to be dedicated to the adaptation task. In order to overcome these issues, a novel technique is proposed in this paper, in which gain estimation is adopted in place of parameters-based calculation. The MTPA tracking process gain is estimated by proper demodulation and filtering of the current vector magnitude component at twice the injection frequency. The obtained signal is then used for gain adaptation of the MTPA tracking loop. The method theoretical basis will be first introduced and the concept demonstrated by means of simulations. Implementation has been carried out using the hardware of a standard industrial drive and a 2.2 kW IPMSM. Experimental test results show the effectiveness of the proposal, with performances comparable to the previously proposed parameter-based gain adaptation.