Matteo Berto

This paper presents a quasi-static model for assessing potential energy savings through partial electrification of a land leveler implement. The quasi-static model simulates the behavior of the hydraulic circuit components, including the pump and a spool-type flow divider, for a commercial land leveler used in agricultural applications. Two electrification schemes are presented. In the first scheme, the pump, originally driven at fixed speed by the PTO, is driven at variable speed by an electric drive, with no changes in the hydraulic circuit. In the second electrification scheme, the decentralization of the hydraulic system is implemented by using separate variable-speed pumps for each actuator. Results show significant potential energy savings of 9–22% with the first electrification scheme and 45–53% with the second scheme, compared to the traditional non-electrified setup. Our findings demonstrate that electrification could be a strategic choice to improve the efficiency of tractor implements and agricultural machinery.

Motor characterization consists in measuring or simulating the flux linkages maps on a grid of current points. These maps are required to compute the incremental inductances and self-sensing capabilities of the considered motor on the same grid. The method proposed in this paper allows the reconstruction of the incremental inductances maps using less samples than the full (conventional) characterization, i.e. only the samples of the flux linkages along the current domain borders. The method relies on the coenergy model and it is validated on the measured maps of a synchronous reluctance motor. The code used to compute the coenergy, the incremental inductances, and selfsensing capabilities is available as an open source package.

Convergence region and estimation error of high frequency injection sensorless control strictly depend on the selected synchronous machine and on the actual operating point. An accurate knowledge of the motor parameters is required to compute the self-sensing capability range. The aim of this article is to show a fast solution to identify the convergence region based on incremental parameters approximation with less experimental measurements than the conventional approach. The proposed method to reconstruct the motor convergence region is fully offline. It requires few samples of the inverse incremental inductances, which are processed through some math and a simple fitting procedure. The method is validated through experimental measurements for two different types of synchronous motors for a sensorless drive application.

This paper presents an investigation on the self-sensing capability of a dual three-phase synchronous reluctance motor. Self-sensing capability refers to the ability of the motor to properly operate in a sensorless drive. The multiphase machine is decomposed into two different three-phase systems according to the multi-stator approach. Several supply scenarios are studied where the two three-phase windings are controlled at different operating points along a reference trajectory. The analysis is carried out both with FEA simulations and experimental tests. In the first part of the paper the rotor is locked to derive the observer trajectories and find the regions in which the motor can operate without position sensor. A comparison between simulated and experimental results is given. Finally, a sensorless control strategy that allows exploiting the motor self-sensing capability under position sensor fault is developed and validated through experimental tests.

Signal injection sensor-less control for synchronous machines is known to be afflicted by an estimation error dependent on the load current. The estimation error is related to the cross-saturarion and the saliency of the adopted synchronous machine. A motor can be more or less suitable for signal injection sensorless control compared to other motors with different designs or sizes. A sensorless drive can even be afflicted by the control divergence when the machine is highly saturated, resulting in a useless drive. Moreover, even when the control converges, the actual current control trajectory is different from the given reference. In this paper, a measurement procedure of the convergence region, i.e. the operating points where the motor can be successfully controlled without a position sensor is presented and validated. In particular, two different synchronous motors are considered, a permanent magnet assisted synchronous reluctance motor (PMA-SynRM) and a synchronous reluctance motor (SynRM).

The convergence and the estimation error of a high frequency voltage injection sensorless control depends strictly on the synchronous machine adopted and on the working point where it operates. In order to estimate the self-sensing capability range of the motor, it is necessary to know its parameters accurately. The aim of this paper is to show a new solution to identify the convergence range through a differential parameter approximation with less experimental and computational burden. The method is validated through finite element analysis and experimental measurements for two different types of synchronous motors.

This paper deals with the sensorless detection of rotor position of synchronous reluctance motors in the low speed operating region. In particular, the position estimation is obtained by means of an high frequency voltage signal injection. The convergence and the estimation error of all such sensorless control algorithms of reluctance synchronous motors result troublesome. In fact, they strictly depend on the current working point where they operate. In order to evaluate the self-sensing capability range, an accurate modeling of motor parameters should be required. This paper proposes an innovative solution to identify the self-sensing convergence region through a differential parameters approximation. Advantages of this method include a lower commissioning effort and a reduced computational burden maintaining accurate reliability. The new approach was validated using experimental measurements.

This paper deals with an experimental investigation on the self-sensing capability of a dual three-phase synchronous reluctance machine. Sensorless control is affected by an estimation error which depends on the load current. This error is related to the cross-saturation and the saliency of the adopted machine. Thus, a sensorless estimator could be unstable when the motor is heavily saturated. Self-sensing capability of a dual three-phase synchronous reluctance machine was experimentally studied. Two motor configurations were analysed, namely when one or both three-phase systems are supplied. A control strategy which exploits the described motor self-sensing capability is proposed and validated.

The article deals with a position sensorless control for synchronous motor drive with an ease tuning procedure and a reduced number of tunable parameters. The rotating high-frequency (HF) signals injection is implemented and the elliptical shape of the HF-induced current trace is fitted by means of the least square (LS) algorithm. The ellipse tilt is related to the rotor position and the latter is estimated by processing the fitted coefficients of the ellipse mathematical equation. The proposed LS algorithm processes the measured currents, without the need to filter them as occurs in conventional injection methods. Furthermore, no motor parameters are required to tune the proposed rotor position observer. The method was validated throughout several experimental tests performed on an interior permanent magnet synchronous motor.

The paper deals with the online incremental inductances estimation of a synchronous motor at low speeds using a high-frequency voltage injection. The control scheme is analogous to that used in position estimation algorithms, with the difference that the current control and the rotating voltage injection operate on the real dq axes. Thus a position sensor is required to apply this method. The corresponding current response is measured, filtered, and processed with an ellipse fitting technique. The estimated ellipse coefficients are then used to retrieve the incremental inductances online without the need of any post processing. A novel formulation to express the estimation error valid for other conventional signal injection techniques is presented. The method has been validated experimentally on a reluctance synchronous motor at locked rotor and during load and speed transients.