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The primary objective of this work is to optimize the induction motor rotor flux so that maximum efficiency is attained in the facets of parameter and load variations. The conventional approaches based on loss model are sensitive to modelling accuracy and parameter variations. The problem is further aggravated due to nonlinear motor parameters in different speed regions. Therefore, this work introduces an adaptive neuro-fuzzy inference system-based rotor flux estimator for electric vehicle. The proposed estimator is an amalgamation of fuzzy inference system and artificial neural network, in which fuzzy inference system is designed using artificial neural network. The training data for neuro-fuzzy estimator is generated offline by acquiring rotor flux for different values of torque. The conventional fuzzy logic and differential calculation methods are also developed for comparative analysis. The efficacy of developed system is established by analyzing it under varying load conditions. It is revealed from the results that suggested methodology provides an improved efficiency i.e. 94.51% in comparison to 82.68% for constant flux operation.

When changing the parameters of the control object to ensure the required quality of control, the tuning parameters of the control system must be changed. Investigation of the sensitivity of mathematical models helps to choose the right technical parameters of the regulators. Therefore, there is an urgent scientific task, which consists in the development of mathematical models for calculating the steady-state values ​​of the sensitivity functions of the coordinates of non-linear systems to changes in their parameters. When synthesizing observers of the rotor flux linkage, it is indicated that the signal for evaluating the rotor flux linkage is most sensitive to a change in the active resistance of the rotor of an induction machine. However, the numerical values ​​of the transmission coefficients between the coordinates of the observer and the increments of the parameters of the asynchronous machine during its operation are not given, which does not allow a comparative analysis of the degree of influence of changes in certain parameters of the asynchronous machine on the signals of the observer of the flux linkage. The task is to find and compare the numerical values ​​of the functions of the sensitivity of the coordinates of the observer of the rotor flux linkage to the change in the parameters of the asynchronous machine by joint analytical solution of the static equations of the observer's sensitivity model and the state model of the asynchronous machine. In this work, analytical expressions are obtained for the steady-state values ​​of the sensitivity functions of the coordinates of such a nonlinear object as an observer of the rotor flux linkage to a change in the parameters of an asynchronous machine. A comparative analysis of the values ​​of the transmission coefficients between the parameters and coordinates in the system asynchronous machine — observer of the rotor flux linkage for its various rotation speeds is carried out. The proposed technique makes it possible to find the numerical values ​​of the transmission coefficients and to compare the degree of influence of various parameters of the asynchronous machine on the coordinates of the flux linkage observer. Transient processes obtained in the course of solving the equations of the dynamics of an asynchronous electric drive with an observer of flux linkage complement the results of analytical calculations. The performed calculations are aimed at increasing the depth of analysis of the properties of the flux link observer, which helps to reasonably choose the structure of feedbacks when synthesizing a closed observer.

Electrical machines are widely used in home appliances, the performance of which is mostly related to the quality function of the electrical machines. What has been used so far in home appliances brought with themselves a wide assortment of advantages and disadvantages. With the aim to overcome the drawbacks of the previously implemented electrical motors in washing machines, a new configuration of flux switching permanent magnet motor (FSPM) with the segmented outer rotor (SOR‐FSPM) is proposed benefitting from a direct driven drum. To reduce the cogging torque as well as torque ripple and to improve the total harmonic distortion, cutting the stator in a way to lower overlapping between the rotor and stator pole, inserting notches into the poles of the rotor to modify the air gap between the stator teeth and the rotor segments are proposed. The Taguchi method and sensitivity analysis are further applied to find the best combination set of changes in such a way to smoothen the chart showing reluctance between stator and rotor and fix the zero‐point crossing of the flux linkages in different rotor positions. Finally, the proposed SOR‐FSPM is prototyped, and experimental results along with the finite element method results are discussed and compared in order to verify the design process.

With the wide applications of dual‐rotor flux‐modulation machines for the growing wind power generations, research activities for the control of dual‐rotor flux‐modulation machines are intensified in recent years. Most of the existing control schemes are based on indirect measurements of the d‐axis inductance, the q‐axis inductance and the stator resistance to achieve high torque density and low torque ripple for the dual‐rotor flux‐modulation machines. However, conventional measurements of the d‐axis inductance, the q‐axis inductance and the stator resistance may suffer from (i) low accuracy and (ii) additional sensor costs. To this end, an adaptive differential evolution algorithm is proposed to identify the machine parameters by considering the magnetic saturation and cross‐coupling issue at low rotational speed of dual‐rotor flux‐modulation machines. Finite element analysis is adopted in simulation to preliminarily monitor the actual machine parameter values based on the length and cross section area of the conductor and inductance matrix computation. Both simulation and experimental results reveal that the adopted adaptive differential evolution algorithm can identify the three parameters more steadily and accurately than the conventional genetic algorithm.

In this paper, a new approach being different from the concept of DTC and IFOC for a robust torque control design for induction motor is addressed. The design is based on the framework of singularly perturbed system theory and linear varying parameter systems. In these systems, the rotor flux is considered to be a time-varying parameter in order to guarantee a robust torque control with LPV flux observer with respect to the speed and resistance variations. In fact, this observer is designed to estimate the rotor flux as well as an MRAS observer is introduced to estimate the mechanical speed and rotor resistance. The main feature of this proposed structure is the enhancement of robustness with flux, speed and rotor resistance variation. This improvement leads to a considerable decrease of the torque ripples and ensures the stability for the entire operating range. The obtained simulations and experimental results are used to validate the effectiveness of the proposed control strategy.

In this article, the torque ripple of an induction motor due to dc injection for the stator resistance estimation is analyzed. In the analysis, the fundamental component of rotor flux is used for rotor flux orientation to avoid the perturbation issue in synchronous reference speed. On the synchronous reference frame, flux and torque fluctuation due to injected dc and arbitrary second harmonic current is calculated. Furthermore, the current reference that nullifies the fundamental frequency torque ripple in the whole operating condition is proposed. An integral-based average filter is applied to extract dc signals in phase voltage and current. Simulations and experiments are carried out to verify the performance of the proposed methods.