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This article presents the DTC-SVM approach for controlling a sensorless speed induction motor. To implement this approach, a practical prototype is built using a microcontroller, an embedded GPS module, and a memory card to collect real-time data during the driving route, such as road geographical data, speed, and time. These data are then utilized in the laboratory to implement the control law (DTC-SVM) on the electric vehicle. The d-q model of the induction motor is first presented to explain the requirements for calculating the rotor speed. Then, an adaptive model reference system speed estimator is developed based on the rotor flux, along with a controller and DTC-SVM strategy, which are implemented using the dSpace 1104 board to achieve the desired performance. The simulation results demonstrate satisfactory speed regulation with the proposed system. In this study too, an electronic differential system is modeled for the four wheels of an electric vehicle equipped with an integrated motor, all controlled by the DTC-SVM strategy. Vehicle speed and electrical vehicle steering angle variations, as well as wheel speeds estimated by code system, are verified using MATLAB/Simulink simulations. [ABSTRACT FROM AUTHOR]

Multiple factors and consequences may lead to a stator winding fault in an external rotor permanent magnet synchronous motor that can unleash a complete system shutdown and impair performance and motor reliability. This type of fault causes disturbances in operation if it is not recognized and detected in time, since it might lead to catastrophic consequences. In particular, an external rotor permanent magnet synchronous motor has disadvantages in terms of fault tolerance. Consequently, the distribution of the air-gap flux density will no longer be uniform, producing fault harmonics. However, a crucial step of diagnosis and controlling the system condition is to develop an accurate model of the machine with a lack of turns in the stator winding. This paper presents an analytical model of the stator winding unbalance fault represented by lack of turns. Here, mathematical approaches are used by introducing a stator winding parameter for the analytical modeling of the faulty machine. This model can be employed to determine the various quantities of the machine under different fault levels, including the magnetomotive force, the flux density in the air-gap, the flux generated by the stator winding, the stator inductances, and the electromagnetic torque. On this basis, a corresponding link between the fault level and its signature is established. The feasibility and efficiency of the analytical approach are validated by finite element analysis and experimental implementation. [ABSTRACT FROM AUTHOR]

Position control in electrical drives is a challenging problem which is complicated by sensor noise and unknown disturbances. This paper proposes a new cascade sensorless speed control technique for induction motor drives suitable for electric vehicle applications using the full-order adaptive Luenberger observer that is insensitive to measurement noise and parametric variation. The adaptive speed law is obtained by the Lyapunov method using the estimated currents and fluxes. This technique ensures the stability of the induction motor considered as nonlinear dynamic system. Since the Luenberger observer works on deterministic environment, and it is most effective when sensor noise is limited, the present study aims to design a robust observer insensitive to measurement noise and parametric variation integrated in a cascade structure. The observer allows the filtering of the measured currents. To highlight the advantages of the new scheme, a comparative study and spectrum analysis will be presented. The proposed structure is verified using MATLAB/Simulink. [ABSTRACT FROM AUTHOR]