Modeling and Control of AC Machine using MATLAB®/SIMULINK

Boufadene, Mourad

doi:10.1201/9780429029653

Cited by 4 publications

(2 citation statements)

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“…The state vector was represented as X, the input as U , and the output as Y . As stated by [16], the state and the input vectors of an IM can be specified by the stator current and the rotor flux components based on their rotational d-q frame. Thus, they can be defined as:…”

Section: Im State-space Mathematical Modelmentioning

confidence: 99%

Induction motor performance improvement using a five-level inverter topology and sliding mode controllers

Fahassa

Abbou

Zahraoui³

et al. 2023

Bulletin EEI

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This research intends to establish a robust vector control (VC) of a 3-ϕ induction motor (IM). The classical 2-level inverter is displaced by a 5-level neutral-pointclamped (NPC) inverter. The 2-level inverter may only supply 8 voltage vectors, while the 5-level NPC inverter can furnish 125 voltage vectors. The objective is to bring about a command voltage vector that converges to the reference voltage vector as closely as possible; hence, guaranteeing a quick response on one hand and improving the dynamic performance on the other hand. A robust sliding mode controller (SMC) structure is used in all regulation loops. Satisfactory results are obtained for various speed zones. The quality and robustness of the global system are tested under resistive torque disturbance, reversal, high, and low-speed ranges in order to prove system stability. All the simulations have been performed under MATLAB/Simulink.

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Section: Im State-space Mathematical Modelmentioning

confidence: 99%

Induction motor performance improvement using a five-level inverter topology and sliding mode controllers

Fahassa

Abbou

Zahraoui³

et al. 2023

Bulletin EEI

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“…The machine parameters are considered constant regardless of the saturation level of the magnetic circuit. 37,38 The objective of this approach is to formulate the stator flux reference in terms of the electromagnetic torque and the rotation speed.…”

Section: Losses Minimization Algorithmmentioning

confidence: 99%

Energy optimization of an electric car using losses minimization and intelligent predictive torque control

Kraiem

Shaaban

2020

Journal of Algorithms & Computational Technology

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Autonomy is considered an important criterion that characterizes the performance of electric vehicles. It is represented by the distance that could be traveled by a fully electric vehicle which mainly depends on several parameters such as the vehicle model, type of battery, type of motor, etc. In this context, to improve the autonomy of electric vehicles, this paper represents an optimization study for the electric motor based on two contributions. The first devise an energy optimization algorithm to reduce the motor losses by calculation of the stator flux reference according to the electromagnetic torque and the rotation speed. The second is concerned with controller parameters adjustment using the Particle Swarm Optimization (PSO) technique to improve the efficacy and robustness of the drive. The performance of this strategy is evaluated in terms of torque, flux ripples, and transient response to step variations of the torque control. A comparative study of the designed PI controllers based on PSO with four other control algorithms and tuning methods is established in order to prove the efficiency of PI_PSO. The analysis, modeling, and simulation results are presented to verify the validity of the proposed overall optimization study.

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Analysis of influencing factors affecting the operational reliability of low-voltage asynchronous electric motors

Romanova

Khromov

Suslov

2021

«Izvestiya vysshikh uchebnykh zavedenii. PROBLEMY ENERGETIKI»

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THE PURPOSE. The main purpose of the work is a comprehensive study of external influences that affect the operational reliability of low-voltage asynchronous motors. Attention is focused on the evaluation of the operational reliability of electric motors, the systematization of their operating conditions, with the simultaneous impact of a group of operational factors. Among these factors that are subject to detailed analysis, we will highlight the following: the asymmetry of the stress and its duration, loading of the motor, the temperature of the environment. In this regard, it becomes obvious that the task of improving the operational reliability of low-voltage asynchronous electric motors depends on a qualitative study of the quantitative values of external influencing factors in various operating modes of electric motors. METHODS. The tool for implementing this task is a visual and effective simulation tool Simulink interactive programming environment Matlab. RESULTS. The research was performed on an asynchronous electric motor with a short-circuited rotor AIR160S8 with PH = 7,5 kW, rated speed n = 1500 rpm. The physical processes of the electric motor under study were modeled by changing the following parameters: the coefficient of stress asymmetry in the reverse sequence (K2U), the load on the motor shaft (Kz), the ambient temperature (tocr), and the duration of stress asymmetry in the reverse sequence (T). Based on the obtained simulation results, groups of planes of the studied quantities are constructed. CONCLUSION. A set of studies performed using the Matlab software package allowed us to estimate the limits of acceptable values of external factors and identify the area of acceptable operation of asynchronous motors. The analysis and discussion of the research results were carried out, and measures were proposed to improve the operational reliability of asynchronous electric motors.

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Modeling and Control of AC Machine using MATLAB®/SIMULINK

Cited by 4 publications

References 0 publications

Induction motor performance improvement using a five-level inverter topology and sliding mode controllers

Induction motor performance improvement using a five-level inverter topology and sliding mode controllers

Energy optimization of an electric car using losses minimization and intelligent predictive torque control

Analysis of influencing factors affecting the operational reliability of low-voltage asynchronous electric motors

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