Modeling and Simulation of a BLDC Motor Speed Control in Electric Vehicles

Baba, Mariem Ahmed; Mohamed, Naoui; Cherkaoui, Mohamed

doi:10.1007/978-3-031-29857-8_88

Cited by 2 publications

(2 citation statements)

References 16 publications

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“…The stator current error e and its derivative e' are normalized before being fed into the FL estimation. The EKF uses the estimated stator resistance along with the rest of the parameters to estimate stator currents, rotor position and speed states [31]. Comparing these estimated values to a threshold where an overtaking confirms the existence of the inter-turn short circuit fault.…”

Section: Proposed Methodsmentioning

confidence: 99%

PMSM Inter-Turn Short Circuit Fault Detection Using the Fuzzy-Extended Kalman Filter in Electric Vehicles

Romdhane,

Naoui,

Mansouri

2023

Electronics

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To avoid damaging the motor and its surrounding equipment, detecting Inter-Turn Short Circuit (ITSC) faults in Permanent Magnet Synchronous Motors (PMSMs) applied in electric vehicles is a crucial task. In this paper, the detection of ITSC faults in stator winding for PMSMs is carried out by means of the Extended KALMAN Filter (EKF) algorithm combined with the Fuzzy Logic Estimator (FLE). To estimate the motor parameters, including the rotor position and speed, the EKF algorithm uses the measured stator currents and voltages beside the stator resistance, which is calculated in advance using fuzzy logic and fed to the EKF. The change behaviors of the estimated parameters were then used to detect short circuit faults in the PMSM. Using Matlab/Simulink, the proposed FL-EKF algorithm was implemented and tested on a faulty PMSM controlled by Field Oriented Control (FOC). The observation of a perfect estimation of the stator resistance through the simulation helps to precisely detect the failure, and that demonstrates the sensitivity and robustness of the proposed approach.

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Section: Proposed Methodsmentioning

confidence: 99%

PMSM Inter-Turn Short Circuit Fault Detection Using the Fuzzy-Extended Kalman Filter in Electric Vehicles

Romdhane,

Naoui,

Mansouri

2023

Electronics

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“…According to a comparative study between electric motors used in EVs carried out by M. Yildirim, M. Polat, and H. Kürüm [4], brushless and induction motors are the most commonly adopted motors in EVs due to their satisfactory characteristics, including their high levels of efficiency and high power densities. BLDC engines have ensured innovative EV models that combine exemplary performance and environmental friendliness [5]. Several types of robust control have been proposed in the literature to control the speed of a BLDC motor, such as fuzzy logic, adaptive control, and neural network control.…”

Section: Introductionmentioning

confidence: 99%

Fault-Tolerant Control Strategy for Hall Sensors in BLDC Motor Drive for Electric Vehicle Applications

2023

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The adoption of the brushless DC motor in the electric drive vehicle industry continues to grow due to its robustness and ability to meet torque–speed requirements. This work presents the implementation of a fault-tolerant control (FTC) for a BLDC motor designed for electric vehicles. This paper focuses on studying the defect in the Ha sensor and its signal reconstruction, assuming possible cases, but the same principle is applied to the other two sensors (Hb and Hc ). In this case, the fault diagnosis allows for the correction and reconstruction of the signal in order to compel the system to work despite the presence of a fault. Indeed, several robust control systems are used within the work to regulate the speed of the motor properly, such as control via fuzzy logic and control via a neural network. This paper presents three BLDC control configurations for EVs, PID, fuzzy logic (FL), and an artificial neural network (ANN), discusses the pros and cons, and develops corresponding mathematical models to enhance a fault-tolerant control strategy which is analyzed and studied using MATLAB-based simulations (by discussing the two cases, the steady state and the transient state), allowing for a novel design based on the analytical models developed. The results obtained from the simulation of this system improved the speed controlled by the neural network compared to the fuzzy logic controller. At the same time, the sensor failure had no effect on the system’s operation due to the efficiency of the FTC control.

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Modeling and Simulation of a BLDC Motor Speed Control in Electric Vehicles

Cited by 2 publications

References 16 publications

PMSM Inter-Turn Short Circuit Fault Detection Using the Fuzzy-Extended Kalman Filter in Electric Vehicles

PMSM Inter-Turn Short Circuit Fault Detection Using the Fuzzy-Extended Kalman Filter in Electric Vehicles

Fault-Tolerant Control Strategy for Hall Sensors in BLDC Motor Drive for Electric Vehicle Applications

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