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Your search keyword '"Akin, Bilal"' showing total 4 results
Start Over Author "Akin, Bilal" Journal ieee transactions on vehicular technology
4 results on '"Akin, Bilal"'

2. An On-Line Multiple Open-Circuit Fault Diagnostic Technique for Railway Vehicle Air-Conditioning Inverters

Author

Tianjian Yu, Kaidi Li, Shu Cheng, Chaoqun Xiang, Akin Bilal, and Xun Wu

Subjects
Computer Networks and Communications, Computer science, Open-circuit voltage, Aerospace Engineering, Fault (power engineering), Power (physics), Computer Science::Hardware Architecture, Reliability (semiconductor), Control theory, Distortion, Automotive Engineering, Line (geometry), Inverter, Electrical and Electronic Engineering
Abstract

The safety and reliability of inverters play a significant role in stable power electronic system operations. Considering a railway vehicle air-conditioning inverter as a case study, this paper presents a generic open-circuit fault diagnosis method that can be applied to various inverter and control schemes. First, a detailed model of three-phase output currents under both normal and fault status is derived, and then the concept of space trajectory is introduced based on the three-phase output currents. The open-circuit faults of the inverter lead to output phase current distortion. Therefore, different types of faults have different space trajectories, and the corresponding shape of the space trajectory is considered to be a fault feature. Then, the fault is located by the direction vector and center-of-mass coordinate. The effectiveness and reliability of the diagnosis method are verified and analyzed using a hardware-in-the-loop test platform.

Published
2020

3. DSP-based sensorless electric motor fault-diagnosis tools for electric and hybrid electric vehicle powertrain applications

Author

Akin, Bilal, Ozturk, Salih Baris, Toliyat, Hamid A., and Rayner, Mark

Subjects
Digital signal processors -- Design and construction, Electric fault location -- Methods, Hybrid vehicles -- Maintenance and repair, Induction electric motors -- Design and construction, Digital signal processor, Business, Electronics, Electronics and electrical industries, Transportation industry
Abstract

The integrity of electric motors in work and passenger vehicles can best be maintained by frequently monitoring their condition. In this paper, a signal processing-based motor fault-diagnosis scheme in detail is presented. The practicability and reliability of the proposed algorithm are tested on rotor asymmetry detection at zero speed, i.e., at startup and idle modes in the case of a vehicle. Regular rotor asymmetry tests are done when the motor is running at a certain speed under load with stationary current signal assumption. It is quite challenging to obtain these regular test conditions for long-enough periods of time during daily vehicle operations. In addition, automobile vibrations cause nonuniform air-gap motor operation that directly affects the inductances of electric motors and results in a noisy current spectrum. Therefore, it is challenging to apply conventional rotor fault-detection methods while examining the condition of electric motors as part of the hybrid electric vehicle (HEV) powertrain. The proposed method overcomes the aforementioned problems by simply testing the rotor asymmetry at zero speed. This test can be achieved at startup or repeated during idle modes, where the speed of the vehicle is zero. The proposed method can be implemented at no cost using the readily available electric motor inverter sensor and microprocessing unit. Induction motor fault signatures are experimentally tested online by employing the drive-embedded master processor [TMS320F2812 digital signal processor (DSP)] to prove the effectiveness of the proposed method. Index Terms--Digital signal processor (DSP)-based fault detection, hybrid electric vehicle (HEV), induction motor, motor fault diagnosis.

Published
2009

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