Skip to Main Content
 

Global Search Box

 
 
 
 

Files

File List


Eeshan_Deosthale_OSU_Thesis.pdf (4.4 MB)

ETD Abstract Container

Abstract Header

Model-Based Fault Diagnosis of Automatic Transmissions

Deosthale, Eeshan Vijay
http://rave.ohiolink.edu/etdc/view?acc_num=osu1542631227815892

Abstract Details

2018, Master of Science, Ohio State University, Mechanical Engineering.
New automatic transmission designs with 6+ speeds provide a significant leap forward in providing greater fuel economy and customer satisfaction compared to earlier transmissions with 5 or lower speeds. The current trend in automatic transmissions is to have an increased number of speed ratios. This, at the same time, puts an additional emphasis on ensuring that the electronic monitoring and controls system has a high level of integrity in terms of fault diagnosis and can detect and isolate all possible critical faults in the system. With increasing number of speed ratios, the number of clutches and thereby clutch faults in these transmissions also increases. Detection and isolation of the clutch faults in all gears is critical, as besides the obvious safety factor, even minor undetected clutch failure or improper fault response may adversely affect the drivability of the vehicle resulting in customer dissatisfaction. This thesis provides a framework for clutch fault diagnosis in automatic transmissions using structural analysis-based diagnosis methods. A generalized way of modeling automatic transmissions for fault diagnosis has been introduced in this thesis. The first step in diagnosis process is to identify the required measurements for diagnosis referred to as sensor placement. This thesis develops a systematic way to perform sensor placement for clutch fault isolation. This thesis makes an effort to identify the minimum number of sensors required for fault diagnosis without compromising performance/safety. In this regard, a way to classify faults according to the risk potential is discussed which would help in reducing the number of sensors required for fault diagnosis. As a preceding step of this, a way to determine fault tolerant action for clutch fault events is discussed. Reducing the number of required sensors can help in significant cost reduction for mass produced systems like automatic transmissions. This thesis also provides a way to design diagnostic tests to detect and isolate faults. A validation of these tests is done through computer simulations as well as using experimental data. Finally, this thesis gives an insight into the ongoing and future work of fault diagnosis in structurally reconfigurable systems which is an extension of the work on automatic transmissions.
Giorgio Rizzoni, Professor (Advisor)
Krishnaswamy Srinivasan, Professor (Committee Member)
Qadeer Ahmed, Dr. (Committee Member)
Majed Mohammed, Dr. (Committee Member)
162 p.
Automotive Engineering; Mechanical Engineering
Automatic Transmission; Fault Diagnosis; Clutch Fault; Structural Analysis; Sensor Placement

Recommended Citations

Citations

  • Deosthale, E. V. (2018). Model-Based Fault Diagnosis of Automatic Transmissions [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1542631227815892

    APA Style (7th edition)

  • Deosthale, Eeshan. Model-Based Fault Diagnosis of Automatic Transmissions. 2018. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1542631227815892.

    MLA Style (8th edition)

  • Deosthale, Eeshan. "Model-Based Fault Diagnosis of Automatic Transmissions." Master's thesis, Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1542631227815892

    Chicago Manual of Style (17th edition)

osu1542631227815892
622
© 2018, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.