Automotive Fault Prognosis

Information System for Early Fault Warning in Automotive

Principal Investigator:
Muhammad Ali Jinnah University, Islamabad
Project Directors:
Dr. Muhammad Aamer Iqbal Bhatti
Dr. Amir Qayyum
Project Details:
Start Date: June, 2009 Duration: 24 months
Project Cost: PKR 14.34 million Project Funding: PKR 14.34 million
Project Status: In progress.
Technical Progress Reports Submitted:
Project Commencement Report, Q1 report.
Pending Reports:
Deliverables Submitted:
1: Engine and coolant models in MATLAB
Pending Deliverables:
Financial Audit Reports Submitted: None.
Project URL: NA
Detailed proposal is available here.

Executive Summary

In the last decade the country has seen rapid expansion of IT infrastructure. In Automotive Industry computers are being used in manufacturing, maintenance, troubleshooting and tracking of vehicle location. After the induction of Electronic Fuel Injection EFI) System, spark ignition is controlled electronically using computers. For control of spark, sensors are installed in the vehicle and Electronic Control Unit (ECU) of the vehicle reads all the data from these sensors.

The basic objective of this project is to develop a hi-fi device for the condition monitoring, early warning and fault diagnostics of automotive engines. Fault Diagnosis is a well established area of research in its own right. The most common applications include the use of parity and Cyclic Redundancy Check (CRC) for detection of error in a stream of data bits. The literature survey reveals that fault diagnostics techniques developed to date may be classified into three groups:

•  Model Based Techniques
•  Knowledge Based Techniques
•  Signal Based Techniques

The project at hand will devise strategies to establish early warning systems for spark ignition automotive engine faults, looking mainly at coolant sub-system and engine system as fault in these systems result in vehicle failure or affect the fuel economy. The proposed techniques will not only use the aforementioned existing techniques but major emphasis would be given to the novel Sliding Mode Observers based strategies.

The project will develop algorithms for the Early Detection of following faults in 1300 cc Spark Ignition Honda City EFI Engine (Gasoline/Petrol):

–  Misfire Detection
–  Manifold Pressure leakage detection
–  Coolant System fault detection
–  Radiator fault
–  Coolant Pump fault
–  Thermostat valve fault
–  Sensor Faults

The choice of Honda City is because of its most EFI enabled status (having more sensors than its competitive makes).

It will also develop a simple and easy to handle hardware where fault detection algorithms execute and inform the user (driver or mechanic) about the possible fault present in the vehicle or the fault (as mentioned in the first objective) likely to occur in the vehicle in the near future and develop user friendly graphical interface for the system.

The key benefits of the project are:

  • The project will develop a novel algorithm and device able to communicate with the Electronic Control Unit of a vehicle.
  • A software would be developed that would acquire the real time data from the vehicle and process the data to diagnose faults in the system which will be able to raise an early warning for the faults initiating in the system.
  • “Down the Street Workshops” and general car drivers would benefit as the hand-held embedded system would have a display and a microcontroller board along with connection cables.