Abstract:
Statistically, 8.29% of total number of vehicles seen on the Sri Lankan road network is
heavy vehicles [5]. India dominates the Sri Lankan heavy vehicle market with a share of
50% followed by other vehicle manufacturing countries [11]. When compared with its
European, Japanese or German counterpart these Indian vehicles are specially designed
for developing countries such as Sri Lanka.
Most heavy vehicle manufactures do not give adequate consideration to provide an early
warning system to help maintain heavy vehicle engines in good condition. Thus this
research proposes such an early warning system which include fan belt condition
indicator, alarm controlled engine cooling temperature indicator, vehicle loading weight
indicator and automated method in keeping records of the engine oil changing period.
The study has been carried out over one year period with selected vehicles from the Sri
Lanka Navy, which possesses a massive heavy vehicle fleet and operates them
frequently all over the Island. The proposals have been made by gathering information
and analyzing data obtained from this fleet during its operation.
The fan belt condition indicator provides an early warning by measuring the level of
wear and tear of the fan belt. The conventional engine temperature indicator has been
replaced with an electronic temperature sensor to provide real time engine temperature
indicator. It also incorporates an alarm to warn of dangerously high temperatures to the
vehicle operator. The weight of cargo loaded to the vehicle is measured through shockabsorber
mounted displacement sensors, providing the operator with an accurate
indication of the load on the vehicle prior to starting the journey. Further, an engine
running hours counter provides an indication of actual engine running period, making it
easy to identify proper time for oil changing.
All the above features are consolidated in to a single display unit on the dashboard using
electronic communication system. This unit called “Engine Quality Monitoring Unit”
will greatly help the maintenance crew to prepare a proper maintenance schedule, fine
tuned for each vehicle in the fleet.
