Modelling of Cranking Behaviour in Heavy Duty Truck Engines
In modern heavy duty trucks the battery is a central component. Its
traditional role as an energy source for engine cranking has been
extended to include powering a number of electrical components on
the truck, both during driving and during standstill. As a consequence
of this it is important to know how much a battery in use has aged and
lost in terms of ca- pacity and power output. The difficulty in
measuring these factors on a battery in use causes problem, since
heavy duty truck batteries are often replaced too early or too late,
leading to unnecessary high replacement costs or truck standstill
respectively.
The overall goal of the effort, of which this thesis is a part, is to
use a model of the cranking behaviour of a heavy duty truck engine,
which depends on the battery condition, to estimate the ageing and
wear of a heavy duty truck battery. This thesis proposes a modelling
approach to model the components involved in engine cranking.
In the thesis work, system identification is made of the systems
forming part of the cranking of a heavy duty truck engine. These
components are the starter battery, the starter motor and its
electrical circuit and the internal combustion engine. Measurement
data has been provided by Scania AB for the evaluation of the
models. The data has been collected from crankings of a heavy duty
diesel engine at different temperatures and battery charge levels. For
every cranking lapse the battery voltage and current have been
measured as well as the engine rotational speed.
A starter battery model is developed and evaluated. The resulting
battery model is then incorporated into two different engine cranking
models, Model 1 and Model 2, including a starter motor model and an
internal combustion engine model apart form the battery model. The two
cranking models differ in several aspects and their differences and
resulting evaluations are discussed.
The battery model is concluded to be sufficiently accurate during
model verification, however the two cranking models are not. Model 2
is verified as more correct in in its output than Model 1, but neither
is sufficiently accurate for their purpose. The conclusion is drawn
that the modelling approach is sound but development of Model 2 is
needed before the model can be used in model-based condition
estimation.
Erik Andersson
2015
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Senast uppdaterad: 2021-11-10
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