Abstract:
The use of microprocessor-based control systems on agricultural tractors has eased
operator burden by allowing changes to tractor and implement settings to be made
with little physical effort. However, maintaining the optimum tractor-implement
settings whilst encountering the variable nature of agricultural conditions still requires
a high level of operator skill, partly due to the need to adjust individual sub-system
controllers. CAN-bus communication between electronically controlled vehicle sub.
systems provided a new opportunity to enhance vehicle powertrain operation, by
intelligently integrating control of the sub-systems. The aim of the project was to
develop ways to improve the operational characteristics of a tractor powertrain, by
investigating system behaviour, and identifying opportunities for intelligent control.
Market research was undertaken which highlighted power-split continuously variable
transmissions as a credible alternative to powershift-type transmissions in specific
specialist applications where the additional purchase price could be justified.
However, there is little scientific evidence to suggest that there are significant
improvements in overall vehicle performance to be gained through the use of a CVT
tractor compared to a well operated powershift-type transmission. Improvements to
gearshift quality and more intelligent use of the powertrain control features could
ensure powershift-type transmissions remain competitive for the foreseeable future.
A dynamic mathematical powertrain model was developed for a lOOkW, 16 speed
semi-powershift transmission, four wheel drive tractor based on fundamental
Newtonian principles. With the addition of implement models, this allowed accurate
representation of the tractor-implement system and provided a platform to develop
improved vehicle control strategies. Validation of the model with experimental data
showed it was an accurate representation of the real system.
The steady state and transient field performance of the tractor operating with a
mouldboard plough, a power harrow and a laden trailer was determined for a number
of tractor-implement configurations across a range of conditions. This provided a
David Sayer, 2005 Cranfield University, Silsoe
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large dataset for this vehicle for use in this, and other investigations. The level of
powertrain loading for field experiments was found to be influenced by soil type,
implement working width and depth as well as forward speed and engine speed. For
the road investigation, the surface quality and terrain were major influencing factors
on performance. It was found there was considerable variation in tractor response to
the different gearshift types experienced in the semi-powershift transmission: the
non-powershift changes being severe, particularly during downshifts; double-swap
powershifts were markedly more severe than single-swap shifts.
A unique investigation of the tractor driveline torque loss characteristics across the
full operating spectrum using the axle dynamometer identified that the torque losses
for this transmission are predominantly speed, rather than torque related. A
mathematical model was developed to predict driveline torque losses from
transmission output speed, flywheel torque and the number of power-transmitting
gears in mesh. The axle dynamometer was also used to successfully replicate field
loading patterns in real time.
Throughout this investigation a number of undesirable powertrain characteristics were
identified. Potential improvements to vehicle performance through the development
of solutions to these characteristics have been made either through analysis of field
data, experiments with the axle dynamometer, or using the developed mathematical
model.