On the use of stochastic dynamic programming for the evaluation of a power-split CVT in a wheel loader
Complex transmission concepts may enable high fuel
efficiency but require much effort in controller development. This
effort should only be spent if the potential of the concept if high, a
potential which can be determined using optimization techniques.
This paper examine the use of stochastic dynamic programming
for transmission potential evaluation, applied on a wheel loader.
The concepts evaluated is the present automatic gearbox and
a multi-mode CVT (MM-CVT). A probabilistic driving cycle
is created from a measurement including 34 loading cycles.
Trajectory optimization is performed both against probabilistic
and deterministic cycles. The paper shows that the introduction of
a probabilistic load highly affect the application of optimization.
It is also shown that the MM-CVT has approximately 20% lower
minimum fuel requirement than the present transmission, and
that this number is not sensitive to the quality of the prediction.
Tomas Nilsson, Anders Fröberg and Jan Åslund
2012
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