On the use of stochastic dynamic programming for evaluating 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.