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Abstract



Optimal Engine Operation in a Multi-Mode CVT Wheel Loader


Throughout the vehicular industry there is a drive for increased fuel efficiency. This is the case also for heavy equipment like wheel loaders. The operation of such machines is characterized by its highly transient nature, the episodes of high tractive effort at low speed and that power is used by both the transmission and the working hydraulics. The present transmission is well suited for this operation, though the efficiency is low in some modes of operation. Both operational advantages and efficiency drawbacks are highly related to the use of a torque converter. Continuously variable transmissions (CVTs) may hold a potential for achieving similar operability with reduced fuel consumption, though such devices increase the demand for, and importance of, active control. Common wheel loader operation is readily described in a framework of loading cycles. The general loading cycle is described, and a transmission oriented cycle description is introduced, in deterministic and stochastic forms, and a description is made on how such cycles are created from measurements. A loading cycle identifier is used for detecting cycles in a set of measured data, and a stochastic cycle is formed from statistics on the detected cycles. CVTs increase the possibility for active control, since a degree of freedom is introduced in the engine operating point. Optimal operating point trajectories are derived, using dynamic programming (DP), for naturally aspirated (NA) and turbocharged (TC) engines. The NA-engine solution is analyzed with Pontryagin's maximum principle (PMP). This analysis is used for deriving PMP based methods for finding the optimal solutions for both engines. Experience show that these methods are ~100 times faster than DP, but since the restrictions on the applicable load cases are severe, the main contribution from these is in the pedagogic visualization of optimization. Methods for deriving suboptimal operating point trajectories for both the NA and the TC engines are also developed, based on the optimization results. The methods are a factor >1000 faster than DP while producing feasible trajectories with less than 5% increase in fuel consumption compared to the optimal. Multi-mode CVTs provide the possibility of even higher efficiency than single mode devices. At the same time, the added complexity makes control development increasingly time consuming and costly, while the quality of the control is decisive for the success of the system. It is therefore important to be able to evaluate the potential of transmission concepts before control development commence. Stochastic dynamic programming is used and evaluated as a tool for control independent comparing of the present transmission and a hydrostatic multi-mode CVT concept. The introduction of a stochastic load complicates the optimization, especially in the feasible choice of states for the optimization. The results show that the multi-mode CVT has at least 15% lower minimum fuel consumption than the present transmission, and that this difference is not sensitive to prediction uncertainties.

Tomas Nilsson

2012

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