Predictive control of a diesel electric wheel loader powertrain
Wheel loaders often have a highly repetitive pattern of operation, which can be used for creating a rough prediction of future operation. As the present torque converter based transmission is replaced with an infinitely variable device, such as an electric or hydraulic transmission, a freedom in the...
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Published in: | Control engineering practice Vol. 41; pp. 47 - 56 |
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Main Authors: | , , |
Format: | Journal Article |
Language: | English |
Published: |
Elsevier Ltd
01-08-2015
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Subjects: | |
Online Access: | Get full text |
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Summary: | Wheel loaders often have a highly repetitive pattern of operation, which can be used for creating a rough prediction of future operation. As the present torque converter based transmission is replaced with an infinitely variable device, such as an electric or hydraulic transmission, a freedom in the choice of engine speed is introduced. This choice is far from trivial in the extremely transient operation of these machines, but the availability of a load prediction should be utilized.
In this paper, a predictive engine and generator controller, based on stochastic dynamic programming, is described, implemented and evaluated. The evaluation is performed against non-predictive controllers in the same system, to lift out any possible benefits of utilizing the repetition based prediction. Simulations and field tests show that the controllers are able to handle disturbances introduced from model errors, the machine environment and the human operator, and that the predictive controller gives around 5% lower fuel consumption than the non-predictive reference controllers.
•Predictive control of a diesel electric wheel loader powertrain.•Examination of cycle based prediction in wheel loader powertrain control.•Using stochastic dynamic programming under severe disturbances and uncertainties.•Powertrain controller evaluation through simulations and realistic field tests.•Fuel benefit shown from using a predictive controller compared to non-predictive. |
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ISSN: | 0967-0661 1873-6939 1873-6939 |
DOI: | 10.1016/j.conengprac.2015.04.008 |