liu.seSearch for publications in DiVA
Change search
ReferencesLink to record
Permanent link

Direct link
Predictive control of a diesel electric wheel loader powertrain
Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
Volvo Construction Equipment, Sweden.
Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
2015 (English)In: Control Engineering Practice, ISSN 0967-0661, Vol. 41, 47-56 p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Elsevier, 2015. Vol. 41, 47-56 p.
Keyword [en]
Diesel engine; Continuously variable transmission; Predictive control; Stochastic dynamic programming
National Category
Mechanical Engineering
URN: urn:nbn:se:liu:diva-112891DOI: 10.1016/j.conengprac.2015.04.008ISI: 000357546200005OAI: diva2:773483
Available from: 2014-12-19 Created: 2014-12-19 Last updated: 2015-07-31Bibliographically approved
In thesis
1. Optimal Predictive Control of Wheel Loader Transmissions
Open this publication in new window or tab >>Optimal Predictive Control of Wheel Loader Transmissions
2015 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The transmissions of present heavy wheel loaders are in general based on torque converters. The characteristics of this component suits these machines, especially in that it enables thrust from zero vehicle speed without risk of stalling the engine, without active control. Unfortunately, the component also causes losses which might become large compared to the transmitted power. One approach for mitigating these losses is to switch to a continuously variable transmission. Changing to such a system greatly increases the possibility, and the need, for actively selecting the engine speed, and here a conflict emerges. A low engine speed is desired for high efficiency but a high speed is required for high power.

Heavy wheel loaders often operate according to a common repeating pattern known as the short loading cycle. This cycle is extremely transient, which makes the choice of engine operating point both important and difficult. At the same time, the repeating pattern in the operation enables a rough prediction of the future operation. One way to use the uncertain prediction is to use optimization techniques for selecting the best control actions. This requires a method for detecting the operational pattern and producing a prediction from this, to formulate a manageable optimization problem, and for solving this, and finally to actually control the machine according to the optimization results. This problem is treated in the four papers that are included in this dissertation.

The first paper describes a method for automatically detecting when the machine is operating according to any of several predefined patterns. The detector uses events and automata descriptions of the cycles, which makes the method simple yet powerful. In the evaluations over 90% of the actual cycles are detected and correctly identified. The detector also enables a quick analysis of large datasets. In several of the following papers this is used to condense measured data sequences into statistical cycles for the control optimization.

In the second paper dynamic programming and Pontryagin’s maximum principle is applied to a simplified system consisting of a diesel engine and a generator. Methods are developed based on the maximum principle analysis, for finding the fuel optimal trajectories at output power steps, and the simplicity of the system enables a deeper analysis of these solutions. The methods are used to examine and visualize the mechanisms behind the solutions at power transients, and the models form the basis for the models in the following papers.

The third paper describes two different concepts for implementing dynamic programming based optimal control of a hydrostatic transmission. In this system one load component forms a stochastic state constraint, and the concepts present two different strategies for handling this constraint. The controller concepts are evaluated through simulations, in terms of implementability, robustness against uncertainties in the prediction and fuel savings.

The fourth paper describes the implementation and testing of a predictive controller, based on stochastic dynamic programming, for the engine and generator in a diesel electric powertrain. The controller is evaluated through both simulations and field tests, with several drivers, at a realistic work site, thus including all relevant disturbances and uncertainties. The evaluations indicate a ∼ 5% fuel benefit of utilizing a cycle prediction in the controller.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2015. 27 p.
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1636
National Category
Mechanical Engineering
urn:nbn:se:liu:diva-112722 (URN)10.3384/diss.diva-112722 (DOI)978-91-7519-171-3 (print) (ISBN)
Public defence
2015-03-20, Visionen, Hus B, Campus Valla, Linköpings universitet, Linköpiong, 14:24 (English)
Available from: 2015-01-12 Created: 2015-01-12 Last updated: 2015-01-12Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Nilsson, TomasFröberg, AndersÅslund, Jan
By organisation
Vehicular SystemsThe Institute of Technology
In the same journal
Control Engineering Practice
Mechanical Engineering

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 117 hits
ReferencesLink to record
Permanent link

Direct link