Self-Learning Control Strategy for Electrified Off-Highway Machines to Optimize Energy Efficiency

Event
SAE 2015 Commercial Vehicle Engineering Congress
Authors Abstract
Content
The electrification of off-highway machines are increasing significantly. Advanced functionalities, beneficial energy efficiency and effectiveness are only a few advantages of electric propulsion systems. To control these complex systems in varying environments intelligent algorithms at system level are needed. This paper addresses the topic of machine learning algorithms applied to off-highway machines and presents a methodology based on artificial neural networks to identify and recognize recurrent load cycles and work tasks. To gain efficiency and effectiveness benefits the recognized pattern settings are applied to the electric propulsion system to adjust relevant parameters online. A dynamic adaption of the DC-link voltage based on the operating points of the machine processes is identified as such a parameter.
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DOI
https://doi.org/10.4271/2015-01-2831
Pages
6
Citation
Pohlandt, C., and Geimer, M., "Self-Learning Control Strategy for Electrified Off-Highway Machines to Optimize Energy Efficiency," Commercial Vehicles 8(2):513-518, 2015, https://doi.org/10.4271/2015-01-2831.
Additional Details
Publisher
Published
Sep 29, 2015
Product Code
2015-01-2831
Content Type
Journal Article
Language
English