Robust Driving Pattern Detection and Identification with a Wheel Loader Application
2014 (English)In: International journal of vehicle systems modelling and testing, ISSN 1745-6436 (print) 1745-6444 (online), Vol. 9, no 1, 56-76 p.Article in journal (Refereed) Published
Information about wheel loader usage can be used in several ways to optimize customer adaption. First, optimizing the configuration and component sizing of a wheel loader to customer needs can lead to a significant improvement in e.g. fuel efficiency and cost. Second, relevant driving cycles to be used in the development of wheel loaders can be extracted from usage data. Third, on-line usage identification opens up for the possibility of implementing advanced look-ahead control strategies for wheel loader operation. The main objective here is to develop an on-line algorithm that automatically, using production sensors only, can extract information about the usage of a machine. Two main challenges are that sensors are not located with respect to this task and that significant usage disturbances typically occur during operation. The proposed method is based on a combination of several individually simple techniques using signal processing, state automaton techniques, and parameter estimation algorithms. The approach is found to berobust when evaluated on measured data of wheel loaders loading gravel and shot rock.
Place, publisher, year, edition, pages
InderScience Publishers, 2014. Vol. 9, no 1, 56-76 p.
Driving cycle; Driving cycle identification; Driving pattern; Pattern identification; Robust detection; State automaton; Usage classification; Usage detection; Wheel loader
Engineering and Technology
IdentifiersURN: urn:nbn:se:liu:diva-92222DOI: 10.1504/IJVSMT.2014.059156ScopusID: 2-s2.0-84893958574OAI: oai:DiVA.org:liu-92222DiVA: diva2:620352