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OPTIMIZING CYCLE TIME OF ELECTRIC AUTONOMOUS HAULERS:A CASE STUDY IN MINING APPLICATIONS
Mälardalen University, School of Innovation, Design and Engineering.
Mälardalen University, School of Business, Society and Engineering.
2023 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Traditionally, the fastest method to travel between two points is perceived as driving at maximumspeed. However, when the vehicle in question is an electric vehicle, the additional time requiredfor charging introduces another variable that can be optimized alongside driving time. This studyexplores the optimization of total time - including both driving and charging - for an autonomouselectric hauler, the TA15, developed by Volvo Construction Equipment, operating within a miningsite scenario.The issue is framed as an optimal control problem, building upon various formulations from relatedwork. An objective function is created, with a weighting factor applied to balance the prioritizationof driving time minimization and charging time minimization. It is discovered that this weightingfactor can be calculated as the inverse of the charging power.The problem is solved using a method called direct collocation, finding the optimal solutions fordriving time minimization only and total time optimization. The results reveal that the solutionfor total time optimization mirrors that of driving time minimization when less energy is neededand a high charging rate is available. However, when the charging rate is low relative to the energyneeded, the optimal solution is no longer simply driving at maximum speed. Instead, adopting aneco-driving approach yields a more time-efficient solution.The models used in this study are based on related work, and the results demonstrate that optimalsolutions exist beyond simply driving at full speed. As the comparison is made using the samemodel, any errors exist in both cases. Consequently, the existence of alternative optimal solutionswithin these models indicates the potential for similar solutions in more accurate models. However,this hypothesis still requires further validation.

Place, publisher, year, edition, pages
2023. , p. 39
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-63775OAI: oai:DiVA.org:mdh-63775DiVA, id: diva2:1779266
External cooperation
Volvo Construction Equipment
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Available from: 2023-07-04 Created: 2023-07-04 Last updated: 2023-07-04Bibliographically approved

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