The effective management of forces within heavy vehicles is essential for achieving desired performance outcomes. In this study, an auto-generated Model Predictive Control Allocation (MPCA) algorithm is presented. The controller is designed to distribute forces among individual actuators in a vehicle, focusing primarily on longitudinal forces while exploring lateral force dynamics. The approach integrates models of the actuators with vehicle dynamics, encompassing both point mass and dynamic vehicle models, within the controller framework. Through simulation, proof of the MPC's superior performance in reference tracking could be demonstrated, especially in comparison with baseline simulations employing force ratio split (FRS) and equal split (ES) distribution methods. Furthermore, findings show that it was possible to achieve a more energy efficient force distribution using the MPCs.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-204466 |
| Date | January 2024 |
| Creators | Jämte, Jonna, Hellberg, Rebecka |
| Publisher | Linköpings universitet, Reglerteknik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
Page generated in 0.0752 seconds