Online velocity trajectory planning for manual energy efficient driving of heavy duty vehicles using model predictive control

This paper presents a novel approach to online velocity trajectory planning for manual energy efficient driving which involves Model Predictive Control (MPC) for map-based anticipatory driving of heavy duty vehicles. The proposed model leads to a Quadratic Programming (QP) optimization problem with...

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Bibliographic Details
Main Authors: Henzler, Michael, Buchholz, Michael, Dietmayer, Klaus
Format: Conference Proceeding
Language:English
Subjects:
Engines
Fuels
Linear programming
Optimization
Torque
Trajectory
Vehicles
Online Access:Request full text
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Summary:This paper presents a novel approach to online velocity trajectory planning for manual energy efficient driving which involves Model Predictive Control (MPC) for map-based anticipatory driving of heavy duty vehicles. The proposed model leads to a Quadratic Programming (QP) optimization problem with sparse matrix structure, allowing to be solved robustly and efficiently. By reducing the optimization problem to a QP standard form, existing and well-proven QP solvers can be used to calculate a reliable solution for a real-time vehicle control application. Evaluations show that the calculation time of the MPC optimization process with a two kilometer long preview horizon is, compared to other literature, significantly reduced to 1.8 milliseconds, while in real-world driving experiments an average fuel consumption reduction of 11.4% compared to normal driving is measured.
ISSN:2153-0009
2153-0017
DOI:10.1109/ITSC.2014.6957956