Explicit use of road topography for model predictive cruise control in heavy trucks
New and exciting possibilities in vehicle control are revealed by the consideration
of topography through the combination GPS and three dimensional road
maps. This thesis explores how information about future road slopes can be
utilized in a heavy truck with the aim at reducing the fuel consumption over
a route without increasing the total travel time.
A model predictive control (MPC) scheme is used to control the longitudinal
behavior of the vehicle, which entails determining accelerator and
brake levels and also which gear to engage. The optimization is accomplished
through discrete dynamic programming. A cost function is used to define the
optimization criterion. Through the function parameters the user is enabled to
decide how fuel use, negative deviations from the reference velocity, velocity
changes, gear shifts and brake use are weighed.
Computer simulations with a load of 40 metric tons shows that the fuel
consumption can be reduced with 2.5% with a negligible change in travel
time, going from Link¨oping to J¨onk¨oping and back. The road slopes are
calculated by differentiation of authentic altitude measurements along this
route. The complexity of the algorithm when achieving these results allows
the simulations to run two to four times faster than real time on a standard
PC, depending on the desired update frequency of the control signals.
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Last updated: 2019-08-05