Model predictive control of HEVs with exhaust aftertreatment system at low ambient temperatures
CCTA, 2021
Author(s): | Meier F., Del Re L. |
Year: | 2021 |
Abstract: | Abstract?Online control of hybrid electric vehicles (HEV) is
mostly centered on fuel consumption and battery management
while emissions are seldom considered. This is frequently
correct, as warmed up exhaust aftertreatment systems show an
extremely high conversion efficiency. However, HEVs typically
shut off the engine during low load phases, which extends
coldstart periods and prevents the aftertreatment to work at
the correct temperature. Latest regulations put additional focus
on real driving coldstart performance though. Against this
background, this paper analyzes the potential relevance and
presents a possible solution by considering it explicitly in the
control approach.
It is shown that an implementable model predictive control
(MPC) strategy can recover a large part of the theoretical
performance as computed by dynamic programming (DP). Optimal
MPC parameter tuning is efficiently performed utilizing
available DP solutions from comparable scenarios. A potential
saving of up to 40% NOx with equal consumption is shown in
this example. |