May 15–17, 2017 in Prague, Czech Republic
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[Further material]
Title: Nonlinear Model Predictive Control of a Thermal Management System for Electrified Vehicles using FMI
Authors: Torben Fischer, Tom Kraus, Christian Kirches and Frank Gauterin
Abstract:Energy-efficient thermal management systems for Emobility
help to decrease energy consumption and increase
range. Due to transient external conditions and the
increasing system complexity, optimization-based control
approaches are required in order to harness the full potential
of such systems. In (Fischer et al., 11th Int. Modelica
Conf, 2015), we have presented a model-based development
cycle for a thermal management system in Emobility
to this end. In this article, we build upon this
work to describe the use of this model within a nonlinear
model predictive control (NMPC) approach. The main
benefits of using an advanced optimization-based control
system in this application are a) the ability to control
the battery temperature and the cabin temperature simultaneously,
b) the increased energy efficiency achieved
by exploiting the predictive character of the optimizationbased
control approach, c) the possibility to include operational
limits as constraints in the optimization problems
and d) the fast reaction to disturbances or model parameter
changes. We evaluate the merit of the proposed advanced
control system by way of a comparison to conventional
PID controller.
Links: Full paper