The book begins with a discussion of dynamic optimization techniques and
methodologies for automotive applications, and includes a basic introduction into
dynamic and trajectory optimization techniques (Chap. 1), and three more specific
methods which are extremum seeking (Chap. 2), Model Predictive Control (Chap. 3)
and an optimal nonlinear feedback regulation technique based on the Hamilton–
Jacobi–Bellman equation (Chap. 4). The latter approach is an example of a theo-
retically advanced methodology that has been shown to be effective for automotive
systems once combined with a suitable system identification method.
The book then proceeds to discuss automotive applications of dynamic
optimization and optimal control at various levels. At a very high level, significant
benefits are expected from its use to control the traffic flows and enforce their
fluidity as discussed in Chap. 5. Much can also be gained at the level of single
vehicle operation and active safety as discussed in Chaps. 6–8. While these three
contributions are mainly centered on handling and safety, two other contributions
(Chaps. 9 and 10) examine applications of dynamic optimization in assistant
systems for vehicle speed control.
Demonstrating optimization potential at powertrain level is pursued next. This
topic addressed especially in the context of hybrid electrical vehicles (HEVs), in
terms of topology optimization in Chap. 11, optimal energy management (Chaps.
12 and 13) where the latter contribution includes battery ageing which is a sig-
nificant consideration in view of battery ageing and cost.
Another application of dynamic optimization, now to coordinated control of
Diesel engine aftertreatment, is the topic of the contribution of Chap. 14. While
the use of dynamic optimization for HEV energy management is relatively well
understood, there is now a growing interest in the use of dynamic optimization to
achieve effective control of aftertreatment systems and emission reductions.
Finally the optimization of engine operation, a topic that has received many
theoretical but also industrial contributions is addressed. Specifically, Chap. 15
addresses the problem of optimal calibration of engine maps by learning methods
from an industrial point of view, and Chap. 16 presents development aspects of a
commercially available optimization tool for a similar task. Chapter 17 tackles the
problem of optimal control of homogeneous charge compression ignited (HCCI)
engines, while Chap. 18 in some sense closes the gap between the vehicle and
engine control addressing the optimal operation at vehicle level while taking into
account the engine operation.
Some general conclusions can be drawn from the discussion. Briefly, there is a
gap between academic and industrial communities. This gap is due to legacy issues
which make it difficult for industrial users to employ or test new optimization and
optimal control methods and the need of the academic community to address more
complex questions that incorporate more realistic models and system engineering
aspects and requirements.
xviii Introduction