Models and Critical Maneuvers for Road Vehicles
As manufacturers are pushing their research and development toward
more simulation based and computer aided methods, vehicle dynamics
modeling and simulation become more important than ever. The challenge
lies in how to utilize the new technology to its fullest, delivering
the best possible performance given certain objectives and current
restrictions. Here, optimization methods in different forms can be a
tremendous asset. However, the solution to an optimization problem
will always rely on the problem formulation, where model validity
plays a crucial role. The main emphasis in this thesis lies within
methodology and analysis of optimal control oriented topics for
safety-critical road-vehicle maneuvers. A crucial element here is the
vehicle models. This is investigated as a first study, evaluating the
degree to which different model configurations can represent the
lateral vehicle dynamics in critical maneuvers, where it is shown that
even the low-complexity models describe the most essential vehicle
characteristics surprisingly well.
How to formulate the optimization problems and utilize optimal control
tools is not obvious. Therefore, a methodology for road-vehicle
maneuvering in safety-critical driving scenarios is presented, and
used in evaluation studies of various vehicle model configurations and
different road-surface conditions. It was found that the overall
dynamics is described similarly for both the high- and low-complexity
models, as well as for various road-surface conditions.
If more information about the surroundings is available, the best
control actions might differ from the ones in traditional safety
systems. This is also studied, where the fundamental control
strategies of classic electronic stability control is compared to the
optimal strategy in a safety-critical scenario. It is concluded that
the optimal braking strategy not only differs from the traditional
strategies, but actually counteracts the fundamental intentions from
which the traditional systems are based on.
In contrast to passenger cars, heavy trucks experience other
characteristics due to the different geometric proportions. Rollover
is one example, which has to be considered in critical
maneuvering. Model configurations predicting this phenomenon are
investigated using optimal control methods. The results show that the
simple first go-to models have to be constrained very conservatively
to prevent rollover in more rapid maneuvers.
In vehicle systems designed for path following, which has become a
trending topic with the expanding area of automated driving, the
requirements on vehicle modeling can be very high. These requirements
ultimately depend on several various properties, where the path
restrictions and path characteristics are very influential
factors. The interplay between these path properties and the required
model characteristics is here investigated. In situations where a
smooth path is obtained, low-complexity models can suffice if path
deviation tolerances are set accordingly. In more rapid and tricky
maneuvers, however, vehicle properties such as yaw inertia are found
to be important.
Several of the included studies indicate that vehicle models of lower
complexity can describe the overall dynamics sufficiently in critical
driving scenarios, which is a valuable observation for future
development.
Kristoffer Lundahl
2016
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Last updated: 2021-11-10
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