Vehicle Level Diagnosis for Hybrid Powertrains
There are possibilities to reduce the fuel consumption in trucks using
hybrid technology. New components are added when hybridizing a
vehicle, and these need to be monitored due to safety and legislative
demands. Diagnosis aspects due to hybridization of the powertrain are
investigated using a model of a long haulage truck. Such aspects are
for example that there are more mode switches in the hybrid powertrain
compared to a conventional vehicle, and there is a freedom in choosing
operating points of the components in the powertrain via the energy
management and still fulfill the torque request of the driver.
To investigate the influence of energy management and sensor
configuration on the performance of the diagnosis system, three
diagnosis systems on vehicle level are designed and implemented. The
systems are based on different sensor configurations; one with a
fairly typical sensor configuration, one with the same number of
sensors but in model sense placed more closely to the components to be
monitored, and one with the minimal number of sensors to ideally
achieve full fault isolability. It is found that there is a connection
between the design of the energy management and the diagnosis systems,
and that this connection is of special relevance when the model used
in the diagnosis is valid only for some operating modes of the
powertrain.
In consistency based diagnosis it is investigated if there exists a
solution to a set of equations with analytical redundancy, where the
redundancy is obtained using measurements. The selection of sets of
equations to be included in the diagnosis and how and in what order
the unknown variables are to be computed affect the diagnosis
performance. A simplified vehicle model is used to exemplify how an
algebraic loop can be avoided for one computational sequence of the
unknowns, but can not be avoided for a different computational
sequence given the same overdetermined set of model equations. A
vehicle level diagnosis system is designed using a systematic method
to obtain unique residuals and that no signal is differentiated. The
performance of the designed system is evaluated in a simulation study,
and compared to a diagnosis system based on the same sets of
equations, but where the residual generators are selected ad hoc. The
results of the comparison are positive, which reinforces the idea of
considering the properties of the residual generators in a systematic
way.
A diagnosis system using a map based model of the electric machine is
designed. The benefits of using map based models are that it is easy
to construct the models if measurements are available, and that such
models in general are accurate. As a consequence of the structure of
the model, full fault isolability is not possible to achieve using
only the model for fault free behavior of the machine. To achieve full
fault isolability, fault models are added to the diagnosis system
using a model with a different model structure. The system isolates
the faults, even though the induced faults are small in the simulation
study, and the size of the faults are accurately estimated using
observers.
Christofer Sundström
2011
Informationsansvarig: webmaster
Senast uppdaterad: 2021-11-10
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