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Model Based Vehicle Level Diagnosis for Hybrid Electric Vehicles
Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

When hybridizing a vehicle, new components are added that need to be monitored due to safety and legislative demands. Diagnostic aspects due to powertrain hybridization are investigated, such as that there are more mode switches in the hybrid powertrain compared to a conventional powertrain, and that there is a freedom in choosing operating points of the components in the powertrain via the overall energy management and still fulfill the driver torque request. A model of a long haulage truck is developed, and a contribution is a new electric machine model. The machine model is of low complexity, and treats the machine constants in a different way compared to a standard model. It is shown that this model describes the power losses significantly better when adopted to real data, and that this modeling improvement leads to better signal separation between the non-faulty and faulty cases compared to the standard model.

To investigate the influence of the energy management design and sensor configuration on the diagnostic performance, two vehicle level diagnosis systems based on different sensor configurations are designed and implemented. It is found that there is a connection between the operating modes of the vehicle and the diagnostic performance, and that this interplay is of special relevance in the system based on few sensors.

In consistency based diagnosis it is investigated if there exists a solution to a set of equations with analytical redundancy, i.e. there are more equations than unknown variables. The selection of sets of equations to be included in the diagnosis system and in what order to compute the unknown variables in the used equations affect the diagnostic performance. A systematic method that finds properties and constructs residual generator candidates based on a model has been developed. Methods are also devised for utilization of the residual generators, such as initialization of dynamic residual generators, and for consideration of the fault excitation in the residuals using the internal form of the residual generators. For demonstration, the model of the hybridized truck is used in a simulation study, and it is shown that the methods significantly increase the diagnostic performance.

The models used in a diagnosis system need to be accurate for fault detection. Map based models describe the fault free behavior accurately, but fault isolability is often difficult to achieve using this kind of model. To achieve also good fault isolability performance without extensive modeling, a new diagnostic approach is presented. A map based model describes the nominal behavior, and another model, that is less accurate but in which the faults are explicitly included, is used to model how the faults affect the output signals. The approach is exemplified by designing a diagnosis system monitoring the power electronics and the electric machine in a hybrid vehicle, and simulations show that the approach works well.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2014. , 10 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1589
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-105487DOI: 10.3384/diss.diva-105487ISBN: 978-91-7519-356-4 (print)OAI: oai:DiVA.org:liu-105487DiVA: diva2:707704
Public defence
2014-04-25, Visionen, Hus B, Campus Valla, Linköpings universitet, Linköping, 10:15 (English)
Supervisors
Available from: 2014-03-25 Created: 2014-03-25 Last updated: 2014-04-08Bibliographically approved
List of papers
1. Overall Monitoring and Diagnosis for Hybrid Vehicle Powertrains
Open this publication in new window or tab >>Overall Monitoring and Diagnosis for Hybrid Vehicle Powertrains
2010 (English)In: Proceedings of the 6th IFAC Symposium on Advances in Automotive Control,  July 12-14, Munich, Germany / [ed] Ansgar Trächtler and Dirk Abel, 2010, 93-98 p.Conference paper, Published paper (Refereed)
Abstract [en]

Designing diagnosis systems for hybrid vehicles include new features compared to conventional vehicles, e.g. mode switches in the system. The influence of this on the performance of the diagnosis system is investigated by design and implementation of diagnosis systems on vehicle level. The diagnosis systems are based on two sensor configurations, one consisting of many sensors and one of few sensors. The diagnosis systems detect specific faults, here specifically faults in the electrical components in a hybrid vehicle driveline, but the methodology is generic. There is a connection between the design of the energy management and the diagnosis system, and this interplay is of special relevance when models of components are valid only in some operating modes. In the systems implemented, the diagnosis system based on few sensors is more complex and includes a larger part of the vehicle model than the system based on more sensors.

Series
Advances in Automotive Control, ISSN 1474-6670
Keyword
sensor placement; sensor configuration; dynamic residual generator; parallel hybrid
National Category
Vehicle Engineering
Identifiers
urn:nbn:se:liu:diva-73890 (URN)10.3182/20100712-3-DE-2013.00128 (DOI)978-3-902661-72-2 (ISBN)
Conference
6th IFAC Symposium on Advances in Automotive Control, July 12-14, Munich, Germany
Available from: 2012-01-16 Created: 2012-01-16 Last updated: 2014-03-25Bibliographically approved
2. A New Electric Machine Model and its Relevance for Vehicle Level Diagnosis
Open this publication in new window or tab >>A New Electric Machine Model and its Relevance for Vehicle Level Diagnosis
2015 (English)In: International Journal of Modelling, Identification and Control, ISSN 1746-6172, Vol. 24, no 1, 1-9 p.Article in journal (Refereed) Published
Abstract [en]

With the electrification of society, especially transportation, the control and supervision of electrical machines become more and more important due to its bearing on energy, environment, and safety. To optimise performance in control and supervision, appropriate modelling is crucial, and this regards both the ability to capture reality and the computational complexity to be useful in real-time. Here, a new low complexity model of the electric machine is proposed and developed. The new model treats the machine constants in a different way compared to a previous standard model, which results in a different expression for power losses. It is shown that this increases model expressiveness so when adapted to real data the result is significantly better. The significance of this modelling improvement is demonstrated using a task in vehicle diagnosis where it is shown that the separation between the non-faulty and faulty cases is better and the resulting performance is improved.

Place, publisher, year, edition, pages
InderScience Publishers, 2015
Keyword
electric machine models, permanent magnet synchronous machine, PMSM, power losses, hybrid electric vehicle, HEV, fault diagnosis, vehicle level diagnosis
National Category
Vehicle Engineering
Identifiers
urn:nbn:se:liu:diva-105485 (URN)10.1504/IJMIC.2015.071704 (DOI)
Note

At the time for thesis presentation publication was in status: Manuscript

Available from: 2014-03-25 Created: 2014-03-25 Last updated: 2016-09-29Bibliographically approved
3. Selecting and Utilizing Sequential Residual Generators in FDI Applied to Hybrid Vehicles
Open this publication in new window or tab >>Selecting and Utilizing Sequential Residual Generators in FDI Applied to Hybrid Vehicles
2014 (English)In: IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, ISSN 2168-2216, Vol. 44, no 2, 172-185 p.Article in journal (Refereed) Published
Abstract [en]

In order to obtain a realistic model of a complex system, thousands of possible residual generators need to be used for diagnosis. Based on engineering insights of the system to be monitored, certain algebraic and dynamic properties of the residual generators may be preferred, and therefore, a method for finding sequential residual generators is developed that accounts for these properties of the residual generator candidates. It is shown that only a small fraction of all residual generator candidates fulfill fundamental requirements, and thereby, proves the value of systematic methods. Furthermore, methods are devised for utilization of the residual generators, such as initialization of dynamic residual generators. A proposed method, considering the fault excitation in the residuals using the internal form of the residuals, significantly increases the diagnosis performance. A hybrid electric vehicle is used in a simulation study for demonstration, but the methods used are general in character and provides a basis when designing diagnosis systems for other complex systems.

Place, publisher, year, edition, pages
IEEE, 2014
Keyword
Fault diagnosis; hybrid electric vehicle; model based diagnosis; residual generation
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-104283 (URN)10.1109/TSMC.2013.2248147 (DOI)000330131800004 ()
Available from: 2014-02-17 Created: 2014-02-14 Last updated: 2014-03-25
4. Diagnostic Method Combining Map and Fault Models Applied on a Hybrid Electric Vehicle
Open this publication in new window or tab >>Diagnostic Method Combining Map and Fault Models Applied on a Hybrid Electric Vehicle
2014 (English)Manuscript (preprint) (Other academic)
Abstract [en]

A common situation in the automotive industry is that map based models are available. In general these models accurately describe the fault free system, and are therefore suited for fault detectability in a diagnosis system. However, one drawback using such a model is that fault isolation then requires that measurements of the faulty system is done, which is costly. Another approach is to use a model of the system where the faults are explicitly included. To directly achieve good diagnostic performance such a model needs to be accurate, which also is costly. Therefore, in the new approach taken here, two models are used in combination to achieve both good fault detectability and isolability in a diagnosis system; one is a map based model, and one is describing how the faults affect the system. The approach is exemplified by designing a diagnosis system monitoring the power electronics and the electric machine in a hybrid electric vehicle. In an extensive simulation study it is shown that the approach works well and is a promising path to achieve both good fault detectability and isolability performance, without the need for neither measurements of a faulty system nor detailed physical modeling. In the designed diagnosis system all faults are fully isolated, and the size of the faults are accurately estimated.

National Category
Vehicle Engineering
Identifiers
urn:nbn:se:liu:diva-105486 (URN)
Available from: 2014-03-25 Created: 2014-03-25 Last updated: 2014-03-25Bibliographically approved

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Sundström, Christofer

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