| 1. |
- Frisk, Erik, et al.
(författare)
-
Diagnosability Analysis Considering Causal Interpretations for Differential Constraints
- 2012
-
Ingår i: IEEE transactions on systems, man and cybernetics. Part A. Systems and humans. - : Institute of Electrical and Electronics Engineers (IEEE). - 1083-4427 .- 1558-2426. ; 42:5, s. 1216-1229
-
Tidskriftsartikel (refereegranskat)abstract
- This paper is focused on structural approaches to study diagnosability properties given a system model taking into account, both simultaneously or separately, integral and differential causal interpretations for differential constraints. We develop a model characterization and corresponding algorithms, for studying system diagnosability using a structural decomposition that avoids generating the full set of system analytical redundancy relations. Simultaneous application of integral and differential causal interpretations for differential constraints results in a mixed causality interpretation for the system. The added power of mixed causality is demonstrated using a Reverse Osmosis Subsystem from the Advanced Water Recovery System developed at the NASA Johnson Space Center. Finally, we summarize our work and provide a discussion of the advantages of mixed causality over just derivative or just integral causality.
|
|
| 2. |
- Hellström, Erik, 1979-, et al.
(författare)
-
Design of an efficient algorithm for fuel-optimal look-ahead control
- 2010
-
Ingår i: Control Engineering Practice. - : Elsevier. - 0967-0661 .- 1873-6939. ; 18:11, s. 1318-1327
-
Tidskriftsartikel (refereegranskat)abstract
- A fuel-optimal control algorithm is developed for a heavy diesel truck that utilizes information about the road topography ahead of the vehicle when the route is known. A prediction model is formulated where special attention is given to properly include gear shifting. The aim is an algorithm with sufficiently low computational complexity. To this end, a dynamic programming algorithm is tailored, and complexity and numerical errors are analyzed. It is shown that it is beneficial to formulate the problem in terms of kinetic energy in order to avoid oscillating solutions and to reduce linear interpolation errors. A residual cost is derived from engine and driveline characteristics. The result is an on-board controller for an optimal velocity profile and gear selection.
|
|
| 3. |
- Hellström, Erik, 1979-, et al.
(författare)
-
Horizon length and fuel equivalents for fuel-optimal look-ahead control
- 2010
-
Konferensbidrag (refereegranskat)abstract
- Recent studies from several authors show that it is possible to lower the fuel consumption for heavy trucks by utilizing information about the road topography ahead of the vehicle. The approach in these studies is receding horizon control where horizon length and residual cost are main topics. To approach these topics, fuel equivalents previously introduced based on physical intuition are given a mathematical interpretation in terms of Lagrange multipliers. Measures for the suboptimality, caused by the truncated horizon and the residual cost approximation, are defined and evaluated for different routes and parameters.
|
|
| 4. |
- Hellström, Erik, 1979-
(författare)
-
Look-ahead Control of Heavy Vehicles
- 2010
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Trucks are responsible for the major part of inland freight and so, they are a backbone of the modern economy but they are also a large consumer of energy. In this context, a dominating vehicle is a truck with heavy load on a long trip. The aim with look-ahead control is to reduce the energy consumption of heavy vehicles by utilizing information about future conditions focusing on the road topography ahead of the vehicle.The possible gains with look-ahead control are evaluated by performing experiments with a truck on highway. A real-time control system based on receding horizon control (RHC) is set up where the optimization problem is solved repeatedly on-line for a certain horizon ahead of the vehicle. The experimental results show that significant reductions of the fuel consumption are achieved, and that the controller structure, where the algorithm calculates set points fed to lower level controllers, has satisfactory robustness to perform well on-board in a real environment. Moreover, the controller behavior has the preferred property of being intuitive, and the behavior is perceived as comfortable and natural by participating drivers and passengers.A well-behaved and efficient algorithm is developed, based on dynamic programing, for the mixed-integer nonlinear minimum-fuel problem. A modeling framework is formulated where special attention is given to properly include gear shifting with physical models. Fuel equivalents are used to reformulate the problem into a tractable form and to construct a residual cost enabling the use of a shorter horizon ahead of the vehicle. Analysis of errors due to discretization of the continuous dynamics and due to interpolation shows that an energy formulation is beneficial for reducing both error sources. The result is an algorithm giving accurate solutions with low computational effort for use in an on-board controller for a fuel-optimal velocity profile and gear selection.The prevailing approach for the look-ahead problem is RHC where main topics are the approximation of the residual cost and the choice of the horizon length. These two topics are given a thorough investigation independent of the method of solving the optimal control problem in each time step. The basis for the fuel equivalents and the residual cost is formed from physical intuition as well as mathematical interpretations in terms of the Lagrange multipliers used in optimization theory. Measures for suboptimality are introduced that enables choosing horizon length with the appropriate compromise between fuel consumption and trip time.Control of a hybrid electric powertrain is put in the framework together with control of velocity and gear. For an efficient solution of the minimum-fuel problem in this case, more fuel equivalence factors and an energy formulation are employed. An application is demonstrated in a design study where it is shown how the optimal trade-off between size and capacity of the electrical system depends on road characteristics, and also that a modestly sized electrical system achieves most of the gain.The contributions develop algorithms, create associated design tools, and carry out experiments. Altogether, a feasible framework is achieved that pave the way for on-board fuel-optimal look-ahead control.
|
|
| 5. |
- Hellström, Erik, 1979-, et al.
(författare)
-
Management of kinetic and electric energy in heavy trucks
- 2010
-
Ingår i: Transmission and Driveline, 2010. - : SAE International. - 9780768034257
-
Konferensbidrag (refereegranskat)abstract
- Hybridization and velocity management are two important techniques for energy efficiency that mainly have been treated separately. Here they are put in a common framework that from the hybridization perspective can be seen as an extension of the equivalence factor idea in the well known strategy ECMS. From the perspective of look-ahead control, the extension is that energy can be stored not only in kinetic energy, but also electrically. The key idea is to introduce more equivalence factors in a way that enables efficient computations, but also so that the equivalence factors have a physical interpretation. The latter fact makes it easy to formulate a good residual cost to be used at the end of the look-ahead horizon. The formulation has different possible uses, but it is here applied on an evaluation of the size of the electrical system. Previous such studies, for e.g. ECMS, have typically used a driving cycle, i.e. a fixed velocity profile, but here the extra freedom to choose an optimal driving pattern is added.
|
|
| 6. |
- Krysander, Mattias, et al.
(författare)
-
A Structural Algorithm for Finding Testable Sub-models and Multiple Fault Isolability Analysis
- 2010
-
Ingår i: 21st Annual Workshop Proceedings. - : phm society. - 9781936263028
-
Konferensbidrag (refereegranskat)abstract
- Structural methods have previously been used to perform isolability analysis and finding testable sub-models, so called Minimal Structurally Overdetermined (MSO) sets, Analytical Redundancy Relations (ARR), or Possible Conflicts (PC). The number of MSO sets grows exponentially in the degree of redundancy making the task of computing MSO sets intractable for systems with high degree of redundancy. This paper describes an efficient graph-theoretical algorithm for computing a similar, but smaller, set of testable submodels called Test Equation Supports (TES). A key difference, compared to an MSO based approach, is that the influence of faults is taken into account and the resulting number of testable models as well as the computational complexity of finding them can be reduced significantly without reducing the possible diagnosis performance. It is shown that the TESs in a direct way characterize the complete multiple fault isolability property of a model and thus extends previous structural approaches from the single-fault case.
|
|
| 7. |
- Larsson, Emil, 1981-
(författare)
-
Diagnosis and Supervision of Industrial Gas Turbines
- 2012
-
Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Monitoring of industrial gas turbines is of vital importance, since it gives valuable information for the customer about maintenance, performance, and process health. The performance of an industrial gas turbine degrades gradually due to factors such as environment air pollution, fuel content, and ageing to mention some of the degradation factors. The compressor in the gas turbine is especially vulnerable against contaminants in the air since these particles are stuck at the rotor and stator surface. The loss in compressor performance, due to fouling, can partially be restored by an on-line/off-line compressor wash. If the actual health state of the gas turbine is known, it is possible to efficiently plan the service and maintenance and thereby reduce the environmental impact and the fuel cost for the customer.A thermodynamic gas turbine modeling package, called GTLib, is developed in the equation-based object-oriented modeling language Modelica. Using the GTLib package, a gas turbine model can be constructed. The gas turbine model can be used for performance calculation and as a base when diagnosis tests are generated. These tests can be used in a diagnosis and supervision system to detect compressor fouling and abrupt sensor faults. One of the benefits with using GTLib is the ability to model a lean stoichiometric combustion at different air/fuel ratio. Using the air/fuel ratio concept, an arbitrary number of gas species in the in-coming air can be considered. The number of equations is reduced if the air/fuel ratio concept is considered instead of modeling each gas species separately. The difference in the number of equations is significant if many gas species are considered.When the gas turbine components deteriorate, a mismatch between the nominal performance model and the measurements increase. To handle this, the gas turbine model is augmented with a number of estimation parameters. These estimation parameters are used to detect slow deterioration in the gas turbine components and are estimated with a Constant Gain Extended Kalman Filter (CGEKF). The state estimator is chosen using structural methods before an index reduction of the model is performed. Experimental data is investigated and it is shown that the performance degradation due to compressor fouling can be estimated. After the compressor is washed, the performance of the compressor is partially restored. An abrupt sensor fault of 1% of the nominal value is introduced in the discharge temperature of the compressor. The sensor fault can be detected using the CUSUM algorithm for change detection.Finally, the overall thesis contribution is the calculation chain from a simulation model used for performance calculation to a number of test quantities used in a diagnosis and supervision system. Since the considered gas turbine model is a large non-linear DAE model that has unobservable state variables, the test construction procedure is automatically performed with developed parsers.
|
|
| 8. |
- Larsson, Emil, 1981-, et al.
(författare)
-
Fault Isolation for an Industrial Gas Turbine with a Model-Based Diagnosis Approach
- 2010
-
Ingår i: Proceedings of ASME Turbo Expo. - : ASME Press. - 9780791843987 ; , s. 89-98
-
Konferensbidrag (refereegranskat)abstract
- Model based diagnosis and supervision of industrial gas turbines are studied. Monitoring of an industrial gas turbine is important as it gives valuable information for the customer about service performance and process health. The overall objective of the paper is to develop a systematic procedure for modelling and design of a model based diagnosis system, where each step in the process can be automated and implemented using available software tools. A new Modelica gas media library is developed, resulting in a significant model size reduction compared to if standard Modelica components are used. A systematic method is developed that, based on the diagnosis model, extracts relevant parts of the model and transforms it into a form suitable for standard observer design techniques. This method involves techniques from simulation of DAE models and a model reduction step. The size of the final diagnosis model is 20% of the original model size. Combining the modeling results with fault isolation techniques, simultaneous isolation of sensor faults and fault tolerant health parameter estimation is achieved.
|
|
| 9. |
- Larsson, Emil, 1981-, et al.
(författare)
-
Fault Tolerant Supervision of an Industrial Gas Turbine
- 2013
-
Ingår i: Proceedings of ASME Turbo Expo. - 9780791855188
-
Konferensbidrag (refereegranskat)abstract
- Supervision of the performance of an industrial gas turbine is important since it gives valuable information of the process health and makes efficient determination of compressor wash intervals possible. Slowly varying sensor faults can easily be misinterpreted as performance degradations and result in an unnecessary compressor wash. Here, a diagnostic algorithm is carefully combined with non-linear state observers to achieve fault tolerant performance estimation. The proposed approach is evaluated in an experimental case study with six months of measurement data from a gas turbine site. The investigation shows that faults in all gas path instrumentation sensors are detectable and isolable. A key result of the case study is the ability to detect and isolate a slowly varying sensor fault in the discharge temperature sensor after the compressor. The fault is detected and isolated before the wash condition of the compressor is triggered, resulting in fault tolerant estimation of compressor health parameters.charge temperature sensor after the compressor. The fault is detected and isolated before the wash condition of the compressor is triggered, resulting in fault tolerant estimation of compressor health parameters.
|
|
| 10. |
- Larsson, Emil, et al.
(författare)
-
Gas Turbine Modeling for Diagnosis and Control
- 2014
-
Ingår i: Journal of engineering for gas turbines and power. - : American Society of Mechanical Engineers (ASME). - 0742-4795 .- 1528-8919. ; 136:7, s. 071601-
-
Tidskriftsartikel (refereegranskat)abstract
- The supervision of performance in gas turbine applications is crucial in order to achieve: (i) reliable operations, (ii) low heat stress in components, (iii) low fuel consumption, and (iv) efficient overhaul and maintenance. To obtain a good diagnosis of performance it is important to have tests which are based on models with high accuracy. A main contribution is a systematic design procedure to construct a fault detection and isolation (FDI) system for complex nonlinear models. To fulfill the requirement of an automated design procedure, a thermodynamic gas turbine package (GTLib) is developed. Using the GTLib framework, a gas turbine diagnosis model is constructed where component deterioration is introduced. In the design of the test quantities, equations from the developed diagnosis model are carefully selected. These equations are then used to implement a constant gain extended Kalman filter (CGEKF)-based test quantity. The test quantity is used in the FDI-system to supervise the performance and in the controller to estimate the flame temperature. An evaluation is performed using experimental data from a gas turbine site. The case study shows that the designed FDI-system can be used when the decision about a compressor wash is taken. Thus, the proposed model-based design procedure can be considered when an FDI-system of an industrial gas turbine is constructed.
|
|
