Physical system modeling: Algorithms for assessing model quality based on design specifications
Başlık çevirisi mevcut değil.
- Tez No: 402953
- Danışmanlar: PROF. JEFFREY L. STEIN, DOÇ. HUEI PENG
- Tez Türü: Doktora
- Konular: Makine Mühendisliği, Mechanical Engineering
- Anahtar Kelimeler: Model Accuracy, Model Validity, Physical System Models, Dynamic Models, System Design, Virtual Prototyping, Automated Modeling, Model Reduction, Proper System Models
- Yıl: 2002
- Dil: İngilizce
- Üniversite: University of Michigan
- Enstitü: Yurtdışı Enstitü
- Ana Bilim Dalı: Belirtilmemiş.
- Bilim Dalı: Belirtilmemiş.
- Sayfa Sayısı: 189
Özet
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Özet (Çeviri)
Dynamic models of physical systems with physically meaningful states and parameters, have become increasingly important parts of the design, control and even procurement processes. The successful use of models in this context requires that the models are of sufficient quality. However, while algorithms have been developed to help formulate and integrate physical system models, and while algorithms have been developed to generate minimum complexity physical system models subject to a modeling metric constraints, missing from the literature are the algorithms to assess the“quality”of dynamic system models. The objective of this research is to develop a methodology to quantify the accuracy of the predicted system variables and to determine the validity of a model of given complexity with respect to a set of criteria derived from engineering design specifications or measurement noise. Another objective of this thesis is to integrate the methodology with an activity based Model Order Reduction Algorithm (MORA) (Louca et. al, 1998) to quantify the accuracy of the different models as a function of activity, that is a measure of complexity. The last objective aims to generate proper system models with desired accuracy. Accuracy & Validation Algorithm for Simulation (AVASIM), proposed in this dissertation, is a time-domain perspective comparing the model's time based output trajectories to targets at user-defined points. In addition, the model accuracy over the total horizon of interest is also used. The tolerances on specific time points and overall response are determined by the user's domain knowledge (design specifications) or the measurement noise associated with empirical validation studies. The performance of the models is formulated as a performance index that is determined from measures such as relative error, residuals sum, etc. to quantify the accuracy with respect to the target points and overall response. The validity of the models is then determined by comparing the performance indices to that of a“threshold model”derived from the design specifications or measurement noise on a data set. To illustrate the basic idea of AVASIM, two case studies based on automotive applications are presented. First, the handling performance of a TruckSim type vehicle dynamics model of a Grand Jeep Cherokee subjected to steering inputs is presented. The required system response and measurement noise statistics are obtained from vehicle measurements. The methodology is then applied to five TruckSim models with different complexities generated by the application of the Activity Metric and MORA. In the second case study, a full system model of International Class VI Truck is used as an illustrative example to quantify the accuracy and validity of a hierarchy of models generated by MORA. The tolerances are derived from the set of design specifications that arise from the design requirements in this case study. The model accuracy is shown to decrease with the MORA-defined complexity of the reduced models. Also the complexity of the model needed to predict accuracy within the usersupplied specifications is shown. Results from both the Grand Cherokee and International truck case studies show that accuracy and validity of the reduced models can be systematically assessed using the proposed AVASIM. Integration of AVASIM with MORA seems to be a very powerful design tool to generate the proper design model with desired accuracy.
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