An Algorithm for Obtaining Proper Models of Distributed and Discrete Systems

Wilson, Bruce H.; Stein, Jeffrey L.

doi:10.1115/1.2801111

Cited by 37 publications

(17 citation statements)

References 1 publication

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“…A fundamental objective of model reduction techniques is the systematic formulation of a minimally complex model that represents all behaviour of interest in the original model to a sufficient level of precision [1]. This objective echoes Einstein's famous sentiment that models should be made as simple as possible, but no simpler [2].…”

Section: Introductionmentioning

confidence: 91%

Reduction of a Vehicle Multibody Dynamic Model Using Homotopy Optimization

Hall¹,

Loh²,

Schmitke³

et al. 2013

Archive of Mechanical Engineering

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Despite the ever-increasing computational power of modern processors, the reduction of complex multibody dynamic models remains an important topic of investigation, particularly for design optimization, sensitivity analysis, parameter identification, and controller tuning tasks, which can require hundreds or thousands of simulations. In this work, we first develop a high-fidelity model of a production sports utility vehicle in Adams/Car. Single-link equivalent kinematic quarter-car (SLEKQ, pronounced "sleek") models for the front and rear suspensions are then developed in MapleSim. To avoid the computational complexity associated with introducing bushings or kinematic loops, all suspension linkages are lumped into a single unsprung mass at each corner of the vehicle. The SLEKQ models are designed to replicate the kinematic behaviour of a full suspension model using lookup tables or polynomial functions, which are obtained from the high-fidelity Adams model in this work. The predictive capability of each SLEKQ model relies on the use of appropriate parameters for the nonlinear spring and damper, which include the stiffness and damping contributions of the bushings, and the unsprung mass. Homotopy optimization is used to identify the parameters that minimize the difference between the responses of the Adams and MapleSim models. Finally, the SLEKQ models are assembled to construct a reduced 10-degree-of-freedom model of the full vehicle, the dynamic performance of which is validated against that of the high-fidelity Adams model using four-post heave and pitch tests.

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Section: Introductionmentioning

confidence: 91%

Reduction of a Vehicle Multibody Dynamic Model Using Homotopy Optimization

Hall¹,

Loh²,

Schmitke³

et al. 2013

Archive of Mechanical Engineering

View full text Add to dashboard Cite

show abstract

“…Wilson and Stein (1995) developed MODA (Model Order Deduction Algorithm) that deduces the needed system model complexity from subsystem models of variable complexity using a frequency-based metric. Additional work on deduction algorithms for generating proper models in an automate fashion has been reported by Ferris et al (1994), Ferris and Stein (1995) and Walker et al (1996).…”

Section: Introductionmentioning

confidence: 99%

Bond Graph Based Modal Representations And Model Reduction Of Lumped Parameter Systems

Louca

2006

ECMS 2006 Proceedings Edited By: W. Borutzky, A. Orsoni, R. Zobel

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Modal analysis is extensively used to study dynamic behavior of continuous and lumped parameter linear systems. More specifically, modal analysis can be used for the analysis and controller design of dynamic systems. In both cases, reduction of model size without degrading the accuracy is often required for the efficient use of the model. The reduction of modal models has been extensively studied and many reduction techniques are available. The majority of these techniques use frequency as the metric to determine the reduced model. This paper describes a new method for calculating the modal power of lumped parameter systems with the use of the bond graph representation, which is developed through a power conserving modal decomposition. This method is then used to reduce the size of the model. This technique is based on the Model Order Reduction Algorithm (MORA), which uses an energy-based metric to generate a series of proper reduced models. An illustrative example is provided to demonstrate the calculation of the modal power and the elimination of unimportant modes or modal elements using MORA.

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“…Wilson and Stein (1995) developed the concept of a "proper model" -the model described by the minimal set of physical parameters required to predict dominant system dynamics -along with an algorithm that deduces the "appropriate" system model complexity from subsystem models of variable complexity. Additional work on deduction algorithms for generating proper models has been reported by Ferris et al (1994), Ferris and Stein (1995), and Walker et al (2000).…”

Section: Systematic Treatment Of Model Complexitymentioning

confidence: 99%

Generating proper dynamic models for truck mobility and handling

Louca

Rideout

Stein

et al. 2004

IJHVS

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In previous work, a "proper model" was defined as the model of minimal complexity, with physically meaningful parameters, which accurately predicts dynamic system outputs. Proper models can be generated by an energy-based model reduction methodology that removes unnecessary complexity from models (linear or nonlinear) without altering the physical interpretation of the remaining parameters and variables. Energy-based model reduction allows design in a search space of reduced dimension, and in general improves computational efficiency.The current work demonstrates the effectiveness and utility of an energy-based model reduction algorithm for vehicle system modeling applications. Model reduction is performed for two different vehicle modeling applications. The first case study focuses on the vehicle dynamics model of a military heavy-duty tractor semitrailer. The full model is developed using a classical multibody system approach and accurate reduced models are then generated for a lane change maneuver. The second case study develops, validates, and reduces an integrated vehicle system model of a single-unit medium-size commercial truck composed of engine, drivetrain, and vehicle dynamic subsystems. The systematically reduced model accurately predicts vehicle forward speed/acceleration and engine behavior during full-throttle acceleration and braking with a twofold increase in computation efficiency.The reduced models generated by the energy-based methodology retain predictive quality, are useful for studying trade-offs involved in redesigning components and control strategies for improved vehicle performance, and are less computationally intensive.

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An Algorithm for Obtaining Proper Models of Distributed and Discrete Systems

Cited by 37 publications

References 1 publication

Reduction of a Vehicle Multibody Dynamic Model Using Homotopy Optimization

Reduction of a Vehicle Multibody Dynamic Model Using Homotopy Optimization

Bond Graph Based Modal Representations And Model Reduction Of Lumped Parameter Systems

Generating proper dynamic models for truck mobility and handling

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