Numerical methods in vehicle system dynamics: state of the art and current developments
(2011) In Vehicle System Dynamics 49(7). p.1159-1207- Abstract
- Robust and efficient numerical methods are an essential prerequisite for the computer based dynamical analysis of engineering systems. In vehicle system dynamics, the methods and software tools from multibody system dynamics provide the integration platform for the analysis, simulation and optimization of the complex dynamical behaviour of vehicles and vehicle components and their interaction with hydraulic components, electronical devices and control structures.
Based on the principles of classical mechanics, the modelling of vehicles and their components results in nonlinear systems of ordinary differential equations (ODEs) or differential-algebraic equations (DAEs) of moderate dimension that describe the dynamical behaviour in... (More) - Robust and efficient numerical methods are an essential prerequisite for the computer based dynamical analysis of engineering systems. In vehicle system dynamics, the methods and software tools from multibody system dynamics provide the integration platform for the analysis, simulation and optimization of the complex dynamical behaviour of vehicles and vehicle components and their interaction with hydraulic components, electronical devices and control structures.
Based on the principles of classical mechanics, the modelling of vehicles and their components results in nonlinear systems of ordinary differential equations (ODEs) or differential-algebraic equations (DAEs) of moderate dimension that describe the dynamical behaviour in the frequency range required and with a level of detail being characteristic of vehicle system dynamics. Most practical problems in this field may be transformed to generic problems of numerical mathematics like systems of nonlinear equations in the (quasi-)static analysis and explicit ODEs or
DAEs with a typical semi-explicit structure in the dynamical analysis. This transformation to mathematical standard problems allows to use sophisticated, freely available numerical software that is based on well approved numerical methods like the Newton-Raphson iteration for nonlinear equations or Runge-Kutta and linear multistep methods for ODE/DAE time integration.
Substantial speed-ups of these numerical standard methods may be achieved exploiting some specific structure of the mathematical models in vehicle system dynamics.
In the present paper, we follow this framework and start with some modelling aspects being relevant from the numerical viewpoint. The focus of the paper is on numerical methods for static and dynamic problems including software issues and a discussion which method fits best for which class of problems. Adaptive components in state-of-the-art numerical software like stepsize and order control in time integration are introduced and illustrated by a well known benchmark problem from rail vehicle simulation.
Over the last few decades, the complexity of high-end applications in vehicle system dynamics has frequently given a fresh impetus for substantial improvements of numerical methods and for the development of novel methods for new problem classes. In the present paper, we address three of these challenging problems of current interest that are today still beyond the mainstream of numerical mathematics: (i) Modelling and simulation of contact problems in multibody dynamics, (ii) Real-time capable numerical simulation techniques in vehicle system dynamics and
iii) Modelling and time integration of multidisciplinary problems in system dynamics including co-simulation techniques. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/2163389
- author
- Arnold, Martin ; Burgermeister, Bernhard ; Führer, Claus LU ; Hippmann, Gerhard and Rill, Georg
- organization
- publishing date
- 2011
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- vehicle system dynamics, differential-algebraic equations, differential equations, numerical methods
- in
- Vehicle System Dynamics
- volume
- 49
- issue
- 7
- pages
- 1159 - 1207
- publisher
- Taylor & Francis
- external identifiers
-
- wos:000298956300006
- scopus:84856867049
- ISSN
- 1744-5159
- DOI
- 10.1080/00423114.2011.582953
- language
- English
- LU publication?
- yes
- additional info
- The information about affiliations in this record was updated in December 2015. The record was previously connected to the following departments: Numerical Analysis (011015004)
- id
- d3d3f208-6eb3-4fa1-8d9b-b5aaad851ffa (old id 2163389)
- alternative location
- http://dx.doi.org/10.1080/00423114.2011.582953
- date added to LUP
- 2016-04-01 10:39:37
- date last changed
- 2022-03-19 22:45:46
@article{d3d3f208-6eb3-4fa1-8d9b-b5aaad851ffa,
abstract = {{Robust and efficient numerical methods are an essential prerequisite for the computer based dynamical analysis of engineering systems. In vehicle system dynamics, the methods and software tools from multibody system dynamics provide the integration platform for the analysis, simulation and optimization of the complex dynamical behaviour of vehicles and vehicle components and their interaction with hydraulic components, electronical devices and control structures.<br/><br>
Based on the principles of classical mechanics, the modelling of vehicles and their components results in nonlinear systems of ordinary differential equations (ODEs) or differential-algebraic equations (DAEs) of moderate dimension that describe the dynamical behaviour in the frequency range required and with a level of detail being characteristic of vehicle system dynamics. Most practical problems in this field may be transformed to generic problems of numerical mathematics like systems of nonlinear equations in the (quasi-)static analysis and explicit ODEs or<br/><br>
DAEs with a typical semi-explicit structure in the dynamical analysis. This transformation to mathematical standard problems allows to use sophisticated, freely available numerical software that is based on well approved numerical methods like the Newton-Raphson iteration for nonlinear equations or Runge-Kutta and linear multistep methods for ODE/DAE time integration.<br/><br>
Substantial speed-ups of these numerical standard methods may be achieved exploiting some specific structure of the mathematical models in vehicle system dynamics.<br/><br>
In the present paper, we follow this framework and start with some modelling aspects being relevant from the numerical viewpoint. The focus of the paper is on numerical methods for static and dynamic problems including software issues and a discussion which method fits best for which class of problems. Adaptive components in state-of-the-art numerical software like stepsize and order control in time integration are introduced and illustrated by a well known benchmark problem from rail vehicle simulation.<br/><br>
Over the last few decades, the complexity of high-end applications in vehicle system dynamics has frequently given a fresh impetus for substantial improvements of numerical methods and for the development of novel methods for new problem classes. In the present paper, we address three of these challenging problems of current interest that are today still beyond the mainstream of numerical mathematics: (i) Modelling and simulation of contact problems in multibody dynamics, (ii) Real-time capable numerical simulation techniques in vehicle system dynamics and<br/><br>
iii) Modelling and time integration of multidisciplinary problems in system dynamics including co-simulation techniques.}},
author = {{Arnold, Martin and Burgermeister, Bernhard and Führer, Claus and Hippmann, Gerhard and Rill, Georg}},
issn = {{1744-5159}},
keywords = {{vehicle system dynamics; differential-algebraic equations; differential equations; numerical methods}},
language = {{eng}},
number = {{7}},
pages = {{1159--1207}},
publisher = {{Taylor & Francis}},
series = {{Vehicle System Dynamics}},
title = {{Numerical methods in vehicle system dynamics: state of the art and current developments}},
url = {{http://dx.doi.org/10.1080/00423114.2011.582953}},
doi = {{10.1080/00423114.2011.582953}},
volume = {{49}},
year = {{2011}},
}