scholarly journals Automatic, black-box model order reduction using radial basis functions

Author(s):  
Matthew B. Stephanson ◽  
Jin-Fa Lee
2016 ◽  
Vol 64 (9) ◽  
Author(s):  
Matthias Geuß

AbstractThis thesis deals with model order reduction of parameter-dependent systems based on interpolation of locally reduced system matrices. A Black-Box method is proposed that automatically determines the optimal design parameters and delivers a reduced system with desired accuracy. In addition, the method is extended to stability preservation and interpolation for high-dimensional parameter spaces.


2015 ◽  
Vol 48 (1) ◽  
pp. 168-169 ◽  
Author(s):  
M. Geuss ◽  
B. Lohmann ◽  
B. Peherstorfer ◽  
K. Willcox

Author(s):  
Franz Pichler ◽  
Niels Koester ◽  
Alexander Thaler

Purpose This paper aims to present a fully coupled thermo-electrical finite-element battery model with an applied model-order reduction. The model is used to analyse the thermal design of battery modules during typical drive-cycles of electric vehicles. Design/methodology/approach A model-order reduction is applied, in which the electrical linear bus-bars are analysed in an a-priori step. For these bus-bars, special distributed basis-functions are computed, which make the solution of differential Ohm's law unnecessary during the transient simulation. Furthermore, the distributed basis-functions are used to strongly couple the non-linear battery models, which reduces the iterations needed to simulate them. Findings Altogether, this results in a fast simulation scheme for coupled linear and non-linear electrical components and their thermal behaviour. Originality/value The presented method delivers an innovative approach, on how to systematically minimize the computational effort in a system of linear and non-linear electrical components, while keeping the full three-dimensional information of the original problem.


Sign in / Sign up

Export Citation Format

Share Document