MIMO Interconnects Order Reductions by Using the Global Arnoldi Algorithm

Abstract

We propose the global Arnoldi algorithm for MIMO Error information in the reduced system will be a guideline RLCG interconnect model order reductions. This algorithm is for the order selection scheme. In the second reduced-order an extension of the standard Arnoldi algorithm for systems system we can keep the simple formulation described in the with multi-inputs and multi-outputs (MIMO). By employing the B congruence transformation with the matrix Krylov subspace, the BA algorithm In addition, the transfer matrix of the second one-sided projection method can be used to construct a reduced-reduced system is identical to those of the original system with order system. Two kinds of reduced systems using the global additive perturbation matrix.Arnoldi algorithm will be proposed. The first q-th order of these reduced systems' moments will still be preserved. The transfer II. PRELIMINARY matrix residual error of the reduced system will also be derived A linear, time-invariance, RLCG interconnect circuit can be analytically. Experimental results demonstrate the feasibility and represented in the following modified nodal analysis (MNA) the effectiveness of the proposed method. r formula:

Control Oriented Thermal Modeling of Lithium Ion Batteries from a First Principle Model via Model Reduction by the Global Arnoldi Algorithm

“…If the node of interest is subjected to environmental temperature from the top or bottom, T T (t) = T env or T B (t) = T env , respectively. The vertical overall heat transfer coefficients for a node subjected to conduction from the top or bottom is [15] where y is the vertical thickness (m) of the node of interest. For a node subjected to convection from the top or bottom, the overall heat transfer coefficient is…”

“…The goal of this section is to capture those dynamics while making the model more applicable to control design. The Global Arnoldi Algorithm (GAA) 15 is used to reduce high order non-linear MIMO systems into a substantially lower order set of equations. Typically, the algorithm is applied to linearized or weakly non-linear systems.…”

“…Chen et al 14 applied the combination of the Taylor series expansion and the Arnoldi algorithm to a weakly nonlinear system and obtained good results. Lai et al 15 applied the Global Arnoldi Algorithm (GAA) to a Multiple Input Multiple Output (MIMO) RLCG (Resistance, Inductance, Capacitance, and Conductance) system and obtained good results. This work will show that the GAA allows for the reduction of a complex high order nonlinear battery thermal model without the use of experimental data or parameter estimation.…”