Complexity adaptation of simulation models in a function-based modular framework

This paper presents a method for complexity adaptation of simulation models in a function-based modular framework. By this means, the problem of inappropriate simulation model complexity leading to inaccurate predictions and poor extrapolation within entire-system simulations is avoided. The function-based modular framework describes a process that separates entire-system simulations into defined individual subsystems called functions. Thus the basis for storing different complex simulation models within the separated functions is set, ensuring consistent interfaces, independent of any simulation tool, with which they are simulated. To adapt the complexity of simulation models encapsulated in the functions to simulation purposes, a method for complexity quantification is introduced, using concepts from information theory and statistical methods. To prove the functionality and reliability of the method, example different complex battery simulation models are taken into account and quantified, demonstrating the potential for complexity adaptation of every individual subsystem within entire-system simulations.