HPnGs go Non-Linear: Statistical Dependability Evaluation of Battery-Powered Systems

Hybrid Petri nets with general transitions (HPnGs) provide a formalism for modeling safety-critical systems and evaluating their dependability with means of model checking. HPnGs form a restricted subclass of Stochastic Hybrid Automata and allow discrete, continuous and stochastic variables. Previously, discrete-event simulation and Statistical Model Checking (SMC) have been used to overcome the restrictions of existing analytical approaches, e.g., to a limited number of random variables. Also when simulating, the evolution of continuous variables has been restricted to piecewise-linear trajectories, where derivatives do not change between two events. Here, we extend the modeling formalism, the simulation and SMC approach to variables with a non-linear continuous evolution. The core idea of this extension lies in transforming the input system into a so-called second-order quantized state system. A case study on the Kinetic Battery Model validates our approach by comparing results to those obtained by Matlab.