A time management optimization framework for large-scale distributed hardware-in-the-loop simulation

Abstract

Large-scale distributed HIL(Hardware-In-The-Loop) simulation is an important and indispensable method for testing and verifying complex engineering systems. An important necessary condition for realizing HIL simulation is that the speedup ratio of full-speed simulation must be greater than 1, and satisfying this condition becomes more and more difficult with the ceaselessly increasing scale of simulation. Aiming at the problem how to maximizing the speedup ratio, a time management optimization framework for large-scale distributed HIL simulation is proposed in this paper. Different from other works on performance optimization of HIL simulation, in this paper, the problem is focused on simulation speedup ratio and is considered in the range of analysis simulation, which means causal abnormity is intolerable. According to this goal, a new formal description framework of distributed simulation is given based on the automata theory. Then the basic objective and condition of distributed simulation are formally analyzed, which results in the conclusion that the classical Local Causality Constraint for distributed simulation is only a sufficient condition rather than sufficient and necessary condition. Based on this, the optimization problem for simulation speedup ratio is radically analyzed and the overall strategy for this problem is given. Considering different conditions, two different levels of optimization mechanisms respectively for time advance and task partition are given. And finally, the application and experiment result shows the effectiveness of the proposed method.