Computationally efficient modeling of load dynamics in turbocharged internal combustion engines

Abstract

Hybridization of non-road mobile machinery offers benefits for energy efficiency and decarbonization tasks. Hybrid electric power trains combine combustion engines with electric machines and batteries. Thus, it is important to model engine dynamics accurately so that the operation of different kinds of power train systems can be controlled and optimized. This study compares several transfer function- and time-series-based methods to model dynamic torque in combustion engines. Models are compared with experimental data on real engines. A new simulation method called Dynamic Torque Limiter (DTL) is developed and validated. The DTL method employs both a time-based limitation parameter, which models the turbocharger lag, and a transfer function, which models the fuel injection dynamics of the typical engine.