Bond Graph-Based Energy Balance Analysis of Forward and Backward Looking Models of Parallel Plug-In Hybrid Electric Vehicle 2022-01-0743

Design and optimization of a plug-in hybrid electric vehicle (PHEV) control strategy is typically based on a backward-looking (BWD) powertrain model, which ensures a high computational efficiency by neglecting the powertrain dynamics. However, the control strategy developed for BWD model may considerably underperform when applied to a forward-looking (FWD) powertrain model, which includes a dynamic driver model, powertrain dynamics, and corresponding low-level controls. This paper deals with bond-graph based modelling and energy balance analysis of BWD and FWD powertrain models for a P2 parallel PHEV-type city bus equipped with a 12-speed automated manual transmission. The powertrain consists of a motor/generator (M/G) machine supplied by the lithium-ion battery and placed at the transmission input shaft, and an internal combustion engine which can be disconnected from the rest of the powertrain by a main clutch placed between the engine and M/G machine. The BWD model is implemented in Matlab/Simulink environment whereas FWD model is developed in Simcenter Amesim. The BWD and FWD models are tested for different driving cycles reflecting different driving conditions. It is shown that the powertrain transient-related losses occurring during transmission gear shifting and engine switching predominantly contribute to the difference in energy consumption of the FWD model compared to the BWD model. It is also shown that, as the number of powertrain shifting and switching events is reduced by proper tuning of high-level control strategy, the difference between FWD- and BWD-model-related energy consumption becomes lower for the same driving cycle.