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Abstract-Hybrid electric vehicles (HEVs) have attracted a lot of attention due to environmental and efficiency reasons. Typically, an HEV combines two power trains, a conventional power source such as a gasoline engine, a diesel engine, or a fuel cell stack, and an electric drive system (involving a motor and a generator) to produce driving power with a potential of higher fuel economy than conventional vehicles. Furthermore, such vehicles do not require external charging and thus work within the existing fueling infrastructures. The power-split power train configuration of an HEV has the individual advantages of the series and parallel types of HEV power train configurations. A sophisticated control system, however, is required to manage the power-split HEV power trains. Designing such a control system requires a reasonably accurate HEV system plant model. Much research has been done for developing dynamic plant models for the series and parallel types, but a complete and validated dynamic model for the power-split HEV power train is still in its infancy. This paper presents a power-split power train HEV dynamic model capable of realistically replicating all the major steady-state and transient phenomena appearing under different driving conditions. A mathematical derivation and modeling representation of this plant model and its components is shown first. Next, the analysis, verification, and validation through computer simulation and comparison with the data actually measured in the test vehicle at the Ford Motor Company's test track is performed. The excellent agreements between the model and the experimental results demonstrate the fidelity and validity of the derived plant model. Since this plant model was built by integrating the subsystem models using a system-oriented approach with a hierarchical methodology, it is easy to change subsystem functionalities. The developed plant model is useful for analyzing and understanding the dominant dynamics of the power train system, the interaction between subsystems and components, and system transients due to the change of operational state and the influence of disturbances. This plant model can also be employed for the development of vehicle system controllers, evaluation of energy management strategies, issue resolution, and verification of coded algorithms, among many other purposes.

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