This thesis investigates modeling and simulation of hybrid electric vehicles with particular emphasis on transient modeling and real-time simulation. Three different computer models, i.e. a steady state model, a fully-detailed transient model and a reduced-intensity transient model, are developed for a hybrid drive-train in this study. The steady-state model, which has low computational intensity, is used to determine the optimal battery size and chemistry for a plug-in hybrid drive-train. Simulation results using the developed steady state model show the merits of NiMH and Li-ion battery technologies. Based on the obtained results and the reducing cost of Li-ion batteries, this battery chemistry is used throughout this research. A fully-detailed transient model is developed to simulate the vehicle behaviour under different driving conditions. This model includes the dynamics of the power train components such as the engine, the power-electronic converters and vehicle controllers of all levels. The developed transient model produces an accurate representation of the drive-train including the switching behaviour of the power electronic converters. A reduced-intensity transient model (also referred to as a dynamic average model) is developed for real-time hardware-in-loop simulation of the vehicle. By reducing the computational demand of the detailed transient model using averaging techniques, the reduced-intensity model is implemented on a real-time simulator and is interfaced to an external subsystem such as an actual battery. The setup can be used to test existing and emerging battery technologies, which may not have an accurate mathematical model. Extensive tests are performed to verify the accuracy and validity of the results obtained from the developed hardware-in-loop simulation setup.

This thesis investigates modeling and simulation of hybrid electric vehicles with particular emphasis on transient modeling and real-time simulation. Three different computer models, i.e. a steady state model, a fully-detailed transient model and a reduced-intensity transient model, are developed for a hybrid drive-train in this study. The steady-state model, which has low computational intensity, is used to determine the optimal battery size and chemistry for a plug-in hybrid drive-train. Simulation results using the developed steady state model show the merits of NiMH and Li-ion battery technologies. Based on the obtained results and the reducing cost of Li-ion batteries, this battery chemistry is used throughout this research. A fully-detailed transient model is developed to simulate the vehicle behaviour under different driving conditions. This model includes the dynamics of the power train components such as the engine, the power-electronic converters and vehicle controllers of all levels. The developed transient model produces an accurate representation of the drive-train including the switching behaviour of the power electronic converters. A reduced-intensity transient model (also referred to as a dynamic average model) is developed for real-time hardware-in-loop simulation of the vehicle. By reducing the computational demand of the detailed transient model using averaging techniques, the reduced-intensity model is implemented on a real-time simulator and is interfaced to an external subsystem such as an actual battery. The setup can be used to test existing and emerging battery technologies, which may not have an accurate mathematical model. Extensive tests are performed to verify the accuracy and validity of the results obtained from the developed hardware-in-loop simulation setup.

The purpose of this thesis is to use automation to create appropriate models in PSS/E with the data from Hardware-in-Loop real-time simulations. With the increase in technology of power electronics, the use of High Voltage Direct Current Technology and Flexible Alternating Current Transmission System devices in the electrical power system have increased tremendously. Static Var Compensators are widely used and it is important to have accurate and reliable models for studies relating to power systems planning and interaction. An automation method is proposed to find the parameters of an SVC model in PSS/E with the data from the Hardware-in- loop real-time simulation of the SVC physical controller using Hypersim. The effect of the SVC on the system under steady state and fault conditions are analyzed with HIL simulation of an SVC physical controller in Hypersim and its corresponding model in PSS/E in the IEEE 14 bus system. The parameters of the SVC model in PSS/E can be effectively varied to bring its response closer to that of the response from HIL simulations in Hypersim. An error function is used as a measure to understand the extent of difference between the model and the physical controller.