Optimal energy management system of plug-in hybrid electric vehicle using hybrid dynamical system
Plug-in Hybrid Electric Vehicles (PHEVs) utilize power from an internal combustion engine and electric motor to drive the vehicle. The electric motor is driven by an onboard battery, which can be charged through grid power supply. These two sources of energy can be used in several different ways to drive vehicle. By using a Plug-in Hybrid Electric Vehicle, energy usage from battery and engine can be optimized so that total energy usage is minimized. In Plug-in hybrid electric vehicles, the vehicle operates in various modes such as EV mode, battery charging mode, regenerative mode, etc. In each of these modes, the vehicle is operated by a different source. For each mode, a non-linear mathematical model is derived to describe the dynamics of the vehicle. Mode switching combined with system dynamics models a Plug-in Hybrid Electric Vehicle that operates in different modes. This system can be described using a Hybrid dynamical systems framework. In this thesis, a hybrid dynamical system based Plug-in Hybrid Electric Vehicle model is developed. It also describes the vehicle dynamics of PHEV and its subsequent use to develop a hybrid dynamical system of PHEV. The proposed hybrid dynamical system model of PHEV can be easily extended to other powertrain architectures. This hybrid system of PHEV is used to solve a non linear constrained optimization problem such that minimum total energy is consumed by PHEV. To solve this optimization problem, a dynamic programming method for the hybrid dynamical system is used. For Real-time implementation of this energy minimization system, a sub-optimal Model predictive control based on hybrid dynamical system is formulated and then used to solve the optimization problem. Finally, this model predictive control is implemented on a Real-time controller and practical implementation is demonstrated.
Hu, Purdue University.
Electrical engineering|Mechanical engineering
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