Effect of Driving patterns on Components sizing of a Series PHEV

In the past decade, it has been demonstrated that Plug-in Hybrid Electric Vehicles (PHEVs) can significantly reduce petroleum consumptions. However, the extend to which these vehicles can reduce the petroleum consumption highly depends on components size and driving patterns. In other words, PHEVs show the best benefits if the components are dimensioned to match the driver’s driving behavior. In this paper, the effect of different driving patterns on the optimal sizing of three major components of series PHEVs, i.e., battery, electric motor, and engine generator unit is studied. Different driving cycles are generated stochastically from real driving data using Markov chains, to represent life-time driving patterns of different drivers. To find the optimal size of the components, the problem is formulated as a convex optimization problem. The optimization variables (the variables of component size and energy management) are obtained by minimizing a cost function which is the sum of the operational and component costs.