A crucial step towards the large-scale introduction of plug-in hybrid electric vehicles (PHEVs) in the market is to reduce the cost of its battery systems. Currently, battery cycle- and calendar-life represents one of the greatest uncertainties in the total life-cycle cost of battery systems. The field of battery aging modeling and prognosis has seen progress with respect to model-based and data-driven approaches to describe the aging of battery cells. However, in real world applications cells are interconnected and aging propagates. The propagation of aging from one cell to others exhibits itself in a reduced battery system life. This paper proposes a control-oriented battery pack model that describes the propagation of aging and its effect on the life span of battery systems. The modeling approach is such that it is able to predict pack aging, thermal, and electrical dynamics under actual PHEV operation, and includes consideration of random variability of the cells, electrical topology and thermal management. The modeling approach is based on the interaction between dynamic system models of the electrical and thermal dynamics, and dynamic models of cell aging. The system-level state-of-health (SOH) is assessed based on knowledge of individual cells SOH, pack electrical topology and voltage equalization approach.