2010-01-2310 Maximizing Net Present Value of a Series PHEV by Optimizing Battery Size and Vehicle Control Parameters R. Vijayagopal, J. Kwon, A. Rousseau Argonne National Laboratory P. Maloney The MathWorks, Inc. Copyright © 2010 SAE International ABSTRACT For a series plug-in hybrid electric vehicle (PHEV), it is critical that batteries be sized to maximize vehicle performance variables, such as fuel efficiency, gasoline savings, and zero emission capability. The wide range of design choices and the cost of prototype vehicles calls for a development process to quickly and systematically determine the design characteristics of the battery pack, including its size, and vehicle-level control parameters that maximize the net present value (NPV) of a vehicle during the planning stage. Argonne National Laboratory has developed Autonomie, a modeling and simulation framework. With support from The MathWorks, Argonne has integrated an optimization algorithm and parallel computing tools to enable the aforementioned development process. This paper presents a study that utilized the development process, where the NPV is the present value of all the future expenses and savings associated with the vehicle. The initial investment on the battery and the future savings that result from reduced gasoline consumption are compared. The investment and savings results depend on the battery size and the vehicle usage. For each battery size, the control parameters were optimized to ensure the best performance possible with the battery design under consideration. Real-world driving patterns and survey results from the National Highway Traffic Safety Administration were used to simulate the usage of vehicles over their lifetime. INTRODUCTION Plug-in hybrid electric vehicles (PHEVs) have demonstrated great potential with regard to petroleum displacement. Since the benefits of PHEV technology rely heavily on the battery [1], the development of new generations of advanced batteries with a long life and low cost is critical. The objective of the study is to determine the most effective battery power and energy, based on different cost assumptions, to optimize the net present value (NPV). To achieve that goal, Autonomie, Argonne's vehicle simulation tool, is used along with an optimization algorithm developed by The MathWorks. The PHEV used for this analysis is a midsize passenger car. The characteristics of this vehicle are shown in Table 1. Table 1. PHEV specifications Component Technology Specification Comments Motor PM induction 120-kW peak Steady-state efficiency map Engine Gasoline 110 kW Hot, steady-state fuel map Generator PM induction 50-kW peak Steady-state efficiency map Battery pack Saft, Li 16 kWh, scalable Internal resistance, open circuit voltage as a function of battery state-of-charge Vehicle Series PHEV Midsize sedan Drag coefficient: 0.31; frontal area: 2.06; test weight: 1,350 kg Components and their sizes differed when comparing a conventional vehicle and series PHEV. While the battery size changed, the other hybrid powertrain components were left unaltered. This allowed the focus to be placed entirely on the effect of battery size and its economic impact on the vehicle cost. The cost of the battery was considered as an investment, and the gasoline savings (compared with a conventional vehicle) was considered as a cost savings. Since the investment and operating cost was very specific to vehicle use during its