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The Future Automotive Systems Technology Simulator (FASTSim) is a high-level advanced vehicle powertrain systems analysis tool supported by the U.S. Department of Energy's Vehicle Technologies Office. FASTSim provides a quick and simple approach to compare powertrains and estimate the impact of technology improvements on light-and heavy-duty vehicle efficiency, performance, cost, and battery life. The input data for most light-duty vehicles can be automatically imported. Those inputs can be modified to represent variations of the vehicle or powertrain. The vehicle and its components are then simulated through speed-versus-time drive cycles. At each time step, FASTSim accounts for drag, acceleration, ascent, rolling resistance, each powertrain component's efficiency and power limits, and regenerative braking. Conventional vehicles, hybrid electric vehicles, plug-in hybrid electric vehicles, all-electric vehicles, compressed natural gas vehicles, and fuel cell vehicles are included. Powertrains with electric-traction drive can optionally be simulated using electric roadway technologies such as dynamic wireless power transfer. FASTSim also has an interface for running large batches of real-world drive cycles. FASTSim's calculation framework and balance among detail, accuracy, and speed enable it to simulate thousands of driven miles in minutes. The key components and vehicle outputs have been validated by comparing the model outputs to test data for many different vehicles to provide confidence in the results. A graphical user interface makes FASTSim easy and efficient to use. FASTSim is freely available for download from the National Renewable Energy Laboratory's website (see www.nrel.gov/fastsim). Powertrain Components FASTSim captures the key inputs for most high-level vehicle powertrain modeling. They include parameters that define the vehicle, including the fuel storage, fuel converter, motor, traction battery, wheel, and energy management strategy.

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The Automotive Deployment Options Projection Tool (ADOPT) is a light-duty vehicle consumer choice and stock model supported by the U.S. Department of Energy's Vehicle Technologies Office. It estimates technology improvement impacts on future U.S. light-duty vehicles sales, petroleum use, and greenhouse gas emissions. ADOPT uses techniques from the multinomial logit method and the mixed logit method to estimate vehicle sales. Specifically, it estimate sales based on the weighted value of key attributes including vehicle price, fuel cost, acceleration, range and usable volume. The average importance of several attributes changes nonlinearly across its range and changes with income. For several attributes, a distribution of importance around the average value is used to represent consumer heterogeneity. The majority of existing vehicle makes, models, and trims are included to fully represent the market. The Corporate Average Fuel Economy regulations are enforced. The sales feed into the ADOPT stock model. It captures key aspects for summing petroleum use and greenhouse gas emissions. This includes capturing the change in vehicle miles traveled by vehicle age, the creation of new model options based on the success of existing vehicles, new vehicle option introduction rate limits, and survival rates by vehicle age. ADOPT has been extensively validated with historical sales data. It matches in key dimensions including sales by fuel economy, acceleration, price, vehicle size class, and powertrain across multiple years. A graphical user interface provides easy and efficient use. It manages the inputs, simulation, and results.

United States imported almost half of its petroleum. Lightweighting vehicles reduces that dependency directly by decreasing the engine, braking and rolling resistance losses, and indirectly by enabling a smaller, more efficiently operating engine to provide the same performance.The Future Automotive Systems Technology Simulator (FASTSim) tool was used to quantify these impacts. FASTSim is the U.S. Department of Energy's (DOE's) highlevel vehicle powertrain model developed at the National Renewable Energy Laboratory. It steps through a time versus speed drive cycle to estimate the powertrain forces required to meet the cycle. It simulates the major vehicle powertrain components and their losses. It includes a cost model based on component sizing and fuel prices.FASTSim simulated different levels of lightweighting for four different powertrains. The four powertrains included a conventional gasoline engine vehicle, a hybrid electric vehicle (HEV), a plug-in hybrid electric vehicle (PHEV), and a battery electric vehicle (EV).Weight reductions impacted the conventional vehicle efficiency more than the HEV, PHEV and EV. Although lightweighting impacted advanced vehicle efficiency less, it reduced component cost and overall costs more. Under the assumed current battery costs, however, the PHEV and EV were still more expensive than the conventional vehicle and HEV. Assuming the DOE's battery cost target of $125/kWh and improved battery life, however, the PHEV and EV attained similar cost and lightweighting benefits. Generally, lightweighting was cost effective when it cost less than $6/kg of mass eliminated.

Electrifying transportation can reduce or eliminate dependence on foreign fuels, emission of green house gases, and emission of pollutants. One challenge is finding a pathway for vehicles that gains wide market acceptance to achieve a meaningful benefit. This paper evaluates several approaches aimed at making plug-in electric vehicles (EV) and plug-in hybrid electric vehicles (PHEVs) cost-effective including opportunity charging, replacing the battery over the vehicle life, improving battery life, reducing battery cost, and providing electric power directly to the vehicle during a portion of its travel. Many combinations of PHEV electric range and battery power are included. For each case, the model accounts for battery cycle life and the national distribution of driving distances to size the battery optimally. Using the current estimates of battery life and cost, only the dynamically plugged-in pathway was cost-effective to the consumer. Significant improvements in battery life and battery cost also made PHEVs more cost-effective than today's hybrid electric vehicles (HEVs) and conventional internal combustion engine vehicles (CVs).

A systems-level modeling suite underpins estimates of greenhouse gas and other benefits of deploying co-optimized fuels and engines.