NREL releases enhanced FASTSim vehicle simulation tool for wider array of analyses
23 May 2018
New and enhanced versions of NREL’s Future Automotive Systems Technology Simulator (FASTSim) are now available for free download in Python and Microsoft Excel formats. FASTSim provides a quick and simple way to compare powertrains and estimate the impact of technology improvements on light-, medium-, and heavy-duty vehicle efficiency, performance, cost, and battery life. It accommodates a range of vehicle types, including conventional vehicles, electric-drive vehicles, and fuel cell vehicles.
The versions of FASTSim recently posted on the website feature a wider vehicle range capability and updated vehicle models along with the addition of fuel cell vehicles to the roster of vehicle types.
—NREL Senior Engineer Aaron Brooker
FASTSim facilitates large-scale evaluation of vehicle performance under a range of driving conditions. This flexible simulation tool enables researchers to quantify relative energy consumption differences among a variety of vehicle or powertrain alternatives and determine how these differences change in varying driving environments or applications.
FASTSim can perform an assortment of tasks extremely quickly using basic computing resources:
< 0.1 second to simulate second-by-second standard duty cycles;
< 10 seconds to estimate vehicle efficiency, fuel economy, acceleration, battery life, and cost; and
< 5 minutes to perform powertrain comparisons of efficiency and cost.
FASTSim models a wide variety of vehicle powertrains and fuel converter types:
Conventional vehicles: spark injection, Atkinson, diesel, and hybrid diesel
Electric-drive vehicles: hybrid, plug-in hybrid, and all-electric
Hydrogen fuel cell vehicles
The default model includes a variety of vehicles and drive cycles—including standard US drive cycles as well as European and Japanese cycles—and an option for adding additional vehicles and custom cycles.
NREL developed two versions of FASTSim to accommodate a wider array of analyses, Brooker said.
The easy-to-use Excel version features an interactive user interface that simplifies the process of importing new vehicle data and custom drive cycles. In addition to calculating energy consumption, the Excel version of FASTSim enables life-cycle cost comparisons, battery life comparisons, component sizing tradeoffs, and more. It can also handle design-of-experiment inquiries.
The Python version of FASTSim is compatible with large datasets. Pairing with the Transportation Secure Data Center, for example, facilitates simulations of multi-day travel incorporating vehicle dwell times. When paired with geo-spatial duty cycles, FASTSim helps users draw conclusions at the regional level by incorporating such factors as temperature, roadway characteristics, or driving behavior.
The Python version of FASTSim is also customizable for performing more specific analyses. The component models in the Python version are easily expandable and can be adjusted to incorporate additional energy consumption impacts. Model flexibility and speed simplify A/B comparisons for a vehicle powertrain, control strategy, or technology. Its large number of included vehicles and computational efficiency makes calculating impacts at the fleet-level easy.
Resources
Brooker, A., Gonder, J., Wang, L., Wood, E. et al. (2015) “FASTSim: A Model to Estimate Vehicle Efficiency, Cost, and Performance,” SAE Technical Paper 2015-01-0973, 2015, doi: 10.4271/2015-01-0973
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