FASTSim: Future Automotive Systems Technology Simulator
The Future Automotive Systems Technology Simulator (FASTSim™) provides a streamlined approach for comparing powertrains and estimating the impact of technology improvements on light-, medium-, and heavy-duty vehicle performance, cost, efficiency, and battery life.
This extremely fast tool features an intuitive Python interface and can rapidly perform simulations using basic computing resources.
FASTSim models a range of vehicle powertrains and fuel converter types:
Conventional vehicles: spark ignition (Otto, Atkinson, Miller), diesel, and compressed natural gas
Electric-drive vehicles: hybrid, plug-in hybrid, and all-electric
Hydrogen fuel cell vehicles.
The default model includes a variety of vehicles and duty cycles as well as an option to add additional vehicles and custom cycles.
Download FASTSim
Install FASTSim directly from PyPl.
For installation instructions and guidance on using the tool, visit the FASTSim documentation site on GitHub.
Feedback
Although NLR does not provide technical support for FASTSim, we welcome your feedback. Please email your feedback or report issues to fastsim@nlr.gov. Alternatively, you can open an issue on GitHub.
Publications
The following publications provide examples of how FASTSim can be used to compare powertrains, assess component improvements, or conduct other types of vehicle analyses.
The Current State of Heavy-Duty Trucking in the UK and the U.S.: Challenges and Digital Simulations to Support Electrification, Clean Energy and Equitable Transportation Solutions (2027)
Green Urban Mobility: Optimizing Hydrogen Public Transport From Demand to Energy Supply, International Conference on Electrical, Computer and Energy Technologies (2026)
A Physics-Based Normalized Reduced-Order Model for Trip-Level Energy Consumption Estimation of Electric Buses, IEEE Access (2026)
Ambient and Initial Temperature Effects on Battery Electric Vehicle Range and Energy Consumption Rate Modeled in FASTSim, WCX SAE World Congress Experience (2026)
Future Projections of Lifecycle Cost and Emissions of Light-Duty Vehicles, World Electric Vehicle Journal (2026)
A Comprehensive Study of Electric Vehicle Performance Under Diverse Powertrain Architecture Using 1D Simulation Approach, Automotive Experiences (2026)
Energy-Closure Framework for Physics-Consistent Electric Vehicle Fleet Estimation, IEEE Transactions on Transportation Electrification (2026)
Empowering Electric Bus Deployment with Standardized Transit Data, Transportation Research Record: Journal of the Transportation Research Board (2026)
Drive Cycles, Battery Pack Design, and Usage Considerations for Long-Haul and Regional-Haul Electric Trucks, Journal of Power Sources (2026)
PV System Technology Considerations for PV-Powered Passenger Vehicles, International Energy Agency Report (2026)
Performance Analysis of a Small-Sized Hybrid Vehicle on a Real-World Inclined Route Under WLTP, ARTEMIS, and NEDC Drive Cycles, Fuel Cells (2026)
Linear Programming Formulation for Planning of Future Model-Year Mix of Electrified Powertrains, World Electric Vehicle Journal (2026)
Impact Assessment of Battery-Electric HDVs Charging Loads on the Transmission and Distribution System in Iceland, Applied Energy (2026)
Electric Vehicle Energy Consumption Modeling Using Real-World Driving Data: System Identification vs. Machine Learning, IEEE Transactions on Intelligent Vehicles (2026)
Assessment of Heavy-Duty Fueling Methods and Components—Modeling and Analysis, NLR Technical Report (2025)
Thermal Intelligence Big Data and AI for Sustainable Battery and Cabin Heat Management in Electric Vehicle, American Journal of Engineering and Technology (2025)
Impact of EV Charging Stations Reliability, Resilience, and Location on EV Adoption, Continuing Education and Development Report (2025)
Green Hydrogen for Road Transport in Western Australia, Future Energy Exports Cooperative Research Centre Report (2025)
A Methodological Framework for Developing Novel Vehicle Concepts Based on Quantified End-Customer Techno-Economic Criteria, Technical University of Liberec Dissertation (2025)
Comprehensive Framework for Energy Consumption Estimation in Electric Vehicles, IEEE Transactions on Intelligent Transportation Systems (2025)
Advancements in AI-Powered Electric Vehicle Routing: Multi-Constraint Optimization and Infrastructure Integration Approaches for Evolving EVs—A Survey, IEEE Access (2025)
The CanBikeCO Full Pilot: Long-Term Results and Analysis from an E-Bike Program in Colorado, USA, International Journal of Sustainable Transportation (2025)
HD ADOPT: Heavy-Duty Vehicle Choice Model Documentation, NLR Strategic Partnership Project Report (2025)
Route Energy Prediction (RouteE) Powertrain Validation Report, NLR Technical Report (2025)
Optimising Fast-Charging Infrastructure for Long-Haul Electric Trucks in Remote Regions Under Adverse Climate Conditions, eTransportation (2025)
Combining Statistical and Machine Learning Methodologies in Energy Consumption Forecasting for Electric Vehicles, Preprints (2025)
Deep Q-Learning Based Optimal Energy Management of a Plug-in Hybrid Electric Vehicle, ASME International Mechanical Engineering Congress (2025)
Research on the Correlation Mechanism Between Complex Slopes of Mountain City Roads and the Real Driving Emission of Heavy-Duty Diesel Vehicles, Sustainability (2025)
How To Cite FASTSim
If you use FASTSim for work described in a publication, please notify us and include this citation in your publication:
Brooker, A., Gonder, J., Wang, L., Wood, E. et al., "FASTSim: A Model To Estimate Vehicle Efficiency, Cost, and Performance," SAE Technical Paper 2015-01-0973, 2015, doi:10.4271/2015-01-0973.
More Information
For more information about FASTSim, refer to these seminal publications.
FASTSim Validation Report, NLR Technical Report (2021)
FASTSim: A Model to Estimate Vehicle Efficiency, Cost, and Performance, SAE World Congress (2015)
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Last Updated Sept. 30, 2026