PSAT Technical Information

PSAT, developed with MATLAB R14SP3, is used in powertrain development to optimize a vehicle and its components with regard to the following:

• Fuel consumption for any driving cycle or profile
• Vehicle performance, including acceleration and grade
• Drivetrain configuration, including conventional, electric, fuel cell, series hybrid, parallel hybrid, and power split hybrid
• Realistic control strategy development
• Component technologies
• Component sizing
• Transmission ratios

Flexible and Reusable

PSAT was designed to be a single tool that can be used to meet the requirements of automotive engineering throughout the development process:

• Each drivetrain configuration is constructed built according to user input so that vehicle architectures can be compared and the most appropriate one selected. More than 400 pre-selected configurations are available.
• PSAT can be used for light- as well as heavy-duty vehicles and has built-in tools for scaling the components when specific data are not available.
• Different levels of modeling (from lookup tables to high-fidelity physics based) can be used as all component models have the same number of input/output parameters.
• Control strategies and shifting algorithms options can easily be added and compared.
• HTML reports can be generated for simulations and test data.
• Unique driving cycles (such as an aggregation of cycles) can be created, and several cycles can be run in a row as each simulation is saved in four files.
• When used on a network, several instances of PSAT can be run simultaneously, which solves some versioning problems.
• All simulations are saved, providing the ability to reload the results or rerun the same simulation.
• Extensive post-processing allows for understanding and improving the system.
• Tests or simulations can be replayed and compared simultaneously for validation.
• Test data (from vehicle or component) can be integrated, and the test can be replayed by using an animation interface.

Easy to Use

• A user-friendly GUI has been incorporated.
• The drivetrain configuration, component models, and data sets for the simulation can be selected. New initialization files, component models, and controls can be integrated within minutes without any code modification.
• Specific colors are used for different blocks of the component models and controls (e.g., red for input blocks, yellow for constants).
• The subsystems of the models are grouped by function (e.g., torque, speed, and inertia calculations for the transmission model).
• Extensive documentation is available.

Fast and Accurate

• By using test data from Argonne’s Advanced Powertrain Research Facility, conventional and mild hybrid vehicles have been validated within 2% (Honda Insight, Ford P2000) and full hybrid vehicles (Toyota Prius) within 5% for both fuel economy and battery state-of-charge on several driving cycles.
• The Simulink code can be compiled to speed up the simulation (more than six times faster).
• Ongoing use of PSAT by Argonne and licensees ensures continued product improvement and enhancements.

Simulation Services

Argonne National Laboratory provides simulation services, consultation, and reporting of results for interested clients.

System Requirements

• Memory (RAM): minimum of 1 GB; 2 GB or more recommended
• Platform: PC (XP); MATLAB, Simulink and StateFlow required (Version R14SP3 or R2006b prefered), Matlab Report Generator Toolbox Optional
• Disk storage: approximately 250 MB of storage to run; a minimum of 100 MB to store results

High-Fidelity Dynamic Models

In addition to dynamic models developed at Argonne, such as GCTool, other high-fidelity models have been linked with PSAT. The following models require separate licensing with the developers.

• The Tubocharged Diesel Engine Simulink (TDES) module, developed by Assanis & Associates, is a transient, thermodynamic, physically based, crank-angle-resolved, turbocharged, intercooled diesel engine simulation module that can be coupled to the rest of the vehicle propulsion system in Simulink. This module can accept driver command, external load, and environmental conditions from the top system level and produce (a) torque at the flywheel, (b) realistic speed variations depending on active and resistive torque, and (c) other engine system variables of interest to the analyst (e.g., cylinder pressure and temperature histories, air/fuel ratio histories, thermodynamic conditions in manifolds, mass flow rates, and enthalpy rates between components). For maximum flexibility and to compensate for a possible lack of engine design data for new configurations, automatic scaling routines are included. Depending on specified values for engine displacement and number of cylinders, the code will automatically adjust the size of engine parts, manifolds, valves, and turbomachinery. For information, contact Dennis Assanis.
• The battery model developed at the Pennsylvania State University GATE Center is a thermal-electrochemical coupled model based on computational fluid dynamics, a computationally robust framework. Simulating Dynamic Stress Test (DST), Simplified Federal Urban Driving Schedule (SFUDS), and actual field driving cycles and comparing them with experimental data has demonstrated the robustness of this model for lead-acid, nickel-metal hydride, and lithium-ion cells. The potential advantages of using this first-principles approach instead of the lumped equivalent circuit approach lie in the ability of this model to adapt to design changes. For example, a change in the electrode structure (porosity, thickness), separator characteristics, or particle size of the active material would change the internal resistance term because of changes in the ohmic, kinetic, or diffusion effects. The need for building a physical prototype, conducting more experiments, and repeating the procedure can be avoided by using the first-principles approach. For information, contact Chao-Yang Wang.

June 5, 2007