Matlab announces Argonne, Tesla using their tools

The Mathworks announced two customers this week using their tools in science and engineering. The first at Argonne

The MathWorks today announced that Argonne National Laboratory significantly reduced the simulation time of models built with the Powertrain System Analysis Toolkit (PSAT) by using Parallel Computing Toolbox and MATLAB Distributed Computing Server from The MathWorks.

PSAT is an industry-standard model that enables automotive engineers to assess design tradeoffs by simulating a large number of advanced powertrain configurations. Using two other MathWorks products, Simulink and Stateflow, Argonne, funded by the US Department of Energy, developed PSAT in conjunction with leading automotive manufacturers to help automotive engineers evaluate fuel economy and performance of advanced vehicle designs, including hybrid electric vehicles (HEVs) and plug-in HEVs. Argonne used Parallel Computing Toolbox with PSAT to execute simulations on a 16-node cluster—reducing the overall run time from two weeks to one day. Using MATLAB Distributed Computing Server also enabled Argonne to move its simulations with ease from a desktop computer to a cluster in one hour.

And the second announcement is that Tesla is using Matlab to evaluate design tradeoffs for the 2008 Tesla Roadster

The MathWorks today announced that Silicon Valley electric vehicle maker Tesla Motors employed Model-Based Design tools from The MathWorks to develop the 2008 Tesla Roadster, the world’s first electric production sports car.

To meet aggressive technology goals on a strict budget and timeline, the Tesla Motors design team relied on Simulink and MATLAB to model the entire vehicle and its major subsystems. Engineers combined individual models for each major system of the car, including the motor, battery, transmission, brakes, tires, power electronics, and control systems, into one full-system model, which they used to simulate and predict overall vehicle performance before building prototype vehicles. The simulated results were then compared against road-test results from prototype vehicles to refine the full-system model. This approach shortened overall design and test processes and helped Tesla Motors to deliver the 2008 Tesla Roadster for a fraction of the typical vehicle program cost.