MapleSim 6: Advances in System-Level Modeling

September 04 2012 laurent 680
MapleSim 6


MapleSim has seen a rapid evolution since its inception in 2008 as a multi-domain system-level modeling and simulation environment. Market response has been outstanding: Maplesoft has been working with an expanding list of key industry players such as AISIN AW Co., Ltd. and B&R,  while major customers like NASA’s Jet Propulsion Laboratory join a fast-growing user base of companies enjoying the benefits of a high-performance simulation environment built on top of a symbolic computing engine. The latest release, MapleSim 6, delivers major enhancements along all three pillars of innovation that this product has become known for: Modelica, advanced analysis, and fast HIL code.

If there had been any question about the potential of Modelica as the standard open model description language when we started the MapleSim project in 2005, there can be no question today. Modelica is ubiquitous in many parts of Europe and enjoys rapid growth of its user base around the world, notably in both North America and Japan. In MapleSim 6, you will find a friendly Modelica environment that gives you access to the full power of the language. At the same time, we have taken great care to keep MapleSim easy to use and learn, leading to productive usage as quickly as possible. For example, while you can now browse the Modelica code for any library component with just one click, you can also see all definitions and equations of that component at a glance without having to follow chains of inheritance manually.

MapleSim's interactive analysis environment, based on Maple, is certainly unique among physical modeling tools. Template documents provide easy access to common tasks like building custom components, performing optimization, or Monte-Carlo analysis. The true power, however, comes with the API, which gives you full command-based control over setting up, running, and analyzing models and simulations. Combined with Maple's computational capabilities, I have seen the API perform sophisticated parameter sweeps - distributed in parallel over all the cores of your machine. Another example is a multi-body model, where Maple was used to compute explicit (symbolic) formulas for inverse kinematics and inverse dynamics. Those formulas were then plugged into a MapleSim model using a custom component to yield blindingly fast simulations. The possibilities with the MapleSim API are virtually endless, but at the same time easily accessible due to the open nature of the Maple environment.

The third pillar for MapleSim is the ability to generate very fast (and royalty-free) simulation code for HIL/SIL. This is another example where the underlying symbolic computing engine becomes a distinct advantage. Being able to simplify and optimize at the equation level allows MapleSim to consistently outrun its competitors. For hardware-in-the-loop simulations, execution speed makes the difference between being able to run a model in real-time or having to compromise on fidelity. MapleSim's automatic simplifications and optimizations are loss-less and yield simulation code that is typically a factor of 3 to 20 times faster than using other tools. In addition, symbolic computing techniques in Maple pave the way to further model reduction, for example for applications like model predictive control.

As a whole, MapleSim 6 offers all the ingredients to tackle today's most sophisticated engineering challenges across a large variety of disciplines and industries, and has the potential of making a significant difference within your toolchain.

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