{"id":245,"date":"2017-09-28T07:44:19","date_gmt":"2017-09-28T07:44:19","guid":{"rendered":"https:\/\/blogs.mathworks.com\/student-lounge\/?p=245"},"modified":"2017-09-28T07:49:27","modified_gmt":"2017-09-28T07:49:27","slug":"racecar-small-workflow-professional","status":"publish","type":"post","link":"https:\/\/blogs.mathworks.com\/student-lounge\/2017\/09\/28\/racecar-small-workflow-professional\/","title":{"rendered":"Racecar: Small – Workflow: Professional"},"content":{"rendered":"

In today\u2019s blog post I am happy to introduce\u00a0Jose Avendano Arbelaez<\/a>, a first-time guest in this blog. We have been collaborating on a nice hardware-software demo including a (model) racecar.<\/p>\n

—<\/p>\n

This article is particularly suited for automotive student teams, but it is clearly not exclusive to them. All models related to the demo have been published on the MATLAB Central File Exchange<\/a> and two instructional videos have been released: #1<\/a>, #2<\/a>. With this blog post, I am going to share our desired learning outcomes and some background information.<\/p>\n

Why?<\/h1>\n

Vehicle modeling has proven to give teams a competitive advantage in student competitions. This can be combined with model-based design<\/a> to simulate and prototype systems in an optimal manner. Model-based design involves stages like defining requirements, modeling the system, deploying onto microcontrollers and testing all connected through the same modeling approach. This saves time and increases the quality of the final product. We decided to show how to apply\u00a0all stages of product development\u00a0to reach the ready-to-race car.<\/p>\n

Our Approach<\/h1>\n

Since we couldn\u2019t show these features implemented on a full-size vehicle we decided to go with a small-scale version. Our RC racecar demo shows how easy it is to deploy vehicle dynamics controllers that you have previously designed and validated using Simulink. In this case, the Texas Instruments C2000 hardware support package<\/a> was a good interface to the actuators and sensors that we had available in our car. MATLAB and Simulink also enable testing of our design. For this, we implemented CAN communication, a functionality\u00a0of the Vehicle Network Toolbox<\/a>, to both acquire data through Simulink and use the logged data directly in simulations.<\/p>\n

\"\"<\/a><\/p>\n

Programming the ECU using\u00a0Simulink Hardware Support Packages<\/h1>\n

As mentioned before, to get the Simulink model to interact with actual hardware we used the TI C2000 Support package for Embedded Coder<\/a>. One of the biggest time-saving features of Simulink is that it can automatically generate code for different hardware platforms, including many low-cost solutions. For our application, the C2000 support package was fully integrated with the Texas Instruments development tools.<\/p>\n

Making some hardware drivers using the Simulink blocks provided by the support package, meant that we could evaluate the behavior of the car in a matter of minutes. This is done by just clicking the \u201cBuild\u201d button, and from there we could evaluate the actual car\u2019s behavior in a matter of minutes. Check out the video for a detailed explanation of the process and the algorithms.<\/p>\n

[VIDEO]<\/strong>\u00a0MATLAB and Simulink Racing Lounge \u201cRemote Control Racecar, Part 1: Programming ECUs Using Simulink Hardware Suppor<\/a>t\u201c<\/p>\n