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Software extends hardware-in-the-loop real-time simulation

Somewhat similar to automotive development, in the space industry the design, building and testing of planetary rover prototypes is extremely expensive, and system testing typically does not occur until late in the design/testing process—leading to a long, protracted development time. In response to such timing issues, Amir Khajepour, Canada Research Chair in Mechatronic Vehicle Systems and engineering professor in the Mechanical and Mechatronics Engineering department at the University of Waterloo (Canada), and his team worked with the Canadian Space Agency (CSA) and Maplesoft, to develop a hardware-in-the-loop (HIL) test platform for solar-powered planetary rovers.


The CSA has a strong history of applying symbolic techniques in space robotics modeling—having used these techniques in the design of various space robotic systems deployed on the U.S. Space Shuttle and the International Space Station. This new HIL initiative uses MapleSim, the latest generation of Maplesoft's symbolic modeling technology, to rapidly develop high fidelity, multi-domain models of the rover subsystems.

The team's approach allows component testing within a simulation loop before a full rover prototype is available, essentially creating a virtual testing environment for the component under test by “tricking” it into thinking it is operating within a full prototype. Using the MapleSim  modeling and simulation tool, high fidelity and computationally efficient models were created for this real-time application.

With this test platform, scenarios that are hard to replicate in a lab setup (such as the Martian environment) or components that are not yet available, can be modeled while hardware components that are available can communicate with these software models for real-time simulations. The goal is to progressively add hardware components to the simulation loop as they become available. In this way, system testing takes place even without all the hardware components, bridging the gap between the design and testing phases.

The main advantage of this approach is that it significantly reduces the overall project development time. In addition, this method allows for component testing under dangerous scenarios without the risk of damaging a full rover prototype.

Rover kinematics
Besides simulating the rover dynamics, the MapleSim modeling environment was used to automatically generate the kinematic equations of the rover.


These equations then formed the basis for other tasks in the project such as HIL simulations, rover exploration-path planning, and power optimization. The modular system setup also enables users to quickly change the rover configuration and explore different approaches in a short time.

Hardware-in-the-loop framework
The figure below shows an overview of the test platform. Information regarding the rover’s position, orientation, tilt, speed, and power consumption (obtained from dynamic models of the rover) is used as input to the software models. A library of rover components was developed within MapleSim and imported within LabView Real-Time where the HIL program and GUI of the simulations were developed. The program was then uploaded to the embedded computer within National Instruments PXI, where communication between the hardware components and the software models was established and the real-time simulation run.


“Due to the multidomain nature of the system (mechanical, electrical and thermal), it was desirable to model all the components within one modeling environment such that critical relationships can be easily discovered. In addition, computational efficiency is crucial in real-time simulations,” said Khajepour. He added, MapleSim was found to be an excellant environment for the application because of its multidomain abilities, use of symbolic simplification for higher computational efficiency, and ease of connectivity to LabVIEW.”

Development of custom components and power management
In addition to making use of MapleSim’s built-in component library, custom components were also readily developed. A model to estimate the solar radiation that a tilted surface (i.e. solar panels) would receive on Mars was implemented using MapleSim’s Custom Component Block. This model took into account the sun’s position, the rover’s latitudinal and longitudinal position as well as orientation and tilt as it traveled from point A to point B. This was used together with a solar array model (see figure below) to estimate the power generation of a rover throughout the day.


“The intuitive nature of MapleSim allowed my team to create high fidelity models in a short period of time,” said Khajepour. “This played a key role in the success of this modular HIL test platform which allowed for component testing, power level estimation, as well as the validation of power management and path planning algorithms.”

The team also used MapleSim as a tool in an earlier part of the project to develop the power management system of the autonomous rovers. They used the software to rapidly develop high-fidelity, multidomain models of the rover subsystems. The goal was to develop a path planning algorithm that took rover power demands (and generation) into account. Using the models developed, the path planner determined the optimum path between point A and point B, such that the rover maintained the highest level of internal energy storage—while avoiding obstacles and high risk sections of the terrain.

Step one of this three-year project was to develop the initial rover model, including such aspects as battery, solar power-generation, and terrain and soil conditions. Including a full range of HIL testing phases with real-time hardware and software using system models was critical for optimizing system parameters that maximized power conservation while still achieving mission goals.

“With the use of MapleSim, the base model of the rover was developed in a month,” says Khajepour. “We now have the mathematical model of the 6-wheeled rover without writing down a single equation. MapleSim was able to generate an optimum set of equations for the rover system automatically, which is essential in the optimization phase.” The symbolic techniques that lie at the heart of the software generate efficient system equations, without loss of fidelity—thus eliminating the need to simplify the model manually to reduce its computational complexity.

GUI
Khajepour also noted the graphical interface. In MapleSim, a design engineer can readily re-create the system diagram on his/her screen using components that represent the physical model. The resulting system diagram looks very similar to what an engineer might draw by hand. MapleSim can then easily transform the models into realistic animations. These animations make it substantially easier to validate the system diagram and give greater insight into the system behavior.

“The ability to see the model, to see the moving parts, is very important to a model developer,” says Khajepour. “I am now moving to MapleSim in most of my projects.”


Additional material:
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This story appeared first on Automotive Designline courtesy of EE Times USA

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