The environmental impact of systems is an issue that has gained importance over the last years. Energy consumption and carbon footprint are terms that have already found their way into legislation. In engineering this is reflected in the new projects that have specific demands on power consumption and energy efficiency. About 80% of the design decisions that influence the power consumption and energy efficiency of a machine are made in the early stages of a design. The rest is made in later stages. Therefore it is very important for engineers to evaluate the energy performance at the very very early stage of the design process. Controllab has created a modeling and simulation program (20-sim) that can help engineers to perform an energy scan in all stages of a design. The program supports modeling with physical components. During simulation, the energy consumption of each component is automatically calculated, allowing engineers to compare different designs on energy consumption.

If you have a project, in which power consumption and energy efficiency are extremely important parameters we can help:

• Energy scan: modeling designs and simulation of the energy consumption
• Alternative designs: finding the optimal design with respect to energy consumption
• Efficiency: predicting the overall efficiency of components
• Carbon Footprint: Translation power consumption into a carbon footprint
• Heat Generation: The heat generation due to energy losses and temperature rise of a machine.

Example

In November 2007 the Solar Team Twente competed for the second time in the World Solar Challenge. This event is held every two years in Australia. The goal is to cover a distance of 3012 kilometers in the shortest time possible with the sun as the only allowable energy source. Determining the optimal speed of the solar vehicle is one of the key factors in winning the race.

Therefore the solar car and its environment have been modeled in 20-sim. The car model consists of components for the electric drives, batteries, solar cells, frame and wheels. All components include energy losses and the efficiency rates were validated using measurement data. The environment model includes the amount of sunshine, direction of the light, track elevation etc. and contains a link to a database to include real-time race parameters.

The model can be used to predict car speed and the battery levels. Using the time domain toolbox of 20-sim, the optimal race strategy can be found: which (variable) car speed will lead to a maximum distance covered per day.