Kite Power System Data Fusion

One of the new promising approaches in “green” energy production is airborne wind energy production, since wind power extracted scales cubically with the height, i.e. generation at high altitudes is of great interest. This means that either the whole system including the generators and power electronics are flying, or only a wing-like structure tethered to the ground is flying. The latter one makes use of the pulling force of the cable to generate power at ground.

The Automatic Control Lab (IfA) is developing a small scale steering unit to autonomously fly a kite tethered on the ground. A first prototype of such a system has been built during the last year and first test results are done. Therefore various improvements and adaption on the hardware and software are needed.

The goal of the project is create a software tool to process and inspect the logged data of test runs with the kite power system.

• Design a kite power data collection tool
• Design a sensor fusion and filter for the kite attitude and velocity

The student(s) should be familiar with programming (Matlab, Python, or C) and experience with filters would be advantageous. She or he should be motivated to code a software tool and apply it to real data collected in field tests.

· Data Collection:
Our kite system collects a large set of heterogeneous data. Not all sensors are logged by the same device and not all have the same sampling rate. Therefore the synchronization and sensor fusion plays a crucial part in evaluating the data. The goal of this project is to enhance the existing data collecting and processing framework and additionally implementing some filter algorithm to extract good state trajectories and attenuate the noise present on the signals. A first task would be to improve the current data collection system which extracts corresponding data logs from all different files which belong to one test run. Once these files are identified it should create a new log file with all the data in it while making sure that the time information of each sensor does not get lost.

· Sensor Fusion and Filtering:
From the log files created in the first task the data should be filtered to extract the kite trajectories. The filter should be capable of dealing with multi rate sensor signals and incorporate a simple kite model. It should also feature switches to fuse different sensor setups. This means not all IMU’s we are going to use have the same sensors with the same noise and accuracy specification and also the kite ground unit can provide some measurements for the kite which might not be available every time. Most IMU's do already have such an algorithm for their sensors but it cannot use the additional sensor information such as the line angles nor can it know what system it is mounted on. This additional knowledge can be used in the design of such a filter software and improve the trajectory estimates.

Besides the hardware and software work a detailed documentation and project report has to be written.
This project could also be done as a Group Project.