Modern DC power systems consist of a large number of power electronic converters and associated
equipment. On a ship, this power system is typically divided into two identical parts on the port and
starboard sides. These duplicated power systems are often isolated from each other to prevent a fault on one side from propagating to the other side and affecting the entire system, avoiding a total blackout on the ship. A major drawback of this two-split configuration, though, is that it is impossible to share power between both sides, reducing the functionality of the system. Therefore, to connect both sides while maintaining the safety of an isolated system, a solid-state circuit breaker (SSCB) can be used, which is reusable, unlike a fuse, and is able to interrupt the current much faster than a standard mechanical circuit breaker. However, due to the relative novelty of this component, the impact of mission profile variation and electrical disturbance on the SSCB lifetime is unknown.

To obtain the SSCB lifetime, mission profile analysis was performed, resulting in a lifetime as a consequence of wear-out failure mechanisms due to thermomechanical fatigue that would be used as the base case. Based on the mission profile, an SSCB model was designed following considerations for: Current interrupter topology, rated voltage/current of the components, peak voltage/current of the components, voltage clamping circuit, and the cooling. After choosing suitable components, their junction temperature profiles were obtained via iterative calculations with the power loss and the junction temperature using a Cauer model without thermal capacitance. With the rainflow counting algorithm, information regarding the cycle count, temperature swing, mean temperature, minimum temperature and the power-on-time per class was obtained. These were used in the CIPS with correction lifetime model, which obtained the cycle-to-failure of each relevant component. Transforming them into a reliability curve per component and multiplying them together resulted in the reliability curve of the SSCB. To estimate the impact on the lifetime of the electrical noise through the SSCB in comparison to the mission profile, a dynamic model was designed to take thermal capacitance into account, unlike the iterative model.

To quantify the impact of different stressors on the SSCB lifetime, changes in the mission profile, SSCB configuration and operational parameters compared to the base case are made. It was seen that the charging current, corresponding to changes in the maximum stress within the mission profile, has the most significant impact on the SSCB lifetime, while having a relatively minor drawback of a varying charging period. Bi-directional charging and changes in the coolant temperature were shown to have a relatively low impact on the lifetime. Load sharing between parallel components in a module significantly increased the lifetime, but at a cost of practically investing in a second SSCB. Concerning the impact of noise on SSCB lifetime with respect to the damage done by the mission profile, it can be concluded that high-frequency noise, such as the common-mode and differential-mode noise, has a negligible effect on the lifetime of the SSCB when solely focusing on wear-out mechanisms due to thermomechanical fatigue.

Purpose
The main purpose of this report is to find out whether the OpenBCI "Ultracortex Mark IV" Electroencephalogram (EEG) headset is capable of differentiating EEG-signals of motor execution from neutral state with recorded data and to find out whether it can differ motor executions between left and right hand. Next to that, it is to be determined whether the OpenBCI headset was the optimal one for this purpose.

Method
First, the specifications of different headsets were compared. Afterwards, a montage of the electrodes was designed to detect motor execution and motor imagery, mainly centered around the locations C3, Cz and C4, on the top of the scalp. The software "Openvibe" was used to extract data from the headset during experiments and to record it in a csv file. A subject was asked to follow a video with a sound cue followed by a visual cue instructing to move either its left hand or right hand.


Result
Merging the left and right hand trial data together, the result is that the headset shows in the alpha band (7-12 Hz) mostly a decrease (ERD) in magnitude around the visual cue, sometimes followed by a bigger increase in magnitude (ERS). Looking at the extremes after the cue, it is seen that mostly the difference in magnitude is around a factor 1.5 compared to the average magnitude of before the visual cue. Splitting the trial data between left and right hand, similar results can be seen, but one hand produces slightly more ERD or ERS than the other hand depending on the position of the electrode on the left or right hemisphere of the brain.

Conclusion
The OpenBCI headset can in fact detect a difference between movement of the hands and the neutral state. Differentiating between the movements of left and right hands seems possible from the results, but the difference in the signal of left and right hand is minimal. It is recommended to repeat the experiment with more trials and different subjects to get a more solid conclusion.