Lab 7 introduced the MatLab app AEV Design Analysis Tool, which is used to generate graphical representations of the efficiency of the AEV. These graphs demonstrate the variations in efficiency in a quantitative way.
Alex Tetzloff
In Lab 7 (Design Analysis Tools), the engineering team worked on analyzing the data recorded during the AEV’s trial run.The team learned how to upload wind tunnel and Arduino data into the MATLAB analysis tool. The team also learned how to do performance analysis and how to export plots for use in lab reports. The purpose of this lab was to become familiar with the MATLAB data analysis tool and use the data to improve the performance of the AEV.
In Figure 1, the graph trends represent the different commands in the Arduino code in a Power vs. Distance plot. It shows that the AEV’s motors are running at a fairly constant rate (6-7 Watts) until the AEV travels about 3.5 meters. This beginning part of the plot represents the Arduino commands that get the AEV travelling at a constant rate until it reaches a point close to its destination. Once power starts to drop, it plateaus at 4 Watts until the AEV has traveled around 5 meters total. At this point, the AEV cuts off all power instantly. This coincides with the AEV stopping at the end of the track as it reaches it destination. In Figure 2, the graph trends represents the Arduino commands that the AEV follows in a Power vs. Time graph. The AEV starts out gradually using more power until the 2 seconds mark where it plateaus and starts running at a somewhat steady rate ranging from 6 to 7 Watts. Once the AEV had traveled for 11 seconds, the speed drops, plateaus again and then stops completely just like the plot in Figure 2.
Each team member agrees upon varying responsibilities for the completion of the AEV project. These responsibility assignments were based on each member’s area of expertise/interest. My role in the team is to make sure that the AEV is functioning properly and that its data is useful. If something goes wrong with the AEV, I am in charge of troubleshooting and figuring out how to get the AEV performing at its best. Earlier in the class, I worked with team member J.P. Salopek on the Arduino code and also assisted in the design process for the AEV. The team’s final design was partly based on the design I created combined with team member Jeff Horowitz’s design. I am also in charge of filming and directing the team’s AEV video. I will do my best to create a video that accurately represents the AEV and all of the work the entire team has put into the design.
This lab was very important as it gave the team experience in data analysis and the use of the MATLAB data analysis tool. The team used this information to determine how the AEV would run in an official test and how to properly analyze test results. The team also agreed on various roles for each other and these roles reflected the areas that the team members would be best suited to work in. The knowledge gained in this lab, like all of the previous labs, will assist the team with completing the AEV project.
Appendix:
Figure 1: Power vs. Distance
Figure 2: Power vs. Time
References:
“AEV Lab Manual.” Retrieved from https://eedcourses.engineering.osu.edu/sites/eedcourses.engineering.osu.edu/files/uploads/1182/AEVLab/AEVDocuments/LabManual/AEV_Lab_Manual_Rev_2015_08_07.pdf
Dan Heavern
The Design Analysis Tool Lab consisted of the group using a MatLab application, called the Design Analysis Tool, to track the power usage and track the power versus distance graphs of various AEV designs. The purpose of this lab was to get data on the power usage over time and view the power versus distance graphs as a way to compare the different potential AEV designs. Data was retrieved from the AEV after tests were run using a simple Arduino code. This data was automatically graphed and could then be interpreted.
In figure 1, it is seen that power increases at a constant rate at the start of the test, stays relatively constant, decreases late in the test and stays at a constant, lower power briefly, then decreases to zero at the end of the test. These phases of the graph correspond to different parts of the test. The initial increase shown on the graph corresponds with the initial acceleration of the AEV from rest. During the longest phase of the graph, where power is relatively constant, the AEV travels forward at a constant speed. In order to stop, the direction of the motor was reversed and ran at a lower power, shown by the constant, lower speed section of the graph in figure 1. Then, power to the motors is cut and this is shown in the last portion of the graph. In figure 2, it is seen that power is already at a constant by the time the AEV started to move. This is an important observation, because the power versus distance graph only shows changes in power while the AEV is in motion rather than over constant time intervals. This gives an idea of how the changes in power often occur while the AEV is stationary, as is the case in the initial acceleration and in the final deceleration. These sections are shown as vertical lines in figure 2.
In completing the AEV project, the group must attribute roles to its members for tasks including programming, design, documentation, data analysis, and video production. In the case of Group I, Dan Heavern will contribute to the programming, in addition to analyzing performance tests. J.P. will be the project lead and the lead programmer. Jeffrey Horowitz will head the design of the AEV, and Alex Tetzloff will contribute in various miscellaneous ways throughout the project. The group will work together to keep proper documentation throughout the project and will work together to create a team video.
This lab furthered understanding of data analysis within the group, as well as led to key insights in AEV performance. The group also gained experience uploading data from the AEV and interpreting the data gathered and exporting graphs made from that data.
Appendix:
Figure 1: Time vs. Power
Figure 2: Distance vs. Power
References:
- “AEV Lab Manual.” Retrieved from https://eedcourses.engineering.osu.edu/sites/eedcourses.engineering.osu.edu/files/uploads/1182/AEVLab/AEVDocuments/LabManual/AEV_Lab_Manual_Rev_2015_08_07.pdf
Jeffrey Horowitz
In this lab, the team analyzed data from trials run of the AEV. The team learned how to use a design analysis tool in a MATLAB Graphical User Interface. This GUI downloaded the data from the AEV test trial, performed calculations and plotted results. The arduino data could be easily interpreted from the graphs produced in the program. The team will use this gathered data in order to increase the performance of the AEV.
Assigned activities for the team members include programming, AEV design and completing production of the video. Programming is essential, as trials are constantly run to troubleshoot issues with the performance of the AEV on the track. The performance of the AEV due to the programing is directly tied to its design. The design is constantly adjusted in order to offer the best possible balance and structural integrity. With optimal balance, the code can be adjusted in the best way possible for the success of the AEV in its mission. The data acquired from the graphing program assists the team in what ways the programming can be adjusted. Completing the video is another goal of the team. Though much of the filming can be accomplished during test trials in the lab, the video must be edited and completed out of class. The whole team will lend a hand in the creation of the video.
Throughout the course of this lab, the team used a graphing program in order to analyze data collected from the arduino. The graphing program plotted the results to make it easier for the team to understand the data. The team will use this data in order to make the AEV perform better.
Appendix:
Figure 1: Power vs. Distance
Figure 2: Power vs. TIme
References
- “AEV Lab Manual.” Retrieved from https://eedcourses.engineering.osu.edu/sites/eedcourses.engineering.osu.edu/files/uploads/1182/AEVLab/AEVDocuments/LabManual/AEV_Lab_Manual_Rev_2015_08_07.pdf
JP Salopek
In the Design Analysis Tool Lab (Lab 7), the group worked together when using a MATLAB Graphical User Interface. This tool was used to download arduino data, compute performance analysis calculations, plot results, and much more. The purpose of this lab was to effectively use this tool to upload data and then to use this data to efficiently measure and graph the AEV’s performance quickly and easily. This lab is important because it gives the team insight from the test run and gives the group a chance to makes necessary changes to the AEV’s design to improve its performance and energy consumption.
In Figure 1, the group can infer what commands the arduino is undergoing based on the energy levels and duration of time. For example, the flat lines in Figure 1 are motorSpeed command. The shorter the line the shorter the duration of the command, and the higher the energy level the faster the speed of the AEV. In Figure 2, the AEV seems to not undergo the celerate command (diagonal line on Figure 1). This is because it does not move at all during this time and the power is only plotted when the AEV moves a distance. Thus, the graph only starts to be plotted once it hits the motorSpeed command. This means that there is no way to know the power being used by the AEV on a distance vs. power graph unless the AEV is moving, yet you still do not know the specific time. Otherwise, Figure 1 and Figure 2 are pretty similar to each other for our plotted run.
There are several responsibilities that need to be completed in order to complete the AEV project. These responsibilities include programming, analyzing performances in test runs, perfecting the AEV design, miscellaneous tasks, and creating the AEV video. Dan Heavern will be responsible for analyzing performances in test runs and helping with programming when needed. Jeff Horowitz will be responsible for perfecting the AEV design. Alex Tetzloff will be responsible for miscellaneous tasks and helping the group where extra assistance is needed. I will be responsible for the programming and leading the group. Also, I will inform the team what is required on assignments and what the AEV must be able to do. The group as a whole will complete the video project on the AEV to the best of our ability.
This lab gave the group some ultimate knowledge in a few areas. First, the group was able to become familar with MATLAB based analysis tool. Second, The group learned how to successfully upload the arduino data to the tool. Third, the team learned how to conduct a performance test on the AEV based on energy, time, and distance. Lastly, the group successfully exported the figures to the report. All of the ultimate knowledge that was learned was in accordance with lab objectives and therefore the lab was a success.
Appendix:
Figure 1: Time vs. Power
Figure 2: Distance vs. Power
References:
“AEV Lab Manual.” Retrieved from https://eedcourses.engineering.osu.edu/sites/eedcourses.engineering.osu.edu/files/uploads/1182/AEVLab/AEVDocuments/LabManual/AEV_Lab_Manual_Rev_2015_08_07.pdf