Preliminary Design Review Report
Abstract
The purpose of the lab was to choose an Advanced Energy Vehicle (AEV) design that can complete all the Mission Concept Review (MCR) requirements with best energy efficiency. The mission required a green and effective method of entering the Jurassic Park and picking up the dinosaurs’ cargo back to the Visitor’s Center. In order to complete the requirements, the AEV need to be able to stop right at the entrance to open the gate, attach the cargo with proper speed, and stop right at the Visitor’s Center.
To approach the requirement, four designs were created by the group. The four designs were compared by their balance, minimum blockage, center-of-gravity location, maintenance, cost and durability. After concept screening and scoring, the group chose Design-2 and Design-4 from 4 original designs to continue the test.
Figure 1 Figure 2
The two designs were both tested with same Arduino program code and same propeller with pusher configuration. In this case, only one wind tunnel testing was made and the results were easily comparable. Since the program and the propeller were the same, the propulsion efficiency and power versus time graph are so similar. However, there was a slightly different between the overall energy usages.
After the comparing of energy efficiency and consistency, Design-4 was selected to be used in the final stage of the project because of the less energy usage. The group believed that the Design-4 can be improved by various methods.
Introduction
In this lab, the purpose was to choose an Advanced Energy Vehicle (AEV) design that can complete all the Mission Concept Review (MCR) requirements with best energy efficiency.
At first, the group created 4 plans of developing AEV. The four designs were compared by their balance, minimum blockage, center-of-gravity location, maintenance, cost and durability. After using the method of concept screening and concept scoring, the group finally chose two of the designs to test.
The two designs which were decided to develop in lab 3 are Design-2 and Design-4. Design-2 used the rectangle baseplate and T-shape arm as primary frame. The design used trapezoid wings and 3-inch propeller in order to reduce the air resistance and increase the thrust. Compared with Design-4, Design-2 is better in aerodynamic but short in balance.
Design-4 used the rectangle plate vertically to keep the center of mass along the hanger. In this case, the design is better in balance but short in aerodynamic.
Although the two designs were quite different in shape, the costs of the two designs were the same. Both of the designs’ cost was 168.34 dollars. Since all of the parts on the designs were essential parts and irreplaceable. The cost of the two designs cannot be reduced.
Then the two designs were going to be tested with same Arduino program code and same propeller with pusher configuration in this lab. In this case, only one wind tunnel testing was made and the results were easily comparable.
Experimental Methodology
In order to compare the two designs on the track, the group did the following steps;
First, ran the wind tunnel testing and find the best propeller input power when using EP-3030 propeller at pusher configuration;
(Figure 3. Wind Tunnel Equipment.)
Second, developed the code allowed the AEV set off from the Visitor’s Center and stop at the entrance with the Arduino;
Third, assembled the two designs with the same propeller and configuration and ran them on the track;
Last, downloaded the data from the AEV after each testing and analyzed the data with AEV Analysis Tool on MATLAB.
Results
Both of the designs used same testing code (see Appendix Code), and same propeller EP-3030 with pusher configuration. The wind tunnel testing of the EP-3030 with pusher configuration was made and an Energy Efficiency vs. Advance Ratio Graph was plotted as following.
(Figure 7. Energy Efficiency vs. Advance Ratio Graph.)
The group found the relationship between the Advanced Ratio and Energy Efficiency can be expressed by the equation:
η(J) = -306.9773 * J3 + 177.4551 * J2 – 3.2548 * J + 6.9595
From the graph, the group found that the highest Efficiency was about 14.5% with advance ratio of 0.37.After calculation, the group found that the most efficient input voltage was 1.9V, which is about 26% of the battery voltage.
In order to keep best energy efficiency, the Arduino code commanded the AEV accelerated at the power of 26% and kept moving at this power until reach mark 168. Then the AEV decelerated at the power of 30% for 2 seconds and stopped at the gate sensor. During the testing, both of the AEV designs accomplished the requirements after several times of adjustment. Efficiency and Power vs. Time Graphs were plotted based on the testing results.
Figure 8. Design-2 Efficiency & Power vs. Time Graph
From the above results of the testing, the group found that Efficiency and Power vs. Time graphs were similar between the two designs. The similarity of the graphs was expected, because the program and the propeller were the same, and the mass of the two designs were nearly the same.
The table of the Supplied Energy and Total Energy was made in order to give final analyzing.
Table 1. The table of the Supplied Energy and Total Energy.
| Code | Activity | Supplied Energy (D-2) | Supplied Energy (D-4) |
| brake(4);goFor(1); | Stop at Visitor’s Center for 1s. | 0.0886J | 0.0874J |
| celerate(4,0,26,1); | Accelerate the AEV from stop to 26% power in 1s. | 2.7328J | 2.2903J |
| motorSpeed(4,26);goToAbsolutePosition(168); | Keep all the motor speed at 26% until reach mark 168. | 54.1463J | 52.8873J |
| reverse(4);motorSpeed(4,30);goFor(2); | Change the direction of all the motor and run for 2s at the speed of 30% | 68.0070J | 61.3421J |
| brake(4); | Stop the engine. | 68.0070J | 61.3421J |
| Total Energy Consumption | 68.0070J | 61.3421J | |
From the table above, the group found that there’s a little difference between the total energy consumption. Based on the Figure 8&9, the group thought the difference was directly caused by the different running time of the AEV.
Discussion
After considering about balance, minimum blockage, center-of-gravity location, maintenance, cost and durability, the group chose two designs from 4 original designs by using Concept Screening and Scoring Method.
Table 2. Concept Screening Matrix.
Table 3. Concept Scoring Matrix.
The two designs which were selected in lab 3 are Design-2 and Design-4. Design-2 used the rectangle baseplate and T-shape arm as primary frame. The design used trapezoid wings and 3-inch propeller in order to reduce the air resistance and increase the thrust. From the tables above, Design-2 is better in aerodynamic but short in balance compared with Design-4.
Design-4 used the rectangle plate vertically to keep the center of mass along the hanger. In this case, the design is better in balance but short in aerodynamics.
The result of the test running showed Efficiency and Power vs. Time graphs were similar between the two designs. However, there was a slightly different between the overall energy usages.
The similarity of the graphs was expected, because the program and the propeller were the same, and the mass of the two designs were nearly the same. However, the difference between the total energy usages was unexpected. The group assumed that the Design-4 might cost more energy because of the less aerodynamic shape before the testing. While the testing result shows that the Although Design-4 used less energy than Design-2. After discussion, the group indicated that this was caused by the unbalanced design of the Design-2. The unbalance design increased the normal force on the back wheel and increased the resistance force between the track and arm, especially when passing through the joints on the track.
Conclusion & Recommendations
In order to choose a better energy efficiency AEV designs from two prototypes. The group used the wind tunnel testing to find the best propeller input power; developed the code to test two prototypes on track; and analyzed the data with Matlab. By comparing the energy efficiency vs. time graphs and the total energy consumption, the group finally decided to choose Design-4 as the final AEV design.
During the testing, the group fixed the error recognition of aerodynamic design of the AEV. Based on the above testing result, the group figured out that under such a low speed situation, the air resistance on the AEV can be ignored. In this case, the aerodynamic shape of the AEV was far less important than balance and smooth movement on track.
In this case the Design-4 cannot be improved by installing aerodynamic cover. However, there are still various methods to improve the performance.
In the following labs, the group is going to improve the AEV energy efficiency performance by developing efficient code, reducing the weight, or changing better propeller.
Appendix
Table 4. The Performance Testing Schedule.
| Task | Start Date | Group Member | Work | Status(Percentage) | Due date | Estimate Time(min) |
| PT2:Coding and Adjustment | Nov.7th2014 | Meng | Write and adjust the code. | 30% | Nov.14th2014 | 45 |
| Collect and analyze the date. | 0% | 40 | ||||
| Yuhan | Write the draft of the memo | 20% | 30 | |||
| Fd | Finish the memo. | 0% | 30 | |||
| Update the progress on the website. | 0% | 10 | ||||
| Wilson | Assembling | Done | 10 | |||
| Testing | 0% | 5 | ||||
| PT3:Simulation Test | Nov.14th2014 | Meng | Final adjustment to the code | 0% | Nov.21st2014 | 20 |
| Collect and analyze the date. | 0% | 40 | ||||
| Write the draft of the report. | 0% | 60 | ||||
| Yuhan | Write PT3 TRR. | 0% | 40 | |||
| Fd | Finish the lab report. | 0% | 45 | |||
| Wilson | Update the lab progress on the website. | 0% | 10 |
Figure 10. The SolidWorks model of Design – 2.
Scale: 1:2 Estimate Weight: 0.2596kg Estimate Cost: $168.34
Figure 11. The SolidWorks model of Design – 4.
Scale: 1:4 Estimate Weight: 0.2571kg Estimate Cost: $168.34