The Technical Side (Advanced) R&D

 

           As shown in the table, there is a significant difference between coasting and power braking in terms of both energy and distance. For the data collected for coasting, the mean braking distance is 1.148 m with a standard deviation of 0.306 m while the distance for power braking was 0.0215 m with a standard deviation of 0.015 m. This data shows that the power braking method uses more energy (33.29 J vs. 25.21 J for coasting), but provides a much more reliable stopping distance. Because the AEV emphasizes efficiency as a major design goal, coasting would be the better option if it could reliably fulfill the MCR objectives. However, upon statistical analysis it appears that the large standard deviation means that roughly 40% of coasting stops will fall outside of the acceptable error margin. This effectively rules out pure coasting as a stop method. However, power braking with 35% power for 1 second has nearly 100% precision, so precise that there is probably room to reduce the power/time of the braking and use a combination of power braking and coasting. Because the required power for braking will vary depending on the speed of the AEV, further testing on this will be carried out while simulating the final run.  

 

     For our advanced R&D, we opted to analyze the energy consumption of the AEV. To do this we analyze the amount of energy used in specific test sections and under different conditions. We apply different loads and compare the results to a baseline of constant acceleration and coasting for an equal amount of time. This is the perfect way to connect our first advanced R&D research project with our second, analyzing the coasting versus power braking of the AEV design. We are also going to test servo braking in the near future and compare the energy consumption to both our power braking, coasting, and servo braking graphs. After this analysis, we should have a good idea as to which method of braking is going to be the most energy efficient for our purposes and the AEV design will be changed accordingly.

Since the marksError in our AEV system was 2 marks, our wheel counter system could have not properly functioned while testing our AEV. To fix the problem, the old wheel sensor reflectors were removed and replaced with the new reflectors. This markError could have been due to the frictional forces acting against the propulsion of the AEV. Thus our actual distance traveled would fall short of our expected and calculated theoretical distance. Even though the frictional forces on the AEV body at these speeds are low, they must still be accounted for. As the velocity of the AEV increases from zero, the drag force acting against the propulsion increases as well.

Drag Force = (1/2) * Coefficient * Density * (Velocity) ^2 * Reference Area.

Coasting

reverse(4);  //reverse all motors
motorSpeed(4,35); //run motors at 35% power for 3 seconds
goFor(3);
brake(4); //stop motors

Power Braking

reverse(4); //reverse all motors
motorSpeed(4,35);//run motors at 35% power for 3 seconds
goFor(3);
reverse(4); //reverse all motors
motorSpeed(4,35);//run motors at 35% power for 1 second
goFor(1);
brake(4);//stop motors

Energy Analysis

reverse(4); //reverse all motors
motorSpeed(4,30); //run motors at 30% power for 4 seconds
goFor(4);
motorSpeed(4,0); //stop all motors and continue collecting data for 10 seconds
goFor(10);