Single cylinder engine design and optimization

ESTECO Academy has partnered with Aprilia Racing and Gamma Technologies to sponsor the design and optimization of a single-cylinder, four-stroke, 250cc engine. The aim of this project is to utilize modeFRONTIER and GT-Suite to numerically analize, simulate, and test the ideal race engine.

Background
Grand Prix motorcycle racing is the premier championship of motorcycle road racing, which is divided into three classes: Moto3, Moto2 and MotoGP. Moto3 replaced the 125cc class in 2012 and runs 250cc single-cylinder engines as opposed to the 125cc engines used prior to 2012. Moto GP racing has been the testbed for many different engine technologies including finger follower valvetrains and air valve-springs

Deliverables
The deliverables for the competition include an optimized airbox volume, intake runner, exhaust runner, exhaust pipe length, throttle valve diameter, and valvetrain timing.

Specifications
Displacement: 250cc Cylinder bore = 81 mm  Stroke = 48.5 mm Rev limit 17,500 Conrod length L = 105 mm Inlet Valve Diameter <=34.5 mm (2x) Exhaust Valve Diameter <= 27 mm (2x)  RPM max 17500 1/min Compression Ratio<= 15.8 (compression rate)</li> Valve Cams timing fixed - NOT variable</li> Natural aspiration</li>

Combustion Program (early design development)
We initially used the combustion program created by Jeremy Cuddihy to start early design analysis for the specifications that we were given to us by ESTECO academy. In this way, we were able to calculate the effect of changing the angle of the crank shaft at the start of combustion, shown below:

The combustion code was modified to resemble a crude optimization program so as to take one variable and calculate the max torque over a range of that variable.

Implementation of Dr. Odom's Track Program
The use of Dr. Odom's Track program helped choose what engine parameters to use for our optimization. There were several changes that needed to be made in order to achieve this goal.

The first change: The first change was to model a track similar to one used in moto3 races. The track that we chose to model was the Austrian Grand Pix, seen below. The Austrian Grand Pix has 7 major turns and a lap length of 2.688 miles. While the FinalFormula test track, seen below, has the same number of turns and has a lap length of 2.28 miles.

The second change: The second change was to include fuel consumed by the engine during one lap. To do this we added a a cubic interpolation table with RPM and fuel consumed (lbs/s). We then had TkSolver solve for fuel consumed every 10th of a second using the engine RPM mapped throughout the race course, "fuel_consumed=fuel(engine_rpm)*.1". In this equation fuel is the cubic interpolation table, engine_rpm is the engine RPM mapped during the course, and every number pulled for fuel consumed was multiplied by .1 sec to create a list of fuel used in lbs. The sum of that list is the total fuel consumed. Seen below in the table is a graph of fuel used(lbs) vs. time(sec).

Rendering using Rhinoceros 3D and Flamingo nxt
{| We utilized Rhinoceros 3D and Flamingo nxt to develop photo-realistic renders of an example piston from previous work at the University of Idaho. We created renders of our final piston and connecting rod designs as well as full renders of our final engine design.

Initial Optimization
One of our early goals was to integrate modeFrontier with Matlab, the goal was to use the Combustion program to obtain the optimal values for torque and horsepower. These values allowed us to estimate the maximum forces that our connecting rod would experience.

GT-Suite
The GT-POWER model needed to perform this design process is very similar to the basic single cylinder model provided in the software tutorial. Features such as second intake and exhaust ports were added, and air box components were also created. Constants for things such as the SIWiebe combustion model were obtained from local research. All values of interest were replaced with variables for integration with modeFRONTIER.

Optimization
Final optimization of the GT-POWER model was done with the MOGA-II genetic algorithm in modeFRONTIER. The initial design of experiments was set up using the ISF algorithm in order to ensure uniform distibution of designs. This generated 100 initial designs, and the algorithm was allowed to run for 50 generations generating just over 2000 feasible designs.

Document Archive

 * [[Media:Agenda_-_Final_Formula.pdf]]
 * [[Media:Team_Meeting_Notes_-_Final_Formula_-_Part_1.pdf]]
 * [[Media:Team_Meeting_Notes_-_Final_Formula_-_Part_2.pdf]]
 * [[Media:UIdaho_EstecoPaperSubmission.pdf]]
 * [[Media:UIdaho_EstecoPresentationSubmission.pdf]]