Single cylinder engine design and optimization

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Sponsors [ESTECO Academy, Aprilia Racing, Gamma Technologies]
Team Name Final Formula
Duration Fall 2016 - Spring 2017
Faculty Advisors
Students
  • Brian Remsen
  • David Pick II
  • William Duncan
  • Dylan Johann

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.

Problem Definition[edit]

Background[edit]

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[edit]

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

Specifications[edit]

  • 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)
  • Valve Cams timing fixed - NOT variable
  • Natural aspiration

  • Project Learning[edit]

    Combustion Program (early design development)[edit]

    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:

    Crank Angle (Degrees) Max Torque (ft*lb) Max Power (HP)
    160 16.36 54.51
    170 17.16 57.19
    175 17.09 56.96

    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.

    Graph Description
    Torquevstheta0FF.JPG
    Crankshaft angle at beginning of combustion


    Implementation of Dr. Odom's Track Program[edit]

    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[edit]

    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.
    Photo Overview
    Piston render take 1 - rhino.jpg
    Initial Rendering Attempt
    • An in-house piston model from a yz-250 engine was modified and rendered for the initial testing of Rhino. This was part of an engine redesign project that helped inform the engine modifications for the Formula Hybrid car. The piston was modified to represent a four-valve engine, as per our design specifications. Texture applications, lighting adjustments, and color adjustments were utilized to improve the render realism.
    valign = "center" align = "center" Final Engine Render for PowerPoint Submission
    • The final render was created utilizing the Flamingo NXT plugin for Rhinoceros. Realism was improved through the use of Flamingo material textures and rendering inside a box. The final product has improved realism, detail and is a showcase of our solid modeling program here at the University of Idaho.


    Initial Optimization[edit]

    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.


    Photo Overview
    Combust program-mf.PNG
    modeFRONTIER Combustion Integration
    • Here is an screenshot of the interface used to tie modeFRONTIER into the combustion program written in Matlab.
    valign = "center" align = "center" Running Combustion Program
    • The combustion program does not account for many of the variables that would be present in an functioning engine, however it gives us a good estimate of peak power under optimal circumstances and gave us a good basis for the integration of the GT-Suite model This optimization varied the Exhaust valve opening event, RPM, and Ignition timing.
    Combustion-tqvsrpm.PNG
    Combustion Program Torque Curve
    • Shown is the torque curve generated in ModeFrontier using the Combustion program in matlab. Our optimal peak power with the given specifications was 18.3ftlb of torque.






    Final Product[edit]

    Track[edit]

    Photo Overview


    TrackFF.png
    TKSolver Layout
    • Shown is the X-Y plot of the TKSolver track layout.
    AustrianFF.png
    Comparison
    • To the left is the Austrian Grand Prix. Similar engines are raced on this track as part of Moto3.
    TableFF.png
    Comparison
    • To the left is a table showing the comparison of the Austrian Grand Prix and the TKSolver program. The intention was to model as closely as possible to the Austrian Grand Prix for comparison to actual data.

    Valvetrain[edit]

    Photo Overview



    Intcam8.8.PNG
    Intake Cam and Valvetrain
    • Shown is the 2D model created in VT-DESIGN for the intake camshaft.
    Cam profile.PNG
    Camshaft Profile
    • The base radius was sized to minimize concavity and contact stress while also minimizing mass of the valvetrain. A polynomial lobe profile was chosen for the VT-DESIGN model due to the need to generate a complete lift profile and the simplicity allowed by a reduced number of user input variables
    Valve velocity.PNG
    Valve Velocity
    • The ramp velocities were minimized to ensure follower contact and minimal stresses in the valve and seat at high RPM operation.
    Valve piston clearance.PNG
    Valve Piston Clearance
    • A full interference design was chosen to maximize the compression ration and the valve-piston interference was calculated.
    Finger follower design.PNG
    Roller Finger Follower Design
    • A GTM file was created and prepared to integrate into the full GT-Suite model, however, time constraints did not allow this to be completed. If completed, it would have allowed a full analysis of the valvetrain friction and a quasi-dynamic analysis of the valvetrain forces.



    GT-Suite[edit]

    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.

    Photo Overview
    GTModel.png
    GT-POWER Final Model
    • The 1D simulation of our engine as shown in GT-POWER.
    Torque and Power.png
    Sample Engine Torque and Power Outputs
    BSFC.png
    Sample Engine BSFC



    Optimization[edit]

    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.

    Photo Overview
    Workflow.png
    Integrated Model
    • Here is the final workflow for the combined engine and track models in modeFRONTIER.
    ParetoDesigns.png
    Pareto Designs
    • The designs highlighted in red represent the best in terms of trade off between lap time and fuel consumption
    FinalDesigns.png
    Selected Designs
    • From the designs above three were selected using a linear multi-criteria decision-making model by changing the weights on the desired output variables. Case 2 is a likely design that would be selected for production.



    Team Members[edit]

    Picture Bio Discipline
    William Duncan.jpg
    William Duncan:

    William is a senior in Mechanical Engineering and is graduating in the Spring of 2017. He recently began a carreer as an Associate Manufacturing Engineer at Schweitzer Engineering Laboratories. His hobbies include vehicle restoration, motorcycling, mountain biking, and hiking.

    ME
    Finalformula brian.jpg
    Brian Remsen:

    Brian is a senior in Mechanical Engineering and is graduating in the Spring of 2017. He currently works in the Kibbie Dome as the Operations Coordinator while pursuing his degree. His hobbies include engine building, motorcycling, hunting, and fishing.

    ME
    Picture for capstone.png
    David Pick II:

    David is a senior in Mechanical Engineering and is graduating in the Spring of 2017. He currently involved in mentoring for ME 301 and ME 123 as well as being a section leader for the tenor saxophones in the Vandal Marching Band. His hobbies include hunting, fishing, marching band, jazz band, CAD work, hiking, and woodworking.

    ME
    Dylan Johann:

    Dylan is a senior in Mechanical Engineering and is graduating in the Fall of 2017. He has worked at Vintage Restoration Services Inc. the past three years, and is currently seeking an internship for this summer. His hobbies include motorcycling, hiking, mountain biking, and photography.

    ME

    Document Archive[edit]