1. 1 Micro Urban Electric Vehicle Phase II - Vehicle Modeling Team Members: Brian Kuhn Steve Komperda Matt Leuschke Project Advisors: Dr. Brian Huggins Mr. Steve Gutschlag Dr. Winfred Anakwa

2. 2 Presentation Outline Project Summary Review of Phase I Design Detailed Project Description Conclusion and Future Work

3. 3 Project Summary Multi-year project Goals –Two passenger electric commuter vehicle –Commercially viable –Charging station including the use of a photovoltaic array Zero carbon emissions –Range of a typical daily commute

4. 4 Presentation Outline Project Summary Review of Phase I Design Detailed Project Description Conclusion and Future Work

5. 5 Review of Phase I Design Goals –Design and implement a prototype electric vehicle test platform for testing with the following specifications: Implement regenerative braking –Research Create drive model –Determine vehicle properties –Select optimal components for test platform Battery DC-Motor Control electronics –Acquire and display data from the motor controller and sensors Analyze and evaluate drive model

6. 6 Phase I Final Design Motor –D&D Separately Excited Model: ES-10E-33 8 HP Continuous 6.7” Diameter 11” Length 56 lbs 7/8” x 2” Shaft 3/16” Keyway

7. 7 Phase I Final Design Controller –Alltrax DCX600 24-48V Battery Input 600 Amp Limit for 2 minutes 30 Amp Field Winding Limit Standby current: < 35mA Drives motor to 17 peak HP 18 kHz Operating Frequency -25 C to 75 C Operating Temperature –95 C shutdown

8. 8 Phase I Final Design Battery –3 - 12 Volt Lead Acid Batteries –44 Ah Capacity –Low Cost

9. 9 Phase I Final Design

10. 10 Presentation Outline Project Summary Review of Phase I Design Detailed Project Description Conclusion and Future Work

11. 11 Problem Statement In order to create a commercially viable commuter vehicle, a computer simulation needed to be developed to optimize the vehicle’s components, reducing cost, increasing performance, and limiting need for future testing.

12. 12 Phase II Goals Modeling –Battery –DC Motor –Controller –Vehicle Dynamics –Loads A/C Lighting Heat Verify and Optimize Model

13. 13 Data Acquisition System Data Acquisition –National Instruments –System Details Chassis Modules –+/- 10 volt differential analog input –+/- 60 volt analog input –Thermal couple input –TTL digital input LABView Full Development System

14. 14 Data Acquisition System

15. 15 Data Acquisition System

16. 16 Simulink© Block Diagram

17. 17 Complete Simulink© Model

18. 18 Controller

19. 19 Controller Testing Parameters Measured –Motor and Controller Temperatures –Armature and Field Measurements Voltages Currents Duty Cycles –Potentiometer Voltage (throttle position) Controller Experiment

20. 20 Controller Testing

21. 21 Controller Testing w/ Dynamometer

22. 22 Controller Model Results Controller accepts armature current feedback Controller model provides accurate PWM signals Increases the accuracy of the model under load

23. 23 Simulink© Controller Model

24. 24 Motor

25. 25 Motor Equations V f = R f i f + L f (di f /dt) V a = R a i a + L a (di a /dt) + E g E g = K v *ω*i f T d = K t *i f *i a = J(dω/dt) + B*ω + T L –B = viscous friction constant [N*m/rad/s] –K v = voltage constant [V/A * rad/s] –K t = K v = torque constant –L a = armature circuit inductance [H] –L f = field circuit inductance [H] –R a = armature circuit resistance [ohms] –R f = field circuit resistance [ohms] –T L = load torque [N*m]

26. 26 Ra Measurements Armature Voltage Armature Current Armature Resistance 0.1510.1500 0.332.20.1500 0.4330.1433 0.6750.1340 0.9380.1163 1.14120.0950 1.24150.0827 1.35180.0750 1.4922.50.0662 1.595250.0638 1.8310.0581 1.9735.40.0556 2.1640.70.0531 2.2500.0440 2.3600.0383 2.65700.0379 2.8800.0350 3900.0333 3.351000.0335 41470.0272 4.21600.0263 Motor Testing Ohm’s Law for R f –R f = V f /I f Used zero field tests to get brush R a LUT

27. 27 Motor Testing Motor Parameters –Transient tests for L a, L f, J –Solved for T C and b Used shunt voltage tests to create LUT’s –Replaces polynomial for K m equation –Increases overall accuracy

28. 28 Simulink© Motor Model

29. 29

30. 30 Motor Results Comparison

31. 31 Vehicle Dynamics

32. 32 Vehicle Dynamics InputsInputs –Motor Torque (N-m) –Passenger mass (kg) – User defined –Grade (degrees) – User defined OutputsOutputs –Net Force Available for Acceleration (N) –Vehicle Velocity (mph)

33. 33 Vehicle Dynamics F = F x – R x – D A – mg*sinΘF = F x – R x – D A – mg*sinΘ  F = Net Force Available for Acceleration  F x = Force Developed by Motor (Wheel Tractive Force)  R x = Rolling Resistance Force  R x = C rr N f  D A = Aerodynamic Drag Force  D A = ½*ρv 2 C d A  mg*sinΘ = Force Due to Grade

34. 34 Vehicle Dynamics ConstantsConstants  Vehicle Mass ≈ 180 kg  Wheel Radius = 0.2032 m  Gear Ratio = 4:1  Coefficient of Rolling Resistance ≈ 0.015  Coefficient of Static Friction ≈ 0.025  Coefficient of Drag (C d ) ≈ 0.5  Area (A) ≈ 0.7 m 2  Density of Air (ρ) ≈ 1.2 kg-m -3  Drive train Efficiency ≈ 80%

35. 35 Vehicle Testing Motor Shaft No Load Vehicle Drive Train

36. 36 Simulink© Vehicle Dynamics Model

37. 37

38. 38 Complete System Results Throttle Position = 50% for 30 seconds Results give a good estimation of vehicle performance.

39. 39 Battery Model

40. 40 Battery Model Simplified lead acid battery discharge model E = E 0 – K*Q/(Q – i t )*i(t) – K*Q/(Q-i t )*i t  E = Battery Voltage (V)  E 0 = Constant voltage (V)  K = Polarization constant (Ah -1 )  i(t) = Battery current (A)  i t = Extracted capacity (Ah)  Q = Maximum battery capacity (Ah)

41. 41 Battery Model

42. 42 Battery Results Preliminary model of the battery. Estimates: –Battery Voltage –Battery Response Behavior –State of Charge –Battery Current

43. 43 Presentation Outline Project Summary Review of Phase I Design Detailed Project Description Conclusion and Future Work

44. 44 Conclusion Accurate Models –Motor –Controller –Controller w/ Loads Theoretical Models –Battery –Vehicle Dynamics

45. 45 Future Work Accurate Battery Model Mount Data Acquisition System on Vehicle –Accurately Measure Vehicle Properties Vehicle Mass Load Force Coefficients –Verify Accuracy of the Complete Model

46. 46 Phase III and Beyond Test Regenerative Braking –Model Regenerative Braking Capabilities Include a Model for Auxiliary Loads and Brake Optimize Components Design Charging Station –Zero Carbon Emissions

47. 47 Special Thanks To: Dr. Anakwa Mr. Gutschlag Dr. Huggins Mr. Mattus

48. 48 References [1] Dieter, Kyle, Spencer Leeds, and Nate Mills. Micro Urban Electric Vehicle & Test Platform. Senior Project. Electrical and Computer Engineering Department, Bradley University. May 2009. [2]M. Knauff, J. Mclaughlin, D. Niebur, P. Singh, H. Kwatny, C. Nwankpa & C. Dafis, Simulink Model of a Lithium-Ion Battery for the Hybrid Power System Testbed. 1 Dec. 2009. [3]G. Moleykutty, "Speed Control of a Separately Excited DC Motor," American J. Applied Sciences, 2008. [Online]. Available: http://scipub.org/fulltext/ajas/ajas53227-233.pdf. [Accessed Dec. 3, 2009]. [4]Egeland, Olav, and Jan Gravdahl. "Modeling and Simulation for Automatic Control." Trondheim, Norway: Marine Cybernetics, 2002. Print. [5]"SimPowerSystems - Battery." MathWorks, Web.. [6]Gillespie, Thomas D. Fundamentals of Vehicle Dynamics. 1st ed. SAE International, 1992. Print.

49. 49 Questions?

50. 50 Appendices

51. 51 Appendices Random Facts –Dynamometer is limited to high speed testing due to its use of a “water brake”. –R a vs. I a relationship is caused by higher current densities causing better connections in the “brush” metal.

52. 52 Appendices K = m + (J m *N 2 +J w )/r w 2  K = effective translational and rotational mass  m = mass  J m = inertia of motor shaft  J w = inertia of wheels and axel  r w = radius of wheels

53. 53