1 / 17

GPS-based Optimization of PHEV Power Demands in a Cold Weather City

GPS-based Optimization of PHEV Power Demands in a Cold Weather City. Ryan Smith; Matthew Morison; David Capelle ; Caleigh Christie ; Danny Blair, Ph.D. University of Winnipeg’s Department of Geography. Introduction. What is a PHEV?. http://www.eeh.ee.ethz.ch/. Introduction.

emmet
Download Presentation

GPS-based Optimization of PHEV Power Demands in a Cold Weather City

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. GPS-based Optimization of PHEV Power Demands in a Cold Weather City Ryan Smith; Matthew Morison; David Capelle; Caleigh Christie; Danny Blair, Ph.D. University of Winnipeg’s Department of Geography

  2. Introduction What is a PHEV? http://www.eeh.ee.ethz.ch/

  3. Introduction How do you design a PHEV? • Power Requirements depend onDistance, Speed, Acceleration and Duration • Time available for Battery Recharging • Opportunity (daytime) charging • At-home (evening) charging

  4. Purpose • Modeling power demands of PHEVs under a variety of temperature and recharging scenarios to understand the environmental and economic benefits of PHEV use • Using a duty cycle previously created from a real-time GPS-based dataset collected by the University of Winnipeg’s AUTO21 research team (Smith et al., 2011)

  5. Vehicle Power Demand – the Duty Cycle • A representative, 24-hour profile • Duty Cycles indicate: • Typical speed and acceleration demands • Hours of the day vehicle is in operation • Number of Trips / Day • Time available for Recharging • Derived: Multiple vehicles, thousands of trips over long periods of time

  6. Participants • Seventy-six volunteer drivers collecting GPS data while driving, from Winnipeg & nearby communities. • One year period • Recruitment: • Local media • Word-of mouth • Sample bias towards higher-income households… a good thing?

  7. Equipment • 76 GPS receivers (Otto Driving Companion) • Store 300 hours of data @ one-second intervals • Plug-in to vehicle lighter socket • Transfer data to PC via USB cable • Accuracy: • Position: 10 metres • Speed: 1 km/h myottomate.com/checkoutotto.asp

  8. WPG03 Duty Cycle

  9. Modeling PHEV Power Demands • 3 different types of PHEVs • 4 temperatures • 2 charging scenarios

  10. Governing Equations WPG03 Varied Inputs

  11. Go to… Power Demand Model

  12. Results

  13. Cost Comparison for Overnight Charging Only

  14. Cost Comparison for Opportunity and Overnight Charging \\\\\\\\\\\\\\\

  15. Conclusion • Cold temperatures affect vehicle operation energy costs • Daytime opportunity charging dramatically reduces energy costs • Large battery PHEVs (PHEV20) are not optimal for the WPG03 • From engineering and consumer points of view, optimization (on a per duty cycle basis) is necessary to realize the full environmental and economic benefits of PHEV technology. • Goldilocks effect

  16. Acknowledgments • Frank Franczyk, Persen Technologies Inc. • Department of Geography, University of Winnipeg Funding and Support

More Related