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Using GPS to Monitor Driving and Parking Habits in Winnipeg for PHEV Optimization R.Smith 1, D.Capelle 1 and D.Blair 1 1 University of Winnipeg Department.

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Presentation on theme: "Using GPS to Monitor Driving and Parking Habits in Winnipeg for PHEV Optimization R.Smith 1, D.Capelle 1 and D.Blair 1 1 University of Winnipeg Department."— Presentation transcript:

1 Using GPS to Monitor Driving and Parking Habits in Winnipeg for PHEV Optimization R.Smith 1, D.Capelle 1 and D.Blair 1 1 University of Winnipeg Department of Geography

2 Introduction What is a PHEV?

3 Introduction Power Requirements: Distance, Speed, Acceleration and Duration Time available for Battery Recharging How do you design a PHEV?

4 Purpose Determine the energy demands placed on a PHEV by a typical driver Identify the most suitable public locations for recharging PHEVs Decrease vehicle emissions & petroleum dependence

5 Participants 100 Drivers from Winnipeg & nearby communities One year period Recruitment: –Local media –Word-of mouth –First come first served basis

6 Equipment 100 GPS receivers (Otto Driving Companion) –Store 300 hours of 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

7 Duty Cycle Analysis arcx.com/sites/images/Photos/Underground parking lot at Square One.jpg

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

9 Duty Cycle Construction How many Trips / Cycle ? What is the trip origin and destination ? What hour of the day ? How long and far is the trip ? Speed and acceleration ? What is “Average” or “Typical” ?

10 Isolating Specific Trips HOME WORK HOME to WORK

11 CONGESTED FLOW IDLE CREEP UN-CONGESTED FLOW Simplifying Trips

12 Creating “Blueprints” Idling Micro-trips Un-congested Traffic Flow Creep Congested Traffic Flow % Micro-Trip Types

13 Reconstructing Trips X 100

14 Reconstructing Trips 6.5 km 22 km/h Distance Average Speed

15 Duty Cycle Construction HOME to WORK WORK to SCHOOL SCHOOL to HOME HOME to SHOPPING SHOPPING to HOME TOTAL DISTANCE = 25.4 km TOTAL DURATION = 1:02:54

16 Parking Analysis arcx.com/sites/images/Photos/Underground parking lot at Square One.jpg

17 Suitability Criteria Maximum public availability –Widely-used parking lots Maximum re-charge potential –Long mean parking duration Low Impact on Electric Grid –“Off-peak electric demand” parking

18 Filtering & Manipulation Isolate only Trip-ends from data set –Parking locations Calculate Duration of all Parking Events –Time difference between trip-end and next trip-start Parking On/Off-peak electric demand

19 Potentially Suitable Lots: Widely Used Areas

20 Potentially Suitable Lots: Individual Lot Analysis 78 / 85 (0.92) On-peak/ Off-peak 96 minsmean duration 68# participants STATISTICS On-peak/Off-peak Mean Duration (mins) # Participants GP-5GP-4GP-3GP-2GP-1STATISTICS

21 Ranking Parking Lots Suitability Criteria Widely-used Long mean-parking duration Low impact on electric grid RANK Lot ALot B Widely Used 12 Duration21 Off peak21 SUM54 OVERALL less desirable more desirable

22 Conclusion The Good: GPS and GIS ideal for identifying suitable locations for PHEV recharge infrastructure Applicable to other cities The Bad: Sample size too small GPS data errors

23 Acknowledgments Soheil Shahidinejad, Department of Engineering, University of Manitoba Dr. Jeff Babb, Department of Math and Stats, University of Winnipeg Brad Russell, Department of Geography: Map Library, University of Winnipeg Centre for Forest Interdisciplinary Research (C-FIR) Pam Godin, Leif Norman and Laura Redpath Terry Zdan and Dr. Arne Elias, The Centre for Sustainable Transportation (CST) Funding and Support


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