Driving patterns matter

Transcription

1 Driving patterns matter suddenly! Sten Karlsson Energy and Environment Chalmers University of Technology Gothenburg Presentation at Chalmers Energy Conference, March 28-29, 2012

2 Content Transport electrification and car movements data The Swedish car movement data project Some results for PHEV design and potential

3 Before electrification (interest) Use of various driving data Aggregated: travel, O-D, purpose traffic, capacity Detailed: car emissions modelling driver behaviour, safety

4 ... and after Use of car movement pattern Driving, when, where and how power-train design, energy management users/customers energy system impact Parking, when, where and how charging infrastructure and market electric load impact and management electricity markets

5 Energy efficiency of electrification Honda Insight In between in between Volvo V50 DRIVe In between Energy to car (TTW) conventional (fuel) s/s, mild hybrid full hybrid Toyota Prius III GM Volt Energy to the wheel plug-in hybrid (el + fuel) pure EV (el) Nissan Leaf imiev

6 Important trade-off in electrification Total cost of ownership (TOC): Energy savings visavi Investment cost for drive-line

7 Cost efficiency of drivetrain? Oper. costs ($/km) conventional mild etc. full hybrid plug-in hybrid Battery electric vehicle Capital costs ($/km) technology, driving distance electric drive fraction battery costs movement pattern battery size, movement pattern recharging opportunities movement patterns matter!

8 Large variability in movement patterns Estimated EDF for the individual cars(recharging every break > 6 hrs) => Huge differences in the opportunity to utilize a specific battery! 200 cars in city of Lund, Sweden Batteristorlek (km) Battery size

9 Car movement data is missing! Travel surveys: Track persons, not cars (holds for Sweden, and most other countries) Only for one day (holds for Sweden, and most other countries) Not useful! Accumulated share of a persons total travel distance with car (%) Daily driving distance [km] Daily travel distance with car [km]

10 Greener elsewhere? Loggings with GPS, few and specific Examples: Travel surveys performed/planned (cities in US) Insurance profiling (Octotelematics, Italy) Driving behaviour (Australia) Road pricing trial (Copenhagen) Speed adaptation trial (Sweden) Drive cycle construction, emission modeling (WLTP) PHEV assessment! (of Winnipeg commuting)..

11 The Swedish car movement data project Will contribute with basic data to build knowledge for design and assessment of electrified vehicles and their infrastructure, by logging of car movements (time, position, speed) in the Swedish private car fleet

12 The vehicles Chevrolet Suburban, 1935? 500 privately driven cars, for 2 months each Model yr 2002+, The county of Västra Götaland + Kungsbacka municipality

13 The selection Stratified random selection from car register (ownership, region, model yr, fuel, weight) Request by letter 5-10 % positive response rate Agreement signed

14 The measurement campaigns Position Velocity Satellite-id 500 ICE 20 EV campaigns *100 cars June 2010 Aug 2012

15 Post-processing Increased (x,y,z) accuracy ( (with help of a fixed network) Analysis database (basic data on trips and cars) with web interface <-> road database <-> weather database

16 Data availability For research on Vehicle energy and environmental performance, Traffic safety and Social planning Restriction: handling of personal data Agreement signed with data owner (Lindholmen Science Park)

17 Illustration of preliminary data and results 0,7 Speed distribution 0,6 0,5 Share 0,4 0,3 Car x Average of 254 cars Car y 0,2 0, Speed interval (km/h)

18 Potential for net connectivity 1 Probability for being parked 0,9 Probability 0,8 0,7 Average for 254 cars 0,6 0, Time of day

19 Estimation of optimal individual PHEV battery size Method Movement patterns Trip distances Stop lengths Techno-economic parameters Battery cost ($/kwh,yr) Battery utilization (kwh/kwh) Energy prices ($/kwh) Specific energy use, fuel and electricity (kwh/km) Battery utilization: Marginal recharging frequency [yr -1 ], MRF(AER) Optimality: MRF opt Optimal battery size: AER opt

20 MRF opt? (optimal marginal recharging frequency) Two examples: Current state or slightly better: A future situation?: Parameter MRF opt = 400 MRF opt = 50 Marginal energy battery cost ($/kwh) Battery utilization (kwh/kwh) Energy prices ($/kwh) Quota of specific energy uses (-) Annuity (yr -1 )

21 Resulting PHEV optimal batteries (for 212 cars) MRF opt = 50 MRF opt = 400 Better recharging options 0.5h 4h charging when 10h break Economic performance

22 Potential electrification of vehicle driving Better recharging options Individual batteries One size for all MRF opt Better economic prerequisites

23 Conclusions Movements patterns matter for vehicle electrification Chalmers measure and utilize in research these patterns for Sweden

24 Thank you for your attention! St en Kar l s s on Physi cal Resour ce Theor y Depar t ment of Ener gy and Envi r onment Chal mer s Uni ver si t y of Technol ogy SE Got henbur g, SWEDEN st en. kar l sson@chal mer s. se Tel : Mobi l e: