Observational Evaluation of the Maximum Practical Utilization of Electric Vehicle DCFC Infrastructure
Abstract
:1. Introduction
1.1. Structure of Report
1.2. Literature Review
- There is one destination to drive to, where if one DCFC is occupied, another is nearby
- If all DCFCs are occupied, the risk of a long wait time is reduced, assuming a single queue for whichever DCFC becomes available next.
- Multiple co-located DCFCs offer greater reliability through redundancy. A recent study in California’s Bay Area found that roughly 1 in 4 DCFC were unable to charge a test vehicle [14].
- A charging hub may develop greater and more consistent traffic, so related business opportunities (convenience stores, fast food, etc.) have more potential market. This potentially presents both an improved experience for users and a local business opportunity.
- Having multiple DCFCs of the same make and model increase the efficiency of keeping spare parts, and technician knowledge can be more specialized, reducing maintenance costs and improving uptime.
- There are significant economies of scale in land acquisition, site preparation and permitting, as well as in burying electrical conduit, buying and placing transformers, etc. A large proportion of the cost of a DCFC charging hub in North America are ‘soft costs’, such as process costs and permitting [15].
1.3. Context of This Analysis
2. Materials and Methods
2.1. Data
- (1)
- Locating and deleting duplicated events (same location, start time & kWh delivered).
- (2)
- Aggregating multiple charging events by the same user, at the same location, if 20 min or less –and no other user events– separate the end of one from the start of the next. It was assumed that such iterated charging events reflect unexpected charging session termination before the driver intended. In such cases, other EVs would likely not have had the opportunity to charge, so the utility of the charging infrastructure was legitimately reduced.
- (3)
- Disregarding any charging events remaining after (2) that transfer less than 1 kWh of energy (a sensitivity analysis on this value showed no obvious cut-off points). Such events were inferred to be EV drivers testing the system to verify vehicle compatibility, so will likely become less frequent as EV ownership experience grows.
- (4)
- Disregarding charging events that took place prior to the official launch of the network. Such events were assumed to be technicians verifying the functionality of the equipment.
2.2. Queuing for an Occupied DCFC
2.3. DCFC Utilization Factor
2.4. Computing the Probability of Queuing
- The set of all ~13,000 charging events was segregated into bins by UF. Bin sizes were selected such that 20 bins would span the range of data for each ∆t evaluation.
- For each UF bin, the charging events that started within a fixed time lag (10 min by default) of the previous event’s termination (at that DCFC) were identified and counted as events where there was a queue.
- This count of queuing events was divided by the total number of charging events within that UF bin. This quotient is described as the ‘queue probability’ (QP) for this UF.
- The QP was multiplied by a factor of 78% to account for the vehicles that would have arrived within that 10-min window irrespective of the presence of the previous vehicle (refer to Section 2.2).
- To improve model robustness, bins containing fewer than 6 data points were excluded from subsequent analysis.
3. Results
3.1. Sensitivity to Time Window ∆t Width
3.2. Sensitivity to Time Lag in QP Definition
3.3. Sensitivity to Seasonal Driving Patterns
3.4. Sensitivity to Sub-Regional Driving Patterns
4. Discussion
4.1. DCFC Rated Power
4.2. Vehicles Choosing Not to Queue
4.3. Power Sharing
Driving Patterns
5. Conclusions
5.1. Key Results
5.2. Policy Implications
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
- Wood, E.; Rames, C.; Muratori, M.; Raghavan, S.; Melaina, M. National Plug-In Electric Vehicle Infrastructure Analysis; US Department of Energy: Washington, DC, USA, 2017.
- Baresch, M.; Moser, S. Allocation of e-car charging: Assessing the utilization of charging infrastructures by location. Transp. Res. Part A Policy Pract. 2019, 124, 388–395. [Google Scholar] [CrossRef]
- Bräunl, T.; Harries, D.; McHenry, M.; Wager, G. Determining the optimal electric vehicle DC-charging infra-structure for Western Australia. Transp. Res. D Transp. Environ. 2020, 84, 102250. [Google Scholar] [CrossRef]
- Anegawa, T. Characteristics of CHAdeMO Quick Charging System. World Electr. Veh. J. 2010, 4, 818–822. [Google Scholar] [CrossRef] [Green Version]
- Schulz, F.; Rode, J. Public charging infrastructure and electric vehicles in Norway. Energy Policy 2022, 160, 112660. [Google Scholar] [CrossRef]
- MacKenzie, D.; Jabbari, P.; Khaloei, M. Locating Fast Charging Stations for Safe and Reliable Intercity Electric Vehicle Travel in Washington; PacTrans: Tacoma WA, USA, 2018. [Google Scholar]
- Miele, A.; Axsen, J.; Wolinetz, M.; Maine, E.; Long, Z. The role of charging and refuelling infrastructure in sup-porting zero-emission vehicle sales. Transp. Res. D Transp. Environ. 2020, 81, 102275. [Google Scholar] [CrossRef]
- Brown, A.; Schayowitz, A.; White, E. Electric Vehicle Charging Infrastructure Trends from the Alternative Fueling Station Locator: Fourth Quarter 2021; NREL: Golden, CO, USA, 2022. [Google Scholar]
- ChargeHub, MogileTech; Marcoux, B.; Ouellette, S. Identification of Current and Future Infrastructure Deployment Gaps; Mogile Technologies Inc.: Pointe-Claire, QC, Canada, 2021. [Google Scholar]
- Chakraborty, D.; Bunch, D.S.; Lee, J.H.; Tal, G. Demand drivers for charging infrastructure-charging behavior of plug-in electric vehicle commuters. Transp. Res. D Transp. Environ. 2019, 76, 255–272. [Google Scholar] [CrossRef]
- Terra 360 ABB. ABB Inc. 2022. Available online: https://new.abb.com/ev-charging/terra-360 (accessed on 17 May 2022).
- Federal Highway Administration. Biden-Harris Administration Takes Key Step Forward in Building a National Network of User-Friendly, Reliable, and Accessible Electric Vehicle Chargers; US Department of Transportation: Washington, DC, USA, 2022.
- Illmann, U.; Kluge, J. Public charging infrastructure and the market diffusion of electric vehicles. Transp. Res. D Transp. Environ. 2020, 86, 102413. [Google Scholar] [CrossRef]
- Rempel, D.; Cullen, C.; Matteson Bryan, M.; Vianna Cezar, G. Reliability of Open Public Electric Vehicle Direct Current Fast Chargers. arXiv, 2022; Submitted for Publication. [Google Scholar] [CrossRef]
- Nelder, C.; Rogers, E. Reducing EV Charging Infrastructure Costs; Rocky Mountain Institute: Basalt, CO, USA, 2020. [Google Scholar] [CrossRef]
- Tesla. Find Us | Tesla n.d. Available online: https://www.tesla.com/en_ca/findus? (accessed on 12 June 2022).
- Mihalascu, D. First Audi Charging Hub A Success, Three More Coming This Year; InsideEVs: Miami, FL, USA, 2022; Available online: https://insideevs.com/news/591069/audi-charging-hub-success-three-more-coming-this-year/ (accessed on 8 June 2022).
- Wu, Y.; Ribberink, H. Methodology to Estimate the Need for Direct-Current Fast-Charging Stations along Highways in Canada. J. Transp. Eng. A Syst. 2020, 146, 04020108. [Google Scholar] [CrossRef]
- He, Y.; Kockelman, K.M.; Perrine, K.A. Optimal locations of U.S. fast charging stations for long-distance trip completion by battery electric vehicles. J. Clean. Prod. 2019, 214, 452–461. [Google Scholar] [CrossRef]
- Pathak, C. Electric Vehicle Infrastructure Decision Support System; University of Washington: Tacoma WA, USA, 2021. [Google Scholar]
- Khan, H.O.A.; Saeed, F.; Owais, H.; Khan, A.; Saeed, F.; Arshad, N. Propelling the Penetration of Electric Vehicles in Pakistan by Optimal Placement of Charging Stations. Eng. Proc. 2021, 11, 34. [Google Scholar] [CrossRef]
- Csonka, B.; Csiszár, C. Determination of charging infrastructure location for electric vehicles. Transp. Res. Procedia 2017, 27, 768–775. [Google Scholar] [CrossRef]
- Kavianipour, M.; Fakhrmoosavi, F.; Shojaei, M.H.; Zockaie, A.; Ghamami, M.; Wang, J.; Jackson, R. Impacts of technology advancements on electric vehicle charging infrastructure configuration: A Michigan case study. Int. J. Sustain. Transp. 2022, 16, 597–609. [Google Scholar] [CrossRef]
- Bryden, T.S.; Hilton, G.; Cruden, A.; Holton, T. Electric vehicle fast charging station usage and power require-ments. Energy 2018, 152, 322–332. [Google Scholar] [CrossRef]
- Borlaug, B.; Salisbury, S.; Gerdes, M.; Muratori, M. Levelized Cost of Charging Electric Vehicles in the United States. Joule 2020, 4, 1470–1485. [Google Scholar] [CrossRef]
- Goody, M.; Lepold, S.; Koke, H.; Smallacombe, K. Charge the North: Findings from the complete data set of the world’s largest electric vehicle study. In Proceedings of the 33rd Electric Vehicle Symposium (EVS33), Portland, OR, USA, 14–17 June 2020. [Google Scholar] [CrossRef]
- Field, K. A Quick Guide to Tesla’s New V3 Supercharging; CleanTechnica, Posted 16 August 2019. Available online: https://cleantechnica.com/2019/08/16/a-quick-guide-to-teslas-new-v3-supercharging/ (accessed on 20 June 2022).
- KPMG Canada. 2022 Auto Poll. KPMG 2022. Available online: https://home.kpmg/ca/en/home/insights/2022/01/kpmg-2022-auto-poll.html (accessed on 23 May 2022).
- PlugShare. 2022. Available online: https://www.plugshare.com/ (accessed on 14 October 2022).
- Statcan. National Travel Survey, Fourth Quarter 2018 and Annual 2018; The Daily; Statistics Canada: Ottawa, ON, Canada, 2019.
- Fitzgerald, G.; Nelder, C. EVgo Fleet and Tariff Analysis Phase 1: California; Rocky Mountain Institute: Basalt, CO, USA, 2017. [Google Scholar]
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Pearre, N.S.; Swan, L.G. Observational Evaluation of the Maximum Practical Utilization of Electric Vehicle DCFC Infrastructure. World Electr. Veh. J. 2022, 13, 190. https://doi.org/10.3390/wevj13100190
Pearre NS, Swan LG. Observational Evaluation of the Maximum Practical Utilization of Electric Vehicle DCFC Infrastructure. World Electric Vehicle Journal. 2022; 13(10):190. https://doi.org/10.3390/wevj13100190
Chicago/Turabian StylePearre, Nathaniel S., and Lukas G. Swan. 2022. "Observational Evaluation of the Maximum Practical Utilization of Electric Vehicle DCFC Infrastructure" World Electric Vehicle Journal 13, no. 10: 190. https://doi.org/10.3390/wevj13100190