Computational Challenges and Approaches for Electric Vehicles

Arun Kumar Kalakanti; Shrisha Rao

doi:10.1145/3582076

journal article Jul 17, 2023

Computational Challenges and Approaches for Electric Vehicles

Arun Kumar Kalakanti

Shrisha Rao

ACM Computing Surveys Vol. 55 No. 14s pp. 1-35 · Association for Computing Machinery (ACM)

View at Publisher Save 10.1145/3582076

Abstract

Researchers worldwide have become increasingly interested in developing computational approaches to handle challenges facing electric vehicles (EVs) in recent years. This article examines the challenges and future potential of computational approaches for problems such as EV routing, EV charging scheduling (EVCS), EV charging station (CS) placement, CS sizing, and energy or load management. In addition, a summary of the fundamental mathematical models employed to solve the EV computational problems is presented. We cover recent work on computational solutions for various EV problems utilizing single and coupled mathematical models. Finally, we also examine potential research avenues that researchers could pursue to realize the objective of environment-friendly transportation and smart grids (SGs).

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References

198

[1]

10.1287/inte.1080.0409

[2]

A. Omidvar, R. Tavakkoli-Moghaddam. 2012. Sustainable vehicle routing: Strategies for congestion management and refueling scheduling. In Proceedings of the 2012 IEEE International Energy Conference and Exhibition.

[3]

10.1109/access.2021.3064354

[4]

10.1016/j.epsr.2015.04.003

[5]

10.1016/j.trpro.2014.10.026

[6]

10.1109/itec48692.2020.9161499

[7]

I. E. Agency. 2019. Global EV Outlook 2019. Retrieved from https://webstore.iea.org/global-ev-outlook-2019. Accessed 05-1-2022.

[8]

10.1016/j.enconman.2015.08.059

[9]

10.1016/j.est.2021.103090

[10]

10.3390/su10041076

[11]

10.5815/ijisa.2013.02.05

[12]

10.1016/j.ijepes.2013.06.034

[13]

10.1109/tits.2018.2887194

[14]

10.1109/iecon43393.2020.9255254

[15]

10.1109/jeeit.2019.8717412

[16]

10.3390/electronics10040500

[17]

10.3390/su122310160

[18]

10.1016/j.epsr.2016.06.003

[19]

Simultaneous allocation of electric vehicles’ parking lots and distributed renewable resources in smart power distribution networks

M. Hadi Amini, Mohsen Parsa Moghaddam, Orkun Karabasoglu

Sustainable Cities and Society 10.1016/j.scs.2016.10.006

[20]

10.1016/j.enconman.2010.09.004

[21]

10.1016/j.segan.2016.05.001

[22]

10.1007/978-3-319-20294-5_56

[23]

10.1016/j.energy.2017.05.094

[24]

10.1016/j.asoc.2018.02.025

[25]

10.1109/tits.2020.3038938

[26]

Spatial and Temporal Model of Electric Vehicle Charging Demand

Sungwoo Bae, Alexis Kwasinski

IEEE Transactions on Smart Grid 10.1109/tsg.2011.2159278

[27]

10.1109/tsg.2014.2317523

[28]

10.1109/pacrim.2015.7334804

[29]

10.1016/j.epsr.2012.06.002

[30]

M. S. Bazaraa Hanif D. Sherali and C. M. Shetty. 2006. Nonlinear Programming: Theory and Algorithms . Wiley-Interscience 853. https://www.wiley.com/en-ie/Nonlinear+Programming:+Theory+and+Algorithms +3rd+Edition-p-9780471486008. 10.1002/0471787779

[31]

10.1007/978-3-319-17175-3_7

[32]

10.1109/giis.2014.6934262

[33]

10.1007/s10107-003-0396-4

[34]

10.1002/etep.565

[35]

H. Bhavsar and M. H. Panchal. 2012. A review on support vector machine for data classification. International Journal of Advanced Research in Computer Engineering and Technology 1, 10 (2012).

[36]

10.1007/s10951-017-0538-9

[37]

An Optimized EV Charging Model Considering TOU Price and SOC Curve

Ya Cao, Shengwei Tang, Canbing Li et al.

IEEE Transactions on Smart Grid 10.1109/tsg.2011.2159630

[38]

10.4018/978-1-5225-1829-7.ch017

[39]

10.3390/su14031645

[40]

10.1109/tsg.2016.2635025

[41]

Thomas V. Christensen and Paul Fischer. 2007. Heuristic algorithms for NP-complete problems. (2007). www.imm.dtu.dk. Accessed 05-1-2022.

[42]

10.1109/tpas.1983.317714

[43]

10.1109/tits.2016.2641981

[44]

10.1155/2014/374962

[45]

10.1109/itec48692.2020.9161659

[46]

10.1515/9781400884179/html

[47]

Kalyanmoy Deb. 2016. Practical optimization using evolutionary methods. In Proceedings of the International Workshop on Neural Networks and Genetic Algorithm in Material Science and Engineering. 26–41.

[48]

10.1109/icsgsc52434.2021.9490407

[49]

10.1109/access.2020.2994298

[50]

10.1109/tte.2016.2560524

Showing 50 of 198 references

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References

Details

Published: Jul 17, 2023
Vol/Issue: 55(14s)
Pages: 1-35
License: View

Authors

A

Arun Kumar Kalakanti

Toshiba Software (India) Pvt. Ltd.

S

Shrisha Rao

International Institute of Information Technology Bangalore

Cite This Article

Arun Kumar Kalakanti, Shrisha Rao (2023). Computational Challenges and Approaches for Electric Vehicles. ACM Computing Surveys, 55(14s), 1-35. https://doi.org/10.1145/3582076

Computational Challenges and Approaches for Electric Vehicles

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