Recent AI Applications in Electrical Vehicles for Sustainability
International Journal of Mechanical Engineering |
© 2024 by SSRG - IJME Journal |
Volume 11 Issue 3 |
Year of Publication : 2024 |
Authors : K. Balaji Nanda Kumar Reddy, D.Pratyusha, B. Sravanthi, E. Jayakiran Reddy |
How to Cite?
K. Balaji Nanda Kumar Reddy, D.Pratyusha, B. Sravanthi, E. Jayakiran Reddy, "Recent AI Applications in Electrical Vehicles for Sustainability," SSRG International Journal of Mechanical Engineering, vol. 11, no. 3, pp. 50-64, 2024. Crossref, https://doi.org/10.14445/23488360/IJME-V11I3P106
Abstract:
The integration of Artificial Intelligence (AI) technologies in Electric Vehicles (EVs) offers tremendous potential for driving sustainable transportation solutions. This review paper comprehensively analyzes recent advancements and applications of AI in EVs throughout vehicle control, energy management, powertrain, optimization, battery design, and the regulatory environment of autonomous vehicles. Key facts and figures confirm the environmental benefits of increased adoption of EVs, including significantly fewer greenhouse gases and improved air quality compared to conventional Internal Combustion Engine (ICE) vehicles. Life cycle assessments underscore the sustainability advantages of EVs but also note that further improvements are needed to continue to minimize environmental impact. Technical challenges in AI integration, including data security, data interoperability, and AI processing, are discussed. Policy considerations, including government incentives to continue EV adoption and increased regulation of autonomous vehicle technologies, are also discussed. The review looks to the future with an outlook on potential research directions, including improving AI capabilities for EVs and overcoming infrastructure issues to serve the transportation of tomorrow. The contribution of this paper is to aid in the understanding of the ongoing electrification and digitization of personal transportation, how AI will enable EVs to disrupt the automobile industry and to reduce transport impact. Decreasing the transportation impact will require innovations and technology diffusion in the overarching push for a cleaner, electrified transport system. Within the interdisciplinary research of electrification of personal transportation, it is required to integrate knowledge from business, communication, technologists, policy, and the milieu for urgent sustainability missions.
Keywords:
Electric Vehicles, Artificial Intelligence, Sustainability, Transportation, Renewable energy.
References:
[1] Ulrich Eberle, and Rittmar von Helmolta, “Sustainable Transportation Based on Electric Vehicle Concepts: A Brief Overview,” Energy and Environmental Science, vol. 3, no. 6, pp. 689-689, 2010.
[CrossRef] [Google Scholar] [Publisher Link]
[2] Vidhya Kuruvilla, and Pandiyan Venkatesh Kumar, “Necessity of Artificial Intelligence Techniques for Power Quality Issues in Electric Vehicles,” International Journal of Power Electronics and Drive Systems, vol. 14, no. 4, pp. 2487-2487, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Mekyung Lee, “An Analysis of the Effects of Artificial Intelligence on Electric Vehicle Technology Innovation Using Patent Data,” World Patent Information, vol. 63, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Shen Zhang, “Artificial Intelligence in Electric Machine Drives: Advances and Trends,” TechRxiv, pp. 1-22, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Emiliano Pipitone, Salvatore Caltabellotta, and Leonardo Occhipinti, “A Life Cycle Environmental Impact Comparison between Traditional, Hybrid, and Electric Vehicles in the European Context,” Sustainability, vol. 13, no. 19, pp.1-32, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[6] Runsen Zhang, and Shinichiro Fujimori, “The Role of Transport Electrification in Global Climate Change Mitigation Scenarios,” Environmental Research Letters, vol. 15, no. 3, pp. 1-13, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Pouria Ahmadi, “Environmental Impacts and Behavioral Drivers of Deep Decarbonization for Transportation Through Electric Vehicles,” Journal of Cleaner Production, vol. 225, pp. 1209-1219, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Liqiang Wang et al., “Switching to Electric Vehicles Can Lead to Significant Reductions of PM2.5 and NO2 across China,” One Earth, vol. 4, no. 7, pp. 1037-1048, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[9] Evanthia A. Nanaki, and Christopher J. Koroneos, “Climate Change Mitigation and Deployment of Electric Vehicles in Urban Areas,” Renewable Energy, vol. 99, pp. 1153-1160, 2016.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Timothy J. Wallington et al., “Vehicle Emissions and Urban Air Quality: 60 Years of Progress,” Atmosphere, vol. 13, no. 5, pp. 650- 650, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[11] J. L. Schnell et al., “Potential for Electric Vehicle Adoption to Mitigate Extreme Air Quality Events in China,” Earth’s Future, vol. 9, no. 2, pp. 1-18, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Marilyn A. Brown, and Anmol Soni, “Expert Perceptions of Enhancing Grid Resilience with Electric Vehicles in the United States,” Energy Research & Social Science, vol. 57, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Jihun Han et al., “Safe- and Eco-Driving Control for Connected and Automated Electric Vehicles Using Analytical State-Constrained Optimal Solution,” IEEE Transactions on Intelligent Vehicles, vol. 3, no. 2, pp. 163-172, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[14] Dina G. Mahmoud et al., “Intelligent Battery-Aware Energy Management System for Electric Vehicles,” 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Zaragoza, Spain, pp. 1635-1638, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[15] B. Spoorthi, and P. Pradeepa, “Review on Battery Management System in EV,” 2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP), Hyderabad, India, pp. 1-4, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[16] Shengnan Fang et al., “Design and Control of a Novel Two-Speed Uninterrupted Mechanical Transmission for Electric Vehicles,” Mechanical Systems and Signal Processing, vol. 75, pp. 473-493, 2016.
[CrossRef] [Google Scholar] [Publisher Link]
[17] T. Holdstock et al., “Energy Consumption Analysis of a Novel Four-Speed Dual Motor Drivetrain for Electric Vehicles,” 2012 IEEE Vehicle Power and Propulsion Conference, Seoul, Korea (South), pp. 295-300, 2012.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Sen Yan et al., “A Review on AI Algorithms for Energy Management in E-Mobility Services,” 2023 7th CAA International Conference on Vehicular Control and Intelligence (CVCI), Changsha, China, pp. 1-8, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[19] M.S. Hossain Lipu et al., “Intelligent Algorithms and Control Strategies for Battery Management System in Electric Vehicles: Progress, Challenges and Future Outlook,” Journal of Cleaner Production, vol. 292, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[20] Jing Na et al., “Guest Editorial: AI Applications to Intelligent Vehicles for Advancing Intelligent Transport Systems,” IET Intelligent Transport Systems, vol. 14, no. 5, pp. 267-269, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[21] Andre A. Silva, Ali M. Bazzi, and Shalabh Gupta, “Fault Diagnosis in Electric Drives Using Machine Learning Approaches,” 2013 International Electric Machines & Drives Conference, Chicago, IL, USA, pp. 722-726, 2013.
[CrossRef] [Google Scholar] [Publisher Link]
[22] Wangjie Lang et al., “Artificial Intelligence-Based Technique for Fault Detection and Diagnosis of EV Motors: A Review,” IEEE Transactions on Transportation Electrification, vol. 8, no. 1, pp. 384-406, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[23] Ching Fu Lin, Jyh Ching Juang, and Kun Rui Li, “Active Collision Avoidance System for Steering Control of Autonomous Vehicles,” IET Intelligent Transport Systems, vol. 8, no. 6, pp. 550-557, 2014.
[CrossRef] [Google Scholar] [Publisher Link]
[24] Siddhartha Mal et al., “Electric Vehicle Smart Charging and Vehicle-to-Grid Operation,” International Journal of Parallel, Emergent and Distributed Systems, vol. 28, no. 3, pp. 249-265, 2013.
[CrossRef] [Google Scholar] [Publisher Link]
[25] Xinhui Zhao, and Guojun Liang, “Optimizing Electric Vehicle Charging Schedules and Energy Management in Smart Grids using an Integrated GA-GRU-RL Approach,” Frontiers in Energy Research, vol. 11, pp. 1-20, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[26] Gaetano Abbatantuono et al., “Smart Charging of Electric Vehicles for Low Voltage Grids Optimization,” 2016 IEEE Workshop on Environmental, Energy, and Structural Monitoring Systems (EESMS), Bari, Italy, pp. 1-6, 2016.
[CrossRef] [Google Scholar] [Publisher Link]
[27] Stefan Scheubner et al., “A Stochastic Range Estimation Algorithm for Electric Vehicles Using Traffic Phase Classification,” IEEE Transactions on Vehicular Technology, vol. 68, no. 7, pp. 6414-6428, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[28] Henning Preis, Stefan Frank, and Karl Nachtigall, “Energy-Optimized Routing of Electric Vehicles in Urban Delivery Systems,” Operations Research Proceedings 2012, pp. 583-588, 2013.
[CrossRef] [Google Scholar] [Publisher Link]