EV Battery Liability & Product Recall Coverage: Insurance Solutions for the Rapidly Expanding Electric Vehicle Market
DOI:
https://doi.org/10.63282/3050-9416.IJAIBDCMS-V5I2P115Keywords:
Electric Vehicle, EV Battery, Product Recall, Liability Insurance, Risk Management, Recall Coverage, Automotive Insurance, Lithium-ion Battery, Thermal Runaway, EV MarketAbstract
The electric vehicles (EVs) have been implemented with an unparalleled scale of global adoption that forces the automotive industry to expand with new risk environments and concerns on liabilities to the company. Among them, the dangers of the EV batteries like the thermal runaway, the fire risks and the degradation are issues to the equipment manufacturers, insurance firms, and consumers. In this paper, Yonkers reviews the dynamical field of EV battery liability and product recalls cover within the insurance industry. It provides a detailed discussion of the insurance solutions that are set to meet the EV market with a particular focus on risk assessment strategies, the structure of insurance cover, and regulation. Due to the increased reliance on the lithium ion battery technology, the financial risk that comes with recalling the products and the liability cases has been on the increase. The paper relies on the overview of the existing literature, the models of insurance, and the regulatory frameworks, pointing to the gaps and opportunities of the insurance companies. Based on the combination of qualitative and quantitative designs, the research examines the practical cases of EV recalls, insurance claims patterns, and the recently introduced risk reduction measures. The findings indicate that the effect of financial and operational risk can be reduced to a significant level with the help of the proactive strategy in the form of the predictive analytic, extended product liability coverage, and special recall insurance policies. The paper advises the conclusion of doable recommendations that can be implemented by the automakers, insurers and policy makers to improve EV battery risk management and insurance policies to encourage sustainable growth of the EV markets
References
1. Held, M., Tuchschmid, M., Zennegg, M., Figi, R., Schreiner, C., Mellert, L. D., ... & Nachef, L. (2022). Thermal runaway and fire of electric vehicle lithium-ion battery and contamination of infrastructure facility. Renewable and Sustainable Energy Reviews, 165, 112474.
2. Karri, N. (2021). Self-Driving Databases. International Journal of Emerging Trends in Computer Science and Information Technology, 2(1), 74-83. https://doi.org/10.63282/3050-9246.IJETCSIT-V2I1P10
3. Koroma, M. S., Costa, D., Philippot, M., Cardellini, G., Hosen, M. S., Coosemans, T., & Messagie, M. (2022). Life cycle assessment of battery electric vehicles: Implications of future electricity mix and different battery end-of-life management. Science of The Total Environment, 831, 154859.
4. Almansour, M. (2022). Electric vehicles (EV) and sustainability: Consumer response to twin transition, the role of e-businesses and digital marketing. Technology in Society, 71, 102135.
5. Karri, N. (2021). AI-Powered Query Optimization. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 2(1), 63-71. https://doi.org/10.63282/3050-9262.IJAIDSML-V2I1P108
6. Kulasekhara Reddy Kotte. 2023. Leveraging Digital Innovation for Strategic Treasury Management: Blockchain, and Real-Time Analytics for Optimizing Cash Flow and Liquidity in Global Corporation. International Journal of Interdisciplinary Finance Insights, 2(2), PP - 1 - 17, https://injmr.com/index.php/ijifi/article/view/186/45
7. Aalund, R., Diao, W., Kong, L., & Pecht, M. (2021). Understanding the non-collision related battery safety risks in electric vehicles a case study in electric vehicle recalls and the LG chem battery. IEEE Access, 9, 89527-89532.
8. Hao, H., Sun, Y., Mei, X., & Zhou, Y. (2021). Reverse logistics network design of electric vehicle batteries considering recall risk. Mathematical Problems in Engineering, 2021(1), 5518049.
9. Karri, N. (2022). Leveraging Machine Learning to Predict Future Storage and Compute Needs Based on Usage Trends. International Journal of AI, BigData, Computational and Management Studies, 3(2), 89-98. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V3I2P109
10. Pütz, F., Murphy, F., Mullins, M., & O'Malley, L. (2019). Connected automated vehicles and insurance: Analysing future market-structure from a business ecosystem perspective. Technology in Society, 59, 101182.
11. Sun, P., Bisschop, R., Niu, H., & Huang, X. (2020). A review of battery fires in electric vehicles. Fire technology, 56(4), 1361-1410.
12. Naga Surya Teja Thallam. (2022). Enhancing Security in Distributed Systems Using Bastion Hosts, NAT Gateways, and Network ACLs. International Scientific Journal of Engineering and Management, 1(1).
13. Karri, N., Pedda Muntala, P. S. R., & Jangam, S. K. (2022). Forecasting Hardware Failures or Resource Bottlenecks Before They Occur. International Journal of Emerging Research in Engineering and Technology, 3(2), 99-109. https://doi.org/10.63282/3050-922X.IJERET-V3I2P111
14. Kumar, R. R., Bharatiraja, C., Udhayakumar, K., Devakirubakaran, S., Sekar, K. S., & Mihet-Popa, L. (2023). Advances in batteries, battery modeling, battery management system, battery thermal management, SOC, SOH, and charge/discharge characteristics in EV applications. Ieee Access, 11, 105761-105809.
15. Omariba, Z. B., Zhang, L., & Sun, D. (2018). Review on health management system for lithium-ion batteries of electric vehicles. Electronics, 7(5), 72.
16. Karri, N. (2023). ML Models That Learn Query Patterns and Suggest Execution Plans. International Journal of Emerging Trends in Computer Science and Information Technology, 4(1), 133-141. https://doi.org/10.63282/3050-9246.IJETCSIT-V4I1P115
17. Venkata SK Settibathini. Enhancing User Experience in SAP Fiori for Finance: A Usability and Efficiency Study. International Journal of Machine Learning for Sustainable Development, 2023/8, 5(3), PP 1-13, https://ijsdcs.com/index.php/IJMLSD/article/view/467
18. Pesaran, A., Roman, L., & Kincaide, J. (2023). Electric Vehicle Lithium-Ion Battery Life Cycle Management (No. NREL/TP-5700-84520). National Renewable Energy Laboratory (NREL), Golden, CO (United States).
19. Dhameja, S. (2001). Electric vehicle battery systems. Elsevier.
20. Bisschop, R., Willstrand, O., & Rosengren, M. (2020). Handling lithium-ion batteries in electric vehicles: preventing and recovering from hazardous events. Fire technology, 56(6), 2671-2694.
21. Karri, N., & Jangam, S. K. (2023). Role of AI in Database Security. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 4(1), 89-97. https://doi.org/10.63282/3050-9262.IJAIDSML-V4I1P110
22. Growth in EV production: battery and product recall risk considerations, marsh, 2022. online. https://www.marsh.com/en-gb/industries/automotive/insights/growth-in-ev-production-battery-and-product-recall-risk-considerations.html
23. Tohir, M. Z. M., & Martín-Gómez, C. (2023). Electric vehicle fire risk assessment framework using Fault Tree Analysis. Open Research Europe, 3, 178.
24. Hoang, D. T., Wang, P., Niyato, D., & Hossain, E. (2017). Charging and discharging of plug-in electric vehicles (PEVs) in vehicle-to-grid (V2G) systems: A cyber insurance-based model. IEEE Access, 5, 732-754.
25. Karri, N., & Pedda Muntala, P. S. R. (2023). Query Optimization Using Machine Learning. International Journal of Emerging Trends in Computer Science and Information Technology, 4(4), 109-117. https://doi.org/10.63282/3050-9246.IJETCSIT-V4I4P112
26. Kulasekhara Reddy Kotte. 2023. Integrating Cybersecurity and Real-Time Analytics in Treasury Management: Enhancing Liquidity, Optimizing Working Capital, and Mitigating Financial Risks. International Journal of Professional Studies, 16(1), PP – 61 - 69, https://www.ijps.in/paper.php?id=193
27. Sehrawat, S. K. (2023). Intelligent healthcare management: Advancing healthcare with integrated AI and ML solutions. International Journal of Research in Medical Sciences and Technology, 17(1), v16i01.
28. Arpit Garg, S Rautaray, Devrajavans Tayagi. Artificial Intelligence in Telecommunications: Applications, Risks,and Governance in the 5G and Beyond Era. International Journal of Computer Techniques – Volume10Issue1,January - February – 2023. 1-19.
29. Gopi Chand Vegineni. 2022. Intelligent UI Designs for State Government Applications: Fostering Inclusion without AI and ML, Journal of Advances in Developmental Research, 13(1), PP – 1-13, https://www.ijaidr.com/research-paper.php?id=1454
