Skip to main content
editor@theusajournals.com | Oscar Publishing Services Journal Home
Login

American Journal of Applied Science and Technology

Peer Reviewed | Open Access | E-ISSN: 2771-2745
Published Article

Electromagnetic Compatibility, Intelligent Control, And System-Level Optimization in Electric and Autonomous Vehicles: A Unified Framework for Thermal Management, Wireless Charging, High-Speed Automotive Ethernet, And Sensor Robustness

Electromagnetic Compatibility, Intelligent Control, And System-Level Optimization in Electric and Autonomous Vehicles: A Unified Framework for Thermal Management, Wireless Charging, High-Speed Automotive Ethernet, And Sensor Robustness

Authors

  • Dr. Danny Morgan
    Department of Electrical and Transportation Systems Engineering, University of Rotterdam, Netherlands

Keywords:

Electromagnetic compatibility electric vehicles inductive wireless charging automotive Ethernet

Abstract

The rapid evolution of electric and autonomous vehicles has introduced unprecedented electromagnetic, thermal, computational, and communication complexities within automotive platforms. Electrified propulsion, inductive wireless power transfer, high-speed automotive Ethernet, advanced driver-assistance systems, and sensor-rich autonomous architectures collectively intensify electromagnetic interference risks while demanding stringent regulatory compliance and reliability. This study develops a comprehensive, system-level analytical framework integrating electromagnetic compatibility standards, heating and cooling system design, wireless charging architectures, onboard Ethernet shielding strategies, and intelligent control techniques including fuzzy sets, fuzzy-tree modeling, and particle swarm optimization. Drawing exclusively from established standards and foundational works in electromagnetic compatibility, fuzzy logic, optimization, and automotive systems, this research synthesizes theoretical insights into a cohesive design methodology.

The article critically evaluates regulatory and standardization structures governing vehicle electromagnetic behavior, including CISPR 12, CISPR 25, CISPR 36, ISO 7637 series, and European vehicle type-approval directives. It explores how inductive wireless charging systems and 10G automotive Ethernet exacerbate radiated and conducted emissions, and how shielding and topology-based mitigation approaches can restore compliance. Intelligent modeling techniques are applied conceptually to manage uncertainty in interference-prone environments, particularly for ultrasound-based obstacle detection under electromagnetic disturbances and compressed video transmission for autonomous platforms.

Results demonstrate that electromagnetic resilience must be addressed as a cross-domain optimization problem rather than a component-level afterthought. The proposed unified framework emphasizes proactive EMI anticipation, impedance management, shielding validation, thermal-electromagnetic co-design, and intelligent adaptive control. The discussion elaborates on regulatory challenges, design trade-offs, scalability, and the growing convergence between electromagnetic compatibility and autonomous system reliability. This work contributes a theoretically exhaustive, publication-ready foundation for future interdisciplinary research in electromagnetically robust electric and autonomous vehicle design.

References

European Commission. (2007). EUR-Lex-52007DC0022-EN-EUR-Lex.

European Parliament Council. (2007). Directive 2007/46/EC Definition.

IEC. (2009). CISPR 12:2007+AMD1.

IEC. (2020). CISPR 36.

IEC. (2021). CISPR 25.

ISO. (2011). ISO 7637-2 Road vehicles-Electrical disturbances from conduction and coupling-Part 2.

ISO. (2015). ISO 7637-1 Road vehicles-Electrical disturbances from conduction and coupling-Part 1.

KARIM, A. S. A. (2025). Mitigating electromagnetic interference in 10G automotive Ethernet: hyperLynx-validated shielding for camera PCB design in ADAS lighting control. International Journal of Applied Mathematics, 38(2s), 1257-1268.https://doi.org/10.12732/ijam.v38i2s.718.

Mahesh, A., Chokkalingam, B., & Mihet-Popa, L. (2021). Inductive wireless power transfer charging for electric vehicles-A review. IEEE Access, 9, 137667–137713.

Morgan, D. (2007). A handbook for EMC testing and measurement. Institution of Engineering and Technology.

Sun, S., Liu, G., Pommerenke, D. J., Drewniak, J. L., Kautz, R. W., & Chen, C. (2004). Anticipating EMI and on-board interference in automotive platforms. Proceedings of the International Symposium on Electromagnetic Compatibility.

Vemuri, A. T. (2020). How to design heating and cooling systems for HEV/EVs. Texas Instruments Technical Report SZZY015A.

Williams, K. (2004). Hybrid vehicles 42 volt vehicle electrical systems and the implications for EMC technology. Proceedings of the International Symposium on Electromagnetic Compatibility.

Wiseman, Y. (2024). Video compression prototype for autonomous vehicles. Smart Cities, 7(2), 758–771.

Wu, C. X., Gao, F., Dai, H. Z., & Wang, Z. L. (2019). A topology-based approach to improve vehicle-level electromagnetic radiation. Electronics, 8(3), 364–376.

Yi, D., Joo, J., Piao, Z., Jin, H., & Kim, S. C. (2019). Ultrasound-based obstacle detection system for vehicles under interference environment. Proceedings of the Asia-Pacific Conference on Communications, 95–98.

Zadeh, L. (1965). Fuzzy sets. Information and Control, 8, 338–353.

Zambrano-Bigiarini, M., Clerc, M., & Rojas, R. (2013). Standard particle swarm optimisation 2011 at CEC-2013: A baseline for future PSO improvements. Proceedings of the IEEE Congress on Evolutionary Computation, 2337–2344.

Zhang, J., Mao, J., Dai, J., & Wei, K. (1999). Fuzzy-tree model and its applications to complex system modeling. IFAC Proceedings Volumes, 32(2), 3891–3896.

Zhou, Q., Sumner, M., & Thomas, D. (2013). Mathematical analysis of the equivalent impedance at the harmonic frequency for the proposed aircraft power system. IET Electrical Systems in Transportation, 3(4), 87–101.