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International Journal of Next-Generation Engineering and Technology

Open Access Peer Review International
Open Access

Advanced Evolutionary Optimization and Intelligent Sensor Integration for Electromagnetic Compatibility and Signal Integrity in Autonomous Vehicle Architectures

DOI
Evan Richman 1 ,
4 Institute for Advanced Automotive Systems, University of Stuttgart, Germany

Abstract

The rapid evolution of autonomous driving technologies and the proliferation of high-voltage power electronics have introduced unprecedented challenges in electromagnetic compatibility (EMC) and signal integrity. This study provides a comprehensive investigation into the integration of Advanced Driver Assistance Systems (ADAS) with evolutionary fuzzy logic and high-speed data acquisition frameworks. By synthesizing nature-inspired modeling techniques, such as genetic fuzzy systems and differential evolution, the research addresses the complexities of vehicle-level EMC design for automotive inverters and high-speed Ethernet communication. The study specifically evaluates the performance of 10G automotive Ethernet through HyperLynx-validated shielding methodologies for camera PCB design in lighting control modules. Furthermore, the paper explores the role of on-board diagnostics and panoramic imaging systems in enhancing situational awareness while mitigating common-mode noise propagation in four-wheel-drive electric vehicles. The methodology combines prospective and retrospective performance assessments with advanced video compression strategies to ensure real-time streaming capabilities without compromising data fidelity. Results indicate that the application of evolutionary fuzzy rule forests and symbolic regression significantly improves the predictive accuracy of vehicle flow and sensor interference detection. The research concludes that a holistic approach, blending intelligent computational paradigms with robust hardware shielding, is essential for the sustainable development of the next generation of interconnected, autonomous, and electromagnetically resilient vehicular platforms.

Keywords

ADAS, Electromagnetic Compatibility, Evolutionary Fuzzy Systems, Automotive Ethernet

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