This conference paper was submitted for presentation at the NAFEMS World Congress 2025, held in Salzburg, Austria from May 19–22, 2025.

Abstract

The increasing complexity of modern automotive systems is driving the need for advanced solutions to optimize the design and routing of sensor cables, a critical component in ensuring vehicle safety, performance, and efficiency. Traditional manual methods, such as cable design in CAD and validation through physical prototypes are increasingly insufficient for addressing the challenges posed by intricate geometries, constrained design spaces, and stringent performance requirements. To address these challenges, this study introduces an innovative approach that integrates automation and AI-supported optimization algorithms, reducing time and resources, while enabling an efficient and intelligent design cycle. In this case study, the workflow developed to automate cable routing while adhering to constraints such as minimum bending radii, safe distances from components, and load minimization on cables and clips, highlights the integration of automation and optimization tools with complex cable simulation software. By simulating the nonlinear behaviour of cables in the design environment, this approach eliminates the need for physical prototypes, significantly reducing design cycle times and resource consumption. The core of this advancement lies in the application of evolutionary optimization algorithms, enabling exploration of a high-dimensional design space defined by variables such as clip positioning and cable segment lengths. The optimization workflow consistently identified efficient and feasible solutions, satisfying all constraints, and achieving significant improvements over initial manual designs. The results illustrate substantial improvements over traditional methods. Constraints that were previously challenging to meet are addressed, demonstrating the system'™s ability to manage complex requirements while ensuring compliance. This integration of automation and AI not only accelerates the design process but also improves reliability by systematically respecting all constraints. This study highlights the potential for automation and optimization to transform the cable design process in the automotive industry. By replacing manual trial-and-error methods with data-driven workflows, engineers can achieve faster development cycles and more efficient, robust designs. This approach represents a shift in how critical components are engineered, contributing to the development of smarter and more efficient vehicle systems.