Intelligent Electric Power Steering: Artificial Intelligence Integration Enhances Vehicle Safety and Performance
Vikas Vyas, Sneha Sudhir Shetiya
TL;DR
The paper investigates how integrating Artificial Intelligence with Electric Power Steering (EPS) can enhance vehicle safety, adaptability, and efficiency. It surveys AI methods for predictive control, adaptive torque management, and data-driven diagnostics, and discusses case studies in Lane Centering, Automatic Parking, and Autonomous Steering. It also identifies cybersecurity, privacy, ethical, and computational challenges, proposing future directions toward edge computing, federated learning, and low-power AI to enable safer, more capable autonomous and connected vehicles. Overall, AI-enabled EPS has the potential to significantly improve driver assistance, vehicle stability, and maintenance efficiency, while requiring careful attention to safety standards and security.
Abstract
Electric Power Steering (EPS) systems utilize electric motors to aid users in steering their vehicles, which provide additional precise control and reduced energy consumption compared to traditional hydraulic systems. EPS technology provides safety,control and efficiency.. This paper explains the integration of Artificial Intelligence (AI) into Electric Power Steering (EPS) systems, focusing on its role in enhancing the safety, and adaptability across diverse driving conditions. We explore significant development in AI-driven EPS, including predictive control algorithms, adaptive torque management systems, and data-driven diagnostics. The paper presents case studies of AI applications in EPS, such as Lane centering control (LCC), Automated Parking Systems, and Autonomous Vehicle Steering, while considering the challenges, limitations, and future prospects of this technology. This article discusses current developments in AI-driven EPS, emphasizing on the benefits of improved safety, adaptive control, and predictive maintenance. Challenges in integrating AI in EPS systems. This paper addresses cybersecurity risks, ethical concerns, and technical limitations,, along with next steps for research and implementation in autonomous, and connected vehicles.