Intelligent Electric Power Steering: Artificial Intelligence Integration Enhances Vehicle Safety and Performance
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.
Code (0)
등록된 구현이 없습니다.
Methods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
An Intelligent Question Answering System based on Power Knowledge Graph
The intelligent question answering (IQA) system can accurately capture users' search intention by understanding the natural language questions, searching relevant content efficiently from a massive knowledge-base, and re…
Question AnsweringTo Root Artificial Intelligence Deeply in Basic Science for a New Generation of AI
One of the ambitions of artificial intelligence is to root artificial intelligence deeply in basic science while developing brain-inspired artificial intelligence platforms that will promote new scientific discoveries. T…
Brain Computer InterfaceDecision MakingVisual Commonsense ReasoningProgress in artificial intelligence applications based on the combination of self-driven sensors and deep learning
In the era of Internet of Things, how to develop a smart sensor system with sustainable power supply, easy deployment and flexible use has become a difficult problem to be solved. The traditional power supply has problem…
FrictionArtificial Intelligence in Power System Security and Stability Analysis: A Comprehensive Review
This review comprehensively examines the integration of artificial intelligence (AI) in enhancing the dynamic security assessments of modern power systems. It highlights the pivotal role of AI in facilitating scenario ge…
Electricity Theft Detection using Machine Learning
Non-technical losses (NTL) in electric power grids arise through electricity theft, broken electric meters or billing errors. They can harm the power supplier as well as the whole economy of a country through losses of u…
BIG-bench Machine Learning