Chassis Systems and AI

12429058260?profile=RESIZE_400xAs automotive engineering progresses and moves away from traditional mechanism, the integration of Artificial Intelligence (AI) and Machine Learning (ML) is not just a futuristic possibility; it is increasingly becoming a reality.  These technologies are not only reshaping how vehicles operate but are also enhancing safety, efficiency, and performance.

Dr. Vish Vadari, Senior Technical Specialist Noise, Vibration and Harshness (Global) at ZF Group, explains the potential of AI and ML in optimizing the chassis systems of vehicles, particularly in steering, braking, and suspension.

Understanding the Basics: AI and ML in Chassis Systems - When asked about the basic concept and scope of AI and ML in improving the vehicle’s chassis system, Dr. Vish provided a comprehensive overview.  AI, he explains, encompasses a methodology allowing a system to emulate human-like thinking.  Traditionally, AI was synonymous with expert systems or rule-based logic, where experts designed the rules governing these systems.  However, with the evolution of computing power and algorithms, the scope of AI expanded to incorporate Machine Learning.[1]

Dr. Vish highlights that ML is a subset of AI, focusing on making decisions based on large and complex datasets, often with feedback control logic, as well as stating that the intricate control algorithms in steering, braking, and chassis systems require precise and timely responses, making AI and ML crucial for optimizing their performance.

Integrating AI with Existing Controllers - The question of what the bare minimum is to introduce AI and ML into existing controllers prompted Dr. Vish to explain the current landscape.  Implementing AI and ML tools for online, real-time applications is an ongoing process.  However, these technologies are already being utilized in controllers that operate offline and don’t require real-time responses.

For instance, quality control applications and end-of-line quality checks are areas where AI/ML tools are currently making an impact.  Dr. Vish emphasized that while real time integration may take time, existing applications are already benefiting from these technologies’ accuracy.

Regulatory Updates and Perspectives - Regarding regulatory updates and perspectives on AI and ML data, Dr. Vish provided valuable insights.  He highlighted the profound impact AI/ML methodologies will have on businesses and jobs. As the boundaries of these technologies are still being defined, both individuals and businesses are closely monitoring their potential impacts on products, processes, and services.

Dr. Vish mentioned initiatives such as the bipartisan committee studying AI in US Congress, led by the Senate Majority Leader.  Companies like Amazon, Google, and Meta are also engaging in campaigns to educate lawmakers and the public about AI.

“Senate Majority leader in the Congress, has been leading a voice calling for a comprehensive legislative AI framework and has set up a bipartisan committee to study AI.  Companies including Amazon, Google, and Meta have begun to launch a massive $25 M campaign to educate the lawmakers and the public about the various aspects of AI.”

The evolving regulatory landscape underscores the need for a thoughtful approach to AI integration in chassis systems. 

Enhancing Modularity with AI Modularity, Dr. Vish explained, refers to the extent to which a system can be broken down into interacting modules.  This decomposition reduces complexity and allows for a more manageable design.  In the context of chassis systems, modularity plays a crucial role in breaking down complex problems into simpler, interconnected modules.

By developing greater accuracy in each module, AI can enhance modularity within steering, braking, and suspension systems.  This approach allows for seamless integration of various components, contributing to overall system efficiency and performance.

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Adapting Chassis Systems for ADAS with AI - Advanced Driver Assistance Systems (ADAS) represent a significant advancement in vehicle safety.  Dr. Vish emphasized that AI plays a pivotal role in making steering, braking, and suspension systems adaptable for ADAS applications.  ADAS systems, such as automatic emergency braking and pedestrian detection, rely on advanced technologies to assist drivers and improve overall safety.

Dr. Vish highlighted the modular nature of ADAS, where each safety-critical function can be treated as a separate module.  AI algorithms can first enhance the intelligence and safety of individual chassis systems before integrating them into the broader ADAS framework.

In conclusion, Dr. Vish’s insights underscore the transformative potential of AI and ML in optimizing steering, braking, and suspension systems.  From improving accuracy and efficiency to enhancing safety and adaptability for ADAS, these technologies offer a myriad of benefits.  As the automotive industry continues to embrace AI, we can expect to see increasingly intelligent and responsive vehicles on the road, ultimately leading to safer and more efficient transportation systems.

Link to Automotive Chassis Systems report:

This article is presented at no charge for educational and informational purposes only.

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