AI-based virtual sensors are revolutionizing the management of battery systems by providing reliable estimates for parameters that are traditionally difficult to measure, such as the state of charge (SOC). A recent webinar showcased how these advanced models can be integrated into system-level design, highlighting practical applications and methodologies for implementation.
Integrating AI Models into System Design
The session presented a detailed workflow for designing, verifying, compressing, and deploying AI-driven virtual sensors to embedded processors. By using a unified environment, developers can integrate AI models into Simulink®, which enables system-level simulation and thorough verification processes.
Formal Verification and Optimisation
A key focus of the webinar was on formal verification techniques to assess the behavior of neural networks. This step is essential for making sure that AI models operate reliably within specified constraints. Attendees learned how to optimize these models not only for accuracy but also for memory footprint and execution speed, both of which are important for deployment on embedded systems.
Practical Implementation and Deployment
The integration process involves generating and profiling library-free C code specifically designed for embedded deployment. This approach simplifies the transition from simulation to real-world application, enabling engineers to quickly implement AI solutions in their battery management systems. The webinar also encouraged participants to evaluate design trade-offs, balancing accuracy with performance and deployment objectives.
Industry Collaboration
Presented by IEEE Spectrum and Wiley, and sponsored by Mathworks, this on-demand webinar highlights the collaborative efforts in the industry to apply AI for practical uses. By focusing on virtual sensors in battery management systems, the session aimed to equip engineers with the knowledge needed to improve system performance and reliability.
The impact of this technology goes beyond battery management. As industries increasingly depend on efficient energy solutions, the development of AI-driven virtual sensors will play a significant role in the future of energy systems. This model-based design approach offers benefits across various applications, from automotive to renewable energy sectors, paving the way for smarter, more efficient systems.
As the technology continues to evolve, stakeholders are encouraged to explore these methodologies to maintain a competitive edge in AI and energy management. The webinar serves as a valuable resource for professionals looking to use the capabilities of AI in their designs and implementations.