Session: 06-04: Performance Systems Modeling and Design
Paper Number: 164631
164631 - Leveraging Modeling and Simulation in Virtual Calibration: Ai’s Role in Performance Optimization
Abstract:
In the rapidly evolving field of automotive engineering, calibration is crucial for optimizing a vehicle’s control systems to achieve peak performance, efficiency, and regulatory compliance. Traditionally, calibration has been a time-consuming, manual process. However, as modern powertrain systems become more complex and interconnected, there is a growing need for innovative approaches to keep pace with technological advancements. Powertrain calibration engineers are increasingly adopting virtual environments to conduct these processes. This presents an opportunity for artificial intelligence (AI) to help engineers redefine the possibilities of virtual modeling and simulation, marking a pivotal shift from traditional methods.
In this talk, Morgan Jenkins, Chief Product Officer from Secondmind, will explore the transformational impact of AI, and more specifically, advanced machine learning techniques, on the calibration process. Machine learning models, which can predict outcomes and suggest optimal calibration settings, act as powerful tools to streamline and refine calibration tasks. The talk will delve into how optimization algorithms efficiently explore calibration spaces without the need for physical testing, bolstered by integrating advanced simulation tools to create hybrid models that accelerate the calibration timeline.
Virtualizing the calibration process offers numerous advantages for OEMs and suppliers. By reducing reliance on physical prototypes, companies can significantly cut down on costs and enhance time efficiency. Leveraging advanced machine learning models also empowers engineers to build reliable and accurate calibration maps, with models informed by physics, to increase accuracy and further reduce data requirements. This creates unprecedented flexibility and scalability, and opens up new opportunities for enhancing safety and achieving comprehensive integration of diverse systems and subsystems.
By drawing on real-world examples from EV powertrain calibration, this talk will showcase how such cutting-edge approaches to modeling and simulation can dramatically accelerate development cycles, thus supporting the industry's drive for innovation and alignment with environmental goals. Ultimately, the adoption of these virtualized strategies, using advanced machine learning, sets a new standard for performance optimization, positioning the industry for continued advancement and success in a digital-first landscape.
Presenting Author: Morgan Jenkins Secondmind
Presenting Author Biography: Morgan Jenkins, Chief Product Officer at Secondmind, is a globally-experienced software executive who excels in strategic growth and innovation within the Computer-Aided Design (CAD), Computer-Aided Engineering (CAE), and Electronic Design Automation (EDA) domains. Jenkins has held numerous leadership positions during his career, prior to Secondmind, he was Vice President of Simulation and Test Solutions at Siemens Digital Industries, where he led teams to drive Business Innovation and growth of existing and new products in the Simulation space. At Secondmind, Jenkins is responsible for the entire product lifecycle, from development to market, advancing revenue with strategic and innovative product strategies.
Authors:
Morgan Jenkins SecondmindVictor Picheny Secondmind
Henri French Secondmind
Leveraging Modeling and Simulation in Virtual Calibration: Ai’s Role in Performance Optimization
Paper Type
Technical Presentation Only