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Model-Based Design has been a reliable and powerful framework for designing complex systems for more than two decades. Today’s engineers are confronting new workflows influenced by trends in software development, the integration of AI, and cloud computing. Learn how MathWorks is investing in Model-Based Design to deliver critical capabilities to automate design tasks, prevent defects, and scale to increasingly complex digital systems.

Discover what BAE Systems has achieved with model-based engineering and how their journey with MATLAB^® and Simulink^® has led them to embrace automation within their developments to achieve zero-defect solutions.

Polestar is committed to accelerating the change to a fully electric, climate-neutral future. We are passionate about design and cutting-edge technology, and simulation is a crucial tool in developing the next generation of our electric vehicles.

Electric vehicle design presents a new challenge for modelling and simulation. Optimising a vehicle's energy management requires understanding the interactions between complex mechanical and electrical systems and their control software. Polestar has risen to this challenge by developing a flexible and modular simulation platform using Simulink^® and Simscape™ products.

Discover how Polestar models the performance and energy consumption of the vehicle mechanics, propulsion system, thermal management, cabin comfort, and control software.

The electrification megatrend is well underway as many countries look to decarbonise their economies and move to a net-zero future. Every industry is seeing a boom in new startups looking to disrupt the status quo and established companies needing to pivot or transition their businesses.

The panel of industry experts, all with strong backgrounds in modelling and simulation, will debate what has made them successful at different stages in their journey of developing electrified systems. Learn from the challenges that they faced in their use of Model-Based Design and be inspired by their vision of the future.

Join the Women in Tech networking event hosted by MathWorks—an informal session celebrating women working in science and engineering fields with MATLAB^® and Simulink^®. Hear from leading technical experts, interact with MathWorks leaders and engineers, and exchange ideas with industry peers. Open to all attendees who are interested in diversity, equity, and inclusion.

There has been a recent explosion of research into artificial intelligence (AI) which has demonstrated immense promise across all industries, with levels of performance accuracy previously unobtainable now commonplace.

The rapid evolution and advancement of the tools and techniques used for training cutting-edge AI solutions benefits from a wide variety of tools such as MATLAB^®, PyTorch^® and TensorFlow™ working together. However, to exploit these AI solutions beyond research and into products, it is critical that they can be used for inference “in the wild.”

See how MBDA engineers have successfully imported externally developed AI solutions into full system Simulink^® models for testing and proving, and subsequently deployed these solutions onto embedded hardware.

The explosion of AI has ushered in a new paradigm for designing systems that solve complex problems. The use of AI as a viable alternative to traditional wireless techniques is currently an active area of research. As such, it is being considered as part of 3GPP Release 18. However, gathering real training data and training AI models can be prohibitively expensive and time consuming.

In this master class, learn how you can use MATLAB® to generate synthetic training data for a deep learning neural network applied to a wireless system, and accelerate this using parallel computing on both CPUs and GPUs. See how to automatically classify modulation schemes and perform neural network-based channel estimation. This approach reduces cost, gives flexibility, and can accelerate the process significantly.

Energy storage is one of the key enabling technologies in the electrification of systems. It is applicable at all scales, from power grid and renewable energy storage solutions down to the ubiquitous presence of batteries in consumer electronic devices. Modelling the electrical dynamics of individual battery cells and how differences at the cell level interact at the module and pack level is a critical step in ensuring the safe and performant operation of these systems. Issues such as thermal management can also have a major impact on a whole system’s performance, with product requirements extending beyond pure electrical modelling.

In this talk, hear a MathWorks engineer share different approaches to modelling battery systems that can accelerate the design of packs and control systems. The methods discussed will help engineers better understand common challenges and constraints when integrating energy storage into wider systems.

Tools enabling multiphysics simulation of complex system interactions will also be discussed, including examples of how similar modelling approaches are applicable to a wide range of other energy storage technologies such as fuel cells and flow batteries.

With the challenges of increasing complexity, reduced product timelines, and the need for more reliable testing, it is important to be able to test, deploy, and scale applications in the cloud.

Learn how you can develop, test, and deploy MATLAB® algorithms and Simulink® models in the cloud. Find out how this helps accelerate your development, scale up your testing activities, and support processing data where it is stored in the cloud.

The session will focus on the application of Model-Based Design to cloud-based workflows and demonstrate the tools that are available to accelerate the creation of CI/CD pipelines.

Key points covered will include:

• Developing and scaling in the cloud
• Automating testing of MATLAB and Simulink artifacts in a CI process
• Deploying, running, and monitoring models and algorithms in production in the cloud

In this talk, get an introduction to System Composer™ and hear how it can be used by systems and design engineers to describe architectures, going from high level into detail. See through examples how this creates opportunities for increased traceability and analysis in your design process. Finally, explore the options for connecting System Composer to other MathWorks and third-party design tools.