By navigating our site, you agree to allow us to use cookies, in accordance with our Privacy Policy.

MathWorks Unveils MATLAB and Simulink Release 2022b

R2022b also features the new Medical Imaging Toolbox.

MathWorks has unveiled Release 2022b (R2022b) of the MATLAB and Simulink product families.

Simscape BatteryR2022b introduces two new products and several enhanced features that simplify and automate Model-Based Design for engineers and researchers tasked with delivering product innovations and breakthroughs for their organizations.

The organization’s latest report shows that 58% of global passenger vehicle sales will come from EVs by 2040. Simscape Battery™, one of the top innovations introduced in the R2022b release, provides design tools and parameterized models for businesses designing these types of battery systems.

Engineers and researchers use Simscape Battery to create digital twins, run virtual tests of battery pack architectures, design battery management systems, and evaluate battery system behavior across normal and fault conditions.

The tool also automates the creation of simulation models that match desired pack topology and includes cooling plate connections so electrical and thermal responses can be evaluated.

“We’re excited to launch Simscape Battery as innovation in battery management systems is at an all-time high,” said Graham Dudgeon, Principal Product Manager, Electrical Systems Modeling, MathWorks. “The new product includes many design tools intended to simplify and automate Model-Based Design, including the Battery Pack Model Builder that lets engineers interactively create and evaluate different battery pack architectures.”

R2022b also features the new Medical Imaging Toolbox.

The toolbox provides tools for medical imaging applications to design, test, and deploy diagnostic and radiomics algorithms that use deep learning networks.

Medical researchers, scientists, engineers, and device designers can use Medical Imaging Toolbox for multi-volume 3D visualization, multimodal registration, segmentation, and automated ground truth labeling for training deep learning networks on medical images.


Aishwarya Saxena

A book geek, with creative mind, an electronics degree, and zealous for writing.Creativity is the one thing in her opinion which drove her to enter into editing field. Allured towards south Indian cuisine and culture, love to discover new cultures and their customs. Relishes in discovering new music genres.

Related Articles

Upcoming Events