With R2022b MathWorks has introduced two new products and several enhanced features that simplify and automate Model-Based Design for engineers and researchers looking to deliver product innovations and breakthroughs.
The global battery management systems market is expected to reach $13.4 billion by 2026 and Bloomberg New Energy Finance attributes most of that growth to electric vehicles (EV). In fact, according to its latest report 58% of global passenger vehicle sales will come from EVs by 2040.
In response, Simscape Battery, one of the innovations introduced in the R2022b release, provides design tools and parameterized models for businesses designing battery systems.
Engineers and researchers will be able to use Simscape Battery to create digital twins, run virtual tests of battery pack architectures, design battery management systems, and evaluate battery system behaviour 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 Modelling, 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, which 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 labelling for training deep learning networks on medical images.
R2022b also introduces updates to MATLAB and Simulink tools, including:
AUTOSAR Blockset: Develop services-oriented applications using client-server ARA methods and deploy them on embedded Linux platforms. The tool lets users define data types and interfaces in an architecture model.
Fuzzy Logic Toolbox: Design, analyse, and simulate fuzzy inference systems (FIS) interactively using the updated Fuzzy Logic Designer app. In addition, the enhanced toolbox allows engineers and researchers to design type-2 FIS using command-line functions or the Fuzzy Logic Designer app.
HDL Coder: Generate optimised SystemC code from MATLAB for High-Level Synthesis (HLS) and use the frame-to-sample conversion for model and code optimization.
Model Predictive Control Toolbox: Use neural networks as prediction models for nonlinear model predictive controllers. In addition, the toolbox now lets users implement model predictive controllers that meet ISO 26262 and MISRA C standards.
