S32K3 - Videos

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S32K3 - Videos

S32K3 - Videos

This page summarizes all Model-Based Design Toolbox videos related to S32K3 Product Family.

 NXP MBDT - S32K3 Updates

In this video, we discuss the Model-Based Design paradigm and how to take advantage of the MathWorks ecosystem to generate C code automatically for the NXP S32K3xx. We start our discussion with details about MBDT Concept, Development flow, and Advantages.

Then we compare the NXP's MBDT for S32K1 vs MBDT for S32K3 where we introduce the usage of an "external configuration" tool to handle the MCU Clocks, Pins, and Components configuration particular the NXP S32 Configuration Tools and EB tresos Studio. We then explain how the new paradigm matches a "true" Model-Based Design Approach and helps the development engineers. Finally, we discuss the Toolbox for S32K3, what NXP products integrate, and what applications look like.

Deploying AUTOSAR and Non-AUTOSAR Software Components on NXP S32K3 with MathWorks® Tools

Link to the recording here

AUTOSAR Classic is the proven standard for traditional automotive applications such as powertrain, chassis, body and interior electronics and more. More frequently, OEMs and suppliers would prefer to reuse the tested and proven legacy (non- AUTOSAR) ECU software in next-generation AUTOSAR ECUs.

In this webinar, NXP and MathWorks will show how to use NXP Model-Based Design Toolbox (MBDT) together with MathWorks® Simulink® and Embedded Coder® to develop and deploy MCAL configured (non-AUTOSAR) applications on NXP S32K3 microcontrollers for general purpose. Furthermore, we will illustrate how to convert tested non-AUTOSAR application components to AUTOSAR and then verify and deploy MCAL configured AUTOSAR compliant production code on an S32K3 MCU.

Deploying a Deep Learning-Based State-of-Charge (SoC) Estimation Algorithm to NXP S32K3 Microcontrollers

Link to the recording here

Battery management systems (BMS) ensure safe and efficient operation of battery packs in electric vehicles, grid power storage systems, and other battery-driven equipment. One major task of the BMS is estimating state of charge (SoC). Traditional methods for SoC estimation require accurate battery models that are difficult to characterize. An alternative to this is to create data driven models of the cell using AI methods such as neural networks.

This webinar shows how to use Deep Learning Toolbox, Simulink, and Embedded Coder to generate C code for AI algorithms for battery SoC estimation and deploy them to an NXP S32K3 microcontroller. Based on previous work done by McMaster University on Deep Learning workflows for battery state estimation, we use Embedded Coder to generate optimized C code from a neural network imported from TensorFlow and run it in processor-in-the-loop mode on an NXP S32K3 microcontroller. The code generation workflow will feature the use of the NXP Model-Based Design Toolbox, which provides an integrated development environment and toolchain for configuring and generating all the necessary software to execute complex applications on NXP MCUs. 

A Model-Based Design (MBDT) Environment for Motor Control Algorithm Development

Link to the recording here 

This webinar, co-hosted with MathWorks, shows how to design and develop Motor Control algorithms with Simulink®, using the Embedded Coder and Model-Based Design Toolbox for S32K3xx.

We will introduce the scalable S32K3 MCU family and present its specific motor control modules. We will show how to access and configure the MCU peripherals making the Simulink model hardware aware, and ready to generate, build and deploy the application on the hardware. We will focus on Field Oriented Control (FOC) algorithm and implement a sensorless control of a permanent magnet synchronous motor (PMSM). The FreeMASTER application will be used to control and monitor the algorithm running on the S32K344.

NXP MBDT for S32K3 provides an integrated development environment and toolchain for configuring and generating all the necessary software to execute complex applications on NXP MCUs directly from Simulink®.


Speed-Up BMS Application Development with NXP's High-Voltage Battery Management System Reference Design and Model-Based Design Toolbox (MBDT)

Link to the recording here 

This webinar shows how to design and develop Battery Management Systems, with NXP's High-Voltage BMS Reference Design and Model-Based Design Toolbox for S32K3xx, with Simulink® and Embedded Coder.

During this webinar, we will introduce the ASIL D High Voltage Battery Management System Reference Resign that comprises a Battery Management Unit (BMU), Cell Monitoring Units (CMU), and a Battery Junction Box (BJB). NXP's HV-BMS Reference Design is a robust and scalable solution including hardware designs, production-ready software drivers, and safety libraries, as well as extensive ISO 26262 Functional Safety documentation. The design significantly reduces the development effort and enables an improved time to market with the latest chipset innovations.

Speed Up Electrification Solutions Using NXP Tools

Link to the recording here 

This video provides an overview of the NXP Software and Tools solutions, designed to help customers to speed up application development with design, simulation, implementation, deployment, testing, and validation.

During this session, you will learn about all the steps required to build complete solutions like battery management systems with NXP in-house solutions and NXP Model-Based Design Toolbox with simulation and code generation.

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Last update:
‎03-28-2023 08:10 AM
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