NXPモデルベース・デザイン・ツールナレッジベース

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This video explains how to use a three phase inverter to control the voltage applied on PMSM using various PWM Modulation techniques like: bipolar modulation unipolar modulation sinusoidal modulation space vector modulation third harmonic injection The goal of this video is to cover the topic of Space Vector Modulation and PWM generation that represents the basics for applications we are going to develop throughout https://community.nxp.com/thread/464336 .

This video explains the basics of the Permanent Magnet Synchronous Motors modes of operation with Field Oriented Control. It is not intended to replace a good engineering handbook and to go thru all the details of construction or mathematical models of the PMSM. The topics highlighted in this video are chosen to provide specific details that represents the basics of PMSM motor control theory. The goal of this video is to refresh your knowledge about the motors and to explain some key aspects of the theory behind PMSM and Field Oriented Control that we are going to use in the next modules of the https://community.nxp.com/thread/464336

This video shows the overall motor control application developed with Model Based Design Toolbox. We are going to assemble all the blocks developed throughout this course and we will have the motor running under Speed Controller supervision. We also discuss about the FreeMASTER and you can easily create nice control panels for the applications and how you can validate the Speed Controller and overall Motor Control application. We discuss about: - Speed Controller implementation in Simulink for real time systems; - Motor and Inverter protection for over-current, over- and under-voltage; - FreeMASTER control panel using HTML and Java Script; - Various tests on the MPC5744P DevKit and MotorGD DevKit; NOTE: Chinese viewers can watch the video on YOUKU using this link 注意：中国观众可以使用此链接观看YOUKU上的视频

In this video we discuss about control system theory and the mathematics behind the speed controller designing process. We are going to analyse the control system stability based on poles and zeros location and then we will compute the PI speed controller gains using the Root Locus allocation method. For the cases where the system transfer function is unknown we are discussing Ziegler Nichols method for finding the controller gains and we are going to verify the control system designing process by simulating a BLDC motor behavior and building a PI speed controller to handle the system response. We discuss about: - How to choose the controller type based on system transfer function; - How to analyze system stability starting from the characteristic polynomial; - What are the gain, zeros and poles of closed loop transfer function; - Root Locus allocation method based on second order ideal model with dumping factor and natural frequency; - Ziegler Nichols tuning methods; - Simulink models for BLDC motor and PI Speed Controller NOTE: Chinese viewers can watch the video on YOUKU using this link 注意：中国观众可以使用此链接观看YOUKU上的视频

In this video we show how to build, simulate and test a speed estimator based on Hall Sensors for a BLDC motor. The estimator is first tested under Matlab Simulink environment and then ported into the Open Loop Control Simulink model and tested on the MPC5744P Development Kit with FreeMASTER over CAN interface. We discuss about: - How to compute the speed; - How to build a speed estimator based on Hall sensors; - Step-by-step model building an enhancements; NOTE: Chinese viewers can watch the video on YOUKU using this link 注意：中国观众可以使用此链接观看YOUKU上的视频

In this video we discuss about Open Loop Control strategy and for the first time in this course we will put together all the models we have created so far and build the Simulink model that will allow us to rotate the BLDC motor. We discuss about: - Open Loop Control diagram; - Step-by-step model building an enhancements; - Test the open loop control system on the BLDC motor; NOTE: Chinese viewers can watch the video on YOUKU using this link 注意：中国观众可以使用此链接观看YOUKU上的视频

特集記事

Product Release Announcement Automotive Embedded Systems NXP Model-Based Design Toolbox for S32Z/E – version 1.3.0 The Automotive Processing, Model-Based Design Tools Team at NXP Semiconductors, is pleased to announce the release of the Model-Based Design Toolbox for S32Z/E version 1.3.0. This release supports automatic code generation for ARM Cortex-R52 and DSP/ML processor cores from MATLAB and Simulink for NXP S32Z/E Automotive Real-Time Processors. This new release supports S32Z/E2 families and its cores (Real-Time ARM Cortex-R52 cores and DSP/ML processor). It also supports Multicore, 41 Operators highly optimized for DSP/ML processor, Processor-in-Loop Simulation mode, RTD components (ADC, PWM, DIO, CAN, UART, GPT), FreeMASTER, AMMCLib, and execution profiling. The product comes with 120 examples, covering all DSP/ML processor Operators and demonstrating the usage of the peripherals (e.g.: I/O control, timers and scheduling, communication) and multicore concurrent execution. Target audience: This product is part of the Automotive SW – Model-Based Design Toolbox. FlexNet Location: https://nxp.flexnetoperations.com/control/frse/download?element=6450481 Technical Support: NXP Model-Based Design Toolbox for RADAR issues will be tracked through the NXP Model-Based Design Tools Community space. https://community.nxp.com/community/mbdt Release Content: Automatic C code generation from MATLAB® for NXP S32Z2/E2 packages, including rev. B0 S32E2xx-bga975 S32Z2xx-bga594 S32Z2xx-bga400 Automatic C code generation from MATLAB® for NXP S32Z2/E2 cores ARM Cortex-R52 Cluster 0 and Cluster 1 cores DSP/ML processor Multicore support using Concurrent Execution from Simulink Homogeneous multicore execution between ARM Cortex-R52 Cluster 0 and Cluster 1 cores using IPCF Heterogenous multicore execution between ARM Cortex-R52 Cluster 0 Core 0 and SPF2 core using OpenAMP MCAL components supported (based on RTD version 2.0.0) ADC PWM DIO CAN UART GPT Software-in-the-Loop and Processor-in-the-Loop (SIL/PIL) simulation modes MATLAB scripts Simulink models Includes MATLAB API and Simulink Library blocks for the 41 Operators highly optimized for DSP/ML processor Includes AMMCLib (v1.1.38) blocks and examples FreeMASTER support and examples Support for MATLAB versions: R2022a R2022b R2023a R2023b R2024a 120 examples: 41 Operators for DSP/ML processor Multicore I/O control Timers and scheduling Communication (CAN) SiL, PiL FreeMASTER For more details, features, and how to use the new functionalities, please refer to the Release Notes and Quick Start Guides documents attached. MATLAB® Integration: The NXP Model-Based Design Toolbox extends the MATLAB® experience by allowing customers to evaluate and use ARM Cortex-R52 cores and DSP/ML processor from NXP’s S32Z/E Realt-Time Processors and evaluation board solutions out-of-the-box. NXP Model-Based Design Toolbox for S32Z/E version 1.3.0 is fully integrated within MATLAB® environment. Target Audience: This release (1.3.0) is intended for technology demonstration, evaluation purposes, and prototyping on NXP S32Z/E Real-Time Processors and Evaluation Boards. Useful Resources: Examples, Trainings, and Support: https://community.nxp.com/community/mbdt

特集記事

Product Release Announcement Automotive Processing NXP Model-Based Design Toolbox for RADAR – version 1.0.0 The Automotive Embedded Systems, Model-Based Design Tools Team at NXP Semiconductors, is pleased to announce the release of the Model-Based Design Toolbox for RADAR version 1.0.0. This release supports automatic code generation for ARM Cortex-A53, NXP SPT Accelerator and NXP LAX Accelerator cores from MATLAB for NXP S32R45 Automotive Microprocessors. This release adds support for code generation and execution on both LAX cores, OpenMP code generation for parallel execution of for loops, and Processor-in-the-Loop (PIL) simulation, improves the code generation and Radar processing demo, and adds support for new exponential, logarithmic, min, max, and thresholding LAX kernels. The product comes with 60+ examples, covering the supported RSDK SPT and LAX Kernels from MATLAB API and demonstrating the programming of the LAX accelerator from MATLAB environment. Target audience: This product is part of the Automotive SW – Model-Based Design Toolbox. FlexNet Location: https://nxp.flexnetoperations.com/control/frse/download?element=6450491 Technical Support: NXP Model-Based Design Toolbox for RADAR issues will be tracked through the NXP Model-Based Design Tools Community space. https://community.nxp.com/community/mbdt Release Content: Automatic C code generation from MATLAB® for NXP S32R45: ARM Cortex-A53 NXP LAX Accelerator Code generation and execution on both LAX cores Support for execution of RSDK SPT kernels: rangeFFT, dopplerFFT, NonCohComb Support Linux application build and run NXP Auto Linux BSP 37.0 for S32R45 Includes MATLAB API for additional RSDK LAX Kernels highly optimized for LAX accelerator add, sub, mul, div, times, cT, inv abs, abs2, sqrtAbs, conj, norm, norm2 diag, eye, zeros, ones, find, sort exp, log, log2, log10, min, max, thresbit cospi, sinpi, tanpi, cispi, sincpi acospi, asinpi, atanpi, atan2pi Processor-in-the-Loop (PIL) simulation mode Improved code generation and reduced memory usage Support for Radar SDK version 1.2.0 Support for MATLAB versions: R2023a R2023b R2024a R2024b More than 60 examples showcasing the supported functionalities: Cholesky Gauss-Newton Eigen (new) Kalman Filter Linear Regression Large Matrix Multiplication Navier-Stokes QR Factorization (updated) MUSIC DoA (updated) Radar processing demo – Automated Driving Toolbox scenario (updated) Standalone and Processor-in-the-Loop (PIL) simulation Range FFT, Doppler FFT, and Non-Coherent Combining offloaded to NXP SPT accelerator MUSIC DoA offloaded to NXP LAX accelerator Radar processing demo – RoadRunner Toolbox scenario (new) Processor-in-the-Loop (PIL) simulation For more details, features, and how to use the new functionalities, please refer to the Release Notes and Quick Start Guides documents attached. MATLAB® Integration: The NXP Model-Based Design Toolbox extends the MATLAB® experience by allowing customers to evaluate and use ARM Cortex-R52 core, NXP SPT Accelerator, and NXP LAX Accelerator from NXP’s S32R45 processor and evaluation board solutions out-of-the-box. NXP Model-Based Design Toolbox for RADAR version 1.0.0 is fully integrated with MATLAB® environment. Target Audience: This release (1.0.0) is intended for technology demonstration, evaluation purposes, and prototyping on NXP S32R45 Processors and Evaluation Boards. Useful Resources: Examples, Trainings, and Support: https://community.nxp.com/community/mbdt

特集記事

Product Release Announcement Automotive Embedded Systems NXP Model-Based Design Toolbox for LAX – version 1.2.0 RTM The Automotive Embedded Systems, Model-Based Design Tools Team at NXP Semiconductors, is pleased to announce the release of the Model-Based Design Toolbox for LAX version 1.2.0 RTM. This release supports automatic code generation for ARM Cortex-A53 and NXP LAX Accelerator cores from MATLAB for NXP S32R45 Automotive Microprocessors. This release adds support for RSDK 1.2.0, improves to code generation and Radar processing demo, and adds support for new trigonometric LAX kernels. The product comes with 60 examples, covering the supported RSDK LAX Kernels by MATLAB API and demonstrating the programming of the LAX accelerator from MATLAB environment. Target audience: This product is part of the Automotive SW – Model-Based Design Toolbox. FlexNet Location: https://nxp.flexnetoperations.com/control/frse/download?element=3983168 Technical Support: NXP Model-Based Design Toolbox for LAX issues will be tracked through the NXP Model-Based Design Tools Community space. https://community.nxp.com/community/mbdt Release Content: Automatic C code generation from MATLAB® for NXP S32R45: ARM Cortex-A53 NXP LAX Accelerator Support Linux application build and run NXP Auto Linux BSP 37.0 for S32R45 Includes MATLAB API for additional RSDK LAX Kernels highly optimized for LAX accelerator add, sub, mul, div, times, cT, inv abs, abs2, sqrtAbs ¸conj, norm, norm2 diag, eye, zeros, ones, find, sort cospi, sinpi, tanpi, cispi, sincpi acospi, asinpi, atanpi, atan2pi Improved code generation and reduced memory usage Support for Radar SDK version 1.2.0 Support for MATLAB versions: R2021a R2021b R2022a R2022b R2023a R2023b R2024a More than 60 examples showcasing the supported functionalities: Cholesky Gauss-Newton Eigen (new) Kalman Filter Linear Regression Navier-Stokes QR Factorization (updated) MUSIC DoA (updated) Radar processing demo (updated) Range FFT, Doppler FFT, and Non-Coherent Combining offloaded to NXP SPT accelerator MUSIC DoA offloaded to NXP LAX accelerator For more details, features, and how to use the new functionalities, please refer to the Release Notes and Quick Start Guides documents attached. MATLAB® Integration: The NXP Model-Based Design Toolbox extends the MATLAB® experience by allowing customers to evaluate and use NXP LAX Accelerator from NXP’s S32R45 MPU and evaluation board solutions out-of-the-box. NXP Model-Based Design Toolbox for LAX version 1.2.0 is fully integrated with MATLAB® environment. Target Audience: This release (1.2.0 RTM) is intended for technology demonstration, evaluation purposes, and prototyping on NXP S32R45 MCUs and Evaluation Boards. Useful Resources: Examples, Trainings, and Support: https://community.nxp.com/community/mbdt

NXPモデルベース・デザイン・ツールナレッジベース

NXP Model-Based Design Tools Knowledge Base

ディスカッション

MBDT Happy New Year 2020

MBDT S32K1xx v4.1.0 General Updates

NXP CUP - MBDT Demo

Torque Control with S32K14x and MotorGD Development Kits Using Model-Based Design Toolbox

V/F Scalar Control of PMSM using Model-Based Design Toolbox and S32K

How to Convert DC to AC Voltage Using Various PWM Modulation Techniques

How to Build a FOC Control System for PMSM using S32K144EVB

How PMSM Works With Field Oriented Control

Control an LED via Push Button with Model-Based Design Toolbox on S32K

S32K1xx - NXP’s Model-Based Design Toolbox Installation

S32K1xx - Help

S32K1xx - BASIC and ADVANCED Modes for Configuration

S32K1xx – Motor Control Applications

S32K1xx – Implement full-duplex SPI via FlexIO interface

S32K1xx - Low Power Modes Demonstration

Motor Control Class: Motor Control System

Motor Control Class: Closed Loop Control

Motor Control Class: Speed Estimator

Motor Control Class: Open Loop Control System for a BLDC Motor

Model Based Design - Test Platform

NXP Model-Based Design Toolbox for S32Z/E - version 1.3.0

NXP Model-Based Design Toolbox for RADAR - version 1.0.0

NXP Model-Based Design Toolbox for LAX v1.2.0 - Product Release Announcement