Product Release Announcement Automotive Embedded Systems NXP Model-Based Design Toolbox for S32M2 – version 1.1.0   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 S32M2 version 1.1.0. This release supports automatic code generation for S32M2 peripherals and applications prototyping from MATLAB/Simulink for NXP S32M2 Automotive Microprocessors. This product adds support for S32M41, S32M242, S32M43, S32M244, S32M274, S32M276 MCUs and part of their peripherals, based on RTD MCAL components (ADC, AE, DIO, CAN, Can_Trcv, DPGA, GDU, GPT, LIN, LIN_Trcv, MCL, PWM, MCL, MCU, PORT, QDEC, SPI, UART). In this release, we have also added support for FreeMASTER, AMMCLib, and MATLAB support for the latest versions. The product comes with over 85 examples, covering all supported peripherals, and Simulink simulation modes Software-in-the-Loop, Processor-in-the-Loop, and External Mode. Target audience: This product is part of the Automotive SW – Model-Based Design Toolbox. FlexNet Location: https://nxp.flexnetoperations.com/control/frse/download?element=6481361 Technical Support: NXP Model-Based Design Toolbox for S32M2 issues will be tracked through the NXP Model-Based Design Tools Community space. Release Content: Automatic C code generation from MATLAB® & Simulink® for NXP S32M2 derivatives: S32M241 S32M242 S32M243 S32M244 S32M274 S32M276 Support for the following peripherals (MCAL components): ADC AE CAN CAN_Trcv DIO DPGA GDU GPT ISR LIN LIN_Trcv MCL MCU MEMORY PROFILER PWM PORT QDEC SPI UART Profiler in PIL mode Provides 2 modes of operation Basic – using pre-configured configurations for peripherals; useful for quick hardware evaluation and testing Advanced – using S32 Configuration Tool or EB Tresos to configure peripherals/pins/clocks Provides Motor Control examples MBDT for S332M2 1.1.0 provides examples for PMSM sensorless, open loop and closed-loop hall sensors motor control applications, supporting S32 Configuration Tools. Each of them has a detailed description of the hardware setup and an associated FreeMASTER project which can be used for control and data visualization. Integrates the Automotive Math and Motor Control Library version 1.1.38 All functions in the Automotive Math and Motor Control Functions Library v1.1.38 are supported as blocks for simulation and embedded target code generation. Integration with FreeMASTER MBDT for S332M2 1.1.0 delivers several Simulink example models and associated FreeMASTER projects to demonstrate how our toolbox interacts with the real-time data visualization tool and how it can be used for tuning embedded software applications. Support for Custom Default Project MBDT for S332M2 1.1.0 provides support for users to create their own custom default project. This could be very useful when having a custom board design – the configuration for it needing to be created only once. After that configuration is saved as a custom default project, it can be used for other models that are developed. Support for custom board initialization MBDT for S332M2 1.1.0 generates the components’ peripherals initialization function calls as configured in the Board Initialization window, which can be customized to each Simulink model. This feature allows users to set a custom order for the components initialization, the insertion of the Custom code sequences, or share the custom initialization with multiple Simulink models via the Export and Import functionality. Integration with S32 Config Tools version v1.7 Integration with S32 Design Studio MBDT for S332M2 1.1.0 automatically generates the <model_name>_Config folder, next to the Simulink model location, providing user the opportunity to easily import the generated code from Simulink into S32 Design Studio. Each time the code is generated, the  <model_name>_Config folder is updated with the new changes. Toolbox also provides a mechanism to launch an S32 Design Studio instance, with the imported generated code project in the Project Explorer tab from S32DS. Simulation modes       Toolbox provides support for the following simulation modes (each of them being useful for validation and verification): Software-in-Loop (SIL) Processor-in-Loop (PIL) External mode      Support for application execution profiling Custom Linker File and Startup Code Users can choose to use custom files for this process, from the Build Options group which can be found in the Target Hardware Resources, as illustrated in the image below. Examples for every peripheral/function supported       We have added over 60 examples, including: CDD Blocks (Ae, Dpga, Gdu, Mcl, Qdec) Communication (Can, Lin, Spi, Uart) AMMCLib IO Blocks (Adc, Dio, Pwm) ISR Blocks (Hardware Interrupt Handler) MCAL Blocks (Gpt) Utility Blocks (FreeMASTER, Memory, Profiler, Registers) Software-in-the-Loop / Processor-in-the-Loop / External mode 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 Support for MATLAB® versions R2021a R2021b R2022a R2022b R2023a R2023b R2024a R2024b   The NXP Model-Based Design Toolbox extends the MATLAB® and Simulink® experience by allowing customers to evaluate and use NXP’s S32M2 MCUs and evaluation board solutions out-of-the-box with:   Target Audience This release (MBDT for S32M2 1.1.0) is intended for technology demonstration, evaluation purposes, and prototyping of S32M2 MCUs and Evaluation Boards.   Useful Resources Examples, Trainings, and Support: https://community.nxp.com/community/mbdt DEMO Motor Control Rapid Prototyping on NXPs S32M2 with MathWorks and the Model-Based Design Toolbox This training shows how to design and develop motor control algorithms with Simulink® (MathWorks) and the Model-Based Design Toolbox for S32M2. Presentation introduces NXP’s S32M2 family, an integrated solution for 12V Motor Control and 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 target. The FreeMASTER software tool is used to control and monitor the algorithms running on the S32M2. First application focuses on a simple scalar control (also known as open-loop control or Volts per Hertz control) algorithm for a permanent magnet synchronous motor (PMSM). Second application shows how MATLAB and Simulink works together with the MBDT for S32M2 focusing on a workflow of implementing a predictive maintenance motor control application. Toolbox is used to acquire data from an accelerometer mounted on the motor. The motor is spinning at various speeds, and the vibrations are monitored using FreeMASTER. Data is transferred to MATLAB, where is preprocessed and a Support Vector Machine is trained. Then the resulted classifier is transferred to Simulink where together with the Model-Based Design Toolbox for S32M2 code is generated and deployed on the MCU. For more details about the demo mentioned above, please check this webinar a full demo description.        

  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    

Introduction With the latest advances in microcontrollers, they are getting faster and more efficient, being able to successfully run complex algorithms in a reasonable time. One important category are Artificial Intelligence algorithms. Using both NXP ® and MathWorks ® ecosystem, the steps to deploy an AI algorithm to NXP hardware are simplified and straight forward. The article provides guidance on how to implement a State-of-Charge (SoC) estimation algorithm based on a feedforward deep learning network developed by Mathworks' experts (Battery State of Charge Estimation in Simulink Using Deep Learning Network). The algorithm is then deployed on i.MX RT1060 Evaluation Kit using NXP Model Based Design Toolbox for I.MX RT. As the main objective of the article is to demonstrate how to run an AI algorithm on NXP evaluation board, the example is ran in Processor-in-the-Loop (PIL) simulation mode. This type of simulation represents an important step in the validation process of an algorithm, corner cases can be easily replicated as the input data can be directly loaded from MATLAB's workspace. The execution of the algorithm is done on the microcontroller. For a more detailed overview of the execution of the algorithm, code profiling options can be enabled to generate a report which details execution times.   What BMS is Battery Management System (BMS) is a critical component in battery-driven devices, such as electric vehicles. Their main objective is to ensure that the battery pack remains in an optimal and safe operating mode. At the core of the most tasks, the BMS must compute the State-of-Charge (SoC) estimation. To make a precise estimation, the algorithm requires an accurate model of the actual cells, which are difficult to characterize. An alternative to this approach is to create data driven models of the cell using AI methods such as neural networks.   Deep Learning Toolbox The Deep Learning Toolbox™ developed by Mathworks provides a framework for deep neural networks to be used in algorithms. It enables the user to use convolutional neural networks (ConvNets, CNNs) and long short-term memory (LSTM) networks to perform classification and regression on image, time-series and text data. The network and layer graphs are not mandatory to be created in MathWorks ecosystem, as other frameworks can be used, such as TensorFlow™ 2, TensorFlow-Keras, PyTorch ® .   Prerequisite Software To create, build and deploy a Simulink Model onto the i.MX RT RT1060 EVK, the following software is required: MATLAB R2022a Deep Learning Toolbox Simulink ® MATLAB ® Coder™ Simulink ® Coder™ Embedded Coder ®  Support Package for ARM Cortex-M Processors i.MX RT MBD Toolbox (version 1.3.0)   Prerequisite hardware The hardware required for this example is i.MX RT1060 Evaluation Kit. The i.MX RT1060 crossover MCUs are part of the EdgeVerse™ edge computing platform. The core of the MCU is a Arm ® Cortex ® -M7 core at 600 MHz. The device is fully supported by NXP’s MCUXpresso Software and Tools, a comprehensive and cohesive set of free software development tools.   Model - Overview The BatterySOCSimulinkEstimation model included in the Deep Learning Toolbox computes the SoC estimation using two methods: first method uses a neural network and the second one uses the extended Kalman filter algorithm. By plotting data generated by these two estimations and comparing it to the true values, it is possible to validate that the FNN predicts the SoC with an accuracy of 3 within a temperature range between -10 C and 25 C.   Note! Before making any modification to the model included in the toolbox, it is recommended to create a backup of the example in order to be able to revert to the original state. For this example, the predictions are done on the i.MX RT1060 evaluation board in PIL mode while the Kalman filter is locally computed on the computer. Referenced Model From the original model, the FNN block must be added in a new blank model. As the newly created model is used in a Referenced model, an input port must be added to received data (make sure the Port dimensions is set to 5), and one output port to return the data computed. The other settings for all these 3 blocks can be left default. Next, in the Model Settings the following changes must be made: Hardware Implementation Hardware Board: NXP MIMXRT1062xxxxA Target Hardware Resources Download Type: OpenSDA OpenSDA drive: Click on browse and select the partition assigned to the IMXRT1060 PIL Communication interface: Serial Interface Hardware UART: LPUART1 Serial port: The COM port assigned to the board (it can be found by using Device Manager or by running serialportlist command in MATLAB Command Window) Baudrate: 115200 Code generation Verification Check Enable portable word sizes   Top model Based on the BatterySOCSimulinkEstimation model included in the Deep Learning Toolbox, the FNN block must be removed (either deleted or commented). A ModelReference subsystem must be added to the model. In the Block Parameters of the ModelReference subsystem, select the model created and configured above. Simulation Mode must be set to Processor-in-the-Loop (PIL). Another modification that must be done is the sample time of the nnInput Data Read Memory block which must be changed from 0 (continuous) to -1 (inherited).   Next, in the Model Settings the following changes must be made: Hardware Implementation Hardware Board: NXP MIMXRT1062xxxxA Target Hardware Resources Download Type: OpenSDA OpenSDA drive: Click on browse and select the partition assigned to the IMXRT1060 PIL Communication interface: Serial Interface Hardware UART: LPUART1 Serial port: The COM port assigned to the board (it can be found by using Device Manager or by running serialportlist command in MATLAB Command Window) Baudrate: 115200 Code generation Verification Check Enable portable word sizes   Deployment and validation Now that both models (top model and referenced model) are configured, SIL/PIL manager can be opened from the APPS tab in Simulink. In the SIL/PIL tab, the simulation must be selected to SIL/PIL only (red rectangle) and the System Under Test to Model Blocks in SIL/PIL mode (blue rectangle). Before the simulation is started, the BatterySOCSimulinkEstimation_ini.m script must be executed to load the necessary data into MATLAB's workspace. The script can be found next to the Simulink Model included in the Deep Learning Toolbox. From the top model, the SOC scope can be opened to display the generated data. The simulation can be started from the RUN button within the scope. Note! Diagnostic Viewer can provide important information if there are any errors within the models. If the simulation is successfully deployed on the target, the data plotted into the scope should look like this:   Code profiling Code profiling is an important tool to validate an algorithm as it provides important information about the execution time. The time is measured by the timer configured in Model Settings -> Hardware Implementation -> Hardware board settings -> Target hardware resources -> Profiling Timers. By default, the PIT timer, channel 0, is used. The Code generation can be enabled from Model Settings -> Code Generation -> Verification -> Code execution time profiling -> Measure task execution time. The generated report can either be Coarse (referenced models and subsystems only) or Detailed (all function call sites). When the simulation is completed, a small window is opened. The Profiling report can be opened by clicking on the view the full code execution profiling report.   Conclusion The NXP and Mathworks ecosystems enable the users to deploy an Artificial Intelligence algorithm onto the NXP hardware. In the end, I strongly recommend the users interested in BMS and Artificial Intelligence to watch the Deploying a Deep Learning-Based State-Of-Charge (SOC) Estimation Algorithm to NXP S32K3 Microcontrollers webinar hosted by Javier Gazzarri (MathWorks) and Marius Andrei (NXP).   EdgeVerse and NXP are trademarks of NXP B.V. All other product or service names are the property of their respective owners. © 2023 NXP B.V. Arm, Cortex are trademarks and/or registered trademarks of Arm Limited (or its subsidiaries or affiliates) in the US and/or elsewhere. The related technology may be protected by any or all of patents, copyrights, designs and trade secrets. All rights reserved. PyTorch, the PyTorch logo and any related marks are trademarks of The Linux Foundation. MATLAB, Simulink, Stateflow and Embedded Coder are registered trademarks and MATLAB Coder, Simulink Coder, Deep Learning Toolbox are trademarks of The MathWorks, Inc. See mathworks.com/trademarks for a list of additional trademarks. TensorFlow, the TensorFlow logo and any related marks are trademarks of Google Inc.

        Product Release Announcement Automotive Processing NXP Model-Based Design Toolbox for HCP – version 1.2.0 RFP       The Automotive Processing, Model-Based Design Tools Team at NXP Semiconductors, is pleased to announce the release of the Model-Based Design Toolbox for HCP version 1.2.0. This release supports automatic code generation from MATLAB/Simulink for S32G2xx, S32S2xx, and S32R41 MPUs. This new product adds support for new MATLAB versions R2022a and R2022b for running in Processor-in-the-Loop mode.   FlexNet Location: https://nxp.flexnetoperations.com/control/frse/download?element=13897177   Technical Support: NXP Model-Based Design Toolbox for HCP issues will be tracked through NXP Model-Based Design Tools Community space. https://community.nxp.com/community/mbdt     Release Content Automatic C code generation from MATLAB® for NXP S32G2xx derivatives: S32G274A Automatic C code generation from MATLAB® for NXP S32S2xx derivatives: S32S247TV Automatic C code generation from MATLAB® for NXP S32R4x derivatives: S32R41 Supported Evaluation Boards GoldBox Development Platform (S32G-VNP-RDB2 Reference Design Board) GreenBox II Development Platform X-S32R41-EVB Development Board Support for MATLAB versions: R2020a R2020b R2021a R2021b R2022a R2022b Tools update for S32R41: S32 Flash Tool v2.1 S32 Debugger v3.5 Simulation mode: We provide support for Software-in-Loop (SIL) and Processor-in-Loop (PIL) simulation mode with code execution profiling: Includes an Example library with 16 examples that cover: Software-in-Loop (SIL), Processor-in-Loop (PIL) GUI to help you setup the toolbox and the evaluation board :     For more details, features, and how to use the new functionalities, please refer to the Release Notes document attached.   MATLAB® Integration The NXP Model-Based Design Toolbox extends the MATLAB® and Simulink® experience by allowing customers to evaluate and use NXP’s S32G2xx, S32S2xx, and S32R41  processors and evaluation board solutions out-of-the-box with: NXP Model-Based Design Toolbox for HCP version 1.2.0 (RFP) is fully integrated with MATLAB® environment in terms of installation:       Target Audience This release (1.2.0 RFP) is intended for technology demonstration, evaluation purposes, and prototyping S32G2xx, S32S2xx, and S32R41 and Evaluation Boards.   Useful Resources Examples, Trainings and Support: https://community.nxp.com/community/mbdt    

        Product Release Announcement Automotive Processing NXP Model-Based Design Toolbox for HCP – version 1.1.0 RFP       The Automotive Processing, Model-Based Design Tools Team at NXP Semiconductors, is pleased to announce the release of the Model-Based Design Toolbox for HCP version 1.1.0. This release supports automatic code generation from MATLAB/Simulink for S32G2xx, S32S2xx, and S32R41 MPUs. This new product adds support for running Processor-in-Loop and Software-in-Loop simulation on S32R41 (ARM Cortex-A53).   FlexNet Location: https://nxp.flexnetoperations.com/control/frse/product?child_plneID=683951   Technical Support: NXP Model-Based Design Toolbox for HCP issues will be tracked through NXP Model-Based Design Tools Community space. https://community.nxp.com/community/mbdt     Release Content Automatic C code generation from MATLAB® for NXP S32G2xx derivatives: S32G274A Automatic C code generation from MATLAB® for NXP S32S2xx derivatives: S32S247TV Automatic C code generation from MATLAB® for NXP S32R4x derivatives: S32R41 Supported Evaluation Boards GoldBox Development Platform (S32G-VNP-RDB2 Reference Design Board) GreenBox II Development Platform X-S32R41-EVB Development Board Support for MATLAB versions: R2020a R2020b R2021a R2021b Simulation mode: We provide support for Software-in-Loop (SIL) and Processor-in-Loop (PIL) simulation mode with code execution profiling:   Includes the HEV demo (S32G2xx, S32S2xx):   Includes the RADAR demo - MFSK Radar Range and Speed Estimation on Multiple Targets (S32R41), in collaboration with Gamax Laboratory Solutions Kft.:   Includes an Example library with 16 examples that cover: Software-in-Loop (SIL), Processor-in-Loop (PIL)   GUI to help you setup the toolbox and the evaluation board :     For more details, features and how to use the new functionalities, please refer to the Release Notes document attached.   MATLAB® Integration The NXP Model-Based Design Toolbox extends the MATLAB® and Simulink® experience by allowing customers to evaluate and use NXP’s S32G2xx, S32S2xx, and S32R41  processors and evaluation board solutions out-of-the-box with: NXP Model-Based Design Toolbox for HCP version 1.1.0 (RFP) is fully integrated with MATLAB® environment in terms of installation:       Target Audience This release (1.1.0 RFP) is intended for technology demonstration, evaluation purposes and prototyping S32G2xx, S32S2xx, and S32R41 and Evaluation Boards.   Useful Resources Examples, Trainings and Support: https://community.nxp.com/community/mbdt    

General Installer and Setup  How to install the license of MBDT for S32K3?  How to setup the S32K344 toolbox and EVB?  How to export the generated code to S32DS3.4? Export generated projects in MBDT for s32k3XX  Programming methods MBDT for S32k3 using P&E Multilink Custom code usage SENT Protocol Support in S32K3 MBDT Custom project usage How to use custom project configuration Sequential reset S32K344-Q172 sequential reset SIL / PIL / External Mode External mode External mode example wouldn't compile after update  S32K3X4EVB-Q257 with MBDT PIL Example: Not able to run Simple PIL S32CT example Peripherals ADC How to add a new ADC channel using the external configuration tool  SPI How to send 32 bit frames  DIO S32K3x4-Q172P_with_MBDT_Blink_Project DIO and PWM configuration issues ICU PWM Duty cycle measurement PWM PWM raising edge and falling edge detection Interrupt based PWM generation CAN FreeMASTER over CAN connection issue  Apps Motor Control SPI configuration MODEL based design tool box- 32 bit instruction (SIMULINK) 

          Product Release Announcement Automotive Processing NXP Model-Based Design Toolbox for S32K3xx – version 1.1.0 RTM     Austin, Texas, USA December 20, 2021 The Automotive Processing, Model-Based Design Tools Team at NXP Semiconductors, is pleased to announce the release of the Model-Based Design Toolbox for S32K3xx version 1.1.0. This release supports automatic code generation for S32K3xx peripherals and applications prototyping from MATLAB/Simulink for NXP S32K3xx Automotive Microprocessors. This new product adds support for S32K344 and S32K312 MCUs and part of their peripherals, based on RTD MCAL components (ADC, PWM, MCL, DIO, CAN, SPI, UART, GPT). To enable BMS applications development, we have added support for MC33775A battery cell controller (& MC33664PHY). In this release, we have also added 2 new motor control applications (for both PMSM and BLDC), as well as updated FreeMASTER, AMMCLib, and GCC compiler to the latest versions. The product comes with over 100 examples, covering everything that is supported, including demos for battery cell controllers (BCC) and motor control.   Target audience: This product is part of the Automotive SW – S32K3 Standard Software Package.   FlexNet Location: https://nxp.flexnetoperations.com/control/frse/download?element=12920897   Technical Support: NXP Model-Based Design Toolbox for S32K3xx 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 S32K3xx derivatives: S32K344 S32K312   Support for the following peripherals (MCAL components): ADC PWM MCL CAN SPI UART GPT DIO   Support for MC33775A battery cell controller & MC33664PHY The toolbox provides support for the MC33775A and MC33664. The MC33775A is a lithium-ion battery cell controller IC designed for automotive applications which perform ADC conversions of the differential cell voltages and battery temperatures, while the MC33664 is a transceiver physical layer transformer driver, designed to interface the microcontroller with the battery cell controllers through a high speed isolated communication network. The ready-to-run example provided with the MBDT for S32K3 shows how to communicate between the S32K344 and the MC33775A via the MC33664 transceiver. The MCU configures the battery cell controller to perform Primary and Secondary chains conversion, reads the cell voltages conversion results from the MC33775A, and displays the values to the user over the FreeMaster.     Added new motor control examples The toolbox provides examples for both 3-shunt PMSM and BLDC motor control applications. Each of them has a detailed description of the hardware setup and an associated FreeMASTER project which can be used for control and data visualization.     Support for custom default project configuration The toolbox provides support for users to create their custom default project configurations. This could be very useful when having a custom board design – only needing to create the configuration for it once. After it is saved as a custom default project, it can be used for every model that is being developed.     Support for AUTOSAR blockset (SW-C deployment) Updated to the latest version of RTD (v1.0.0) and GCC(v10.2) Provides 2 modes of operation: Basic – using pre-configured configurations for peripherals; useful for quick hardware evaluation and testing Advanced – using S32Configuration Tool or EB Tresos to configure peripherals/pins/clocks Integrates the Automotive Math and Motor Control Library release 1.1.26: All functions in the Automotive Math and Motor Control Functions Library v1.1.26 are supported as blocks for simulation and embedded target code generation.   FreeMASTER Integration We provide several Simulink example models and associated FreeMASTER projects to demonstrate how our toolbox interacts with the real-time data visualization tool and how it can be used for tuning embedded software applications.   Support for MATLAB versions We added support for the following MATLAB versions: R2020a R2020b R2021a R2021b   S32Design Studio Integration We provide a simple mechanism to let users the opportunity to export the code generated from Simulink and import it directly into S32Design Studio. This functionality can be useful if the model needs to be integrated into an already existing project or for debugging purposes.     Simulation modes: We provide support for the following simulation modes (each of them being useful for validation and verification): Software-in-Loop (SIL) Processor-in-Loop (PIL) External mode     Examples for every peripheral/function supported: We have added over 100 examples, including: Motor control applications (PMSM and BLDC) Communication (SPI, CAN, UART) AMMCLib Timer control (GPT) DIO FreeMASTER SIL / PIL / External mode   For more details, features, and how to use the new functionalities, please refer to the Release Notes document attached.   MATLAB® Integration The NXP Model-Based Design Toolbox extends the MATLAB® and Simulink® experience by allowing customers to evaluate and use NXP’s S32K3xx MCUs and evaluation board solutions out-of-the-box with: NXP Model-Based Design Toolbox for S32K3xx version 1.1.0 is fully integrated with MATLAB® environment in terms of installation:       Target Audience This release (1.1.0) is intended for technology demonstration, evaluation purposes, and prototyping S32K3xx MCUs and Evaluation Boards.   Useful Resources Examples, Trainings, and Support: https://community.nxp.com/community/mbdt    

Product Release Announcement EDGE PROCESSING  NXP Model-Based Design Toolbox for i.MX RT Crossover MCUs – version 1.2.0     The Edge Processing Tools Team at NXP Semiconductors is pleased to announce the release of the Model-Based Design Toolbox for i.MX RT 1xxx Series version 1.2.0. This release supports automatic code generation for peripherals and applications prototyping from MATLAB/Simulink for NXP’s i.MX RT 117x, 106x & 101x Series of crossover MCUs.   NXP Download Location https://www.nxp.com/webapp/swlicensing/sso/downloadSoftware.sp?catid=MCTB-EX   MATHWORKS Download Location https://www.mathworks.com/matlabcentral/fileexchange/81051-nxp-support-package-imxrt1xxx   Version 1.2.0 Release Content Automatic C code generation based on MCUXpresso SDK 2.9.1/2.9.2 drivers and MCUXpresso Configuration Tools 9.0 initializations from MATLAB®/Simulink® for: i.MX RT 1176: MIMXRT1176DVMAA,MIMXRT1176AVM8A,MIMXRT1176CVM8A i.MX RT 1175: MIMXRT1175DVMAA,MIMXRT1175AVM8A,MIMXRT1175CVM8A i.MX RT 1173: MIMXRT1173CVM8A i.MX RT 1172: MIMXRT1172DVMAA,MIMXRT1172AVM8A,MIMXRT1172CVM8A i.MX RT 1171: MIMXRT1171DVMAA,MIMXRT1171AVM8A,MIMXRT1171CVM8A i.MX RT 1061: MIMXRT1061CVJ5A,MIMXRT1061CVL5A,MIMXRT1061DVJ6A,MIMXRT1061DVL6A i.MX RT 1062: MIMXRT1062CVJ5A,MIMXRT1062CVL5A,MIMXRT1062DVJ6A,MIMXRT1062DVL6A i.MX RT 1064: MIMXRT1064CVJ5A,MIMXRT1064CVL5A,MIMXRT1064DVJ6A,MIMXRT1064DVL6A i.MX RT 1011: MIMXRT1011CAE4A,MIMXRT1011DAE5A   Multiple options for configuration of MCU packages, Build Toolchain and embedded Target Connections are available via Simulink Model Configuration UI       Multiple MCU peripherals and Drivers supported. The following subsystems highlighted in red as supported in Simulink environments in various forms: blocks, files, options i.MX RT 117x derivatives   i.MX RT 106x derivatives i.MX RT 101x derivatives     Basic and Advanced Simulink Block configuration modes via MCUXpresso Configuration Tools 9.0 UIs for Pins, Clocks, and Peripherals       MATLAB/Simulink versions 2019a – 2021b are supported for Design, Simulation, Code Generation, and Deployment of applications on i.MX RT 117x,106x & 101x Series. Other i.MX RT devices will be supported in future versions of the toolbox. Support for Software-in-Loop (SiL), Processor-in-Loop (PiL), and External Mode; RTCESL – Real-Time Control Embedded Software Motor Control and Power Conversion Libraries (limited support designed for Motor Control applications). A future update will enhance the number of functionalities supported by Simulink.     Simulink Example library with more than 190 models to showcase various functionalities:   Integrated PMSM Motor Control Sensor/Sensor-less application for both IMXRT1060-EVK and IMXRT1170-EVK:     Target Applications with MATLAB/Simulink This release of the Model-Based Design Toolbox can be used to design, build, and test applications from multiple domains: INDUSTRIAL AC Meters Motion Control Robotics HMI SMART CITY/HOME Video Surveillance Identification Appliances Speakers   AUTOMOTIVE HVAC ECU     Target Audience This release is intended for technology demonstration, evaluation purposes, and prototyping for i.MX RT 1xxx MCUs and their corresponding Evaluation Boards: EVK-MIMXRT1170 EVK-MIMXRT1060 EVK-MIMXRT1064 EVK-MIMXRT1010   Useful Resources Examples, Training, and Support: https://community.nxp.com/community/mbdt Technical by System Tools: https://web.microsoftstream.com/channel/618ab630-c8da-4fa8-ade8-5aa70a353124    

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

This video shows how to navigate within the integration Matlab help for NXP's Model-Based Design Toolbox for S32K1xx. The following items will be highlighted: Getting HELP Open Examples Support via Community

This video shows the main differences between basic and advanced modes for peripheral configuration

This video shows how easy it is to build a motor control application for BLDC with NXP's Model-Based Design Toolbox

This video demonstrates how to: Wake up on time interrupt Read temperature via FlexIO interface Relay information to host PC via UART interface Go to sleep to preserve the power

This video highlights the main features added in the version 4.1.0 of the NXP Model-Based Design Toolbox for S32K1xx Series

Wanna see & play something cool ?  You can see it live in June during Mathworks Expo:  - Munich, Germany on June 27th  - China on June 20th an 27th If you want more details - leave a comment below Check our video showing the demo:  Video Link : 7851 

Are you interested in such demo? You can see it live in June during Mathworks Expo in Munich, Germany on June 27th See how we built it here. If you want more details - leave a comment below

      Product Release Announcement Automotive Microcontrollers and Processors NXP Model-Based Design Toolbox for MPC57xx – version 3.0.0     Austin, Texas, USA February 18, 2019 The Automotive Microcontrollers and Processors’ Model-Based Design Tools Team at NXP Semiconductors, is pleased to announce the release of the Model-Based Design Toolbox for MPC57xx version 3.0.0. This release supports automatic code generation for peripherals and applications prototyping from MATLAB/Simulink for NXP’s MPC574xB/C/G/P series.   FlexNet Location https://nxp.flexnetoperations.com/control/frse/download?element=10769197   Activation link https://nxp.flexnetoperations.com/control/frse/download?element=10769197   Technical Support NXP Model-Based Design Toolbox for MPC57xx issues are tracked through NXP Model-Based Design Tools Community space. https://community.nxp.com/community/mbdt   Release Content Automatic C code generation based on PA SDK 2.0.0 RTM drivers from MATLAB®/Simulink® for NXP MPC574xB/C/G/P derivatives: MPC5744B, MPC5745B, MPC5746B                                                (*new) MPC5744C, MPC5745C, MPC5746C, MPC5747C, MPC5748C      (*new) MPC5746G, MPC5747G, MPC5748G                                               (*new) MPC5741P, MPC5742P, MPC5743P, MPC5744P                             (*upd) Multiple options for MCU packages, Build Toolchains and embedded Target Connections are available via Model-Based Design Toolbox MPC574x Simulink main configuration block Enhanced user experience with a complete redesign of all Simulink Library blocks compared with v.2.0.0 to support: Similar look & feel with Model-Based Design Toolbox for S32K14x Series Basic and Advanced configurations modes based on PA SDK 2.0.0 RTM standard API Integration with MathWorks SW environment: Installer, Help and online Add-on Manager for distribution and installation MPC574xP Ultra-Reliable MCU for Automotive & Industrial Safety Applications and MPC574xB/C/G Ultra-Reliable MCUs for Automotive & Industrial Control and summary of the peripherals coverage by Model-Based Design version 3.0.0 is highlighted in red:   Redesigned the main Simulink Embedded Target library for supporting future additions for other MPC57xx derivatives, Automotive Math and Motor Control Libraries and MPC57xx Examples:   Implement communication port auto discovery to allow easy configuration for downloading the generated code to NXP targets and new Diagnostic options to helps with model creation or migration. 100% MPC574x supported peripheral coverage with examples. Currently there are 102 examples available as part of the toolbox that exercise all the functionalities supported. The examples are grouped into two categories: MPC574x Generic examples that can be run on any of the MPC574x Evaluation Boards MPC574x Targeted examples that are configured for a single target (e.g.: might contains peripherals that are available only on a specific target) Motor Control examples for PMSM and BLDC based on FOC and 6-step commutation with Closed and Open loop control Enable MATLAB code profiler for NXP targets for measuring the function execution time using Software -in-the-Loop or Processor-in-the-Loop modes For more details, features and how to use the new functionalities, please refer to the Release Notes and Quick Start Guide documents attached.   MATLAB® Integration The NXP Model-Based Design Toolbox extends the MATLAB® and Simulink® experience by allowing customers to evaluate and use NXP’s MPC57xx MCUs and evaluation boards solutions out-of-the-box with: NXP Support Package for MPC57xx Online Installer Guide Add-on allows users to install NXP solution directly from the Mathwork’s website or directly from MATLAB IDE. The Support Package provide a step-by-step guide for installation and verification. NXP’s Model-Based Design Toolbox for MPC57xx version 3.0.0 is fully integrated with MATLAB® environment in terms of installation, documentation, help and examples;   Target Audience This release (v.3.0.0) is intended for technology demonstration, evaluation purposes and prototyping for MPC574xB/C/G/P MCUs and their corresponding Evaluation Boards: DEVKIT-MPC5744P PCB RevX1 SCH RevB DEVKIT-MPC5748G PCB RevA SCH RevB Daughter Card MPC574XG-256DS RevB Daughter Card X-MPC574XG-324DS RevA Daughter Card MPC5744P-257DS RevB1 Daughter Card SPC5746CSK1MKU6 Motherboard X-MPC574XG-MB RevD Motherboard MPC57XX RevC        

BLDC OpenLoop Voltage Control example for MPC574xP(Panther)+MotorGD Features: - Commutation based on HALL sensor transitions - Voltage read via SW1(++) and SW2(--) - Voltage can be read from POT if VoltageReqSource=0 - Motor can rotate CW (default) or CCW via SW1/SW2 Copyright (c) 2017 NXP version 1.0.1 Model Based Design ToolBox

Hello all, sharing the latest version of S12ZVM Power Dissipation Calculator started by Carlos Vazquez and Anita Maliverney. With this excel sheet is possible estimate the power dissipated for any MCU of S12ZVM family, considering: supply voltages, digital modules, gate drive unit, charge pump, communication transceivers, etc.   Updated static and dynamic consumption current of S12ZVMC256, S12ZVM32 and S12ZVMB. Regards.

    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