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Product Release Announcement EDGE PROCESSING NXP Model-Based Design Toolbox for DSC MC56F8x MCUs - version 1.0.0 Bucharest, Romania December 15th , 2021 The Edge Processing Tools Team at NXP Semiconductors is pleased to announce the release of the Model-Based Design Toolbox for DSC MC56F8x Series version 1.0.0. This release supports automatic code generation for peripherals and applications prototyping from MATLAB/Simulink for NXP’s DSC MC56F81xxx and MC56F83xxx Series of MCUs based on DSP568000E core. NXP Download Location https://www.nxp.com/webapp/swlicensing/sso/downloadSoftware.sp?catid=MCTB-EX MATHWORKS Download Location https://www.mathworks.com/matlabcentral/fileexchange/103600-nxp-support-package-dsc Version 1.0.0 Release Content Automatic C code generation based on MCUXpresso SDK 2.7.3 drivers and MCUXpresso Configuration Tools 10.0 initializations from MATLAB®/Simulink® for: MC56F81xxx MC56F81868VLH, MC56F81646VLF, MC56F81648VLH, MC56F81663VLC, MC56F81666VLF, MC56F81668VLH, MC56F81743VLC, MC56F81746VLF, MC56F81748VLH, MC56F81763VLC, MC56F81766VLF, MC56F81768VLH, MC56F81866VLF, MC56F81643VLC MC56F83xxx MC56F83789VLL, MC56F83683VLH, MC56F83686VLL, MC56F83689VLL, MC56F83763VLH, MC56F83766VLK, MC56F83769VLL, MC56F83783VLH, MC56F83786VLK, MC56F83663VLH 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 MC56F81xxx derivatives MC56F83xxx derivatives Basic and Advanced Simulink Block configuration modes via MCUXpresso Configuration Tools 10.0 UIs for Pins, Clocks, and Peripherals MATLAB/Simulink versions 2020a – 2021b are supported for Design, Simulation, Code Generation, and Deployment of applications on MC56F81xxx and MC56F83xxx Series. Other MC56F8x devices will be supported in future versions of the toolbox. Support for Software-in-Loop (SiL), Processor-in-Loop (PiL); RTCESL – Real-Time Control Embedded Software Motor Control and Power Conversion Libraries for DSP568000E core. Simulink Example library with more than 100 models to showcase various functionalities: Integrated PMSM Motor Control Sensor/Sensor-less application for MC56F83000-EVK: Integrated application that uses the on board FXOS8700CQ accelerometer and magnetometer sensor for both MC56F81000-EVK and MC56F83000-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 Target Audience This release is intended for technology demonstration, evaluation purposes, and prototyping for DSC MC56F8x MCUs and their corresponding Evaluation Boards: EVK-MC56F81000 EVK-MC56F83000 Useful Resources Examples, Training, and Support: https://community.nxp.com/community/mbdt

Product Release Announcement Automotive Processing NXP Model-Based Design Toolbox for S12ZVMx – version 1.4.0 Austin, Texas, USA September 9, 2020 The Automotive Processing, Model-Based Design Tools Team at NXP Semiconductors, is pleased to announce the release of the Model-Based Design Toolbox for S12ZVMx version 1.4.0. This release supports automatic code generation for S12ZVM peripherals and applications prototyping from MATLAB/Simulink for NXP S12ZVMx Automotive Microprocessors. This new release adds extended MATLAB version support (R2015a-R2020a), integrates with AMMCLib v1.1.21, is compatible with MathWorks Automotive Advisory Board checks, adds over 50 new examples and more. FlexNet Location: https://www.nxp.com/webapp/swlicensing/sso/downloadSoftware.sp?catid=MCTB-EX Activation link: https://www.nxp.com/webapp/swlicensing/sso/downloadSoftware.sp?catid=MCTB-EX Technical Support: NXP Model-Based Design Toolbox for S12ZVMx issues are 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 S12ZVMx derivatives: S12ZVM 32/L31/16: MC9S12ZVM16 MC9S12ZVML31 MC9S12ZVM32 S12ZVML/C 128/64/32: MC9S12ZVML32 MC9S12ZVML64 MC9S12ZVMC64 MC9S12ZVML128 MC9S12ZVMC128 S12ZVMC256: MC9S12ZVMC256 Integrates the Automotive Math and Motor Control Library release 1.1.21: All functions in the Automotive Math and Motor Control Functions Library v1.1.21 are supported as blocks for simulation and embedded target code generation for: Bit Accurate Model for 16-bit fixed-point implementation Bit Accurate Model for 32-bit fixed-point implementation Bit Accurate Model for floating-point single precision implementation Extended support for MATLAB versions We extended support for our toolbox to cover a wider range of MATLAB releases – starting from R2015a and going up to R2020a. This way we want to avoid locking out users that have constraints regarding MATLAB versions. Motor control examples We have added new motor control examples – BLDC (closed loop) and PMSM (closed loop, sensorless): MAAB Checks (MathWorks Automotive Advisory Board) The toolbox is compatible with MathWorks Automotive Advisory Board checks – reports can be generated from Model Advisor: Updated examples: We have added over 50 new examples, including: Motor control (both BLDC and PMSM) AMMCLib GDU (Gate Drive Unit) Profiler 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 S12ZVMx MCUs and evaluation boards solutions out-of-the-box with: NXP Support Package for S12ZVMx 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 Model-Based Design Toolbox for S12ZVM version 1.4.0 is fully integrated with MATLAB® environment in terms of installation: Target Audience This release (1.4.0) is intended for technology demonstration, evaluation purposes and prototyping S12ZVMx MCUs 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 1.3.0 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 1.3.0. This release supports automatic code generation from MATLAB/Simulink for S32G2xx, S32R41x, and S32S2xx MCUs. This new product adds support S32R41 Cut 1.1 and S32G3, C++ code generation for S32G2 and S32G3, Radar examples for S32R41, and support for MATLAB versions R2021a - R2023b for running in Software-in-the-Loop and Processor-in-the-Loop modes. FlexNet Location: https://nxp.flexnetoperations.com/control/frse/download?element=3742498 Technical Support: NXP Model-Based Design Toolbox for HCP 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 S32G2xx derivatives: S32G274A Automatic C code generation from MATLAB® for NXP S32G3xx derivatives: S32G399A Automatic C code generation from MATLAB® for NXP S32R4x derivatives: S32R41 (including Cut 1.1) Automatic C code generation from MATLAB® for NXP S32S2xx derivatives: S32S247TV Supported Evaluation Boards GoldBox 2 Development Platform (S32G-VNP-RDB2 Reference Design Board) GoldBox 3 Development Platform (S32G-VNP-RDB3 Reference Design Board) X-S32R41-EVB Development Board GreenBox 2 Development Platform Support for MATLAB® versions: R2021a R2021b R2022a R2022b R2023a R2023b S32G2 and S32G3 support: SIL and PIL simulation modes with code execution profiling. C++ code generation. S32R41 support: SIL and PIL simulation modes. Code execution profiling using PMU cycle counter. Tools updates: S32 Flash Tool v2.1.4, S32 Debugger v3.5 Includes an Example library with 20+ examples that cover: Software-in-Loop (SIL), Processor-in-Loop (PIL) MathWorks Automotive Adaptive Cruise Control Using FMCW and MFSK Technology examples ported to S32R41: MSFK Radar Range and Speed Estimation of Multiple Targets FMCW Radar Multiple Targets Range and Speed Estimation 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, S32G3xx, S32S2xx, and S32R41 MCUs and evaluation board solutions out-of-the-box with: Model-Based Design Toolbox for S32M2xx version 1.3.0 is fully integrated with MATLAB® environment in terms of installation: Target Audience This release (1.3.0 RFP) is intended for technology demonstration, evaluation purposes and prototyping of S32G2xx, S32G3xx, S32R41, and S32S2xx MCUs and Evaluation Boards.. Useful Resources Examples, Training, and Support: https://community.nxp.com/community/mbdt

In this video we show the hall pattern identification procedure that can be applied to any motor in case you have no datasheet available. We will read the hall sensors outputs via the microprocessor and save the information for later use. We show: - How to prepare the Hardware setup - How to go over each identification table - row by row - to apply DC voltage and rotate the rotor in different sectors 360 degrees. 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

1. Introduction The scope of this article is to show how easy it is to use MBDT, FreeMASTER and some knowledge in electronics to create a simple and useful project: monitor USB voltage and current consumption. I used this setup it to monitor USB voltage and current while my smartphone is charging, but it can be used in other purposes too, like monitoring power consumption of some devices connected on USB charger/power bank/PC, or it can be used to find some charging issues, or maybe you just want to find out if your phone charger supports fast charging, or to characterize a power bank. 2. Overview 2.1 Functional Description This project can measure USB voltage and current by measuring USB voltage and a voltage drop across a resistor through which current flows from a USB power source to a USB load. The voltage given by current flow is amplified by an electronic circuit and sampled by MPC5744P-DEVKIT board through the ADC converter, then data is sent to PC and then are displayed through a FreeMASTER project as numerical values and as oscilloscope chart. The MPC5744P-DEVKIT board is programmed by MBDT. To build this simple project, you need three components: Matlab with MBDT toolbox installed, FreeMASTER Run-Time Debugging Tool, a very simple electronic circuit, and an MPC5744P-DEVKIT. As can be seen in fig.1, the project can be split into two main parts: Hardware Setup and Software Setup. Fig. 1: USB Voltage And Current Monitor block diagram 2.1 Hardware Setup Custom Electronic Board The simplest way to measure current is to use a simple resistor connected in series with the load (USB output in our case). The Ohm law gives us a linear relationship between voltage and current in an electrical circuit: U = R * I U is the voltage (measured in volts V) drop across the resistor, R is the resistance of the resistor (measured in ohm Ω) and I is the current (measured in amps A) which we need to measure. Most of the USB chargers can supply a maximum of 3A and most of the smartphones can drain less than 3A. Giving that I considered designing this circuit to measure around maximum 3A. Let suppose that we use a simple 1ohm resistor. If we do simple math using Ohm formula, then it can be seen that for 3A the voltage across our resistor (there) will be 3V (U = 1 * 3). Fig. 2: USB connectors and current "sensor" In Fig. 2 on the left side is a USB input connector, on the right side is the output USB connector and both GND lines are connected through R1 current sensor. The current "I" will flow, as can be seen in Fig. 2, from USB input through VBUS line to VBUS on USB output, than will flow through our load connected to USB output and then through GND on the same connector thru R1 and at least to GND on USB input connector. This current will create a voltage across R1 (UR1) equal with 3V (if we use 3 amps current and 1-ohm resistor). One of USB standard charging it specifies that the lowest (standard) voltage it's 5V. In our case, using this 1 ohm resistor will cause 3V loss, then the voltage at USB outputs will be 2V (unacceptable). In most of the digital electronic circuits, when it's used 5 volts power, the voltage tolerance it's about 10% (0.5V) which means the voltage can be between 4.5V and 5.5V. Let's try to create a maximum voltage drop across this resistor about 3 times lower than the 0.5V, e.g.: 150mV. Then the current sensor resistor is R1 = 0.15V / 3A = 0.05ohm. To measure this drop voltage we could use any ADC channel on MPC5744P-DEVKIT, but if the voltage reference of ADC is set to 5V, the resolution of ADC is 5V/4096 = 1.22mV, which means the equivalent ADC resolution corresponding to current measurement is about 24mA (1.22mV correspond to 24mA). If we consider electrical noise on USB connectors, it's very possible that the out signal will be "drowned" in electrical noise or the results will be not very satisfactory. The solution to that problem is to "rescale" this 0V --> 0.15V range to 0V --> 5V. We can do that by using operational amplifier circuits. I used what I found on the moment in my electronic components, an LM358 IC. This IC is not the best, but for the demo, it's ok to be used. Fig. 3: USB current and voltage monitor A few ideas of this electronic design: this IC contains two operational amplifiers, first amplifier coefficient is set thru R5 and R4 (34 amplification coefficient) and the signal is connected on his noninverting input, the lowest current that can be measured is approx. 0.7mA, the second amplifier is set as a buffer amplifier, note: if the maximum current used by the load is maximum 3A, the Zenner diode it's not necessary. By using this amplifier, the range is rescaled to 0 --> 5.1V. To measure the voltage at USB input we use R9 and R10 divider resistor and will use the formula U_R9 = U_USB * ( R9/(R9 + R10)). And by using for R9 10K and for R10 33K the voltage measured by ADC for maximum USB standard charging is U_R9 = 20V * (10/(43)) = 4.65V. This circuit has been developed on prototyping PCB. The outputs of this circuit are connected to two ADC (current signal to PTB13 and voltage signal to PTB14) channels of MPC5744P-DEVKIT and those can be found on CN1 connector ("USB voltage", "USB current" and GND). MPC5744P-DEVKIT Evaluation Board The main scope of this devkit is to get current and voltage data from the custom board and to convert it to digital data and send it to the PC through the UART interface. As can be seen in fig. 4, I used three wires to connect the custom electronic board to the devkit (two ADC and GND). On MPC5744P-DEVKIT the ADC voltage reference must be set to 5V (jumper J19 --> 2-3) and the data will be sent to PC through UART (USB --> OpenSDA). The MPC5744P-DEVKIT must be connected to PC thru USB cable. All other jumpers can be let in the default state. Fig. 4: Hardware setup (load is a USB led light) 2.1 Software Setup MBDT Application Model For software development, I used Matlab with the MBDT toolbox. The first step is to create a new Simulink project using MBDT. The project contains three main parts: configuration blocks variable declaration blocks main loop, where the values are taken from the output of ADC block, and after using some simple maths functions, resulted in values are stored in current and voltage variables. After getting the values from ADC blocks, we must apply some math functions to reverse the effect created in the electronic circuit. Part of the configuration blocks contain: MPC5744P configuration block, ADC configuration block, which has two channels are configured, FreeMASTER block used to observe the current, voltage, and other parameters over UART through the FreeMASTER protocol. Part of the variables declaration is used to declare all variables used to get values from ADC peripheric, intermediate values, and final values. Part of the main loop consists of simple mathematical functions that have the role to convert ADC values to current and voltage values. The first thing executed is taking the ADC current and voltage values, then those values are converted to floating-point type the multiplied with a constant (ADC_Vref /ADC_resolution = 5/4095) which represent ADC voltage resolution. Then, for USB current value, the result must be divided with operational amplifier factor (34), after that, we could subtract from the result that operational amplifier input offset (if it is measured any relevant value) and the last thing to do to get the USB current is to convert from voltage to current using ohm law (U = R * I). To get the USB voltage, the first step is similar to the USB current value, using the resistor divider formula we get the final value. For using different opamp IC, if the non-inverting input is too high, it is recommended to be measured while the electric circuit is on and the value to be updated in the model (variable Current_offset). Fig. 5: MBDT Application Model FreeMASTER project To view data in real-time, the first thing is to open the FreeMASTER project and, select "Tools", then "Connection Wizard ...", then hit "Next" button, select the first option "Use the direct connection to an on-board USB port", then select the serial com port assigned to MPC5744P-DEVKIT and 115200 baud rate. The USB current and voltage can be observed In the FreeMASTER project as a numerical value and as an oscilloscope view by selecting "RAW data" to plot raw ADC USB current and voltage values. To plot the real USB current and voltage values, in the Project Tree, please select "Voltage and current" oscilloscope. Fig. 6: FreeMASTER USB current and voltage monitor In Fig. 6 it can be seen current and voltage variations in time for fast charging transitions when my smartphone is connected to the original charger.

Product Release Announcement Analog & Automotive Embedded Systems NXP Model-Based Design Toolbox for S32K3 – version 1.7.0 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 S32K3 version 1.7.0. This release supports automatic code generation for S32K3 peripherals and applications prototyping from MATLAB/Simulink for NXP S32K3 Automotive Microprocessors. This new product adds support for S32K310, S32K311, S32K312, S32K314, S32K322, S32K324, S32K328, S32K338, S32K341, S32K342, S32K344, S32K348, S32K358, S32K364, S32K366, S32K374, S32K376, S32K388, S32K394 and S32K396 MCUs, and part of their peripherals, based on RTD MCAL components (ADC, CAN, DIO, FEE, GPT, I2C, ICU, LIN, MEM, MCL, PWM, SPI, UART), and support for the GD3162 Gate Driver based on the S32K396 GD3162 Software. In this release, we have also updated the RTD, S32 Configuration Tools, AMMCLib, FreeMASTER, and MATLAB support for the latest versions. The product comes with over 180 examples, covering all the features and functionalities of the toolbox, including new demos for motor control applications. Target audience: This product is part of the Automotive SW – Model-Based Design Toolbox. FlexNet Location: https://nxp.flexnetoperations.com/control/frse/download?element=7608021 Technical Support: NXP Model-Based Design Toolbox for S32K3 issues will be tracked through the NXP Model-Based Design Tools Community space. Release Content: Automatic C code generation from MATLAB® for NXP S32K3 derivatives: S32K310 S32K311 S32K312 S32K314 S32K322 S32K324 S32K328 S32K338 S32K341 S32K342 S32K344 S32K348 S32K358 S32K364 S32K366 S32K374 S32K376 S32K388 S32K394 S32K396 Support for the following peripheral components and functions: ADC CAN DIO eTPU FEE GD3162 GPT I2C ICU LIN MCL (including DMA support) MEM Memory read/write PWM Profiler Registers read/write SPI UART New RTD version supported (6.0.0) Integrates S32K396 GD3162 v2.0.2 The toolbox enables access to the GD3162 gate driver for S32K396 derivatives from Simulink models, by delivering a library block (Gd3162) that generates code on top of GD3162 components API. New S32 Configuration Tools version supported (2024.R1.8)😎 Integration with EB tresos v29.0.0 Provides 2 modes of operation: Basic – using pre-configured configurations for peripherals; useful for quick hardware evaluation and testing Advanced – using S32 Configuration Tools or EB tresos to configure peripherals/pins/clocks Default Configuration Project Templates targeting all the supported S32K3 derivatives The toolbox delivers default configuration projects, available in both S32 Configuration Tools and EB tresos, covering an initial enablement of the on-board peripherals, pins, and clocks, for all the supported S32K3 derivatives. The desired template, which represents the starting point for enabling the hardware configuration of the application, can be selected via a dropdown widget. Support for creating and using Custom Project Templates The toolbox provides support to use and create custom project templates. This could be very useful when having a custom board design – offering the possibility to create the configuration for it only once. After it is saved as a custom project template, it can be used for every model that is being developed. Such custom projects, addressing specific hardware designs are offered inside the current version of the toolbox to integrate the following EVBs: MCTPTX1AK324 S32K344-WB S32K396-BGA-DC1 MR-CANHUBK344, alongside a set of examples specifically created to target this hardware design and a series of articles (available on NXP Community) demonstrating how to use the toolbox features and functionalities for creating applications for custom boards. The toolbox has been tested and validated on the official NXP Evaluation Boards S32K31XEVB-Q100 S32K312EVB-Q172 XS32K3X2CVB-Q172 XS32K3X4EVB-Q257 XS32K3XXEVB-Q172 MR-CANHUBK344 S32K3X4EVB-T172 S32K344-WB XS32K3X8CVB-Q172 S32K388EVB-Q289 XS32K396-BGA-DC XS32K396-BGA-DC1 Integrates the Automotive Math and Motor Control Library release 1.1.41 All functions in the Automotive Math and Motor Control Functions Library v1.1.41 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. S32 Design Studio integration We provide the feature of importing the code generated from a Simulink model inside the S32 Design Studio IDE. This functionality can be useful if the model needs to be integrated into an already existing project or for debug 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) including AUTOSAR SW-C deployment External mode GD3162 Applications To demonstrate the integration and support of the GD3162 gate driver IC, we have included a reference Simulink application that configures six GD3162 devices in a daisy-chain topology using SPI communication. The setup enables sequential initialization, configuration, and status monitoring of each GD3162 device using the S32K396 as a controller MCU. Motor Control Applications The toolbox provides examples for 1-shunt and 2-shunt PMSM and BLDC motor control applications, supporting both S32 Configuration Tools and EB tresos. Each of the examples provides a detailed description of the hardware setup and an associated FreeMASTER project which can be used for control and data visualization. The toolbox also demonstrates the integration of the Motor Control Blockset in developing such applications. For demonstrating the S32K3 eTPU Software integration, we have included a PMSM application where the FOC algorithm runs on the main CPU of the S32K396 MCU, while the analog sensing, software resolver, and PWM signals generation are offloaded to the eTPU co-processor. The motor control applications were developed and validated on the MCSPTE1AK344 and MCSPTR2AK396 Motor Control kits. Support for MATLAB versions We added support for the following MATLAB versions: R2021a R2021b R2022a R2022b R2023a R2023b R2024a R2024b R2025a Examples for every peripheral/function supported More than 180 examples showcasing: I/O Control Timers and scheduling Communication (CAN, I2C, LIN, SPI, UART) Memory handling Motor Control applications (BLDC and PMSM) AMMCLib FreeMASTER SIL / PIL / 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: The NXP Model-Based Design Toolbox extends the MATLAB® and Simulink® experience by allowing customers to evaluate and use NXP’s S32K3 MCUs and evaluation board solutions out-of-the-box. NXP Model-Based Design Toolbox for S32K3 version 1.7.0 is fully integrated with MATLAB® environment. Target Audience: This release (1.7.0) is intended for technology demonstration, evaluation purposes, and prototyping S32K3 MCUs and Evaluation Boards. Useful Resources: Examples, Trainings, and Support: https://community.nxp.com/community/mbdt

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

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 Analog & Automotive Embedded Systems NXP Model-Based Design Toolbox for S32K3 – version 1.8.0 The Analog & Automotive Embedded Systems, Model-Based Design Tools Team at NXP Semiconductors, is pleased to announce the release of the Model-Based Design Toolbox for S32K3 version 1.8.0. This release supports automatic code generation for S32K3 peripherals and applications prototyping from MATLAB/Simulink for NXP S32K3 Automotive Microprocessors. This new product adds support for S32K310, S32K311, S32K312, S32K314, S32K322, S32K324, S32K328, S32K338, S32K341, S32K342, S32K344, S32K348, S32K356, S32K358, S32K364, S32K366, S32K374, S32K376, S32K388, S32K389, S32K394 and S32K396 MCUs, and part of their peripherals, based on RTD MCAL components (ADC, CAN, DIO, FEE, GPT, I2C, ICU, LIN, MEM, MCL, PWM, SPI, UART). In this release, we have also updated the RTD, S32 Configuration Tools, AMMCLib, FreeMASTER, and MATLAB support for the latest versions. The product comes with over 130 examples, covering all the features and functionalities of the toolbox, including new demos for motor control applications. Target audience: This product is part of the Automotive SW – Model-Based Design Toolbox. FlexNet Location: https://nxp.flexnetoperations.com/control/frse/download?element=7690521 Technical Support: NXP Model-Based Design Toolbox for S32K3 issues will be tracked through the NXP Model-Based Design Tools Community space. Release Content: Automatic C code generation from MATLAB® for NXP S32K3 derivatives: S32K310 S32K311 S32K312 S32K314 S32K322 S32K324 S32K328 S32K338 S32K341 S32K342 S32K344 S32K348 S32K356 S32K358 S32K364 S32K366 S32K374 S32K376 S32K388 S32K389 S32K394 S32K396 Support for the following peripheral components and functions: ADC CAN DIO eTPU FEE GPT I2C ICU LIN MCL (including DMA support) MEM Memory read/write PWM Profiler Registers read/write SPI UART New RTD version supported (7.0.0) New S32 Configuration Tools version supported (2025.R1.8)😎 Integration with EB tresos v32.0.0 Provides 2 modes of operation: Basic – using pre-configured configurations for peripherals; useful for quick hardware evaluation and testing Advanced – using S32 Configuration Tools or EB tresos to configure peripherals/pins/clocks Default Configuration Project Templates targeting all the supported S32K3 derivatives The toolbox delivers default configuration projects, available in both S32 Configuration Tools and EB tresos, covering an initial enablement of the on-board peripherals, pins, and clocks, for all the supported S32K3 derivatives. The desired template, which represents the starting point for enabling the hardware configuration of the application, can be selected via a dropdown widget. Support for creating and using Custom Project Templates The toolbox provides support to use and create custom project templates. This could be very useful when having a custom board design – offering the possibility to create the configuration for it only once. After it is saved as a custom project template, it can be used for every model that is being developed. Such custom projects, addressing specific hardware designs are offered inside the current version of the toolbox to integrate the following EVBs: S32K312MINI-EVB MCTPTX1AK324 S32K344-WB S32K3-T-BOX S32K396-BGA-DC1 MR-CANHUBK344, alongside a set of examples specifically created to target this hardware design and a series of articles (available on NXP Community) demonstrating how to use the toolbox features and functionalities for creating applications for custom boards. The toolbox has been tested and validated on the official NXP Evaluation Boards S32K31XEVB-Q100 S32K312EVB-Q172 S32K312MINI-EVB MCTPTX1AK324 XS32K3X2CVB-Q172 S32K3-T-BOX MR-CANHUBK344 XS32K3X4EVB-Q257 XS32K3X4EVB-Q172 S32K3X4EVB-T172 S32K344-WB XS32K3X8CVB-Q172 S32K388EVB-Q289 S32K389EVB-Q437 XS32K396-BGA-DC XS32K396-BGA-DC1 Integrates the Automotive Math and Motor Control Library release 1.1.42 All functions in the Automotive Math and Motor Control Functions Library v1.1.42 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. S32 Design Studio integration We provide the feature of importing the code generated from a Simulink model inside the S32 Design Studio IDE. This functionality can be useful if the model needs to be integrated into an already existing project or for debug 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) including AUTOSAR SW-C deployment External mode Motor Control Applications The toolbox provides examples for 1-shunt and 2-shunt PMSM and BLDC motor control applications, supporting both S32 Configuration Tools and EB tresos. Each of the examples provides a detailed description of the hardware setup and an associated FreeMASTER project which can be used for control and data visualization. The toolbox also demonstrates the integration of the Motor Control Blockset in developing such applications. For demonstrating the S32K3 eTPU Software integration, we have included a PMSM application where the FOC algorithm runs on the main CPU of the S32K396 MCU, while the analog sensing, software resolver, and PWM signals generation are offloaded to the eTPU co-processor. The motor control applications were developed and validated on the MCSPTE1AK344 and MCSPTR2AK396 Motor Control kits. Support for MATLAB versions We added support for the following MATLAB versions: R2023b R2024a R2024b R2025a R2025b Examples for every peripheral/function supported More than 130 examples showcasing: I/O Control Timers and scheduling Communication (CAN, I2C, LIN, SPI, UART) Memory handling Motor Control applications (BLDC and PMSM) AMMCLib FreeMASTER SIL / PIL / External mode For more details, features, and how to use the new functionalities, please refer to the Release Notes and User Manual 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 S32K3 MCUs and evaluation board solutions out-of-the-box. NXP Model-Based Design Toolbox for S32K3 version 1.8.0 is fully integrated with MATLAB® environment. Target Audience: This release (1.8.0) is intended for technology demonstration, evaluation purposes, and prototyping S32K3 MCUs 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 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

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

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