R2024a

New Features, Bug Fixes, Compatibility Considerations

Simulink Editor

 Preserve signal line shape when moving and resizing blocks

In Simulink^® versions before R2024a, when you move or resize a block, all other blocks stay in place, and the signal lines connected to the block move to accommodate the change in block position or size.

As a result, the signal lines may bend, and the block may cover nearby blocks. You may need to clean up the diagram.

Starting in R2024a, when you move or resize a block with three or more ports, any straight signal lines connecting the block to nearby blocks with one or two ports do not change shape. Instead, the connected blocks move.

If straight signal lines connect the block to a chain of consecutive blocks with one or two ports that are close to each other, the signal lines in the chain do not change their shape. Instead, the blocks move.

The affected signal lines and blocks highlight in green. This new functionality does not affect signal lines with branches or Simscape™ connections.

To temporarily turn the functionality off, hold the space bar while you move or resize a block. When you release the space bar, the functionality turns back on.

To turn the functionality off across MATLAB^® sessions, in the Simulink Editor, on the Modeling tab, from Environment, clear Preserve Alignment. To turn the functionality back on, select Preserve Alignment.

Preserve signal line shape when moving and resizing blocks

Convert Goto and From blocks to signal lines

You can simplify your model diagrams by replacing lengthy signal lines with sets of connected Goto and From blocks. However, when you want to trace a signal path, seeing the signal lines can be useful.

You can convert signal lines and virtual buses to Goto and From block sets, and you can convert Goto and From block sets to signal lines. A Goto and From block set is a connected group of Goto and From blocks that have the same tag.

To convert a Goto block and all From blocks to which it connects or a From block and the Goto block to which it connects to a signal line, select the block. Pause on the ellipsis that appears above the selected block. In the action menu that expands, select Convert to signal.

To convert a signal line or bus to a Goto and From block set, select the signal line or bus. Pause on the ellipsis that appears. In the action menu that expands, select Convert to Goto and From blocks.

For more information about converting between signal lines and blocks, see Convert Signal Lines to Goto and From Block Sets.

Search for and select blocks connected without signal lines using toolstrip button

Related blocks connect to each other without signal lines.

When you select one of a set of related blocks, you can now use the Related Blocks button in the Simulink Toolstrip to find and switch selection to a different block in the set. For example, if you select a Goto block, you can switch the selection to a From block with the same tag. The button both switches selection to the related block and automatically navigates you to the location of the related block.

To switch selection from related block to another, in the toolstrip, on the block-specific tab of the selected block (for example, the Goto tab for a Goto block), in the Navigate section, click Related Blocks.

If the selected block only has one related block, the selection switches to the related block. If the selected block has more than one related block, a list of related blocks appears. Navigate to the name of the block you want to select by clicking or using the arrow keys on your keyboard, then press Enter.

For more information, see Search for Blocks Connected Without Signal Lines.

Enhancements to Model Finder

Model Finder has these enhancements to enable you to search for phrases, customize the Model Finder user interface (UI), and manage databases with ease.

• Model Finder now supports using quotation marks for searching phrases to get more targeted results.

• Model Finder UI includes newly added sections and tabs with additional features:

  1. Layout — Customize the UI layout by using buttons to toggle the visibility of the Recent, Databases, Filters, and Information panes.

  2. View — Customize the search results layout using these options:

     • Models — Select this view to display the models that match your search query. In this view, the search results include both standalone models and models that are referenced by examples and projects. You can view the list of examples and projects that use a specific model in the Information pane.

     • Categorized — Select this view to display the examples and projects that match your search query. You can view the list of models used in a specific example or project in the Information pane.

  3. Databases — Select the databases from the available list of databases registered with Model Finder to set the search location.

  4. Copy Command — To copy the command that opens a specific search result, click Copy Command.

  5. Location — Display the path on your system that stores a previously opened search result using the Model Finder. To copy the path, click the copy icon .

  6. Recommended Licenses — Display the licenses recommended to simulate a model, example, or project. The icons and indicate whether you have the license.

  7. File References — Display the external files that are referenced in the search result.

  8. Database — Manage databases by navigating to the Database tab. Within the tab, you have the option to create, import, delete, and view the contents of a database.

For more information, see Model Finder.

There are some changes in the functions used to configure database settings in Model Finder. For more information, see Model Finder function updates.

View block icons in the quick insert menu

Starting in R2024a, when you double-click the Simulink Editor canvas, the quick insert search results display block icons with the block names to enable you to easily identify the blocks.

 Functionality being removed or changed

Model Finder function updates

Errors

Model Finder functions have these changes:

• The modelfinder.registerDatabase function is now renamed to modelfinder.importDatabase.

• The modelfinder.unregisterDatabase function is now renamed to modelfinder.deleteDatabase.

• Model Finder no longer supports interactive mode to create, import, delete, set search, or set default database using the modelfinder.createDatabase, modelfinder.importDatabase, modelfinder.deleteDatabase, modelfinder.setSearchDatabase, and modelfinder.setDefaultDatabase functions.

• The functions modelfinder.createDatabase, modelfinder.importDatabase, and modelfinder.deleteDatabase no longer accept multiple input arguments.

Simulation Analysis and Performance

 Control simulation execution and tune parameter values in scripted simulations

The new Simulation object represents a simulation of a model and provides an interface to control the simulation execution and to tune parameter values during simulation. The Simulation object supports all simulation modes, including rapid accelerator, and deployment with Simulink Compiler™. You can use the Simulation object to:

• Configure, run, and interact with simulations.

• Step forward through major time steps in simulation.

• Write and deploy scripts that interact with simulations while they run.

• Build and deploy apps that run and interact with simulations.

While you can programmatically interact with simulations you run using Simulation objects, you cannot interact with the model or simulation associated with a Simulation object using the Simulink Editor while the simulation has a status other than inactive.

For more information, see Run Simulations Programmatically.

 Interactively build custom apps with Simulink models using MATLAB App Designer

Interactively build a custom app that interfaces with a Simulink model using MATLAB App Designer. Use the App Designer design environment to:

• Perform common simulation tasks from the app, such as starting and stopping the simulation and viewing simulation progress, using Simulink UI components.

• Tune model variables from the app while the simulation runs by connecting UI components to variables.

• Visualize simulation signals in the app by connecting signals to a time scope UI component.

To use Simulink UI components, in App Designer, drag the components from the Simulink section of the Component Library onto the canvas, or use these functions:

• uisimdatabutton — Use simulation data buttons to load input data or save output data.

• uisimcontrols — Use simulation controls to start, stop, pause, and continue a simulation.

• uisimprogress — Use a simulation progress bar to view the simulation progress as it runs.

• uisimvartuner — Use a variable tuner component to modify model variables from a table.

• uitimescope — Use a time scope to visualize signal data in the app while the simulation runs.

For more information, see Create App for Simulink Model.

Debug simulation execution using the Execution Order viewer while stepping block by block

The debugging capability to step through execution block by block that was added in R2023a has improved integration with the Execution Order viewer.

• Execution order highlighting no longer conflicts with the block-by-block debugging highlighting that indicates the block on which the simulation is paused.

• The Execution Order viewer highlights the row in the execution list that corresponds to the block on which the simulation is paused, so you can track the position in the execution list alongside the location of the block in the model.

• The Breakpoints List now has a button to open the Execution Order viewer.

Debug simulation execution using the Execution Order viewer while stepping block by block

Increased flexibility for stepping block by block in simulation debugging session

When the Pause within time step option is selected in the Breakpoints List and a model contains at least one breakpoint before you start a simulation, you can use the Step Over button to step through the simulation block by block. Starting in R2024a, the Step Over button is available to start stepping block by block anytime such a simulation is paused, including when the simulation is paused between major time steps.

In R2023a and R2023b, the Step Over button was available only while paused within a time step. After the simulation paused within a time step, the Step Over became unavailable if you advanced the simulation through major time steps by using the Step Forward and Step Back buttons. You could not step block by block again until the simulation paused within a time step on a breakpoint.

For more information, see Debug Simulation Using Signal Breakpoints.

Improved support for stepping between Simulink block diagrams and Stateflow charts in simulation debugging sessions

Debugging simulations by stepping block by block in the Simulink Editor has enhanced support for stepping between Simulink block diagrams and Stateflow^® charts, including support for these situations:

• Stepping into and out of a function-call subsystem that is controlled by a Stateflow chart

• Stepping into and out of a Simulink function inside a Stateflow chart

• Stepping into and out of a Simulink-based state inside a Stateflow chart

To enable stepping into Stateflow charts in a simulation debugging session, enable the Allow setting breakpoints during simulation configuration parameter before starting the simulation debugging session. For more information, see Breakpoints List.

sldebug prompt in MATLAB Command Window indicates when simulation debugging session is paused within time step

When you start a simulation debugging session using the Simulink Editor, you can issue some programmatic simulation debugging commands, such as probe or stop, while the simulation is paused within a time step. The sldebug command prompt (sldebug >>) now replaces the MATLAB command prompt (>>) to indicate in the MATLAB Command Window when the simulation is paused within a time step. As in prior releases, you can issue both MATLAB commands and the supported simulation debugging commands at the sldebug command prompt.

For more information, see Simulink Debugging Programmatic Interface.

View simulation time in Simulink Editor status bar during programmatic simulations

When you run a simulation using the sim function and the model is open, the status bar at the bottom of the Simulink Editor window for the model now updates to show the current simulation time for normal and accelerator mode simulations.

View simulation time in Simulink Editor status bar during programmatic simulations

Run fast restart simulations using scalar Simulink.SimulationInput objects

You can now configure a Simulink.SimulationInput object to enable fast restart for an individual simulation you run using the sim function and a scalar SimulationInput object. Fast restart saves time in iterative simulation workflows by compiling the model only once, for the first simulation that has fast restart enabled. When you enable fast restart for an individual simulation using the sim function, at the end of the simulation, the FastRestart parameter remains enabled in the model and the model is initialized in fast restart.

You can also use the setModelParameter function to enable fast restart by setting the FastRestart parameter on a Simulation object.

The FastRestart parameter applies for only individual simulations you run one at a time. To use fast restart for multiple simulations you run together using an array of SimulationInput objects, use the UseFastRestart name-value argument.

For more information, see How Fast Restart Improves Iterative Simulations.

Profile execution of iterative simulations using Simulink Profiler and fast restart

Analyze the execution and performance of iterative simulations more quickly by using the Simulink Profiler with fast restart enabled. Fast restart saves time in iterative simulation workflows by compiling the model for the first simulation and then skipping the termination and compilation phases for subsequent simulations. To allow skipping the compilation phase, fast restart restricts the types of modifications you can make to the model. Fast restart is not supported for all models. For more information, see Get Started with Fast Restart.

Enabling and disabling the Simulink Profiler while initialized in fast restart is not supported. To use fast restart with the Simulink Profiler, enable fast restart, and then run a profiling simulation using the Simulink Profiler. After you finish profiling the simulation execution, disable fast restart to terminate the profiling simulation. Disabling fast restart also disables the profiler.

Increased default line width in visualizations

Starting in R2024a, the default line width for signals plotted in the Simulation Data Inspector, the Record block, the Playback block, and the Dashboard Scope block is 2 (px).

Improved support for importing MDF-files into the Simulation Data Inspector

The Simulation Data Inspector now offers improved performance and support for importing MDF-files.

• Multidimensional data is now imported as a single signal with multidimensional sample values. After importing, you can choose to represent the data as a single signal with nonscalar sample values or expand the signal into a set of signals, called channels, with scalar sample values. Previously, multidimensional data was imported as channels that could not be collapsed into a single signal with multidimensional sample values.

• You can now import string data.

• Importing large MDF-files into the Simulation Data Inspector is now faster due to improved performance.

 Functionality being removed or changed

Code Analyzer warning for sim function syntaxes that return multiple output arguments

The Code Analyzer warns about calls to the sim function that return multiple output arguments. Since R2009b, the single simulation output syntaxes have been recommended, and multiple output syntaxes have been discouraged.

Support for syntaxes that return multiple output arguments will be removed in a future release.

Consistent error handling for sim function with scalar SimulationInput object

Behavior change

Starting in R2024a, the sim function has consistent default behavior and options for simulations you run using Simulink.SimulationInput objects. In prior releases, the sim function overwrote the CaptureErrors parameter for a single simulation if you specified one or more name-value arguments in addition to the scalar SimulationInput object, including the StopOnError name-value argument.

SimulationInput Dimensions	CaptureErrors	StopOnError	Behavior Change
scalar	"off" by default. To enable this parameter, specify the parameter on the SimulationInput object using the setModelParameter function.	This name-value argument has no effect when you run a single simulation.	Some calls to the sim function in scripts or functions from previous releases might not return a Simulink.SimulationOutput object when the same calls had returned the simulation output in previous releases. To restore the prior behavior, specify the CaptureErrors parameter as "on".
vector, matrix, array	Always "on".	"off" by default. Specify this name-value argument as "on" to skip subsequent simulations if a simulation error occurs.	No change.

slprofreport function has been removed

The slprofreport function and the ability to view profiling data generated prior to R2020a has been removed in R2024a. In R2020a, the Simulink Profiler was enhanced to capture profiling data as a Simulink.profiler.Data object to support programmatic analysis of the profiling results. Since R2020a, the slprofreport function has supported generating profiler reports only from profiler data generated prior to R2020a.

Executing size computation phase using model name requires input arguments

Behavior change

In previous releases, typing the name of the model with one or more output arguments and no input arguments executed the size computation phase of simulation. The table describes the behavior for using the model name as a programmatic interface without any input arguments starting in R2024a.

R2024a Behavior	Code Example
Typing the model name with one output argument returns the model handle.	h = MyModel;
Passing the model name to a function without single or double quotes is equivalent to passing the model handle to the function.	open_system(MyModel)
Typing the model name with multiple output arguments and no input arguments causes the software to issue an error.	[sys,x0,blks,st] = MyModel; Too many output arguments.

To execute the size computation phase of simulation, you must specify input arguments.

[sys,x0,blks,st] = MyModel([],[],[],"sizes");

For more information, see Use Model Name as Programmatic Interface.

Using the model name as a programmatic interface to get a model handle is not recommended. Instead, after loading the model, use the get_param function to get the Handle parameter for the model. For example, this get_param command gets the handle for a model named MyModel.

h = get_param("MyModel","Handle");

Component-Based Modeling

 Use local solvers for components with faster dynamics

Local solvers for referenced models can now use a fixed step size that is smaller than the step size for the parent solver. Since R2022a, the software has required the local solver step size to be larger than the step size for the parent solver, limiting the use of local solvers to components with slower dynamics compared to the rest of the system. Starting in R2024a, you can use local solvers for components with dynamics that are faster or slower compared to the rest of the system.

Using a local solver can facilitate system composition and integration by:

• Allowing system-level simulations to solve referenced models using the same solver and step size that were used to design and test each component in isolation.

• Reducing the number of adjustments you need to make to configuration parameters of referenced models when integrating components into larger systems.

For some systems, using a local solver can improve simulation performance by allowing you to:

• Choose a solver that is more appropriate to solve the system in the referenced model.

• Choose different step sizes for one or more components instead of using a single step size for the entire system, which can reduce the number of redundant calculations in simulations of systems with a wide range of dynamics among components.

  For an example, see Improve Simulation Performance by Using Local Solvers.

For more information, see Use Local Solvers in Referenced Models.

Use local solvers for components that contain blocks that wrap state values

Starting in R2024a, you can configure a referenced model that contains a block with wrapped states to use a local solver. Wrapping states can improve numerical stability for systems with cyclical state values and allows the state value to wrap to the start of the cycle without resetting the solver, which can slow simulation performance.

For example, you can model the angular position of a wheel as having a value that is always between 0 and 2π. When the wheel rotates beyond an angular position of 2π, the angular position wraps back to 0 rather than continually increasing.

For more information, see Use Local Solvers in Referenced Models.

Variant Manager for Simulink: Enhanced variant configuration workflow for simulation and testing

Starting in R2024a, models that have variant configurations created using Variant Manager for Simulink have more streamlined simulation and testing workflows. You can now specify variant configurations as inputs to command line functions used to run single or multiple simulations, test cases, or test case iterations on the model. The specified variant configurations are applied before model simulation. This new workflow scales for models with a large number of variant control variables and provides traceability from the result object to the variant configuration used during simulation or testing.

Before R2024a, you had to either set the variant control variables that form a variant configuration as inputs to the command line functions, or activate the variant configuration by invoking the Simulink.VariantManager.activateModel function in callbacks before running the simulation or test.

New command line workflow for simulation and testing:

• For simulation functions such as sim, parsim, and batchsim, you can set the VariantConfiguration property in the Simulink.SimulationInput object using the setVariantConfiguration function. For an example, see Run Simulations for Variant Models Using Variant Configurations.

• In the Simulink Test™ programmatic interface, you can specify the variant configuration to use when running a test case. You can also run the same test case for different variant configurations in the model by creating test case iterations. To specify the configuration that must be activated for each iteration, set the VariantConfiguration property in the sltestiteration object. The TestCaseResult and TestIterationResult objects store the variant configuration used for each test case or iteration. The test specification report and test results report show these variant configurations as well. For an example, see Run Tests for Variant Models Using Variant Configurations.

Variant Manager for Simulink: View variant parameters grouped by bank

In the Variant Parameters tab in Variant Manager, use the Bank per row option to switch to a view in which parameters are grouped based on the variant parameter bank they belong to.

Variant Manager for Simulink: Support for Variant Start and Variant End blocks

Variant Start and Variant End blocks are now supported in Variant Manager tasks such as viewing and interacting with the blocks from the model hierarchy, importing control variables, understanding variable usage in a variant configuration, and activating a variant configuration.

Variant Manager for Simulink: Support for startup variant activation time in Variant Analyzer

The Variant Analyzer tool supports analyzing variant configurations for a model that contains variant blocks with startup variant activation time.

Variant Start and Variant End Blocks: Define conditions in a bounded region without creating a level of hierarchy

Starting in R2024a, use the Variant Start and Variant End blocks to limit variant condition propagation in a bounded region without introducing a level of hierarchy in the model. A bounded region is any region between the outport of a Variant Start block and the corresponding inport of the Variant End block without any intersection. You only need to specify the variant conditions and parameters on the Variant Start block.

Automated port synchronization in Variant Subsystem and Variant Assembly Subsystem blocks

When working with Variant Subsystem or Variant Assembly Subsystem blocks, the ports on the blocks match the ports in their underlying variant choices. In previous releases, you were required to manually analyze, copy, and paste the ports in these blocks to align them with the ports in variant choices, which was a time-consuming and error-prone process. Starting in R2024a, Simulink provides options to add missing ports and delete unused ports in Variant Subsystem and Variant Assembly Subsystem blocks to match the ports of the underlying variant choices. During simulation, if Simulink encounters a port mismatch between a Variant Subsystem or Variant Assembly Subsystem block and its variant choices, the resulting error message now provides these two options to resolve the issue:

• Add missing ports — Adds missing ports to the Variant Subsystem or Variant Assembly Subsystem block, aligning them with the ports in the variant choices.

• Add and delete ports — Adds missing ports and removes unused ports from the Variant Subsystem or Variant Assembly Subsystem block, aligning them with the ports in the variant choices. The deleted ports cannot be recovered, and any associated properties are lost.

Alternatively, you can use the Simulink.VariantUtils.updateVariantSubsystemPorts function to align the ports in a Variant Subsystem or Variant Assembly Subsystem block with the ports in its variant choices.

Use adapted rate-based model blocks as choices in a Variant Subsystem block

Starting in R2024a, you can use adapted rate-based model blocks as variant choices in a Variant Subsystem block. When you add adapted rate-based models as variant choices, the inports in the variant subsystem are matched to the port names of the respective rate-based models.

Define variant control variables of a Simulink Function block in the mask or model workspace

Starting in R2024a, you can define the variant control variables of a Simulink Function block with update diagram activation time in the mask or model workspace.

Access the mask of the active variant choice on Variant Subsystem block

Starting in R2024a, you can access the mask of the active variant choice of the Variant Subsystem directly without having to navigate inside the Variant Subsystem block with the following conditions:

• If the Variant Subsystem block is unmasked, double-clicking on the block opens the mask of its active choice. Clicking on the Look under mask badge or selecting the corresponding option from the context menu of the Variant Subsystem block takes you directly inside the active choice.

• If the Variant Subsystem block is masked and the active choice also has a mask, then the mask of the Variant Subsystem block gets the preference and double-clicking on the block will open the Variant Subsystem block mask.

Specify variant choices as an array of strings in Variant Assembly Subsystem block

Starting in R2024a, you can specify Variant choices specifier as an array of strings in Variant Assembly Subsystem block.

Propagate variant conditions to elements connected to the inport bus of the Bus Creator block in variant models with busses

Starting in R2024a, the variant conditions propagate to the elements connected to the inport bus of the Bus Creator block. Additionally, the generated code is optimized to execute based on the selected variant, eliminating any unnecessary code execution for inactive variants. Previously, in variant models that included buses, the elements connected to the inport bus of the Bus Creator block would always be active, regardless of the selected variant.

Specify custom header files without #include directive

Starting in R2024a, the Include headers parameter in Simulation Target and Code Generation tabs support a list of custom header files without #include directive. For more information, see Include headers.

Simulink Code Importer: Import C++ Class as reusable Simulink library

Starting in R2024a, you can use the Simulink Code Importer to import a C++ class to a Simulink Library from your custom C++ code library. For example, using the Simulink Code Importer you can import C++ class to a C Function block after analyzing the custom code for classes and their dependencies. For more information, see Import Custom C++ Class Using the Simulink Code Importer Wizard.

New example of modeling a Battery Management System

A new example shows how to design, model, and simulate a Battery Management System (BMS) for an NMC (Nickel-Manganese-Cobalt) cell with 3 Amp hr capacity. This example will include the best practices for collaboration, model composition and components, and interface and data management. For more information, see Use Model-Based Design To Build a Battery Management System.

New example of modeling a Battery Management System

Convert logically executed Subsystem blocks to Subsystem Reference Blocks to reuse in models

You can now convert logically executed Subsystem blocks such as If Action Subsystem, Switch Case Action Subsystem, For Iterator Subsystem, and While Iterator Subsystem to Subsystem Reference and reference them in models to promote reusability and modularity. For information on converting Subsystem blocks to Subsystem Reference blocks, see Convert Subsystem to a Referenced Subsystem.

Optimized loading of models with Variant Assembly Subsystem blocks

Starting in R2024a, when you load a model with a Variant Assembly Subsystem block that has variant choices stored in subsystem files, only the active choice is loaded. This optimization shortens the loading time for such models.

Share port constraints with other masked blocks

Starting in R2024a, you can create shared port constraints enabling you to reuse them with other masked blocks. By saving the port constraints separately in an XML file, you can easily apply them to multiple masked blocks to achieve consistency and efficiency.

For more information on sharing a port constraint, see Share Port Constraints Across Multiple Masked Blocks.

Use constraints on literal edit parameters

You can associate constraints to literal edit parameters. If the Evaluate option in the Mask Editor is not selected, Simulink takes a literal reading of the input entry as you type it in the mask parameter dialog box. For example, you can store an IP address including the dots in a literal edit parameter. Simulink does not evaluate the parameter as if it were a mathematical expression. For more information, see Custom Constraint for Mask Parameter.

Optimized execution of mask parameter callback

Starting in R2024a, mask callback parameter does not execute if the parameter value remains unchanged. This improves the efficiency of mask callbacks by preventing unnecessary execution when the parameter value remains the same.

 Functionality being removed or changed

Extraneous discrete derivative signals diagnostic has been removed

Errors

The Extraneous discrete derivative signals (ModelReferenceExtraNoncontSigs) diagnostic configuration parameter has been removed.

When a discrete input to a Model block connects to the input of a block that has continuous states, the software resets the solver each time the discrete signal updates. The software does not issue a warning or error. Previously, the default behavior of this diagnostic was for the software to issue an error.

To diagnose solver resets, use the Solver Profiler instead. The Solver Profiler provides the number of resets and the reset sources. For more information, see Solver Resets.

Invalid root Inport/Outport block connection diagnostic has been removed

Errors

The Invalid root Inport/Outport block connection (ModelReferenceIOMsg) diagnostic configuration parameter has been removed.

When internal connections to the root-level port blocks of a model are invalid, the software silently inserts hidden blocks to satisfy the constraints wherever possible. This behavior matches the previous default behavior.

To diagnose and fix invalid connections, use Model Advisor check Check for invalid root input and output port connections (Simulink Check) (ID: mathworks.hism.hisl_0079) instead.

Reference tunable mask enumeration parameter by its name in child blocks to obtain the custom value associated with the option

Behavior change

If a mask enumeration parameter refers an external enumeration file or enumeration class for its options, you can now reference the parameter by its name in child blocks to obtain the custom value associated with the option during simulation and code generation.

Previously, child blocks had to reference tunable mask enumeration parameters using an internally created value array that contained the option values. The parameter name was referred to as valueArrayName(<parameterName>) to obtain the custom value for an option. For more information, see Tune Mask Enumeration Parameters - Popup and Radio Button.

lcc-win64 compiler not supported

Errors

The lcc-win64 compiler is no longer supported. For information about supported compilers, see Supported and Compatible Compilers - Windows.

Simulink.VariantControl object does not support Simulink.Parameter object with slexpr or nonscalar values

Behavior change

Starting in R2024a, the Simulink.VariantControl object does not support setting its Value property to a Simulink.Parameter object with Value set to the slexpr function or a nonscalar value.

Project and File Management

Project API: Find project files by label

You can now programmatically perform an advanced search in a project using the findFiles function. Supported workflows include:

• Listing all files in a project

• Filtering files that are not part of the project

• Finding files by label or category name

• Creating test suites from test files in a project and its references

Project API: Reanalyze all project dependencies

You can now programmatically reanalyze all files in your project and perform a complete dependency analysis by using the updateDependencies function.

Project API: Export list of project files to archive

You can now programmatically export a list of project files to an archive by using the export function.

For projects that have missing files, you can enable the export function to ignore the missing files.

Project Upgrade: Check for compatibility issues and upgrade project with improved usability and appearance

For projects that contain only MATLAB files, use Project Upgrade to check for compatibility issues with the current release. For projects that also contain Simulink models and libraries, you can apply fixes and automatically upgrade your project to the current release.

You can now easily interpret the upgrade results and examine the checks marked as need attention. You can also access frequent actions from the Project Upgrade toolstrip:

• Rerun checks.

• View changes that the upgrade applied.

• Save results in a report.

For more information, see Check for Compatibility Issues and Upgrade Simulink Models Using Project Upgrade.

Project Upgrade: Check for compatibility issues and upgrade project with improved usability and appearance

Source Control: Support for signing Git commits

You can now enable the MATLAB Git™ integration to sign Git commits automatically. For more information, see Enable Signing Commits.

Source Control: Support for Git hooks

MATLAB Git integration can now run Git hooks with no additional setup. Starting in R2024a, you do not need to install Cygwin™ on Windows^®.

Supported hooks are pre-commit, commit-msg, post-commit, prepare-commit-msg, pre-push, pre-merge-commit, post-checkout, and post-merge. For more information, see Set Up Git Source Control.

Source Control API: Discard changes in Git repositories programmatically

You can now programmatically restore modified files in a Git repository using the discardChanges function.

Dependency Analysis API: Analyze Files in Toolbox and Files with Unsaved Changes

You can now programmatically include files inside of a toolbox and files with unsaved changes in your dependency analysis using the dependencies.fileDependencyAnalysis function.

Source Control in MATLAB Online: Expanded support for Git workflows

MATLAB Online™ now provides expanded support for Git workflows:

• Squashing Git commits

• Rebasing Git branches

Design Evolution Manager in MATLAB Online: Quickly browse, view, and switch between evolution trees

Use the Tree Browser pane to quickly browse, view, and switch between evolution trees in the current project and its referenced projects.

Design Evolution Manager in MATLAB Online: Quickly browse, view, and switch between evolution trees

Design Evolution Manager in MATLAB Online: Generate report of evolution tree

Click the Generate Report button to generate a PDF report that summarizes an evolution tree, including the evolution tree hierarchy and metadata.

Design Evolution Manager in MATLAB Online: Generate report of evolution tree

polyspaceArtifact Function: Generate artifacts necessary for Polyspace analysis without regenerating code

In R2024a, you can generate Polyspace^® artifacts for a Simulink model without regenerating the code by calling the function polyspaceArtifact. You do not need to integrate Polyspace with Simulink to use this function. The function polyspaceArtifact is available with Simulink R2024a. This function generates two artifacts:

• Data range specifications — The data ranges of the generated code summarized in an XML file.

• Link-to-model data — The data to link the generated code to the Simulink model summarized in an XML file.

This function generates individual XML files. Access to individual Polyspace artifacts outside of an archive can be useful in a continuous integration workflow.

Some changes in your model might require updating these artifacts without requiring updates to the generated code. For examples, If you change the Minimum or Maximum attribute of a signal in your model, only the data range specification needs to be updated to run a more precise Polyspace analysis. Use polyspaceArtifact function to generate the new data range specification XML file quickly without requiring a complete regeneration of your code.

For more details about the function, see polyspaceArtifact.

 Functionality being removed or changed

dependencies.fileDependencyAnalysis(modelname,manifestfile) syntax will be removed

Warns

The dependencies.fileDependencyAnalysis(modelname,manifestfile) syntax of the dependencies.fileDependencyAnalysis function will be removed in a future release. Use the dependencies.fileDependencyAnalysis(modelname, ManifestFile="manifestFileName") syntax instead. Starting in R2024a, scripts using dependencies.fileDependencyAnalysis(modelname,manifestfile) warn.

Data Management

Programmatically interact with workspaces and data dictionaries using a common interface

You can now use a common command-line interface to programmatically interact with the base workspace, model workspace, and the Design Data section of a data dictionary. Create a data connection object to any of these types of data sources by using the Simulink.data.connect function. Then use the object to interact with your design data.

• Read variables by using dot notation (for example val = ds.x).

• Assign variables by using dot notation (for example ds.x = val).

• Read and assign multiple variables by using the get and set object functions.

• Work with data sources by using object functions that are similar to functions you use when working with the base workspace (such as who, exists, and clear).

• Manage changes to data sources by using the hasUnsavedChanges, saveChanges, and discardChanges object functions.

• Open the data source in Model Explorer by using the show object function.

• Get the metadata available for a specific variable by using the getMetadata object function.

By default, tab completion for the data connection object includes only functions available to the object. The Simulink.data.connect function provides the option to configure tab-completion to include only object functions, only variables, or both functions and variables.

Type Editor: Manage types across multiple external data sources associated with your model

When the Type Editor is docked in a model window, the Type Editor displays the available types for the model grouped by source. Create, edit, and assign types stored in the base workspace or data dictionaries.

For more information, see Type Editor.

Type Editor: Manage types across multiple external data sources associated with your model

Create Simulink.Bus objects from bus element port specifications

To create Simulink.Bus objects from buses at bus element ports, use the Simulink.Bus.createObject function.

Signal Editor tool updates

The Signal Editor tool has these updates:

• Move signals in Signal Editor

• Change x- and y-axes limits

• Synchronize signals by time

• Signal and associated table data selection now linked

Move signals in Signal Editor

The Signal Editor tool Move button has been removed. The move action is now combined with the select action. You can select and move one point, two contiguous points on the same line, or the entire plot. In releases prior to R2024a, the Move button enabled you to move only the entire plot. For more information, see Move Signal Points in Signal Editor.

Change x- and y-axes limits

Change plot x- and y-axes limits in the SignalX.Scenario Axes Properties panes. When you change the limit, the plot adjusts your view. For an example, see Change x- and y-axes limits.

Synchronize signals by time

To synchronize all the signals in open plots by time (x-axis), select Synchronize X-limits in the Synchronize.SignalX Axes Properties pane. Use this setting to also synchronize zooming, panning, and fit-to-plot. For an example, see Add and Edit Multidimensional Signals.

Signal and associated table data selection now linked

Signals in the plot or data table are now linked. Selecting a point in the plot highlights the associated data in the table. Vice versa, selecting a data point in the table highlights the associated point in the plot. Deleting a point in the plot deletes the associated data in the table. Vice versa, deleting a data point in the table deletes the associated point in the plot. For an example, see Add and Edit Multidimensional Signals.

Move signal points in Create Signal live task

The Create Signal Move button has been replaced by the Select and Move point(s) button . The move action is now combined with the select action. This button enables you to select and move one signal point, two contiguous signal points on the same line, or the entire plot. In releases prior to R2024a, the Move button enabled you to move only the entire plot. For more information, see Create Signal.

Access context-sensitive help in Root Inport Mapper

The Root Inport Mapper tool has added access points for context-sensitive help:

• In the Scenarios pane title bar, click the context menu icon.

  

• Right-click a row of the Scenarios pane.

  

fixdt supports C/C++ code generation

The fixdt function now supports C/C++ code generation.

New configuration parameters for finer control of parameter overflow and precision loss diagnostics

Simulink has new configuration parameters that give you finer control over filtering of parameter overflow and precision loss diagnostics.

Access these new parameters in the Diagnostics > Data Validity pane of the Configuration Parameters dialog box:

• Bits of error threshold — Set a threshold of one bit, half bit, or zero bits for parameter overflow detection.

• Suppress double to single detection — Suppress the double to single parameter precision loss detection.

• Absolute difference threshold — Report parameter precision loss when the quantization error exceeds both absolute and relative difference thresholds.

• Relative difference threshold — Report parameter precision loss when the quantization error exceeds both absolute and relative difference thresholds.

New configuration parameters for finer control of parameter overflow and precision loss diagnostics

Parameter Quantization Advisor: Toolstrip-based UI

The Parameter Quantization Advisor interface now includes a simplified toolstrip with new features.

• Filter data:

  • Use the Overflow, Underflow, and Precision Loss filters to show or hide diagnostic data.

  • Use the Parameters Without Diagnostics filter to show or hide issues that are lossless and quantization issues that are filtered out due to Configuration Parameter settings.

• Open the Configuration Parameters dialog box directly from the app using the Model Settings button.

• Refresh data in the app using the Refresh Data button.

• Diagnostics that are suppressed with Simulink.SuppressedDiagnostic are now automatically hidden in the app. You can use the Parameters Without Diagnostics filter to display these diagnostics in the app.

Parameter Quantization Advisor: Toolstrip-based UI

Parameter Quantization Advisor: Support for structures, bus, and Simulink.Parameter objects

The Parameter Quantization Advisor now supports structures, bus objects, and Simulink.Parameter objects.

To open the app for a Simulink.Parameter object, at the MATLAB command prompt, enter this command.

parameterQuantizationAdvisor('model name','Simulink.Parameter object name')

To open the app for a parameter with a structure value, at the MATLAB command prompt, enter this command.

parameterQuantizationAdvisor('block path','parameter name')

Use symbolic expressions for string data types

Starting in R2024a, you can use symbolic expressions for the maximum length of string data types for a subset of Simulink blocks. Symbolic expressions allow you to:

• Update the maximum length simply by updating the corresponding symbolic expression values.

• Avoid rebuilding the model each time you need to update the maximum length.

For more information on creating string data types, see stringtype.

 Functionality being removed or changed

Error reported when you load MPT objects last created or modified before R2012b

Behavior change

In R2024a, if you load a .mat file or a .slx file that contains mpt.Signal or mpt.Parameter objects that were last created or modified before R2012b, Simulink reports one of these error messages:

• Class mpt.CustomRTWInfoSignal not supported in R2024a and removed in R2024b. Migrate instances of this class to the new supported class.

• Class mpt.CustomRTWInfoParameter not supported in R2024a and removed in R2024b. Migrate instances of this class to the new supported class.

To resolve this error, load the .mat file or .slx file in a release later than R2012a and before R2024a. Then resave the file.

Block Enhancements

Dock dashboard panels

You can now dock dashboard panels to the Simulink Editor window. You can use the docked panel to monitor signals and control parameters during simulation without covering the model diagram in the canvas.

To dock a panel, select the panel. If the panel has multiple tabs, select any tab. Then, pause on the ellipsis (…) that appears. In the action menu that expands, click the Dock button .

To return the docked panel to the canvas, click the Open in canvas button .

For more information, see Dock Panels.

Use Expand Scalar block to create scalar expanded matrices

To create scalar expanded matrices, use the new Expand Scalar block.

New Array Processing Subsystem block

Use the new Array Processing Subsystem block to apply an algorithm to each element of a matrix, similarly to the arrayfun function. Use Array Processing Subsystem blocks to efficiently process large input matrices such as image and video data.

New Pixel Processing Subsystem block

Use the new Pixel Processing Subsystem block to apply an algorithm to each pixel in multichannel image data and derive a single-channel output image. The Pixel Processing Subsystem block processes n-dimensional input data like a Neighborhood Processing Subsystem block that has a 1-by-1-by-n neighborhood size.

For an example of how to use the Pixel Processing Subsystem block, see Convert RGB Image to Grayscale by Using a Pixel Processing Subsystem Block.

MinMax block supports specified dimensions

The MinMax block now enables you to find minimum or maximum values over a specified dimension using these new parameters:

• Apply over — Apply function over all or specified dimensions.

• Dimension — Dimension over which to apply the function.

Sum, Sum of Elements, Subtract, Add, Product, Matrix Multiply, and Product of Elements blocks have new parameter names

These parameters for the Add, Sum, Sum of Elements, Subtract, Product of Elements, and Product, Matrix Multiply blocks have been renamed.

Block	New Parameter Name	Old Parameter Name
Sum, Sum of Elements, Subtract, Add	Apply over	Sum over
Product, Matrix Multiply, Product of Elements	Apply over	Multiply over

Width block supports symbolic dimensions

The Width block has these changes:

• Support for symbolic dimensions.

• New parameter, Always use constant sample time.

Data store blocks support indexing for symbolic dimensions

The Data Store Read and Data Store Write blocks now support indexing when the Data Store Memory block uses symbolic dimensions.

From Spreadsheet block supports relative and full paths for File name

The From Spreadsheet block now supports relative and full paths for File name for simulation and code generation. In releases prior to R2024a, if you specified a relative path for File name, the From Spreadsheet block changed the relative path to the full path during code generation.

Support for variable-size input signals in Discrete Filter and Discrete Transfer Fcn blocks

The Discrete Filter and the Discrete Transfer Fcn blocks support variable-size input signals when you set the Input processing parameter to Columns as channels (frame based).

When the input is a variable-size signal, you can change the frame size (number of rows) of the signal during simulation but the number of channels (columns) must remain constant.

Write to base workspace variable or variable in data dictionary using Parameter Writer block

Starting in R2024a, you can use a Parameter Writer block to write to a base workspace variable or a variable that you create in Simulink.data.Dictionary. To configure a Parameter Writer block to write to such a variable, in the Block Parameters dialog box:

• Select Base workspace variable from Destination parameter options.

• Enter the variable name in Workspace variable name field.

Before R2024a, you could only write to a model workspace variable or a block parameter using Parameter Writer block. The new parameter, Destination replaces the existing Access model workspace variable parameter.

Monitor signal values during simulation using customizable Half Gauge and Quarter Gauge blocks

To monitor signal values during simulation, you can now use Half Gauge and Quarter Gauge blocks that can be customized to look like gauges in real systems. The new blocks are located in the Customizable blocks library. The blocks are functionally the same as the Circular Gauge block but are visually pre-configured to look like gauges shaped as a half- and quarter-circle, respectively.

Display block from Customizable Blocks library can display strings

The Display block from the Customizable Blocks library can now connect to and display signals that are strings.

Deploy dashboard panel as web app or standalone desktop app

With a Simulink Compiler license, you can now deploy a dashboard panel, packaged with the model to which the panel connects, as a standalone desktop app or as a web app. You can use the app to operate the controls and monitor the displays on the panel independent of Simulink.

To learn how to deploy panels, see Deploy Dashboard Panel as App.

Dashboard panels support Windows display scaling of over 100%

Dashboard panels support Microsoft^® Windows display scaling values higher than 100%.

Programmatically add data to the Playback block

The Playback block now has a Signals parameter that you can use to retrieve information about signals in the block or add new signals to the block using the get_param and set_param functions.

For example, to add signals from the workspace to the Playback block programmatically:

1. Use the Simulink.playback.createSignals function to create a Simulink.playback.Signal object for the signals you want to add to the Playback block. Specify the source of the data as the workspace, and list the variable names of the signals to be added.

2. Use the set_param function to set the Simulink.playback.Signals object as the value of the Signals parameter.

pbSig  = Simulink.playback.createSignals("workspace","Variables",["x1","x2"]);
set_param("PlaybackModel/Playback","Signals",pbSig);

For more information, see Simulink.playback.Signal and Simulink.playback.createSignals.

Search for signals to add to the Playback block

When you use the Add Signals dialog box to add signals to the Playback block, you can now search for specific signals. As you type the signal name, the table of signals updates to display only the signal names that contain your search term. You can also refine your search to exclude partial matches, match specific capitalization, or use regular expressions to find signals that follow a certain pattern.

Search for signals to add to the Playback block

Support for target-specific code generation for C Function block

Starting in R2024a:

• You can specify target-specific code for code generation interactively using the Code generation tab in the C Function Block Parameters dialog box. Before R2024a, you could specify the code only programmatically by using #ifndef MATLAB_MEX_FILE.

• The target-specific code you specify does not need to be compatible with desktop MEX compilers.

• You can embed the target-specific code in the model-generated code without optimizations.

Report error and warning messages in C/C++ code in C Function block

Starting in R2024a, you can report run-time errors and warnings in C/C++ code that you write in a C Function block. Use slError and slWarning to report run-time errors and warnings, respectively. Error messages indicate unexpected conditions in the code, and warning messages flag potential issues in the code. An error message terminates the simulation. If you see a warning message, you can either terminate or continue with the simulation. For more information, see Report Run-time Errors and Warnings in Simulink.

You can view the error and warning messages using the Diagnostic Viewer in the Simulink canvas.

Specify custom code in C Function block

Starting in R2024a, you can specify your custom C code locally in a C Function block. For multiple C Function blocks, this change allows you to specify only the dependencies associated with the custom code for a specific C Function block. In the Block Parameters dialog box, click the down arrow next to icon and select Use Block Custom Code option.

Before R2024a, you could specify the code only globally using model configuration parameters.

Specify row-major and column-major arrays in custom code for C Function block

Starting in R2024a, you can specify row-major and column-major arrays by using the slSetRowMajor and slSetColumnMajor functions in the C Function block custom code. For more information, see Specify Row-Major and Column-Major Array Layouts in Custom Code.

Out Bus Element block: Specify additional elements and their attributes without adding blocks or bus objects

When a subsystem or model has an output bus element port, you do not need to specify a Simulink.Bus object or add Out Bus Element blocks to:

• Add elements to the output port.

• Specify attributes of the elements at the output port.

For more information, see Define Output Bus Without Extra Blocks or Bus Objects.

To programmatically add elements to the output bus without adding blocks to the block diagram, use the Simulink.Bus.addElementToPort function.

Bus element ports and function ports have more intuitive block interactions

When you interact with In Bus Element, Out Bus Element, Function Element Call, and Function Element blocks, the results of your actions are more consistent and clear.

When you press Ctrl and drag the blocks to a new position, you receive these options:

• New Port — Create a port.

• New Element — Add an element to the port. Out Bus Element and Function Element blocks support this option only when the dragged block represents an element of the port and not the full port.

• Duplicate — Create a duplicate In Bus Element or Function Element Call block. Out Bus Element and Function Element blocks do not support duplication.

These actions consistently create a port:

• Double-click the canvas. In the Quick Insert menu, start typing the name of one of the blocks. Then, select the block from the menu.

• Copy and paste one of the blocks.

For more information about these blocks, see In Bus Element, Out Bus Element, Function Element Call, and Function Element.

Bus Selector block: Right-click elements in dialog box to access options

In the Block Parameters dialog box of a Bus Selector block, right-click elements and select the desired action.

• Add to output — Add elements from the input bus to the block output.

• Highlight source blocks — Highlight the source blocks of elements in the input bus.

• Remove — Remove elements from the block output.

• Remove all invalid elements — Remove all output elements that are not in the input bus. The invalid element names are red.

For more information, see Bus Selector.

Bus Selector blocks have more intuitive parameter names and interactions

When you interact with Bus Selector blocks, the results of your actions are more clear.

• The Select elements button is now the Add to output button .

• The Selected elements list is now the Output elements list.

• The Output as virtual bus button is now the Output as virtual bus check box.

For more information, see Bus Selector.

Graphical Icon Editor: Reuse common icon elements using base part

Starting in R2024a, you can designate a part of a block icon as the base part, allowing all other parts of the icon to inherit its elements. Designating a base part has these advantages.

• There is no need to duplicate common elements in each part, resulting in a lighter icon file.

• Managing the icon is easier since any changes made to the base part of the icon propagate to all other parts of the icon.

For more information on pinning a part as a base part, see Render Multiple Variations of Same Block Icon Using Parts

Graphical Icon Editor: Evaluated mask workspace variables are supported as icon data

Starting in R2024a, you can access evaluated workspace variables as icon data. You can use these values to set conditional visibility, layout constraints, or text parameterization. Additionally, you can retrieve the integer values of enumerations assigned to the workspace variables.

The syntax to access the evaluated value of a mask workspace variable is:

value@maskWorkspaceVariable === value

For example, set the visibility condition for an icon element.

value@Parameter1 === "10"

The syntax to access the evaluated value of an enumeration member is:

value@enumerationMember === "enumerationValue"

For example: Set the condition visibility for an icon element based on the evaluated value of the enumeration member.

value@open_orifices_pos === '2'

Previously, the condition was set as

open_orifices_pos === 'fluids.thermal_liquid.valves.directional_control_valves.enum.OpenOrifices3Way.PA'

For more information on evaluated parameters, see Set Visibility Condition Based on Evaluated Value of Parameters

Note

The supported datatypes for the resolved parameter are numeric, boolean, and string.

Graphical Icon Editor: Adapt block icon color to Simulink canvas color

Prior to R2024a, the block icon's default color was white, regardless of the canvas color. However, starting from R2024a, you now have the option to make the background of the block icon transparent, allowing the Simulink canvas color to show through. You can also set, the background color of closed shape elements inside the block to inherit the Simulink canvas color. For more information, see the icon properties pane table in Edit Properties of Block Mask Icon and Its Elements.

Graphical Icon Editor: Repeat icon elements on multiple ports

Starting in R2024a, you can use the Repeat Parameterization option to repeat icon elements on multiple ports of a block. You can choose to repeat the elements based on the position of the ports.

For example, you can repeat an icon element for all the left ports of the block and left align the elements of the block.

To repeat an icon element, right-click the element and select Parameterize from the context menu. In the Element Parameterization panel, select the position of the ports and the alignment of the elements for each port.

For more information on repeating icon elements, see Repeat Icon Elements on Multiple Ports.

Graphical Icon Editor: Preview variations of a block icon

Starting in R2024a, you can preview variations of a block icon based on visibility conditions and parameters using the options Parameter Variations and Width Height Variations. These options are available along with other preview options in Simulink canvas. For more information, see Design Complex Block Icon Using Parts and Preview the Variations

Specify height, width, and alignment for an image in a block icon

You can now specify image alignment details by using mask icon drawing commands, including alignment to the left, right, top, and bottom margins. You can also specify the width and height of the image as a percentage of the width and height of the block. For more information, see image.

For example:

image("path\to\image",[leftMargin, topMargin, rightMargin, bottomMargin, widthPercentage, heightPercentage])

image("airplane.jpg",[0,0,10,10,90,90])

Add parameters from base class in system object masks

Starting in R2024a, the Base Class Property parameter in a system object mask allows you to access available parameters from the system object file and modify the mask by adding parameters inherited from the base class. You can add or remove parameters from the base class, but it is not possible to remove parameters from the derived class. This ensures that the necessary parameters and functionality from the derived class are retained in the mask.

For more information, see Create and Customize MATLAB System Icon and Dialog Box Using Mask Editor.

PID Controller Blocks: Use derivative signal from external source

The PID controller blocks now allow you to supply the derivative of the plant signal y directly as an input to the block. This is helpful when you have the derivative signal available in your model and want to skip the computation of the derivative inside the block.

To enable the input port for supplying the derivative, select a controller type that has derivative action and enable the Use externally sourced derivative parameter.

Report runtime diagnostics for MATLAB System block in rapid accelerator mode

Report runtime errors for MATLAB System blocks when simulating in rapid accelerator mode by using one of these options:

• Open the Configuration Parameters window. In the Modeling tab, click Model Settings. In the Configuration Parameters window, click Simulation Target, expand Advanced Parameters, and set the Enable memory integrity checks configuration parameter to Always on.

• Use the set_param function to set the SimIntegrity parameter to 'alwaysOn'. For example, to enable diagnostics for a model named model_name, enter this command:

  set_param('model_name','SimIntegrity','alwaysOn');

Simulate FMU without defining bus objects or enumeration classes

You can now simulate an FMU that contains ports with bus or enumeration data types without having to manually define a bus object or enumeration class in the current Simulink session. The FMU block uses the metadata inside the modelDescription.xml file to determine the signal attributes for bus and enumeration type ports. This enables downstream and upstream blocks to inherit enumeration data type and downstream blocks to inherit bus data types. To enable direct simulation and propagation, open the FMU dialog box and set Type Object attribute to Inherit:auto for input and output ports with enumeration data types and Auto generate for output ports with bus data types.

Generate binary for FMU from source code

You can now generate binaries of FMUs on the corresponding platforms from its source code using the fmudialog.compileFMUSources function. For example, you can use this function to generate the Linux^® binary for an FMU that includes the source code but does not include the binary required for simulation on Linux platform.

Improve simulation performance of Python functions integrated into Simulink using Python Importer

Starting in R2024a, the simulation performance of the blocks generated by Python^® Importer, which integrates Python functions into Simulink, is improved by generating C-wrappers that are used to call the specified Python functions. This enhances the simulation performance of the blocks, enables simulation in rapid accelerator mode, and supports simulation in model reference with accelerator mode. You will need to have Python installed in your system to perform the simulation.

This enhancement is not supported for Python functions that are defined inside classes.

Launch external debugger from Simulink for debugging FMU

You can now directly launch an external debugger for debugging FMU from Simulink without manually configuring the external debugger to connect to Simulink.

Use the fmudialog.compileFMUSources function with 'DebugMode' argument set to 'on' to generate debugging information for an FMU that contains its source code.

To launch the external debugger, go to the Debug tab in Simulink and select Set Breakpoints in Custom Code option.

The Select Entities to Debug dialog box lists the entities that can be debugged. The FMUs that can be debugged are listed under FMU Blocks. Select the FMU that you want to debug and move them to Selected Entities.

Click Open to launch the external debugger.

Assign units to ports and parameters in S-Function Builder

Starting in R2024a, you can assign units to ports and parameters in S-Function Builder.

Use the Simulink.SFunctionBuilder.update function to assign units to ports or parameters. For example, the following code assigns m/s as the unit for the first input of s-function AddOne.

Simulink.SFunctionBuilder.update('AddOne','Input','u0','Unit','m/s');

You can also specify units in the Units column of Ports and Parameters table in the S-Function Builder.

Enhancements to FMU block importing FMU compatible with FMI 3.0 standards

FMU block importing an FMU that is compatible with FMI 3.0 standards has the following enhancements. Starting in R2024a you can:

• Generate code for model that contains the FMU.

• Create FMU from a model that contains FMU.

• Simulate model with FMU in Rapid Accelerator simulation mode.

• Export model with FMU to a protected model.

• Use the FMU inside a model reference in Accelerator simulation mode.

Simulate FMU containing Linux binary on Windows

You can now use the FMU to import and simulate an FMU, compatible with FMI 2.0 standards, with Linux binary on Windows platform.

You will need to install Windows Subsystem for Linux (WSL) Version 2.0.9.0 or newer and FMU Builder for Simulink support package to import and simulate the FMU with Linux on Windows.

Note

This feature requires Simulink Compiler license.

 Functionality being removed or changed

Multiport Switch block has runtime error when input has floating point value

Behavior change

The Multiport Switch block now issues a runtime error when the control signal in the first port has a floating point value that exceeds the datatype range of integers. This range includes Inf and NaN.

Connection to Hardware

Hardware boards and minidrones: Documentation for hardware support packages moved to Simulink documentation

Starting R2024a, the documentation for the following support packages will be included in the Simulink documentation and all updates will be announced in the Simulink release notes.

• Simulink Support Package for Android^® Devices

• Simulink Support Package for Arduino^® Hardware

• Simulink Support Package for LEGO^® MINDSTORMS^® EV3 Hardware

• Simulink Support Package for Parrot^® Minidrones

• Raspberry Pi^® Blockset

In previous releases, the support package documentation was installed when you installed the support package software. To access archived release notes from the previous release, click one of the following links.

• R2023b Android Devices Release Notes

• R2023b Arduino Hardware Release Notes

• R2023b LEGO MINDSTORMS EV3 Hardware Release Notes

• R2023b Parrot Minidrones Release Notes

• R2023b Raspberry Pi Hardware Release Notes

Android Devices: Execute multiple tasks, detect task overruns, and profile code execution times in Android Simulink models

Simulink Support Package for Android Devices now supports these features that facilitate parallel processing of tasks, reduce the risk of timing while executing a task, and enhance overall performance in a real-time system.

• Treat each discrete rate as a separate task — Determine whether the support package executes blocks with periodic sample times individually or in groups.

• Allow tasks to execute concurrently on target — Specify concurrent tasking behavior for an Android Simulink model.

• Detect task overruns — Detect and notify when a task overrun occurs in a Simulink model running on your Android device.

• Run external mode in a background thread — Force the external mode task in the generated code to execute in a background thread.

• Measure task execution time — Measure execution times and generate metrics for blocks inside a Simulink model.

For more information, see Model Multitask Execution and Real-Time Code Execution Profiling on Android Device and Model Code Profiling for Multiband Dynamic Range Compression System Using Android Device.

Arduino Hardware: Configure static IP address

Starting R2024a, you can now configure a static IP address and specify the DNS server address, gateway address, and the subnet mask for these Arduino hardware boards.

• Arduino compatible ESP32 — WROOM

• Arduino compatible ESP32 — WROVER

• Arduino MKR 1000

• Arduino MKR Wi-Fi^® 1010

• Arduino Nano 33 IoT

This release also introduces a new option, Static IP — Advanced, under Configuration Parameters > Target hardware resources > WiFi properties > IP address assignment, which you can use to configure networking properties of these Arduino boards.

Arduino Hardware: Read and write data to on-board Arduino EEPROM

This release introduces the On-board EEPROM Read and On-board EEPROM Write blocks, which you can use to read from and write to the byte-addressable Arduino on-board EEPROM. You can build and deploy the blocks on these Arduino hardware boards.

• Arduino Mega 2560

• Arduino Uno

• Arduino Leonardo

• Arduino Micro

• Arduino Nano 33 IoT

Arduino Hardware: Handle hardware interrupts from ADC and PWM peripherals on Arduino AVR hardware

Simulink Support Package for Arduino Hardware now supports handling hardware interrupts generated by the ADC and PWM peripherals for the AVR family of Arduino hardware. Earlier releases supported handling of hardware interrupts from external pins only.

• Hardware Interrupt — Use this block to trigger a downstream function-call subsystem from an interrupt service routine.

• PWM — Use this block to generate a square wave on the specified output pin of the Arduino AVR hardware.

• Analog Input — Use this block to read the ADC register value at the specified pin of the Arduino AVR hardware.

Arduino Hardware: Control color and brightness of Adafruit NeoPixel strip

This release introduces the NeoPixel block, which you can use to control the color and brightness of individual pixels on the NeoPixel strip. The pixels on the strip are individually addressable RGB and RGBW LEDs that you can use to create different light patterns and effects.

Arduino Hardware: Deploy Simulink models to Teensy 4.0 and 4.1 hardware boards

Simulink Support Package for Arduino Hardware now supports deploying Simulink models on the Arduino compatible Teensy 4.0 and 4.1 hardware boards. The Hardware board drop-down list in the Configuration Parameters dialog box now includes the Teensy 4.0 (Arduino compatible) and Teensy 4.1 (Arduino compatible) options. A new parameter, Terminate Teensy Loader application post deployment has been added under Configuration Parameters > Target hardware resources > Host-board connection

You can use these blocks from the support package library with the Arduino Teensy hardware boards.

Ultrasonic Sensor	LSM6DS3 IMU Sensor	LSM303C IMU Sensor	VL53L0X Time of Flight Sensor
BNO055 IMU Sensor	LSM6DS3H IMU Sensor	LPS22HB Pressure Sensor	BMP280 Pressure Sensor
APDS9960 Sensor	LSM6DSL IMU Sensor	HTS221 Humidity Sensor	LIS3DH Accelerometer Sensor
MPU9250 IMU Sensor	LSM6DSM IMU Sensor	ADXL34x Accelerometer	OV2640 Camera Sensor
MPU6050 IMU Sensor	LSM6DSO IMU Sensor	CCS811 Air Quality Sensor	Digital Input
LSM9DS1 IMU Sensor	LSM6DSR IMU Sensor	ICM20948 IMU Sensor	Digital Output
PWM	Standard Servo Write	I2C Controller Read	Analog Input
Serial Transmit	Standard Servo Read	I2C Controller Write	External Interrupt
Serial Receive	Continuous Servo Write	SPI WriteRead	Protocol Encoder
Protocol Decoder	L293D DC Motor	PCA9685 DC Motor	NeoPixel

Currently, the support package does not support simulating a model to the Arduino compatible Teensy 4.0 and 4.1 hardware boards in the Connected IO and PIL modes.

Arduino Hardware: Use secondary I2C and SPI modules

Starting R2024a, Simulink Support Package for Arduino Hardware supports utilizing the secondary I2C and SPI modules on these Arduino hardware boards.

Secondary I2C Enabled Arduino Boards	Secondary SPI Enabled Arduino Boards
Arduino Due	Arduino compatible ESP32-WROOM
Arduino compatible Teensy 4.0 and 4.1	Arduino compatible ESP32-WROVER

Earlier, you could use only one I2C and SPI module on the Arduino boards.

Arduino Hardware: Detect COM ports automatically using VID and PID numbers

Starting R2024a, Simulink Support Package for Arduino Hardware now automatically detects the COM port of the host machine to which you have connected the Arduino board by using the vendor identification (VID) and product identification (PID) numbers. This release also introduces a new parameter, Verbose output under Configuration Parameters > Target hardware resources > Build Options, which provides additional diagnostics about the Simulink models that you have deployed to the Arduino board.

Arduino Hardware: Save code profiling summary and analysis data

Starting R2024a, Simulink Support Package for Arduino Hardware provides the Summary data only and All data options for saving code profiling data. To access these options, navigate to Configuration Parameters > Code Generation > Verification path, select Measure task execution time (Embedded Coder), and specify an option under Save options (Embedded Coder).

• Summary only data — Use this option to save only code profiling summary data in the base workspace.

• All data — Use this option to save the code profiling measurement and analysis data in the base workspace. This option also enables the streaming of execution times to Simulation Data Inspector during simulations.

Arduino hardware boards with SAM core architecture supports task execution measurement with the Metrics Only saving option. For more information, see Code Execution Profiling for Arduino Hardware in External Mode.

Arduino Hardware: Connected IO support for blocks

You can now deploy a Simulink model to an Arduino board in the Connected IO mode when it contains the following blocks.

Input Capture	WiFi TCP/IP Receive	WiFi UDP Receive
Analog Output	WiFi TCP/IP Send	WiFi UDP Send

Arduino Hardware: Repurpose analog pins as digital pins

Starting R2024a, when using Simulink Support Package for Arduino Hardware, you can repurpose the analog pins as equivalent digital pins on all the Arduino hardware boards. You can also use analog pins in these blocks.

Digital Output	Standard Servo Write
External Interrupt	Standard Servo Read
SPI WriteRead	Continuous Servo Write
Ultrasonic Sensor

Arduino Hardware: Read linear acceleration, angular velocity, and temperature using ADIS16505 sensor

Simulink Support Package for Arduino Hardware now supports interfacing the ADIS16505 sensor connected to the SPI bus of Arduino hardware. You can use the new ADIS16505 6DOF IMU Sensor block to measure linear acceleration and angular velocity along the x-, y- and z- axes, and to measure temperature.

Raspberry Pi Hardware: Customize Raspberry Pi OS setup

When installing Raspberry Pi Blockset, you can download and install only select third-party libraries and packages on your Raspberry Pi operating system. Use the Hardware Setup window to specify the libraries and packages. This update allows you to efficiently manage the resources of your Raspberry Pi operating system by avoiding unnecessary downloads. For more information, see Modularize Installation of Third-Party Packages and Libraries for Raspberry Pi Hardware.

Raspberry Pi Hardware: Support for 64-bit Bullseye Raspberry Pi OS

Starting R2024a, you can use the Raspberry Pi Resource Monitor App app with the 64-bit Bullseye operating system. Earlier, the app supported the 32-bit Bullseye and Buster Raspberry Pi operating system.

Starting this release, you can also simulate a Simulink model in the Normal mode with Connected IO with the 64-bit Bullseye Raspberry Pi operating system

Raspberry Pi Hardware: Support for Raspberry Pi Compute Module 4 hardware board

Starting R2024a, you can use Raspberry Pi Blockset to deploy Simulink blocks and models to the Raspberry Pi Compute Module 4 hardware board.

Raspberry Pi Hardware: Stream video over RTSP using Video Stream Transmit block

This release introduces the Video Stream Transmit block, which you can use to stream video to a network using the real-time streaming protocol (RTSP). For effective use of network bandwidth, you can encode the video stream using the H264 or JPEG protocols. For more information, see Stream Video Over Network Using Raspberry Pi Video Stream Transmit Block.

Raspberry Pi Hardware: Use secondary I2C and SPI modules

Starting R2024a, Raspberry Pi Blockset supports utilizing the secondary I2C and SPI modules on the Raspberry Pi Zero 2 W, 3B, 3B+, 4B, and Compute Module 4 hardware boards. Earlier, you could use only one I2C and SPI module on the Raspberry Pi hardware boards.

Raspberry Pi Hardware: Deploy dashboard blocks using Simulink Online

Starting R2024a, you can deploy all the dashboard blocks in the Simulink Customizable Blocks library to your Raspberry Pi hardware board using Simulink Online. For more information, see Connect to Raspberry Pi Hardware Board in Simulink Online.

Raspberry Pi Hardware: Support added for Apple silicon Mac hardware

Starting R2024a, you can use the Raspberry Pi Blockset to build and deploy Raspberry Pi applications on Apple silicon Mac computers.

MATLAB Function Blocks

Specify header file within coder.ceval command

Starting in R2024a, you can specify a header file for a C/C++ function within a coder.ceval (MATLAB Coder) call by using the "-headerfile" name-value argument. Prior to R2024a, you had to specify a header file separately by calling coder.cinclude (MATLAB Coder) before coder.ceval.

For example, to call the C function foo declared in header file foo.h with input argument x, include this coder.ceval command in your MATLAB code:

y = coder.ceval("-headerfile","foo.h","foo",x);

Use a for-loop that iterates over a cell array inside MATLAB Function block

In R2024a, you can use a for-loop that iterates over a cell array inside a MATLAB Function block. The size of the first dimension of the cell array must be equal to 1. This usage supports iterating over both homogeneous and heterogeneous cell arrays.

For example, define the MATLAB function addStructFields that adds all the fields of an input struct s. In the function code, access the fields of s by looping over the cell array that fieldnames(s) returns.

function out = addStructFields(s)
out = 0;
for f = fieldnames(s)'
    out = out + s.(f{1});
end
end

Use addStructFields to create a MATLAB Function block that adds all elements of an input bus signal and outputs the sum.

Use uint32 enumerations greater than intmax("int32") inside MATLAB Function blocks

Starting in R2024a, you can use MATLAB enumerations derived from base type uint32 with values greater than intmax("int32") inside MATLAB Function blocks.

Enumerations with values greater than intmax("int32") are not supported as input to or output from MATLAB Function blocks.

Prior to R2024a, usage in MATLAB Function blocks supported uint32 enumeration values less than or equal to intmax("int32") only.

See Code Generation for Enumerations.

Control function inlining at the function call site using coder.inlineCall and coder.nonInlineCall

Starting in R2024a, you can call functions using coder.inlineCall (MATLAB Coder) and coder.nonInlineCall (MATLAB Coder) to instruct the code generator whether or not to inline the called function. The coder.inlineCall and coder.nonInlineCall functions override coder.inline directives in the called function.

For example, you can inline function foo and prevent the inlining of function bar in the generated code by calling foo and bar in your MATLAB code using coder.inlineCall and coder.nonInlineCall, respectively.

...
coder.inlineCall(foo);
coder.nonInlineCall(bar);
...

The coder.inlineCall and coder.nonInlineCall functions are subject to the same limitations as the coder.inline directive.

Generate code for alternate execution paths depending on whether configuration settings support unbounded variable-size arrays

In R2024a, you can use the coder.areUnboundedVariableSizedArraysSupported function inside MATLAB Function blocks. The return value of this function depends on whether you perform model simulation or code generation.

• During model simulation, this function returns the state of the configuration parameter Dynamic memory allocation in MATLAB functions.

• During code generation, this function checks the state of the configuration parameters Dynamic memory allocation in MATLAB functions and Support: variable-size signals. If both of these parameters are enabled, the function returns true. Otherwise, it returns false.

In both situations, the return value of coder.areUnboundedVariableSizedArraysSupported indicates whether current configuration settings support unbounded variable-size arrays.

In MATLAB execution, the coder.areUnboundedVariableSizedArraysSupported function always returns true.

For a demonstration of this functionality, consider the MATLAB function sumOfOneToN that computes the sum of the first n natural numbers in two different ways.

function out = sumOfOneToN(n)
if (coder.areUnboundedVariableSizedArraysSupported)
    out = sum(1:n);  % Uses unbounded variable-size array
else
    out = n*(n+1)/2; % Does not use unbounded variable-size array
end

Model simulation with dynamic memory allocation enabled executes the if branch in the function sumOfOneToN. This branch uses an unbounded variable-size array to compute the output.

By contrast, model simulation with dynamic memory allocation disabled executes the else branch in the function sumOfOneToN. This branch does not use unbounded variable-size arrays to compute the output.

Code generation for more MATLAB functions

• cellfun

• copyfile

• getfield

• isenv

• iskeyword

• lsqminnorm

• movefile

• pageinv

• qrdelete

• qrinsert

• sscanf

• setfield

• unsetenv

Code generation for more toolbox functions

In R2024a, you can generate code for many additional toolbox functions and objects. For a list of all functions and objects that are supported for code generation, see:

• Functions and Objects Supported for C/C++ Code Generation (Category List)

• Functions and Objects Supported for C/C++ Code Generation (Alphabetical List)

These are links to the release notes of some toolboxes that added code generation support in R2024a:

Computer Vision Toolbox

See MATLAB Coder Support: Generate C and C++ code using additional functions (Computer Vision Toolbox).

Image Processing Toolbox

See C Code Generation: Generate code from additional functions using MATLAB Coder (Image Processing Toolbox).

Signal Processing Toolbox

See Generate C/C++ code for signal generation and spectral analysis (Signal Processing Toolbox).

Wavelet Toolbox

See C/C++ Code Generation: Automatically generate code for wavelet functions (Wavelet Toolbox).

Modeling Guidelines

New High-Integrity System modeling guidelines

This table lists the high-integrity system modeling guidelines introduced in R2024a.

Guideline	Model Advisor Check
hisl_0078: Usage of identical modeling patterns	Check usage of identical modeling patterns (Simulink Check)
hisl_0079: Connections to root input/output ports	Check for invalid root input and output port connections (Simulink Check)
hisl_0038: Configuration Parameters > Code Generation > Comments	Added configuration parameters Stateflow object comments (Simulink Coder) and MATLAB source code as comments (Simulink Coder) to the guideline.

Removed or modified modeling guidelines

Starting in R2024a, these modeling guidelines have been removed or modified.

Modeling Guideline	Description
cgsl_0101: Zero-based indexing	Removed
hisl_0046: Configuration Parameters > Simulation Target > Block reduction	Removed
hisl_0310: Configuration Parameters > Diagnostics > Model Referencing	Configuration parameter Invalid root Inport/Outport block connection (ModelReferenceIOMsg) is no longer supported in the software, therefore, the parameter is removed from the modeling guideline.
hisl_0037: Configuration Parameters > Model Referencing	Removed configuration parameter Pass fixed-size scalar root inputs by value for code generation from the guideline.