Automotive

Speed-Up Software-Defined Vehicle Development with MATLAB, Simulink, and Polyspace

With Software-Defined Vehicle (SDV), development teams must build new capabilities such as making continuous software releases, reducing lead time for software changes, and minimizing deployment failures. At the same time, the platform team needs to create new software development environments for vehicle computers and zonal controllers, set up continuous integration/continuous delivery (CI/CD) systems, and facilitate the collaboration between system and software developers. MATLAB, Simulink, and Polyspace enable these teams to speed-up the delivery of their products while meeting automotive requirements through early validation, software reuse, and tool integration. With these products, development and platform teams can:

  • Design software features independent of the target platform and deploy them to signal-based and service-oriented middleware such as AUTOSAR
  • Perform early and continuous validation using virtual vehicle and virtual ECU simulation
  • Achieve functional safety (ISO® 26262), quality (Automotive SPICE® or ASPICE), and security targets
  • Automate software integration and testing using CI/CD and DevOps practices
  • Leverage the cloud for collaboration, simulation, and processing fleet data
Software-defined vehicle workflow.

Design, Simulate, and Deploy Signal-Based and Service-Oriented Applications

SDVs integrate both signal-based and service-oriented applications onto newer Electrical/Electronic (EE) architectures with vehicle computers and zonal controllers. This requires developers to target new service-oriented architectures (SOA) and traditional signal-based architectures.

SOAs enable developers with the flexibility to build modular services that are dynamically discovered, published, subscribed to, and reconfigured during runtime. This allows software updates at a feature and function level. SOAs have been widely incorporated into industry standards and in-house frameworks, including AUTOSAR, DDS, and ROS. With Simulink, you can:

  • Author software applications for signal-based and service-oriented architectures, including AUTOSAR Classic and Adaptive
  • Integrate these software applications with commercial or in-house middleware
  • Model and simulate application software components and services
  • Automatically generate production C/C++ code for these software applications

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Shift left software integration.

Shift Left Software Integration with Virtual Vehicle Simulation

With frequent over-the-air (OTA) software updates, testing new software configurations using prototype hardware is no longer feasible. Integration testing also needs to be automated to reduce lead time for software release. Shifting software integration to model-in-the-loop (MIL) and software-in-the-loop (SIL) testing with a virtual vehicle simulation that is integrated with a continuous integration pipeline helps address both issues. With Simulink, Virtual Vehicle Composer, and Simulink Compiler, you can:

  • Automate the assembly of virtual vehicle models 
  • Build virtual Electronic Control Unit (ECU) simulations with a mix of model and code-based components in Simulink and integrate with third-party tools for production Basic Software (BSW) and processor simulation
  • Deploy virtual vehicle and virtual ECU models into continuous integration pipelines

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Achieve Quality, Safety, and Security Targets

Software applications for SDV must meet quality targets while ensuring compliance with safety and security standards. Using MATLAB and Simulink within the Model-Based Design reference workflow, development teams can achieve the objectives imposed by ASPICE process standard, ISO 26262 functional safety standard, and ISO 21434 cybersecurity standard, including UN-ECE WP.29. MATLAB products for model verification, Embedded Coder, and Polyspace code verification are pre-qualified by TÜV SÜD according to ISO 26262 for ASIL A-D. With these products, developers can:

  • Trace requirements to architecture, design, tests, and code 
  • Prove that the software is free of critical run-time errors 
  • Automate verification of models and code to meet quality and safety standards like ASPICE and ISO 26262
  • Check compliance and measure quality of models and code 
  • Enhance software security by checking for vulnerabilities and adherence to standards such as CWE™, CERT®-C, MISRA™, ISO 21434, and more
Quality, safety, and security workflow.

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Automate Processes and Scale from Desktop Computers to the Cloud

Implementing automation at scale is key to reducing software development effort. Development technologies like CI/CD bring automation to developers and, at the same time, ensure reliability through repeatable processes. In addition, cloud technology enables scaling by speeding up software builds and simulations, processing large data sets, and facilitating collaboration of distributed software teams. With MATLAB and Simulink, you can:

  • Integrate with CI/CD systems like Jenkins®, Gitlab® Actions, and Azure® DevOps
  • Process cloud-based data in systems such as AWS® S3 and Azure Blob, and scale as per the need 
  • Scale simulation to clusters and cloud using MATLAB Parallel Server
  • Accelerate training of neural networks on GPUs
  • Develop collaboratively with Git and SVN Source Control  

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