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MathWorks AUTOMOTIVE CONFERENCE

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Demo Stations

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Technology Showcase:


Artificial Intelligence

  • AI in Simulation: Reduced-Order Modeling

    • Workflow for data-driven ROM
    • Different use cases for ROM
    • Examples: Developing AI models for an SI engine and flexible shaft
  • AI Deployment on Embedded Systems and Cloud

    • Deploy AI into an embedded hardware and enterprise system from one code base
    • Fit AI models to embedded hardware with quantization/fixed point conversion
    • Scale to data and users using enterprise deployment
  • AI in Electrification: Battery SOC and SOH Estimation

    • AI use cases in the automotive industry
    • Battery SOC and SOH estimation with deep learning

Electrification and Full Vehicle Simulation

  • Battery Modeling and Management

    • Design and simulate battery and BMS using Simscape Battery
    • Evaluate electrical and thermal responses of different battery pack architectures
  • EV Traction Motors: Motion Control Made Easy

    • Model motors and parameterize your motor models
    • Autotune your speed and current controllers with FOC Autotuner
    • Deploy your motor control algorithms onto your desired target hardware
  • Building Full-Vehicle Simulation Models

    • Simulation of an electric two-wheeler
    • Powertrain architectures for different vehicle models
    • Simulation of vehicle dynamics and optimization of suspension design for ride and handling characteristics

ADAS and Automated Driving

  • Automated Driving: Creating Virtual Worlds and Algorithms

    • Create scenes and scenarios from recorded data
    • Create scenes and scenarios in RoadRunner and interoperate with ASAM standards
    • Develop AD applications: AEB, HLF, parking valet, traffic negotiations
  • Validation and Testing of Automated Driving Features

    • Setting up test automation framework
    • Real-time testing for ADAS ECUs
    • Interfacing with HILs and external hardware

Functional Safety and Cybersecurity

  • Early Verification and Validation Using Model-Based Design

    • Efficient elimination of errors at early stages
    • Continuous and uninterrupted refinement of system and software requirements and architectural designs
    • Complete traceability and improved consistency among requirements, architecture, design, source code, and test cases
    • Certifiable tools and workflow
  • Formal Code Verification

    • Adhere to coding standards: safety and security, robustness checking without testing, and compliance with ISO 26262 and ISO 21434
    • Integrate at different SDLC stages, intuitive and actionable presentation of results, decrease testing efforts
    • Integrate into development workflows—Model-Based Design, devOps, Dockerization—and run on cloud platforms

Developing Applications for Software-Defined Vehicles

  • Design and Develop Service-Oriented Applications

    • Developing service-oriented architectures with Simulink
    • Using SOME/IP communication and DDS data binding
    • Deploying service-oriented architectures on Linux targets
  • Integrating Model-Based Design with Continuous Integration for Agile Workflows

    • Software engineering tasks automation using MATLAB and Simulink in CI
    • MATLAB and CI integration on a CI server or cloud-hosted CI system
    • Integration of MATLAB and Simulink into your CI pipeline

Safety Guidelines:

  1. Masks are mandatory at the venue.
  2. Please keep a soft or hard copy of your vaccine certificate. This is mandatory to gain access to the venue.
  3. Sanitize at regular intervals. Follow other COVID-related guidelines listed by the local government authorities.
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