Demo Stations

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AI in Automotive: Building Smart Apps Using Data and the Cloud

Operationalizing AI Algorithms for Range Estimation

  1. No/low code AI-driven system design
  2. Deploying the models to embedded targets
  3. Continuous improvement on deployed algorithms with MATLAB in the cloud

Battery Fleet Analytics in the Cloud

  1. Accessing data from the cloud
  2. Leveraging the cloud for model training
  3. Deploying AI algorithms on the production server
  4. User RestAPI protocol for fetching results on live dashboards

AI for Product Design Optimization

  1. Building a design of experiments (DOE) table for component design
  2. Creating surrogate AI models from high-fidelity simulations
  3. Running multiobjective design optimization studies using AI models

Robust Workflows for Software-Defined Vehicle App Development

Building Driver Awareness Features Adhering to Functional Safety Workflow Using CI/CD

  1. Innovate and prequalify before submitting to a CI pipeline
  2. Extend Model-Based Design workflows into CI platforms
  3. Simplify adoption by using CI automation support

Application of Formal Methods in the Software Factory for Automotive Software

  1. Software testing in continuous integration (on premises, cloud)
  2. Using formal methods to address vulnerabilities and achieving DevSecOps in the software factory
  3. Establishing a mature issue detection process to enable shift-left verifications
  4. Ensuring modern automotive software compliance to ISO 26262 and ISO 21434

Model-Based Systems Engineering for Electric Vehicle and Charger Development

  1. Requirement management
  2. System and component architecture development
  3. Trade studies for architecture analysis
  4. Compliance to ASPICE standards

Electrification

Live Range Prediction of Electric Vehicles

  1. Electric vehicle modeling for optimal live range predictions
  2. Real-time data integration with maps including route information, traffic congestion, and road elevation
  3. Developing AI-based models to analyze historical driving patterns and adjust predictions
  4. Using cloud-based architecture for data processing and analysis

Electric Vehicle Development: Utilizing System-Level Simulation for Thermal Analysis and Control

  1. Electric vehicle component thermal analysis
  2. Development and testing for vehicle control units, battery management, and thermal management

EV Traction Motor Control Made Easy

  1. Model and parameterize motors
  2. Autotune speed and current controllers with the Field Oriented Control Autotuner block
  3. Deploy motor control algorithms onto desired target hardware

AD/ADAS

Smart Testbench for Automated Driving System Validation

  1. Creating variants for scenarios in Euro NCAP and others
  2. Iteratively identifying the failure scenario for regression testing
  3. Integrated test automation and automatic variant generation for validating ADAS systems

Scene and Scenario Modeling from RoadRunner

  1. Creating scenes and scenarios in RoadRunner
  2. Creating recorded sensor data in scenarios
  3. Interoperating with ASAM standards in OpenDRIVE, OpenSCENARIO, OpenCRG, and Open Simulation Interface (OSI)

System Modeling and Algorithm Development for Automated Parking Valet

  1. Creating scenarios and modeling a MIMO transceiver chain for 4D automotive radar
  2. Antenna array modeling and waveform design I/Q data generation
  3. Perception, sensor fusion, path planning, and controls
  4. Other reference applications including AEB, HLF, parking valet, and traffic negotiations