Course Outline

Introduction to EV Software and Embedded Systems

  • Overview of EV software architecture
  • Key components of embedded systems in EVs
  • Software challenges unique to electric mobility

Control Systems for Electric Vehicles

  • Designing software for motor control and power management
  • Battery management system (BMS) software integration
  • Monitoring and diagnostics for system health

Real-Time Processing and Data Management

  • Implementing real-time data acquisition and processing
  • Data fusion from multiple sensors
  • Ensuring low-latency control in dynamic environments

Autonomous Driving and AI Integration

  • Using machine learning for perception and decision-making
  • Integrating AI algorithms with embedded systems
  • Testing and validation of autonomous functions

Advanced Software Safety and Compliance

  • Applying ISO 26262 for functional safety
  • Ensuring cybersecurity in connected EV systems
  • Developing fault-tolerant software architectures

Hands-On Lab: Building a Basic EV Control System

  • Setting up an embedded software environment
  • Programming control algorithms for motor operation
  • Testing and debugging the control system

Best Practices for EV Software Development

  • Maintaining code quality and efficiency
  • Collaborating in multidisciplinary engineering teams
  • Documenting and testing software components

Future Trends and Innovations in EV Software

  • Next-gen AI for fully autonomous electric vehicles
  • Integration with IoT and smart infrastructure
  • Predictive maintenance using AI-driven analytics

Summary and Next Steps

Requirements

  • Experience with embedded systems programming
  • Knowledge of automotive software development
  • Understanding of real-time processing and control systems

Audience

  • Software developers working on EV applications
  • Embedded systems engineers in the automotive sector
  • AI specialists focusing on autonomous EV technology
 14 Hours

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