Electric Vehicle Software and Embedded Systems

• 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

Electric Vehicle Software and Embedded Systems is a specialized field focusing on developing control systems, real-time processing, and AI-driven applications for modern electric vehicles.

This instructor-led, live training (online or onsite) is aimed at advanced-level automotive software professionals who wish to enhance their expertise in designing embedded systems and intelligent software solutions for electric vehicles, including AI integration for autonomous functionalities.

By the end of this training, participants will be able to:

• Design embedded software for EV control systems.
• Implement real-time data processing for efficient vehicle operation.
• Integrate AI-driven decision-making for autonomous EVs.
• Apply best practices in software safety and automotive compliance.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

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