Undoubtedly, fast and accurate battery models are crucial for various applications such as electric vehicles, renewable energy storage, and portable electronics. Machine learning techniques offer the ability to develop efficient and comprehensive models for automotive simulation including batteries and their thermal aspects. This 45-minute webinar explores how to use machine learning to develop these more efficient models as well as showcase how machine learning algorithms are employed to quickly capture complex behaviors and integrate them into vehicle system models. Additionally, the program will highlight the potential benefits of integrating machine learning into battery modeling processes such as improved prediction accuracy, reduced computational time, and enhanced system optimization capabilities. Topics include:
- How machine learning techniques are used to develop efficient, optimized vehicles
- How machine learning algorithms can capture complex battery behaviors quickly and integrate them into vehicle system models
- How integrating machine learning into engineering processes can lead to improved prediction accuracy, reduced computational time, and enhanced system optimization capabilities
Speaker: Massimiliano Mastrogiorgio, Senior Battery Application Engineer, Gamma Technologies