E2 Promotion lecture by Changfu Zou for Professor

Welcome to the Promotion lecture by Changfu Zou for Biträdande professor/Professor

Title: From Aging Prognosis to Intelligent Control: How Machine Learning is Transforming Battery Management

Abstract: Over the past decade, machine learning has profoundly reshaped how we model, monitor, and control batteries—one of the most complex and indispensable systems in the energy transition. 
This lecture offers a journey through ten years of research progress in data-driven and physics-integrated battery management. 

Part I begins with battery aging prognosis, introducing the fundamentals of machine learning and illustrating how field and fleet data can be transformed into predictive models for lifetime and health trajectory estimation.

Part II explores physics-based machine learning for battery modeling, highlighting the emergence of model-integrated neural networks (MINN) and their Bayesian variant (BMINN) that learn hidden electrochemical dynamics and phase transitions directly from voltage data, bridging first principles with deep learning.

Part III concludes with reinforcement learning for health-aware fast charging, where model-free and lifelong learning strategies are developed to optimize charging speed and longevity simultaneously. 

Together, these topics illustrate how the fusion of physics, data, and intelligence is paving the way toward the next generation of self-adaptive, health-conscious, and performance-optimized battery management systems.

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Welcome!

Ragne Emardson