Introduction to Battery State-of-Health (SOH) Estimation

As battery-powered technologies expand from electric vehicles to grid storage, predicting battery degradation is more critical than ever. This course introduces you to the essential engineering principles of Battery State-of-Health (SOH) estimation. You will transition from understanding basic battery electrochemistry to analyzing algorithms that estimate capacity and predict lifetime performance. What you'll learn: - Understand the primary physical and chemical degradation mechanisms in lithium-ion cells, including SEI layer growth and lithium plating. - Define key battery health metrics such as capacity fade, impedance rise, and remaining useful life. - Apply Weighted Least Squares (WLS) and other mathematical techniques to estimate total battery capacity. - Compare different SOH estimation methodologies, from classic physics-based models to modern data-driven approaches. - Analyze battery test data using clean, structured code snippets to track degradation trends. The curriculum begins with foundational battery terminology and electrochemical concepts before guiding you step-by-step through mathematical modeling and algorithmic implementation. This course is designed for aspiring battery engineers, clean energy enthusiasts, and hardware developers looking to enter the energy storage field with no advanced prior background required. Start reading today to master the core concepts driving modern battery management systems.