This course can also be taken for academic credit as ECEA 5733, part of CU Boulder鈥檚 Master of Science in Electrical Engineering degree. In this course, you will learn how to implement different state-of-health estimation methods and to evaluate their relative merits. By the end of the course, you will be able to: - Identify the primary degradation mechanisms that occur in lithium-ion cells and understand how they work - Execute provided Octave/MATLAB script to estimate total capacity using WLS, WTLS, and AWTLS methods and lab-test data, and to evaluate results - Compute confidence intervals on total-capacity estimates - Compute estimates of a cell鈥檚 equivalent-series resistance using lab-test data - Specify the tradeoffs between joint and dual estimation of state and parameters, and steps that must be taken to ensure robust estimates (honors)
4.5.1: Deriving SPKF method for parameter estimation
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Skills You'll Learn
Matlab, Chemistry, Estimation, Electrical Substation, Mathematical Modeling, Failure Analysis, Statistical Methods, Laboratory Testing, Engineering Calculations, Simulations
Reviews
4.7 (157 ratings)
- 5 stars78.34%
- 4 stars16.56%
- 3 stars3.18%
- 2 stars1.27%
- 1 star0.63%
AS
Apr 9, 2020
A detailed course on battery capacity estimation, which covers overall perspectives, and complications in the SOH estimation of the battery.
DM
Apr 18, 2023
Challenging and sufficient enough to impart the skills necessary to develop reliable battery management systems algorithms.
From the lesson
A Kalman-filter approach to total capacity estimation
Taught By
Gregory Plett
Professor