Course Title:
Battery Management System
Course Description:
This course will provide with a firm foundation in lithium-ion cell terminology and function and in battery-management-system. The course discuss the purpose of each component in an equivalent-circuit model of a lithium-ion battery cell and how to determine their parameter values from lab-test data. The course will also cover how to use them to simulate cell behaviors under different load profiles and State the purpose for each component in an equivalent-circuit model. Knowledge about how to implement different state-of-charge estimation, state-of-health estimation methods and to evaluate their relative merits will also be given. The topics related to design of cell balancing systems and computation of remaining energy and available power for a battery pack will be covered. To summaries, this will extensively cover all the aspects of battery system used in electrical vehicle.
Course instructional level:
Intermediate
Course Duration:
3 Month
Hours: 50
Course coordinator:
Dr Sonali Rangari
Course coordinator's profile(s):
S. C. Rangari received the B.E. degree in Electrical Engineering from the Nagpur University of Maharashtra, in 2002 and the M.Tech and the Ph.D. degrees in Electrical Engineering from the Visvesvaraya National Institute of Technology Nagpur, Maharashtra, in 2008 and 2018, respectively. Since 2009, she has been with the Department of Electrical Engineering at Shri Ramdeobaba College of Engineering and Management Nagpur, as an Assistant Professor. Her current interests include power electronics based drives, Electric Vehicle, distributed generation and control.
Course Contents:
| Module/Topic name | Sub-topic | Duration (as per Coursera) |
| 1. Introduction to battery-management systems | 1a Battery Boot Camp | 24 hours |
| 1b How lithium-ion cells works | ||
| 1c BMS sensing and high-voltage control | ||
| 1d BMS design requirements | ||
| 1e How are cells made? How can they fail? | ||
| 2. Equivalent Circuit Cell Model Simulation | 2a Defining an equivalent circuit model of a Li-ion cell. | 27 hours |
| 2b Identifying parameters of static model | ||
| 2c Identifying parameters of dynamic model | ||
| 2d Simulating battery pack in different configurations. | ||
| 2e Co-simulating battery and electric-vehicle load. | ||
| 2f Capstone project | ||
| 3 Battery State-of-Charge (SOC) Estimation | 3a The importance of a good SOC estimator | 27 hours |
| 3b Introducing the linear Kalman filter as a state estimator | ||
| 3c Understand the linear Kalman filter | ||
| 3d Cell SOC estimation using an extended Kalman filter | ||
| 3e Cell SOC estimation using sigma point Kalman filter | ||
| 3f Improving computational efficiency using the bar-delta method | ||
| 3g Capstone project | ||
| 4 Battery State-of-Health (SOH) Estimation | 4a How does lithium-ion cell health degrade | 22 hours |
| 4 b Total least square battery cell capacity estimation | ||
| 4 c Simplifies total least squares battery cell estimates | ||
| 4 d How to write code for the different total-capacity estimators | ||
| 4 e A Kalman-filter approach to total capacity estimation | ||
| 4f Capstone project | ||
| 5 Battery Pack Balancing and Power Estimation | 5 a. Passive balancing methods for battery packs | 22 hours |
| 5 b Active balancing methods for battery packs | ||
| 5 c How to find available battery power using a simplified cell model | ||
| 5 d How to find available battery power using a comprehensive cell model | ||
| 5 e Future Battery-Management –System Algorithms | ||
| 5f Capstone Project |
Course Outcomes:
After completing this course, learner will be able to:
- To discuss about the lithium-ion cell terminology and function in battery-management-system.
- To obtain the equivalent-circuit model of a lithium-ion battery cell, determine their parameter values from lab-test data, and simulate cell behaviors under different load profiles.
- To implement different state-of-charge estimation, state-of-health estimation methods and to evaluate their relative merits.
- To design cell balancing systems and to compute remaining energy and available power for a battery pack.