Algorithms for Battery Management Systems Specialization

Start Date: 10/21/2018

Course Type: Specialization Course

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Course Syllabus

5 courses

Introduction to battery-management systems

This course will provide you with a firm foundation in lithium-ion cell terminology and function and in battery-management-system requirements as needed by the remainder of the specialization. After completing this course, you will be able to: - List t

Equivalent Circuit Cell Model Simulation

In this course, you will learn the purpose of each component in an equivalent-circuit model of a lithium-ion battery cell, how to determine their parameter values from lab-test data, and how to use them to simulate cell behaviors under differ

Battery State-of-Charge (SOC) Estimation

In this course, you will learn how to implement different state-of-charge estimation methods and to evaluate their relative merits. By the end of the course, you will be able to: - Implement simple voltage-based and current-based state-of-charge es

Battery State-of-Health (SOH) Estimation

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-i

Battery Pack Balancing and Power Estimation
Starts January 2019
In this course, you will learn how to design balancing systems and to compute remaining energy and available power for a battery pack. By the end of the course, you will be able to: - Evaluate different design choices for cell balancing and articulate their relative merits - Design component values for a simple passive balancing circuit - Use provided Octave/MATLAB simulation tools to evaluate how quickly a battery pack must be balanced - Compute remaining energy and available power using a simple cell model - Use provided Octave/MATLAB script to compute available power using a comprehensive equivalent-circuit cell model

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Course Introduction

Algorithms for Battery Management Systems Specialization-Get Started in Algorithms for Battery Management. Learn how to model lithium-ion battery cells, and how to use those models to manage battery packs

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Johnson Matthey Battery Systems Johnson Matthey Battery Systems has worked with McLaren Automotive to develop an advanced lithium-ion battery for the McLaren P1, a limited production plug-in hybrid supercar. Power for the vehicle's electric motor is stored in a 324-cell lithium-ion high density battery pack located behind the cabin. The battery pack is liquid-cooled and the Battery Management System incorporates active cell balancing.
Johnson Matthey Battery Systems The battery management system (BMS) is an essential component within a multiple cell battery pack. It monitors the state of a battery, measuring and controlling key operational parameters, and thus ensuring safety. Johnson Matthey Battery Systems’ BMS incorporates proprietary battery management electronics, and its four main objectives are to protect the cells and the battery from damage, prolong the life of the battery, maintain the battery in a state where it can meet the requirements of the application and to interface with the host application.
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