Lithium-Ion Batteries: Modelling and State of Charge Estimation Lithium-Ion Batteries: Modelling and State of Charge Estimation By Mohammed Sayed Mohammed Farag, B.Sc. A THESIS Submitted to the School of Graduate Studies in Partial Fulfillment of the Requirements for the Degree Master of Applied Science McMaster University © Copyright by Mohammed Farag, June 2013, all rights reserved. PERMISSION TO USE In presenting this thesis in partial fulfillment of the requirements for a Postgraduate degree from McMaster University, I agree that the Libraries of this University may make it freely available for inspection. I further agree that the permission for copying this thesis in any manner, in whole or in part for scholarly purposes, may be granted by the professors who supervised my thesis work or, in their absence, by the Head of the Department or the Faculty Dean in which my thesis work was conducted. It is understood that any copying or publication or use of this thesis or parts thereof for financial gain shall not be allowed without my written permission. It is also understood that due recognition shall be given to me and McMaster University in any scholarly use which may be made of any material in my thesis. Requests for permission to copy or to make other use of material in this thesis, in whole or part, should be addressed to: Head of the Department of Mechanical Engineering McMaster University Faculty of Engineering 1280 Main Street West Hamilton, Ontario L8S 4L6 Canada MASTER OF APPLIED SCIENCE (2013) McMaster University (Department of Mechanical Engineering) Hamilton, Ontario, Canada BACHELOR OF SCIENCE (2008) Ain Shams University (Department of Mechanical Engineering) Cairo, Egypt Lithium-Ion Batteries: TITLE: Modelling and State of Charge Estimation AUTHOR: Mohammed Farag, M.A.Sc (McMaster University) Dr. Saeid Habibi, Professor SUPERVISOR: Department of Mechanical Engineering NUMBER OF PAGES: 169,xx iv “To my parents, Awatef and Sayed Farag, who provided me with their endless love, encouragement, support and absolute confidence in me throughout my life. You will always be the source of inspiration to all what I do in my life “ v ABSTRACT Lithium-ion (Li-ion) cells are increasingly used in many applications affecting our daily life, such as laptops computers, cell phones, digital cameras, and other portable electronic devices. Lithium-ion batteries are increasingly being considered for their use in Electric Vehicles (EV), Hybrid Electric Vehicles (HEV) and Plug-in Hybrid Electrical Vehicles (PHEV) due to their high energy density, slow loss of charge when not in use, and for lack of hysteresis effect. New application domains for these batteries has placed greater emphasis on their energy management, monitoring and control strategies. In this thesis, a comparative study between different models and state of charge (SOC) estimation strategies is performed. Battery models range from black-box representation to detailed electro-chemical reaction models that consider the underlying physics. The state of charge is estimated using the Extended Kalman filter (EKF) and the Smooth Variable Structure Filter (SVSF). The models and SOC estimation strategies are applied to experimental results from BMW Electrical and Hybrid Research and Development center and validated using a simulation model from AVL CRUISE software. Overall, different models and SOC estimation scenarios were studied. An average improvement of 30% in the estimation accuracy was shown by the SVSF SOC method when compared with the EKF SOC strategy. In general, the SVSF SOC estimation technique demonstrates excellent capability and a fast speed of convergence. vi ACKNOWLEDGEMENTS The author would like to express his gratitude to his supervisor, Dr. S.R. Habibi, for his supervision, advice, and guidance from the very early stage of this research until the end. Financial support provided by the McMaster University School of Graduate Studies, the Department of Mechanical Engineering, and the Ontario Government’s Graduate Scholarship Program is acknowledged. I convey special acknowledgement to BMW AG Munich Germany. I was surrounded by knowledgeable and friendly people who helped me on a daily basis. I would like to thank all of my colleagues at BMW for being supportive during my stay in Germany. I would like to thank Dr. Matthias Fleckenstein for his assistance, technical expertise, and support during my internship. I would like to thank my friends providing me with the support and friendship that I needed. Most of all I would like to thank my family, my father Sayed, my mother Awatef, my brother Ahmed and my sister Maii for their endless love, encouragement, support and absolute confidence in me throughout my life. Without them I could not have finished this thesis. vii TABLE OF CONTENTS PERMISSION TO USE .................................................................................................................... III ABSTRACT ....................................................................................................................................... VI ACKNOWLEDGEMENTS ............................................................................................................ VII TABLE OF CONTENTS ............................................................................................................... VIII LIST OF FIGURES ........................................................................................................................... XI NOMENCLATURE ...................................................................................................................... XVII 1. INTRODUCTION ..................................................................................................................... 1 THESIS MOTIVATION ......................................................................................................................... 2 THESIS SCOPE AND OBJECTIVES ....................................................................................................... 3 THESIS ORGANIZATION ..................................................................................................................... 3 2. LITERATURE REVIEW ........................................................................................................... 5 CURRENT AND FUTURE ENERGY SITUATION ................................................................................... 5 EV BATTERIES ENERGY-POWER TRADE-OFF ................................................................................. 7 OVERVIEW OF BATTERY TERMINOLOGIES AND DEFINITIONS ....................................................... 9 GENERAL OPERATING PRINCIPLES OF LI-ION BATTERY .............................................................. 12 BATTERY MODELLING ..................................................................................................................... 15 Ideal Models .............................................................................................................................. 16 Behavioral and Black-box Models ............................................................................................. 16 Equivalent-Circuit Models ........................................................................................................ 17 Electro-Chemical Models ......................................................................................................... 18 STATE OF CHARGE (SOC) DETERMINATION ................................................................................. 19 Discharge Test. .......................................................................................................................... 20 Ampere-Hour Counting ............................................................................................................ 20 Measurement of the Electrolyte Physical Properties ................................................................. 21 Open Circuit Voltage (OCV) .................................................................................................... 21 Artificial Neural Network .......................................................................................................... 22 Impedance Spectroscopy ............................................................................................................ 23 State Estimation Techniques ..................................................................................................... 23 THERMAL MANAGEMENT SYSTEMS ............................................................................................... 23 viii Master of Applied Science McMaster University Mohammed Farag Department of Mechanical Engineering BATTERY AGING MECHANISMS FOR LI-ION. ................................................................................. 23 SUMMARY .......................................................................................................................................... 24 3. STATE OF CHARGE ESTIMATION .................................................................................... 25 STATE AND PARAMETER ESTIMATION THEORY ............................................................................ 25 The Kalman Filter (KF) ............................................................................................................ 27 The Extended Kalman Filter (EKF) ......................................................................................... 30 The Smooth Variable Structure Filter (SVSF) .........................................................................