Modeling and Control of a Modular Battery Management System for Lithium-ion Battery Packs

107 Pages·2017·18.55 MB·English

University of Colorado, Boulder
CU Scholar
Electrical, Computer & Energy Engineering
Electrical, Computer & Energy Engineering
Graduate Theses & Dissertations
Spring 4-1-2017
Modeling and Control of a Modular Battery
Management System for Lithium-ion Battery Packs
Fan Zhang
University of Colorado at Boulder, [email protected]
Follow this and additional works at:https://scholar.colorado.edu/ecen_gradetds
Part of theAutomotive Engineering Commons, and thePower and Energy Commons
Recommended Citation
Zhang, Fan, "Modeling and Control of a Modular Battery Management System for Lithium-ion Battery Packs" (2017).Electrical,
Computer & Energy Engineering Graduate Theses & Dissertations. 153.
https://scholar.colorado.edu/ecen_gradetds/153
This Dissertation is brought to you for free and open access by Electrical, Computer & Energy Engineering at CU Scholar. It has been accepted for
inclusion in Electrical, Computer & Energy Engineering Graduate Theses & Dissertations by an authorized administrator of CU Scholar. For more
information, please [email protected].
Modeling and Control of a Modular Battery Management
System for Lithium-Ion Battery Packs
by
Fan Zhang
B.S., Harbin Institute of Technology, 2012
M.S., University of Colorado Boulder, 2016
A thesis submitted to the
Faculty of the Graduate School of the
University of Colorado in partial fulfillment
of the requirements for the degree of
Doctor of Philosophy
Department of Electrical, Computer, and Energy Engineering
2017
This thesis entitled:
Modeling and Control of a Modular Battery Management
System for Lithium-Ion Battery Packs
written by Fan Zhang
has been approved for the Department of Electrical, Computer, and Energy Engineering
Prof. Dragan Maksimovi´c
Prof. Regan Zane
Date
The final copy of this thesis has been examined by the signatories, and we find that both
the content and the form meet acceptable presentation standards of scholarly work in the
above mentioned discipline.
iii
Zhang, Fan (Ph.D., Electrical, Computer, and Energy Engineering)
Modeling and Control of a Modular Battery Management
System for Lithium-Ion Battery Packs
Thesis directed by Prof. Dragan Maksimovi´c
Highvoltage(HV)tractionbatterypacksinelectric-drivevehicles(HEV,PHEV,BEV)
consist of a large number of battery cells connected in series. As individual cells exhibit
mismatches in characteristics such as capacity, inner resistance, and run-time state-of-charge
(SOC), cell balancing must be incorporated into the battery management system (BMS).
Conventional passive cell balancing does not fully address the mismatch issues, which leads
to shorter battery lifetime, and the need to over-size the battery pack. To overcome the
problems associated with the conventional architecture, a modular battery management
system incorporating both active cell balancing and high voltage (HV) to low-voltage (LV)
dc-dc conversion has been developed. The HV-to-LV converter is a series-input, parallel-
output dc-dc system with inputs connected across the battery cells or cell modules, while
paralleled outputs supply loads on the LV bus. This thesis is focused on modeling, control
and design of the modular battery management system. Several critical issues are addressed:
(1) stability of the converter system with distributed control in energy storage application is
analyzed and simulated; (2) the steady-state model of the dual-active-bridge (DAB) isolated
converterwithphase-shiftmodulationisrefinedandappliedtothemodularconvertersystem
with cell balancing; (3) practical methods for estimation of the Lithium-ion battery state-of-
charge (SOC) and state-of-health (SOH) are developed in forms suitable for implementation
on low-cost microcontrollers. Finally, a modular hybrid balancing system with module-level
active balancing and cell-level passive balancing is developed and experimentally validated.
The techniques developed in this thesis can be applied to designs of large automotive battery
packs with improved performance, reduced size, reduced cost, and longer lifetime.
Dedication
To my parents, and Shanshan, and Robin
v
Acknowledgements
I would like to extend my greatest respect and sincerest gratitude to my advisor,
Professor Dragan Maksimovi´c. Without his guidance, support, and patience, the completion
of my Ph.D. study would be impossible.
I would like to thank Professors Regan Zane, Gregory Plett, and Scott Trimboli, who
inspire me and provide significant help in projects and researches.
I would also like to thank Professors Khurram Afridi, and Hanh-Phuc Le, who give me
valuable support and suggestion in my graduate study.
I am grateful to members of Colorado Power Electronics Center (CoPEC), for the
wonderful experiences in the lab.
SpecialthanktoMr.M.MuneebUrRehmanfromUtahPowerElectronicsLab(UPEL),
Utah State University, for the assistance and collaboration in the project.
Finally, I would like to thank my families for their love and support throughout my
graduate study.
vi
Contents
Chapter
1 Overview of Lithium-Ion Battery Packs and Battery Management Systems 1
1.1 Effect of Cell Mismatch in Large Battery Packs . . . . . . . . . . . . . . . . 2
1.2 Conventional Cell Balancing Techniques . . . . . . . . . . . . . . . . . . . . 4
1.2.1 Passive Balancing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.2.2 Active Balancing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.3 Novel Modular Active Balancing BMS . . . . . . . . . . . . . . . . . . . . . 9
1.4 Thesis Objectives and Organization . . . . . . . . . . . . . . . . . . . . . . . 11
2 Stability of the Modular BMS with Distributed Control of the Series-Input-Parallel-
Output Converter System 13
2.1 Automatic Balancing with Distributed Bus Voltage Regulation . . . . . . . . 16
2.2 SOC Control Loop . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.3 Comprehensive Analysis of the SOC Control Loop . . . . . . . . . . . . . . . 22
2.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
3 Improved Steady-State Model of the Dual-Active-Bridge Converter 30
3.1 A New Approach to Derivation of DAB Steady-State Model . . . . . . . . . 34
3.2 Derivation of Improved DAB Steady-State Model . . . . . . . . . . . . . . . 36
3.3 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
3.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
vii
4 Microcontroller Implementation of Lithium-Ion Battery State-of-Charge Estimation 47
4.1 Battery Cell Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
4.2 SOC Estimation Using Kalman Filter . . . . . . . . . . . . . . . . . . . . . . 51
4.2.1 Introduction to Kalman filter based SOC Estimation . . . . . . . . . 51
4.2.2 SOC Estimation using the Sigma-Point Kalman Filter (SPKF) . . . . 54
4.3 1st-Order SPKF Approach Using Higher-Order Cell Model . . . . . . . . . . 55
4.4 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
4.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
5 Lithium-Ion Battery State-of-Health Estimation Using Long Term Aging Data 63
5.1 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
5.2 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
6 Hybrid Balancing in a Modular Battery Management System 71
6.1 Hybrid Balancing Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
6.1.1 Module-Level Active Balancing . . . . . . . . . . . . . . . . . . . . . 72
6.1.2 Cell-Level Passive Balancing . . . . . . . . . . . . . . . . . . . . . . . 72
6.1.3 Module-Level SOC and SOH . . . . . . . . . . . . . . . . . . . . . . . 73
6.2 Modular Hybrid-Balancing System Implementation . . . . . . . . . . . . . . 75
6.2.1 Shared Battery Cell Measurements . . . . . . . . . . . . . . . . . . . 76
6.2.2 Shared Central BMS Controller . . . . . . . . . . . . . . . . . . . . . 78
6.2.3 Shared Communication Bus . . . . . . . . . . . . . . . . . . . . . . . 78
6.3 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
6.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
7 Conclusions and Future Work 82
7.1 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
7.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
viii
Bibliography 86
ix
Tables
Table
2.1 Parameters in Eq. (2.11) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.2 Parameters in Eq. (2.11), with Droop Control . . . . . . . . . . . . . . . . . 26
3.1 Symbol Definition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
3.2 DAB Prototype . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
3.3 Parameters in the Improved DAB Steady-State Model . . . . . . . . . . . . . 39
3.4 Parameters in the Simplified Improved DAB Steady-State Model . . . . . . . 42
4.1 State-Space Forms for Different Cell Equivalent Circuit Models . . . . . . . . 50
4.2 Basic Kalman Filter Equations . . . . . . . . . . . . . . . . . . . . . . . . . 53
4.3 Extended Kalman Filter Equations . . . . . . . . . . . . . . . . . . . . . . . 54
4.4 Sigma-Point Kalman Filter (SPKF) Equations . . . . . . . . . . . . . . . . . 56
4.5 Experimental Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
5.1 SOC Estimation Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
5.2 Total Capacity Estimation Setup . . . . . . . . . . . . . . . . . . . . . . . . 69
6.1 Comparison of Converter Specifications for An 84-Cell Lithium-Ion Battery
Pack . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75