Comparison of Lithium-Ion Anode Materials Using an Experimentally Verified Physics-Based Electrochemical Model

Researchers are in search of parameters inside Li-ion batteries that can be utilized to control their external behavior. Physics-based electrochemical model could bridge the gap between Li+ transportation and distribution inside battery and battery performance outside. In this paper, two commercially available Li-ion anode materials: graphite and Lithium titanate (Li 4 Ti 5 O 12 or LTO) were selected and a physics-based electrochemical model was developed based on half-cell assembly and testing. It is found that LTO has a smaller diffusion coefficient ( D s ) than graphite, which causes a larger overpotential, leading to a smaller capacity utilization and, correspondingly, a shorter duration of constant current charge or discharge. However, in large current applications, LTO performs better than graphite because its effective particle radius decreases with increasing current, leading to enhanced diffusion. In addition, LTO has a higher activation overpotential in its side reactions; its degradation rate is expected to be much smaller than graphite, indicating a longer life span.

[1]  Massimo Santarelli,et al.  Inverse parameter determination in the development of an optimized lithium iron phosphate – Graphite battery discharge model , 2016 .

[2]  Francesco De Angelis,et al.  Review on recent progress of nanostructured anode materials for Li-ion batteries , 2014 .

[3]  M. Doyle,et al.  Modeling of Galvanostatic Charge and Discharge of the Lithium/Polymer/Insertion Cell , 1993 .

[4]  Le Yi Wang,et al.  A novel method to obtain the open circuit voltage for the state of charge of lithium ion batteries in electric vehicles by using H infinity filter , 2017 .

[5]  Ralph E. White,et al.  Solvent Diffusion Model for Aging of Lithium-Ion Battery Cells , 2004 .

[6]  Ralph E. White,et al.  Effect of Porosity on the Capacity Fade of a Lithium-Ion Battery Theory , 2004 .

[7]  Song-Yul Choe,et al.  Modeling of degradation effects considering side reactions for a pouch type Li-ion polymer battery with carbon anode , 2014 .

[8]  Xuan Zhou,et al.  A novel method for identification of lithium-ion battery equivalent circuit model parameters considering electrochemical properties , 2017 .

[9]  Jasim Ahmed,et al.  Algorithms for Advanced Battery-Management Systems , 2010, IEEE Control Systems.

[10]  Chaoyang Wang,et al.  Solid-state diffusion limitations on pulse operation of a lithium ion cell for hybrid electric vehicles , 2006 .

[11]  Ralph E. White,et al.  Capacity fade analysis of a lithium ion cell , 2008 .

[12]  P. Novák,et al.  A review of the features and analyses of the solid electrolyte interphase in Li-ion batteries , 2010 .

[13]  John B. Goodenough,et al.  The Li‐Ion Rechargeable Battery: A Perspective , 2013 .

[14]  Chaoyang Wang,et al.  Control oriented 1D electrochemical model of lithium ion battery , 2007 .

[15]  Marc Doyle,et al.  Mathematical Modeling of the Lithium Deposition Overcharge Reaction in Lithium‐Ion Batteries Using Carbon‐Based Negative Electrodes , 1999 .

[16]  D. Sauer,et al.  Comprehensive study of the influence of aging on the hysteresis behavior of a lithium iron phosphate cathode-based lithium ion battery – An experimental investigation of the hysteresis , 2016 .

[17]  J. Newman,et al.  Modeling the Performance of Lithium-Ion Batteries and Capacitors during Hybrid-Electric-Vehicle Operation , 2008 .

[18]  Chaoyang Wang,et al.  Power and thermal characterization of a lithium-ion battery pack for hybrid-electric vehicles , 2006 .

[19]  Christopher D. Rahn,et al.  Model-Based Electrochemical Estimation and Constraint Management for Pulse Operation of Lithium Ion Batteries , 2010, IEEE Transactions on Control Systems Technology.

[20]  Wolfgang Dreyer,et al.  The thermodynamic origin of hysteresis in insertion batteries. , 2010, Nature materials.

[21]  Song-Yul Choe,et al.  Dynamic modeling and analysis of a pouch type LiMn2O4/Carbon high power Li-polymer battery based on electrochemical-thermal principles , 2012 .

[22]  Shriram Santhanagopalan,et al.  Multi-Domain Modeling of Lithium-Ion Batteries Encompassing Multi-Physics in Varied Length Scales , 2011 .

[23]  Mohammadhosein Safari,et al.  Analysis of lithium deinsertion/insertion in LiyFePO4 with a simple mathematical model , 2010 .

[24]  Doron Aurbach,et al.  Failure and Stabilization Mechanisms of Graphite Electrodes , 1997 .

[25]  Ralph E. White,et al.  Parameter Estimation and Life Modeling of Lithium-Ion Cells , 2008 .

[26]  Ralph E. White,et al.  A lumped model of venting during thermal runaway in a cylindrical Lithium Cobalt Oxide lithium-ion cell , 2016 .

[27]  Chaoyang Wang,et al.  Micro‐Macroscopic Coupled Modeling of Batteries and Fuel Cells I. Model Development , 1998 .

[28]  Hao Mu,et al.  A systematic model-based degradation behavior recognition and health monitoring method for lithium-ion batteries , 2017 .

[29]  Venkat Srinivasan,et al.  Mathematical Modeling of Current-Interrupt and Pulse Operation of Valve-Regulated Lead Acid Cells , 2003 .

[30]  J. Newman,et al.  Thermal Modeling of the Lithium/Polymer Battery .1. Discharge Behavior of a Single-Cell , 1995 .

[31]  Venkat Srinivasan,et al.  Optimization of Lithium Titanate Electrodes for High-Power Cells , 2006 .

[32]  Chee Burm Shin,et al.  Electrochemical model of a lithium-ion battery implemented into an automotive battery management system , 2015, Comput. Chem. Eng..

[33]  Rui Xiong,et al.  A data-driven based adaptive state of charge estimator of lithium-ion polymer battery used in electric vehicles , 2014 .

[34]  Ralph E. White,et al.  Development of First Principles Capacity Fade Model for Li-Ion Cells , 2004 .

[35]  V. Subramanian,et al.  Towards real-time (milliseconds) parameter estimation of lithium-ion batteries using reformulated physics-based models , 2008 .

[36]  Tanvir R. Tanim,et al.  A Temperature Dependent, Single Particle, Lithium Ion Cell Model Including Electrolyte Diffusion , 2015 .

[37]  M. Armand,et al.  Issues and challenges facing rechargeable lithium batteries , 2001, Nature.

[38]  Chaoyang Wang,et al.  Numerical Modeling of Coupled Electrochemical and Transport Processes in Lead‐Acid Batteries , 1997 .

[39]  Karim Zaghib,et al.  Electrochemical study of Li4Ti5O12 as negative electrode for Li-ion polymer rechargeable batteries , 1999 .

[40]  Venkat Srinivasan,et al.  Discharge Model for the Lithium Iron-Phosphate Electrode , 2004 .

[41]  Bor Yann Liaw,et al.  Micro‐Macroscopic Coupled Modeling of Batteries and Fuel Cells II. Application to Nickel‐Cadmium and Nickel‐Metal Hydride Cells , 1998 .

[42]  Venkat R. Subramanian,et al.  Towards "Real-Time" Simulation of Physics Based Lithium Ion Battery Models , 2007 .

[43]  J. Newman,et al.  Thermal modeling of the lithium/polymer battery. II: Temperature profiles in a cell stack , 1995 .

[44]  Bo Cui,et al.  Advances in spinel Li4Ti5O12 anode materials for lithium-ion batteries , 2015 .

[45]  Ralph E. White,et al.  Capacity Fade Mechanisms and Side Reactions in Lithium‐Ion Batteries , 1998 .

[46]  J. Tarascon,et al.  Comparison of Modeling Predictions with Experimental Data from Plastic Lithium Ion Cells , 1996 .

[47]  Ralph E. White,et al.  Calendar life performance of pouch lithium-ion cells , 2005 .

[48]  Chaoyang Wang,et al.  Modeling discharge and charge characteristics of nickel–metal hydride batteries , 1999 .

[49]  Jun Xu,et al.  A novel multimode hybrid energy storage system and its energy management strategy for electric vehicles , 2015 .

[50]  Hongwen He,et al.  A Double-Scale, Particle-Filtering, Energy State Prediction Algorithm for Lithium-Ion Batteries , 2018, IEEE Transactions on Industrial Electronics.

[51]  Song-Yul Choe,et al.  Development of a physics-based degradation model for lithium ion polymer batteries considering side reactions , 2015 .