Optimal charging profiles for mechanically constrained lithium-ion batteries

Suthar, Bharatkumar; Ramadesigan, Venkatasailanathan; De, Suvranu; Braatz, Richard D.; Subramanian, Venkat R.

doi:10.1039/c3cp52806e

Cited by 57 publications

(33 citation statements)

References 35 publications

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“…The stress model used to estimate intercalation induced stresses is valid only for materials with small volume expansion. The comparison of various models for intercalation induced stresses is performed in Suthar et al 25 for graphite material. For materials with low volumetric expansion such as graphite (with 10% volume expansion), equations given in Table III works reasonably well.…”

Section: Resultsmentioning

confidence: 99%

Effect of Porosity, Thickness and Tortuosity on Capacity Fade of Anode

Suthar

Northrop

Rife

et al. 2015

J. Electrochem. Soc.

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The graphite anode in lithium-ion batteries is vulnerable to capacity fade due to several mechanisms. Advancement in understanding of such capacity fade mechanisms has paved the way for selecting design parameters that consider these effects. This paper shows the effect of porosity, thickness, and tortuosity of the anode on capacity fade mechanisms. Three main capacity fade mechanisms are analyzed in this paper: (1) solid electrolyte interface (SEI) side reaction, (2) lithium plating side reactions and (3) mechanical degradation due to intercalation induced stresses. Moreover, for a given thickness and porosity of anode, the effect of porosity variation on capacity fade mechanisms is also presented. Lithium-ion chemistries are attractive for many applications due to high cell voltage, high volumetric and gravimetric energy density (100 Wh/kg), high power density (300 W/kg), good temperature range, low memory effect, and relatively long battery life.1-3 Capacity fade, underutilization, and thermal runaway are the main issues that need to be addressed in order to use a lithium-ion battery efficiently and safely over a long life.Research on various fronts is underway to address the issues mentioned above. While finding better materials and improving their properties is one approach, the use of system level strategies to reach better efficiency in existing and emerging systems is another approach. The true potential of battery materials cannot be realized due to system level efficiencies, especially where transport effects become dominant (e.g. higher rates of charging/discharging at normal temperature or low temperatures operations).One of the many problems that can be addressed by continuum level modeling approaches is finding the optimum thicknesses and porosities of anode and cathode materials while keeping various processes and objectives in mind. These objectives may be discharge capacities at higher rates, charging time, mechanical degradation due to intercalation induced stresses, loss of active lithium due to parasitic side reaction (SEI layer and lithium plating), safety etc. While one would like to maximize energy density by packing the solid phase material compactly with larger thickness; rate capacity, safety and capacity fade may cause such an approach to be impractical.How should one choose the porosity and length of anode and cathode is an interesting research problem. Design optimization (porosity and thickness) for lithium-ion battery can be traced back to the work done by Prof. Newman using the reaction zone model 4 and with the pseudo two dimensional model. 5 Work on determining the optimal porosity distribution by considering the ohmic drop has been done by Ramadesigan et al. 6 Effect of low temperature and porosity on the performance of lithium-ion batteries is also studied by Ji et al. 7 While these works are based on maximizing the energy/power density of lithium-ion batteries by choosing optimal design parameters, no work has been done in quantifying the effect of design parameters on capaci...

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Section: Resultsmentioning

confidence: 99%

Effect of Porosity, Thickness and Tortuosity on Capacity Fade of Anode

Suthar

Northrop

Rife

et al. 2015

J. Electrochem. Soc.

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“…Furthermore, the coating has to withstand the mechanical demands during cell operation. This includes the mechanical stress during lithium intercalation and de-intercalation due to the expansion and shrinkage of the electrochemically active material particles [1][2][3]. This swelling especially induces mechanical tension at the particle-binder-substrate interface.…”

Section: Introductionmentioning

confidence: 98%

Measuring the coating adhesion strength of electrodes for lithium-ion batteries

Haselrieder

Westphal

Bockholt

et al. 2015

International Journal of Adhesion and Adhesives

160

167

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“…Under such conditions, the average values may suggest that there is nothing to be concerned about, but there may be areas within the electrode that experience conditions which are detrimental to performance and/or life. Inclusion of the stress and other effects into the single particle framework allows for constraints to be implemented to reduce capacity fade in the cell, 68 while inclusion of the same phenomena into the P2D framework allows from local variation to be accounted for, so that the maximum stress development can be minimized. Under conditions with high spatial variation, the maximum stress (as predicted by the P2D model) may be much larger than the average stress (as predicted by the single particle model).…”

Section: Current Approach and The Role Of Efficient Battery Simulationmentioning

confidence: 99%

Efficient Simulation and Reformulation of Lithium-Ion Battery Models for Enabling Electric Transportation

Northrop

Suthar

Ramadesigan

et al. 2014

J. Electrochem. Soc.

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Improving the efficiency and utilization of battery systems can increase the viability and cost-effectiveness of existing technologies for electric vehicles (EVs). Developing smarter battery management systems and advanced sensing technologies can circumvent problems arising due to capacity fade and safety concerns. This paper describes how efficient simulation techniques and improved algorithms can alleviate some of these problems to help electrify the transportation industry by improving the range of variables that are predictable and controllable in a battery in real-time within an electric vehicle. The use of battery models in a battery management system (BMS) is reviewed. The effect of different simulation techniques on computational cost and accuracy are also compared, and the validity of implementation in a microcontroller environment for model predictive control (MPC) is addressed. Using mathematical techniques to add more physics without losing efficiency is also discussed. Behavioral predictions can be made using mathematical models without the need to directly observe the states using expensive and time consuming physical experiments. Such predictions allow for more intelligent design of new systems, which is generally limited by the mathematical techniques used and the computational resources available. An improved modeling and simulation approach can achieve the following goals when applied to engineering systems: r More accurate predictions by using more meaningful models r Faster simulation with fewer computational resources r Optimization of design parameters r Better control, allowing aggressive performance while maintaining safetyHere we focus on the application of such principles to the use of physics-based battery models in battery management systems in electric vehicles.In recent years, battery electric vehicles (BEV) have increased in popularity to reduce the dependence on fossil fuels. Lithium-ion batteries are a popular choice as an energy storage medium for high demand applications due to their large energy density but are not utilized to their full capacity in BEV applications; operating a Li-ion battery too aggressively can lead to reduced cycle life and unpredictable thermal runaway reactions. These challenges reduce the functional capacity of the battery available for propulsion.The consumer expects the vehicle's performance and capabilities to remain uniform regardless of the state of charge or age of the battery, as they have become accustomed to internal combustion engines. When the battery is nearly depleted, it is difficult or impossible to satisfy high power demand, which is aggravated as the battery ages. To avoid these difficulties, the BMS shuts off the battery with a large amount of energy unused, so that Li-ion batteries for EVs are greatly overdesigned and carry extra weight and volume, reducing efficiency and increasing cost.1 Research is underway to better understand the internal limitations of Li-ion batteries including SEI layer growth, side * Electrochemical Society ...

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Optimal charging profiles for mechanically constrained lithium-ion batteries

Cited by 57 publications

References 35 publications

Effect of Porosity, Thickness and Tortuosity on Capacity Fade of Anode

Effect of Porosity, Thickness and Tortuosity on Capacity Fade of Anode

Measuring the coating adhesion strength of electrodes for lithium-ion batteries

Efficient Simulation and Reformulation of Lithium-Ion Battery Models for Enabling Electric Transportation

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