The Effect of Upper Voltage Limits on Electrochemical Performance of Li-Rich Cathode for Lithium Ion Batteries

Abstract

The growing energy use of modern societies has created a major need for better approaches to not only the production and management of energy, but also its storage. As they have high energy density and cyclability lithium-ion batteries (LIBs) serve currently as the secondary rechargeable battery systems for portable devices and electric vehicles (EVs). However, there are weight and volume constraint for the LIB systems especially for vehicle applications due to the limited space and energy consumption. Energy density limitation of LIBs is the main drawback for successful commercialization of EVs because of its direct effect on the vehicle's driving range, so enhancing the negative and positive electrodes by increasing their capacities and operating voltage is the best approach to improve the electro chemical performance of LIBs. Lithium rich layered oxides, which are solid solutions between layered Li[Li1/3Mn2/3]O2 (commonly designated as Li2MnO3) and layered Li[Mn1-y-zNiyCoz]O2, have been comprehensively studied as next generation cathode materials as they show much higher specific capacity (∼250 mAh/g) and operating voltage (>4.5) compared to the commercial cathodes. One of the defining characteristics of lithium-rich layered oxides (LLOs) is that they exhibit a unique first charge profile. The first charge profile can be divided into two regions, the sloping (below 4.5 V) and plateau regions (above 4.5 V), depending on the mechanism of oxidation during lithium-ion extraction. However, increase in voltage results O2 release from Li2MnO3 structure in the form of LiO2. This mechanism is one of the crucial drawbacks for Li-rich cathodes that results in huge capacity fade during cycles because of the structural change that occurs in Li2MnO3 phase (at high voltages). Therefore, in this study, different upper voltage limits (4.2-4.8 V) are investigated for Li[Li0,2Mn0,54Ni0,13Co13]O2 in order to analyze and optimize the capacity retention.