Understanding Voltage Behavior of Lithium-Ion Batteries in Electric Vehicles Applications

Abstract

Electric vehicle (EV) markets have evolved. In this regard, rechargeable batteries such as lithium-ion (Li-ion) batteries become critical in EV applications. However, the nonlinear features of Li-ion batteries make their performance over their lifetime, reliability, and control more difficult. In this regard, the battery management system (BMS) is crucial for monitoring, handling, and improving the lifespan and reliability of this type of battery from cell to pack levels, particularly in EV applications. Accordingly, the BMS should control and monitor the voltage, current, and temperature of the battery system during the lifespan of the battery. In this article, the BMS definition, state of health (SoH) and state of charge (SoC) methods, and battery fault detection methods were investigated as crucial aspects of the control strategy of Li-ion batteries for assessing and improving the reliability of the system. Moreover, for a clear understanding of the voltage behavior of the battery, the open-circuit voltage (OCV) at three ambient temperatures, 10 °C, 25 °C, and 45 °C, and three different SoC levels, 80%, 50%, and 20%, were investigated. The results obtained showed that altering the ambient temperature impacts the OCV variations of the battery. For instance, by increasing the temperature, the voltage fluctuation at 45 °C at low SoC of 50% and 20% was more significant than in the other conditions. In contrast, the rate of the OCV at different SoC in low and high temperatures was more stable.

A Future Perspective on Waste Management of Lithium-Ion Batteries for Electric Vehicles in Lao PDR: Current Status and Challenges

“…State of health (SoH) is a significant process to check the metric of battery operation features before considering them for reuse and forwarding them to the EoL battery recycling process. The SoH calculation monitors the remaining usable life of charge–discharge cycles, determining whether LIBs need to be replaced [ 83 ]. The machine learning method is the prevalent method of SoH estimation of LIBs in EVs and is accurate due to the diverse procedure for SoH estimation.…”

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“…This includes the innovation of novel anode materials like hard carbon, phosphides, and intermetallic compounds, as well as cathode materials such as sodium layered oxides, and sodium layered sulfates. [7][8][9] Nevertheless, just like LIBs, the domain of electrolyte engineering in sodium-ion batteries (SIBs) has been somewhat marginalized in terms of the focus it has received when juxtaposed with the extensive attention given to electrode materials. 1 The limited investigation of electrolytes in SIBs can be attributed to the complexities associated with establishing links between the kinetic aspects of electrolytes at the molecular level and the overall performance of batteries on a macroscopic scale.…”

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“…[ 6 ] However, controlling the PMSM, especially under transient‐state conditions, is complex and requires an appropriate EV controller. [ 7 ] Furthermore, batteries play a pivotal role in determining the performance of an EV. Essentially, batteries are devices that store and release electrical energy through chemical reactions, and when connected to a circuit, a chemical reaction occurs at the electrodes.…”

“…[ 6 ] However, it is important to note that LIBs generate heat both inside cells and at the interconnection positions during charging and discharging, which can lead to excessive battery temperature rise and temperature nonuniformity. [ 7 ] Temperature extremes can significantly influence the efficiency and overall lifespan of lithium‐ion batteries (LIBs). High temperatures can expedite the chemical reactions within the battery, leading to increased degradation, reduced capacity, and even safety risks such as thermal runaway.…”