Modeling and simulation of lithium ion Battery using adaptive techniques

Abstract

Electric vehicles (EVs) are becoming increasingly popular to combat global newlinewarming, rising pollution, and the depletion of natural resources. However, lithium-ion newlinebatteries will be crucial in powering EVs. The lithium-ion battery is one of the most newlinesuccessful energy storage solutions for renewable energy systems with high newlineintermittency. The battery must be safeguarded from irreparable damage and dangerous newlineexplosion to operate safely and securely. As a result, the battery state-of-charge (SOC) newlineis an essential operational parameter that must be kept within a safe range. In the newlinepresence of uncertainties, accurate SOC estimation is challenging. This is mainly due newlineto the difficulties of unknown initial SOC and the unclear internal resistance. Suppose newlinethe accurate SOC is not possible to determine. In that case, many serious consequences newlinewill occur in the battery management system (BMS), which cause battery damage, newlinereduction of battery life cycles, and fire/explosion. To protect the battery from the newlineaforementioned problems, precise SOC estimate algorithms are required newline