The battery pack may reduce an available capacity due to each individual cell imbalance and cause safety problems of the battery pack itself, so it is necessary to design a battery management system with an accurate battery model in consideration of the imbalance. In this paper, the battery pack single model design method is expanded to each individual cell model design method, and the cloud battery management system is applied instead of the ex. The battery pack may reduce an available capacity due to each individual cell imbalance and cause safety problems of the battery pack itself, so it is necessary to design a battery management system with an accurate battery model in consideration of the imbalance. In this paper, the battery pack single model design method is expanded to each individual cell model design method, and the cloud battery management system is applied instead of the existing embedded battery management system. Also, the estimated voltage of the battery model was used to verify the performance of estimating the battery model of each cell, and the optimization method was proposed to update the noise parameter of extended Kalman filter (EKF). In addition, the abnormal behavior was analyzed based on the variance for dominance of noise parameter in the proposed method using the cloud battery management system, and the feasibility of using it as an index to understand the voltage deviation was explained.••••Battery management system with enhanced model-based algorithm using cloud platform••Presenting problems due to single model-based state-of-charge estimation of battery pack••Updated noise parameters to derive the enhanced battery each cell model estimation voltage••Experimental validation using the actual designed battery management system••Battery management systemCloud platformExtended Kalman filterBattery modelAWS Amazon web serviceBMS Battery management systemBMU Battery management unitCAN Controller area networkCMU Cell monitoring unitCC Recently, as the problem of air pollution in the internal combustion engine vehicles has emerged worldwide, countries around the world are realizing carbon-neutral policies. Therefore, many manufacturers have stopped developing internal combustion engine power devices and are developing battery-powered electric vehicles (EV) that fit the current trend. In applications that use battery as power sources, the Battery management system (BMS) is particularly important. BMS performs important functions such as battery state monitoring and diagnosis. When these functions are not performed, problem may occur in battery control and thus safety, reliability, and durability may be defective. BMS usually consist of two main modules: cell monitoring unit (CMU) and battery management unit (BMU), which are designed as integrated systems within a printed circuit board (PCB) or as separate systems consisting of two PCB. CMU measures battery cell voltage, current and temperature through signal collection and filtering, and BMU is applied with embedded functions requiring computational capability, such as battery state estimation and diagnosis algorithm. Accurate estimation of the state-of-charge (SOC), which is one of the important functions of BMS performed in BMU, is the most essential factor for effective operation of battery pack [,,, ].There are various methods for estimate the SOC of battery. The simplest met.
