# A Review of Digital Twin Technology for Electric and Autonomous Vehicles
## 4 Current Issues in Electric Vehicles
### Battery Management Systems  
Worldwide, there are serious challenges, such as global warming and greenhouse gas emissions due to the use of petrol and diesel in vehicles, which result in excessive levels of (CO\({}_{2}\)). EVs are now being promoted and widely regarded as eco-friendly and substitutes for other vehicles based on combustion engines. Rechargeable batteries are widely used as the power supply for electric vehicles. There are many different types of batteries, including lithium-ion, lead-acid, nickel-cadmium, and nickel-metal hydride [52]. The lithium-ion battery is the most used battery, which provides a high density of electric energy, eco-sustainability, and a long life cycle. To keep the EV battery's state of health at a good quality level, we must take proper care of the battery and adhere to proper charging operations (over-charging, current, voltage, or discharging). These operations may cause problems and damage the battery and the EV. Several studies have been conducted on applying IoT and cloud computing to solve BMS issues. Recently, [PERSON] et al. [53] developed a cloud-based battery system to monitor stationary batteries and help in fault diagnosis platforms at a large scale. As the authors claimed, it is a new model, with no comparison made in the previous literature. It incorporates IoT-enabled wireless battery module management systems and a proposed cloud battery management platform to support onboard battery health monitoring and provide intelligent, cost-effective maintenance for large-scale battery energy storage systems (BESSs). The hybrid filter (HF)-based condition monitoring algorithm of cells and the proposed outlier detection-based fault diagnosis algorithm are implemented in the platform. Compared to the Kalman filter family and sliding mode observer, the HF leads to less computational costs and chattering issues, respectively. [PERSON] et al. [54] introduced a cloud framework for EVs to manage the battery information related to the battery replacement system. This cloud-connected battery management system will maximize the value of the shared batteries by using location data cloud to continuously connect to the batteries, manage the SoC, and monitor changes in their characteristics. [PERSON] et al. [55] presented a solution for battery monitoring in a microgrid system based on IoT, but different from [53], the authors presented a smart microgrid by integrating a battery pack, PV system, intelligent electronic device (IED) hybrid inverter, grid connection, and electricity load, where no fault diagnosis was considered. In this framework, the IoT is realized through a communication channel with the IED, data acquisition algorithm, cloud system, and human-machine interface (HMI). The data stored in the cloud system database are processed and analyzed to produce information that can be accessed by users through desktop and mobile devices using the ExtJS/HTML5 framework. The analytical results show good performances for the average execution and connection times within the architecture for the overall BMS-IoT-based data acquisition to the cloud server. Moreover, the availability of monitored data shows satisfactory results for the reliability of the BMS-IoT system data acquisition. The above studies have some drawbacks as the technical details were not introduced in the cloud and the battery diagnostic algorithms that can help improve accuracy and data storage in the cloud were not exhaustively analyzed. Therefore, [PERSON] et al. [56] attempted to overcome these drawbacks by introducing a cloud BMS for battery systems to improve the computational power and data storage capability of cloud computing. The proposed cloud computing system provides computational power and data storage capacity with greater speed and utility. In EVs, charging operation is done by a graded control structure controlled by an aggregator, which controls all EV charging rates. For example, [PERSON] et al. [57] proposed a new approach for smart charging in EVs.