Exact state-of-charge estimation is necessary for every application related to energy storage systems to protect the battery from deep discharging and overcharging. This leads to an improvement in discharge efficiency and extends the battery lifecycle. Batteries are a main source of energy and are usually monitored by management systems to achieve optimal use and protection. Coming up with effective methods for battery management systems that can adequately estimate the state-of-charge of batteries has become a great challenge that has been studied in the literature for some time. Hence, this paper analyses the different energy storage technologies, highlighting their merits and demerits. The various estimation methods for state-of-charge are discussed, and their merits and demerits are compared, while possible applications are pointed out. Furthermore, factors affecting the battery state-of-charge and approaches to managing the same are discussed and analysed. The different modelling tools used to carry out simulations for energy storage experiments are analysed and discussed. Additionally, a quantitative comparison of different technical and economic modelling simulators for energy storage applications is presented. Previous research works have been found to lack accuracy under varying conditions and ageing effects; as such, integrating hybrid approaches for enhanced accuracy in state-of-charge estimations is advised. With regards to energy storage technologies, exploring alternative materials for improved energy density, safety and sustainability exists as a huge research gap. The development of effective battery management systems for optimisation and control is yet to be fully exploited. When it comes to state-of-the-art simulators, integrating multiscale models for comprehensive understanding is of utmost importance. Enhancing adaptability across diverse battery chemistries and rigorous validation with real-world data is essential. To sum up the paper, future research directions and a conclusion are given.
