Optimization techniques of battery packs using re-configurability: A review

It is estimated that by 2030 the world would require nearly 150 GW of battery storage playing a key role in achieving the target of 45 percent power generation from renewable sources (IRENA). Large scale Battery Management Systems (BMS) deployed to support energy storage of Electric Vehicles or off-grid storages needs efficient, redundant and optimized system. To date scheduling methods have been used to increase the efficiency as well as operating time of small scale BMS. But the same is not a practical solution for large scale BMS, as it is not fault tolerant. In literature, Re-configurable BMS (R-BMS) have been rising up as the potential solution in increasing the energy efficiency, operating time as well as reliability of BMS. In this paper a comprehensive review of the existing R-BMS topologies in literature has been investigated and reviewed. To develop a model based R-BMS, we suggest a generalized block for modelling - 'Generalized Particle', and break down the whole R-BMS in functional sub-blocks as sensing, control and actuation. We then identified and focused on different challenges in each of these sub-blocks which are inevitable during real time implementation, thus defining future research scopes.