Abstract
Energy shortage and environmental pollution issues can be reduced considerably with the development and usage of electric vehicles (EVs). However, electric vehicle performance and battery lifespan depend on a suitable battery arrangement to meet the various battery performance demands. The safety, reliability, and efficiency of EVs largely depends on the constant monitoring of the batteries and management of battery packs. This work comprehensively reviews different aspects of battery management systems (BMS), i.e., architecture, functions, requirements, topologies, fundamentals of battery modeling, different battery models, issues/challenges, recommendations, and active and passive cell balancing approaches, etc., as compared to the existing works which normally discuss one or two aspects only. The work describes BMS functions, battery models and their comparisons in detail for an efficient operation of the battery pack. Similarly, the work presents a comprehensive overview of issues and challenges faced by BMS and also provides recommendations to address these challenges. Cell balancing is very important for the battery performance and in this work various cell balancing methodologies and their comparisons are also presented in detail. Modeling of a cell balancer is presented and a comparative study is also carried out for active and passive cell balance technique in MATLAB/Simulink with an eight cell battery packcell balancing approach. The result shows that the active cell balancing technique is more advantageous than passive balancing for electrical vehicles using lithium-ion batteries.
Highlights
In the advanced automobile era, an enormous move towards drive train modification is just around the corner
For real time state of charge (SOC) estimations by simple open circuit voltage (OCV)-SOC models reduces accuracy, accumulates different errors from other estimated parameters, etc. These OCV models cover the estimated SOC range depending on the battery usage pattern and do not cover the entire SOC range which can only be achieved by a complete charge/discharge profile
Based on our comparison between active and passive cell balancing, we found out that active cell balancing is much better and efficient as compared to passive cell balancing because active cell balancing stores energy in the transformer during the ON time and transfer it to the secondary during the off-time and suspend the cell while in the passive cell balancing, the energy stored in the section is discharged until the cell is balanced
Summary
In the advanced automobile era, an enormous move towards drive train modification is just around the corner. Alongside the battery cells themselves, certain olfim38its must be continued to get the most life from the cells These limits include, for example, temperature limits, charging/discharging rate limits, release current cut-off points, and motesmt peexrtraetumre/lliemasitts,ccehllarvgoinltga/gdeislicmhaitrsg.inTghreastee lriemqiutsir,ermeleanstes caurrereonbtsceurtv-oefdf,pcoointsst,raninded, maminotsatienxetdre, maned/laedasmt icneilsltevroeldtagbey laimfriatsm. Direct estimation (Coulomb counting, open circuit voltage (OCV)-based, etc.), model-based (equivalent circuit and electrochemical, etc.) and data driven-based approaches have all been used to calculate OCV for the online estimation of SOC The precision of these models depends on the parameter tuning, training, state observers, and various practical conditions. Every cell has different internal resistance which changes with time/usage, temperature, chemical properties and other environmental conditions as well All of these parameters affect the power value of a cell. BMS should be able to assess the battery conditions regularly and should avoid EOD situations [18]
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