Lithium-ion Battery Mathematical Modelling Using Python and IoT

Optimizing the utilization of lithium battery packs has become essential due to the increased demand for lithium-ion batteries. Because battery deterioration is unavoidable, some recent research has focused on maximizing the usage of lithium-ion battery cells in the pack. Reconfigurable battery packs and cell replacement are two viable ideas for limiting the harmful impact of early-degraded cells on the overall pack. This paper includes designing and developing a battery monitoring system for individual cells in a pack that is integrated with the Internet of Things (IoT), as well as validating simulation results produced with PyBaMM, the Python Battery Mathematical Model. While charging individual cells, the cell balancing factor is primarily considered, and temperature is maintained during both charging and discharging stages. The cell replacement method was developed to increase the overall number of cycles a battery pack has gone through, therefore increasing its life. This procedure is also likely to be more cost- effective than the current basic pack replacement method. Individual cell monitoring and easy access to cells during the failure stage are two design criteria that must be addressed for the cell replacement concept to be successful. Comprehensive testing guarantees that changes aren't impacted, making model expansions easy to adopt.