Charge optimization of lithium-ion batteries for electric-vehicle application

Abstract

In recent years Lithium-Ion battery as an alternate energy source has gathered lot of importance in all forms of energy requiring applications. Due to its overwhelming benefits over a few disadvantages Lithium Ion is more sought of than any other Battery types. Any battery pack alone cannot perform or achieve its maximum capacity unless there is some robust, efficient and advanced controls developed around it. This control strategy is called Battery Management System or BMS. Most BMS performs the following activity if not all Battery Health Monitoring, Temperature Monitoring, Regeneration Tactics, Discharge Profiles, History logging, etc. One of the major key contributor in a better BMS design and subsequently maintaining a better battery performance and EUL is Regeneration Tactics. In this work, emphasis is laid on understanding the prevalent methods of regeneration and designing a new strategy that better suits the battery performance. A performance index is chosen which aims at minimizing the effort of regeneration along with a minimum deviation from the rated maximum thresholds for cell temperature and regeneration current. Tuning capability is provided for both temperature deviation and current deviation so that it can be tuned based on requirement and battery chemistry and parameters. To solve the optimization problem, Pontryagin's principle is used which is very effective for constraint optimization with both state and input constraints. Simulation results with different sets of tuning shows that the proposed method has a lot of potential and is capable of introducing a new dynamic regeneration tactic for Lithium Ion cells. With the current optimistic results from this work, it is strongly recommended to bring in more battery constraints into the optimization boundary to better understand and incorporate battery chemistry into the regeneration process.