Online Health Monitoring in Lithium-Ion Battery for Electrified Transportation Systems
Abstract
Lithium-ion batteries have been proven to be a promising solution for powering vehicles since they feature high energy density, power density, low self-discharge and more importantly, long cycle life. However, due to cycle aging and calendar aging, the degradation of batteries also imposes additional electrical and thermal stress on the cells, resulting in a safety hazard.
This research tries to identify the degraded lithium-ion cells based on their electrical and thermal signatures. To focus on the characteristics of lithium-ion cells for electrified transportation systems, capacity and power are chosen to be indications of degradation level. An online estimation method is proposed to identify these indications and diagnose the health of the lithium-ion cell. Multiple experiments have proved the effectiveness of method. Moreover, the cell performance at various driving scenarios is also studied to understand their electrical and thermal stress under different circumstances. Based on the understanding of electrochemical process and the simulation of equivalent circuit model, the electrothermal behavior of the lithium-ion can be accurately simulated by the model incorporated with the effects of current and temperature. Then, the single-cell model is extended for a pack of batteries and verified by the experiment. The electrical characteristics of the cells in the pack have been studied to identify the possible cell-to-cell imbalance. Based on the electrical characteristics, the discrepant cell among a pack of cells with the parallel structure is identified and its health status is also diagnosed with the proposed estimation method. In this way, the abnormal cells in a pack can be identified and diagnosed in a complete procedure.