Modeling and Lifetime Prediction of Lithium-ion Battery

With the benefits of light weight and high power density, lithium-ion battery has been widely used in more-electric aircraft. However, its weak reliability raises our concern. Therefore, in order to maintain the safe operation of aircraft, it is worth implementing real-time state monitoring and lifetime prediction for lithium-ion battery. This paper proposed a monomer model of lithium-ion batteries based on partnership for a new generation of vehicles (PNGV) model and estimation of the state of charge (SOC). Then, the accelerated aging test was carried out using the proposed model based on Dymola platform. At the same time, particle filter algorithm is applied to evaluate the state of health (SOH) of lithium-ion battery. In this paper, the effectiveness of the proposed method was verified by simulation and experimental data.