Abstract
Simultaneous estimation of the battery capacity and state- of-charge is a difficult problem because they are dependent on each other and neither is directly measurable. This paper proposes a particle filtering approach for the estimation of the battery state-of-charge and a statistical method to estimate the battery capacity. Two different methods and time scales have been used for this estimation in order to reduce the dependency on each other. The algorithms are validated using experimental data from A123 graphite/LiFePO4 lithium ion commercial-off-the-shelf cells, aged under partial depth-of- discharge cycling as encountered in low-earth-orbit satellite applications. The model-based method is extensible to bat- tery applications with arbitrary duty-cycles.
Highlights
Health and lifetime uncertainty presents a major barrier to the deployment of lithium-ion (Li-ion) batteries in large-scale aerospace, electric vehicle, and electrical grid applications with stringent life requirements
The battery capacity estimation has been performed in a different time scale from the SOC estimation and used accumulated past data from both measurement and the particle filter outputs
The estimated value of the battery capacity has been used to modify the parameter of the battery state-space model
Summary
Health and lifetime uncertainty presents a major barrier to the deployment of lithium-ion (Li-ion) batteries in large-scale aerospace, electric vehicle, and electrical grid applications with stringent life requirements. Lee, Nam, & Cho, 2007; Charkhgard & Farrokhi, 2010; Kim & Cho, 2011; Hu, Youn, & Chung, 2012), unscented Kalman filter (Plett, 2006; Sun, Hu, Zou, & Li, 2011) or cubature Kalman filter (Chen, 2012) Those SOC estimation methods work well in certain situations but would not perform properly in other situations. Estimation of battery capacity using partial discharge data is challenging for Li-ion chemistries with a flat open-circuit voltage relationship versus SOC (Plett, 2011). Such is the case for the Li-ion graphite/iron-phosphate chemistry investigated in the present work
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