D-optimal design of experiments applied to lithium battery for ageing model calibration. (15th December 2017)

• Record Type: Journal Article
• Authors: Mathieu, Romain; Baghdadi, Issam; Briat, Olivier; Gyan, Philippe; Vinassa, Jean-Michel
• Is Part Of: Energy. Volume 141(2017)
• Page Start: 2108
• Page End: 2119
• Publication Date: 2017-12-15
• Subjects: Aging model -- Lithium-ion batteries -- Design of experiments -- Capacity fade -- Degradation rate; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2017.11.130
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: This paper exploits an optimal design of experiments to calibrate an ageing model for a graphite/LMO-NMC battery. The study is based on experimental data from the MOBICUS project. It features a D-optimal design for power cycling tests and separate calendar tests controlling temperature (0–60 °C), state-of-charge (SoC, 0–100%), as well as charge/discharge current separately (0, C/3, 1C). Altogether, 27 conditions were executed. The modeling approach makes an analogy between chemical kinetics and battery degradation which allows to identify a rate of capacity fade for constant ageing conditions. Statistical influence of each ageing factors on the degradation rate are studied. Quadratic effects of temperature and SoC are significant on calendar degradation, while an interaction effect between temperature and current describes the coupling to cycling fade. The double quadratic with interaction expression accurately models both calendar and cycling data with R 2 = 0.96. The coupled model is validated on six tests alternating calendar and cycling periods with 1.08% absolute error after 200 days. Feedback is given on the initial design and a new D-optimal of only 10 runs is proposed. The method allows to reduce experimental cost to calibrate an ageing model, which can be used for degradation management of battery-based storage systems. Highlights: Application of a D-optimal design to lithium battery accelerated ageing tests. Study of the statistical influence of temperature, SoC and current on capacity fade. Double quadratic model with interaction fits both calendar and cycling data. Validation of the model on mixed calendar-cycling ageing tests. Proposition of a new D-optimal model to reduce experimental cost.