We design and develop device and methods for battery testing, diagnostics, state-of-charge (SOC), and state-of-health (SOH) estimations.
We study and develop battery conventional and fractional equivalent circuit and physical models, their identifiability and parameter estimation problems in both time and frequency domains, by using advanced least-squares and Bayesian inference algorithms.
- TS Aghdam, SMM Alavi, M Saif, “Structural Identifiability of Impedance Spectroscopy Fractional-Order Equivalent Circuit Models With Two Constant Phase Elements,” Automatica, 144, 110463, 2022.
- PE Jacob, SMM Alavi, A Mahdi, SJ Payne, DA Howey, “Bayesian inference in non-Markovian state-space models with applications to fractional order battery systems,” IEEE Transactions on Control Systems Technology, 26(2), 497 – 506, 2018.
- SMM Alavi, A Mahdi, SJ Payne, DA Howey, “Identifiability of generalised Randles circuit models,” IEEE Transactions on Control Systems Technology, 25(6), pp. 2112 – 2120, 2017.
- SMM Alavi, CR Birkl, DA Howey, “Time-domain fitting of battery electrochemical impedance models,” Journal of Power Sources, 288, pp 345 – 352, 2015.
- SMM Alavi, MF Samadi, M Saif, “Diagnostics in Lithium-Ion Batteries: Challenging Issues and Recent Achievements,” Integration of Practice-oriented Knowledge Technology: Trends and Prospectives, Ed. M. Fathi, pp. 277-291, 2013.
- SMM Alavi, MF Samadi, M Saif, “Plating Mechanism Detection in Lithium-ion Batteries, By Using a Particle-Filtering Based Estimation Technique,” American Control Conference (ACC2013), pp. 43-56-4361, 2013.
- MF Samadi, SMM Alavi, M Saif, “Online state and parameter estimation of the Li-ion battery in a Bayesian framework,” American Control Conference (ACC2013), pp. 4693-4698, 2013.
- MF Samadi, SMM Alavi, M Saif, “An electrochemical model-based particle filter approach for Lithium-ion battery estimation,” The 51st IEEE Conference on Decision and Control (CDC2012), pp. 3074-3079, 2012.