High-level supervisory control systems require information about the internal states of an energy storage system, such as the state of charge and power capability. These quantities are not directly measureable, so models are necessary to estimate this information from the measured voltage, current and temperature. Empirical models often lack accuracy, particularly under extreme operating conditions. However, models that are closer to the physics are mathematically complex and computationally expensive, which is prohibitive for on-board applications. Our efforts here span a wide range of issues, from parameter estimation and identifiability of models, to model order reduction and observer design.

People

Antti Aitio, Nicola Courtier, David Howey

Academic collaborators

Ross Drummond (Oxford), Prof Stephen Duncan (Oxford), Dr Dan Rogers (Oxford)

Projects

• “Multiscale Modelling”, Faraday Institution Project
• “Very Large Scale Battery Management Systems (VLS-BMS) for Grid Energy Storage”, extension to EPSRC project ref. EP/K002252/1.
• “Automated Module-to-pack Pilot Line for Industrial Innovation (AMPLiFII)”, OLEV/InnovateUK Project.
• “Stability and Control of Power Networks with Energy Storage (STABLE-NET), EPSRC project ref. EP/L014343/1.
• “Advanced electric vehicle battery management systems”, Samsung Global Research Outreach (GRO) award.

Recent publications

• A. Aitio, S.G. Marquis, P. Ascencio, D.A. Howey, “Bayesian Parameter Estimation Applied to the Li-ion Battery Single Particle Model with Electrolyte Dynamics”, arXiv preprint arXiv:2001.09890, 2020, and IFAC 2020 paper.
• A.M. Bizeray, J.H. Kim, S.R. Duncan, D.A. Howey, “Identifiability and parameter estimation of the single particle lithium-ion battery model”, IEEE Transactions on Control Systems Technology vol. 99, pp. 1-16, 2018. ArXiv pre-print 1702.02471.
• R. Drummond, S. Zhao, D.A. Howey, S.R. Duncan, “Circuit synthesis of electrochemical supercapacitor models”, Journal of Energy Storage vol. 10, pp. 48-55, 2017
• S. Zhao, Duncan S.R. and Howey, D.A., “Observability analysis and state estimation of lithium-ion batteries in the presence of sensor biases”, IEEE Transactions on Control Systems Technology, vol. 25, no. 1, pp. 326-333, 2017