An optimal charging algorithm to minimise solid electrolyte interface layer in lithium-ion battery

This article presents a novel control algorithm for online optimal charging of lithium-ion battery by explicitly incorporating degradation mechanism into control, to reduce the degradation process. The health of battery directly relates to degradation and capacity fade in cycles of charging. We mainly focus on the growth of the solid electrolyte interface (SEI) layer, which is the primary source of degradation of batteries. This article addresses the challenge of minimising SEI layer growth during charging by incorporating the first-order SEI layer growth rate model into a non-linear model predictive control approach. A single particle model (SPM) is used for optimal charging using orthogonal projection-based model reformulation. Gauss pseudo-spectral method is used for the optimisation of charging trajectories. Results of the optimal algorithm are compared with the traditional constant current constant voltage (CCCV) approach without considering SEI layer growth. It is ensured that overpotential caused by lithium plating remains in a healthy regime which is another feature of the proposed strategy. Simulation results are presented to demonstrate the advantages of the proposed charging method

A Computationally E cient Online Optimal Charging Algorithm to Minimise Solid Electrolyte Interface Layer Growth in Lithium-ion Battery.

PhD Theses.Lithium-ion batteries have emerged as major energy storage devices over the last few decades. For enhanced battery life, understanding the relevant degradation mechanisms and their control has been a signi cant area of research interest. The dissertation explores the state of health in lithium-ion batteries in terms of solid electrolyte interface layer growth. The proposed optimal strategy gives a quantitative approach to measure the interface layer. A novel non-linear model predictive control algorithm is devised for online optimal charging by explicitly incorporating degradation mechanisms into control to reduce the degradation process. Chemical and mechanical degradation mechanisms have been considered separately for the growth of the interface layer. The work addresses the challenge of minimising layer growth during charging using the rst-order model in chemical degradation. However, the interface layer is modelled based on the break and repair e ect in mechanical degradation. A single particle model is used for optimal charging using orthogonal projection-based model reformulation. Gauss pseudo-spectral method is used for the optimisation of charging trajectories. Results of the optimal algorithm are compared with the traditional constant current constant voltage approach without considering the interface layer growth. The aim of using di erent degradation concepts is to nd similarities in charging patterns in lithium-ion batteries. Moreover, it is ensured that overpotential caused by lithium plating remains in a healthy regime considering chemical degradation, i.e. it must be positive during charging. Simulation results have been presented to demonstrate the advantages of the proposed charging method dealing with two side reactions simultaneously. The dissertation extends the results of the proposed non-linear model predictive control strategy considering chemical degradation in two ways. First, the single particle model with temperature dynamics was adopted to examine the thermal behaviour of lithium-ion batteries and temperature control. Second, the di erential atness method is applied to examine its computational bene ts over pseudo-spectral methods. A brief discussion on implementing the proposed algorithm in a battery management system of electric vehicles is presente

MS FT-2-2 7 Orthogonal polynomials and quadrature: Theory, computation, and applications

Quadrature rules find many applications in science and engineering. Their analysis is a classical area of applied mathematics and continues to attract considerable attention. This seminar brings together speakers with expertise in a large variety of quadrature rules. It is the aim of the seminar to provide an overview of recent developments in the analysis of quadrature rules. The computation of error estimates and novel applications also are described

Generalized averaged Gaussian quadrature and applications

A simple numerical method for constructing the optimal generalized averaged Gaussian quadrature formulas will be presented. These formulas exist in many cases in which real positive GaussKronrod formulas do not exist, and can be used as an adequate alternative in order to estimate the error of a Gaussian rule. We also investigate the conditions under which the optimal averaged Gaussian quadrature formulas and their truncated variants are internal