State-of-Charge and State-of-Health variable-gain estimation based on tracking sliding mode differentiators for an electric vehicle Lithium-ion battery

In this paper, new methods to provide on-line measures of the State-of-Charge and State-of-Health of Lithium -ion batteries intended for vehicular applications are presented. The proposal is based on an estimation methodology formulated to determine, and accurately track the variations of the time-varying parameters of an equivalent electric circuit model employed for system modelling during vehicle operation.The proposed Lithium-ion battery parameter estimation method successfully combines recently developed differentiation techniques, i.e. high-order Tracking Sliding Mode differentiators, with a recursive least squares with forgetting factor algorithm, that includes a variable-gain specifically designed for this application. The parameter estimates are employed to efficiently compute the evolution of the State-of-Charge and the State-of-Health.Finally, to assess the algorithms performance, in-silico evaluations are conducted utilising power profiles taken from standardised driving cycles.