R. Morello, R. Di Rienzo, R. Roncella, R. Saletti and F. Baronti, "Tuning of Moving Window Least Squares-based algorithm for online battery parameter estimation," SMACD 2017, Giardini Naxos, Italy, 2017, pp. 1-4.

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Online battery parameter identification algorithms, such as the Moving Window Least Squares, allow model-based state estimators with low computational intensity to be very accurate. This paper presents a procedure for tuning the algorithm parameters by using application-specific current profiles. A gardening application is taken as a case study. The results prove the validity of the proposed procedure and allow us to assess the identification algorithm performance.