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R. Morello, R. Di Rienzo, F. Baronti, R. Roncella and R. Saletti, "System on chip battery state estimator: E-bike case study", IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society, Florence, 2016

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This paper discusses the hardware implementation and experimental validation of a model-based battery state estimator. The model parameters are identified online using the moving window least squares method. The estimator is implemented in a field programmable gate array device as a hardware block, which interacts with the embedded processor to form a system on a chip battery management system (BMS). As a case study, the BMS is applied to the battery pack of an e-bike. Road tests show that the implemented estimator may provide very good performance in terms of maximum and rms estimation errors. This work also proposes a new methodology to assess the performance of a battery state estimator.