FPGA-Based Implementation of Dual Kalman Filter for PV MPPT Applications

Mattia Ricco, Patrizio Manganiello, Eric Monmasson, Giovanni Petrone, Giovanni Spagnuolo

Research output: Contribution to journalArticleScientificpeer-review

31 Citations (Scopus)

Abstract

The way of implementing an adaptive maximum power point tracking algorithm for photovoltaic (PV) applications in a field programmable gate array (FPGA) is described in this paper. A dual Kalman filter allows estimating the settling time of the whole system, including the PV source and the dc/dc converter controlling the operating point thereof, so that the tracking algorithm self adapts its parameters to the actual weather conditions. The real-Time identification need of this application requires an FPGA platform, so that the intrinsic algorithm parallelism is exploited and the execution time is reduced. The tradeoff solutions proposed in this paper, accounting for the algorithm complexity and the limited FPGA hardware, as well as some solutions for optimizing the implementation are described. The proposed adaptive algorithm is implemented in a low-cost Xilinx Spartan-6 FPGA and it is validated through experimental tests.

Original languageEnglish
Pages (from-to)176-185
Number of pages10
JournalIEEE Transactions on Industrial Informatics
Volume13
Issue number1
DOIs
Publication statusPublished - Feb 2017
Externally publishedYes

Keywords

  • Adaptive maximum power point tracking (MPPT) controller
  • dual Kalman filter (DKF)
  • field programmable gate array (FPGA)
  • photovoltaic (PV) system

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