4.8 Article

Real-Time Model-Based Estimation of SOC and SOH for Energy Storage Systems

Journal

IEEE TRANSACTIONS ON POWER ELECTRONICS
Volume 32, Issue 1, Pages 794-803

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPEL.2016.2535321

Keywords

Adaptive algorithms; energy storage systems modeling; runtime model; state of charge; state of health

Funding

  1. Research Project Tecnologie ad alta Efficienza per la Sostenibilita Energetica ed ambientale On-board-TESEO [PON02_153_2939517]

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To obtain a full exploitation of battery potential in energy storage applications, an accurate modeling of electrochemical batteries is needed. In real terms, an accurate knowledge of state of charge (SOC) and state of health (SOH) of the battery pack is needed to allow a precise design of the control algorithms for energy storage systems (ESSs). Initially, a review of effective methods for SOC and SOH assessment has been performed with the aim to analyze pros and cons of standard methods. Then, as the tradeoff between accuracy and complexity of the model is the major concern, a novel technique for SOC and SOH estimation has been proposed. It is based on the development of a battery circuit model and on a procedure for setting the model parameters. Such a procedure performs a real-time comparison between measured and calculated values of the battery voltage while a PI-based observer is used to provide the SOC and SOH actual values. This ensures a good accuracy in a wide range of operating conditions. Moreover, a simple start-up identification process is required based on battery data-sheet exploitation. Because of the low computational burden of the whole algorithm, it can be easily implemented in low-cost control units. An experimental comparison between SOC and SOH estimation performed by suggested and standard methods is able to confirm the consistency of the proposed approach.

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