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An analysis and evaluation of state estimation methods for lithium-ion batteries regarding requirements of 48 V HEV applications

Journal of Energy Storage, vol. 97, pp. 112907

Abstract

To cope with increasingly stricter CO2 emission regulations and to improve comfort features for their customers, the automotive industry introduced 48 V systems in a broad range of their new vehicles powered by a conventional internal combustion engine (ICE). With the addition of a 48 V lithium-ion battery, it becomes crucial to accurately estimate its State of Charge (SoC) and State of Health (SoH) to ensure a safe operating window, high performance and a long lifetime. Several research studies examined a variety of methods to estimate the SoC and SoH. However, self-sufficient 48 V systems challenge state-of-the-art battery state estimation methods due to high C-rates and high SoC variation. Only few methods meet the automotive requirements for real-time applicability on embedded systems and online estimation. This study analyses typical battery usage patterns in 48 V systems and compares it to the ones of battery electric vehicles (BEVs). Various state estimation methods presented in literature including direct measurement, model-based, and data-driven methods are discussed to determine whether the implementation and validation of the proposed method fit the 48 V application scenario. This study shall form the basis for consecutive papers which focus on the implementation and validation of promising methods such as Kalman filters under various operating conditions and real driving data of 48 V hybrid electric vehicles (HEVs).

Authors 6

  1. Jülich Aachen Research Alliance · RWTH Aachen University

    Affiliation as printed

    Chair for Electrochemical Energy Conversion and Storage Systems, Institute for Power Electronics and Electrical Drives (ISEA), RWTH Aachen University, Campus-Boulevard 89, 52074, Aachen, Germany

    Juelich Aachen Research Alliance, JARA-Energy, Templergraben 55, 52056, Aachen, Germany

  2. RWTH Aachen University

    Affiliation as printed

    Chair for Electrochemical Energy Conversion and Storage Systems, Institute for Power Electronics and Electrical Drives (ISEA), RWTH Aachen University, Campus-Boulevard 89, 52074, Aachen, Germany

    Research and Development Mercedes-Benz Cars, Mercedes-Benz AG, 71059, Sindelfingen, Germany

  3. Affiliation as printed

    Mercedes-Benz RD India Pvt., Ltd., 560066, Bangalore, India

  4. Jülich Aachen Research Alliance · RWTH Aachen University

    Affiliation as printed

    Chair for Electrochemical Energy Conversion and Storage Systems, Institute for Power Electronics and Electrical Drives (ISEA), RWTH Aachen University, Campus-Boulevard 89, 52074, Aachen, Germany

    Juelich Aachen Research Alliance, JARA-Energy, Templergraben 55, 52056, Aachen, Germany

  5. Affiliation as printed

    Research and Development Mercedes-Benz Cars, Mercedes-Benz AG, 71059, Sindelfingen, Germany

  6. Forschungszentrum Jülich · Helmholtz-Institute Münster · Jülich Aachen Research Alliance · RWTH Aachen University

    Affiliation as printed

    Chair for Electrochemical Energy Conversion and Storage Systems, Institute for Power Electronics and Electrical Drives (ISEA), RWTH Aachen University, Campus-Boulevard 89, 52074, Aachen, Germany

    Helmholtz Institute Muenster (HI MS), IEK 12, Forschungszentrum Juelich, 52425, Juelich, Germany

    Institute for Power Generation and Storage Systems (PGS), E.ON ERC, RWTH Aachen University, Mathieustrasse 10, 52074, Aachen, Germany

    Juelich Aachen Research Alliance, JARA-Energy, Templergraben 55, 52056, Aachen, Germany

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References 102