Automated feature extraction to integrate field and laboratory data for aging diagnosis of automotive lithium-ion batteries

Cell Reports Physical Science, vol. 4, pp. 101596

Abstract

Battery aging diagnosis using field data readouts presents distinct challenges compared with using laboratory data. These challenges stem from the complexity of the data structure and potential inconsistencies in aging values obtained from variations in battery management system software versions. Consequently, the efficacy of a data-driven approach to identify pertinent aging features from field data becomes susceptible to these factors. In this work, we investigate different feature extraction methods and propose a framework designed to mitigate issues arising from compromised data quality. For this purpose, we leverage the benefits of precise laboratory aging data alongside authentic driving data acquired from a cohort exceeding 600,000 customers to improve the aging diagnosis of vehicle batteries. Moreover, we provide functional fitting of statistical data, addressing the challenges posed by incomplete data structures. We validate our methods by comparing them with state-of-the-art feature extraction techniques, yielding a 57% enhancement in aging estimation accuracy.

Authors 5

1. Valentin Steininger corresponding Aachen Center for Ageing Chair for Electrochemical Energy Conversion and Storage Systems Institute for Power Electronics and Electrical Drives (ISEA)

   BMW (Germany) · Jülich Aachen Research Alliance · RWTH Aachen University

   Affiliation as printed

   BMW AG, Petuelring 130, 80809 München, Germany

   Center for Ageing, Reliability and Lifetime Prediction of Electrochemical and Power Electronic Systems (CARL), RWTH Aachen University, Campus-Boulevard 89, 52074 Aachen, Germany

   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

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

2. Katharina Rumpf

   BMW (Germany)

   Affiliation as printed

   BMW AG, Petuelring 130, 80809 München, Germany

3. Peter Hüsson

   BMW (Germany)

   Affiliation as printed

   BMW AG, Petuelring 130, 80809 München, Germany

4. Weihan Li corresponding Aachen Center for Ageing Chair for Electrochemical Energy Conversion and Storage Systems Institute for Power Electronics and Electrical Drives (ISEA)

   Jülich Aachen Research Alliance · RWTH Aachen University

   Affiliation as printed

   Center for Ageing, Reliability and Lifetime Prediction of Electrochemical and Power Electronic Systems (CARL), RWTH Aachen University, Campus-Boulevard 89, 52074 Aachen, Germany

   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

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

5. Dirk Uwe Sauer Aachen Center for Ageing Chair for Electrochemical Energy Conversion and Storage Systems Institute for Power Electronics and Electrical Drives (ISEA)

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

   Affiliation as printed

   Center for Ageing, Reliability and Lifetime Prediction of Electrochemical and Power Electronic Systems (CARL), RWTH Aachen University, Campus-Boulevard 89, 52074 Aachen, Germany

   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 Münster (HI MS), IEK 12, Forschungszentrum Jülich, 52425 Jülich, Germany

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