September 21, 2026 conference-paper EKF-Based Machine Learning Approach for Battery SOH Prediction in Commercial Vehicles Fleet SAE technical papers on CD-ROM/SAE technical paper series DOI: 10.4271/2026-24-0002 OpenAlex Authors 0 Author list not loaded yet. Cited by 0 stored of 0 References 2 Search Sort Most cited Newest Oldest Patent citations Title Any typearticle review book-chapter conference-paper preprint dissertation book dataset other Any fieldAgricultural and Biological Sciences Arts and Humanities Biochemistry, Genetics and Molecular Biology Business, Management and Accounting Chemical Engineering Chemistry Computer Science Decision Sciences Dentistry Earth and Planetary Sciences Economics, Econometrics and Finance Energy Engineering Environmental Science Health Professions Immunology and Microbiology Materials Science Mathematics Medicine Neuroscience Nursing Pharmacology, Toxicology and Pharmaceutics Physics and Astronomy Psychology Social Sciences Veterinary Open access Large-scale field data-based battery aging prediction driven by statistical features and machine learning 2023 Cell Reports Physical Science article Engineering Advanced Battery Technologies Research Open access 53 citations The future of battery data and the state of health of lithium-ion batteries in automotive applications 2024 Communications Engineering article Engineering Advanced Battery Technologies Research Open access 19 citations 2 results