June 24, 2026 article Physics-informed neural networks for battery modeling and state estimation: A methodological review Renewable and Sustainable Energy Reviews DOI: 10.1016/j.rser.2026.117226 OpenAlex Authors 0 Author list not loaded yet. Cited by 0 stored of 1 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 Physics-informed neural networks for electrode-level state estimation in lithium-ion batteries 2021 Journal of Power Sources article Engineering Advanced Battery Technologies Research cited by 6 patents 149 citations Co-estimation of state of charge and capacity for battery packs in real electric vehicles with few representative cells and physics-informed machine learning 2024 Energy article Engineering Advanced Battery Technologies Research 36 citations 2 results