Battery testing ontology: An EMMO-based semantic framework for representing knowledge in battery testing and battery quality control
Pierluigi Del Nostro, Gerhard Goldbeck, Ferry Kienberger, Manuel Moertelmaier, Andrea Pozzi, Nawfal Al‐Zubaidi R‐Smith, Daniele Toti
Abstract
The demand for advanced battery management systems (BMSs) and battery test procedures is growing due to the rising importance of electric vehicles (EVs) and energy storage systems. The diversity of battery types, chemistries and application scenarios presents challenges in designing and optimizing BMSs and determining optimal battery test strategies. To address these challenges, semantic web technologies and ontologies offer a structured and common vocabulary for information sharing and reuse in battery management and testing. This work introduces the Battery Testing Ontology (BTO), a standardized, comprehensive, and semantically flexible framework for representing knowledge in electrical battery testing and quality control. BTO models a variety of electrical battery cell tests, specifying required test hardware and calibration procedures, mechanical fixturing of batteries, and referencing electrical measurement data. For example, it supports electrochemical impedance spectroscopy, self-discharge and high-voltage separator tests, the latter specifically demonstrating separator requirements, hardware specifications, and measurement details. Positioned within the ontology ecosystem of materials science, BTO aligns with the Elementary Multiperspective Material Ontology (EMMO) and related domain ontologies such as the Characterization Methodology Ontology (CHAMEO). This work elaborates on BTO’s development, structure, components and applications, highlighting its significant contributions to the field of battery testing. • Introduction of the Battery Testing Ontology for battery testing and quality control. • Modeling of various battery cell tests and specifying the required testing hardware. • Support of test design, optimization, and accuracy in measurement setups. • Aligned with EMMO and other ontologies for interoperability. • Compliant with FAIR principles, enhancing data sharing and reuse.