Battery testing ontology: An EMMO-based semantic framework for representing knowledge in battery testing and battery quality control

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.