Pierluigi Del Nostro , Gerhard Goldbeck , Ferry Kienberger , Manuel Moertelmaier , Andrea Pozzi , Nawfal Al-Zubaidi-R-Smith , Daniele Toti
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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.</div></div>","PeriodicalId":55219,"journal":{"name":"Computers in Industry","volume":"164 ","pages":"Article 104203"},"PeriodicalIF":8.2000,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Battery testing ontology: An EMMO-based semantic framework for representing knowledge in battery testing and battery quality control\",\"authors\":\"Pierluigi Del Nostro , Gerhard Goldbeck , Ferry Kienberger , Manuel Moertelmaier , Andrea Pozzi , Nawfal Al-Zubaidi-R-Smith , Daniele Toti\",\"doi\":\"10.1016/j.compind.2024.104203\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>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). 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Battery testing ontology: An EMMO-based semantic framework for representing knowledge in battery testing and battery quality control
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.
期刊介绍:
The objective of Computers in Industry is to present original, high-quality, application-oriented research papers that:
• Illuminate emerging trends and possibilities in the utilization of Information and Communication Technology in industry;
• Establish connections or integrations across various technology domains within the expansive realm of computer applications for industry;
• Foster connections or integrations across diverse application areas of ICT in industry.