Virtualization as a Catalyst for Requirement-Based DevOps in Electrified Powertrain Systems

Dragana Borjan･Franz Eberhard･Stefan Eder･Samuel Swamidass･Avinash Singh (AVL List)

Electrified powertrain development faces rising software complexity, agile practices, and strict safety standards like ASIL-D. Traditional testing with physical prototypes struggles due to late hardware availability and high costs, driving a shift-left strategy for faster time-to-market. AVL applies a requirement-based approach using CI/CD/CT pipelines from specification to validation, integrating model-based sources and dynamic test environments. Virtualization with SiL and FMUs enables continuous integration of vECUs and plant models, improving transparency, reducing prototype dependency, and ensuring compliance. This framework supports early validation of complex E/E architectures and paves the way for AI-driven automation, such as MAESTRA AI for test case generation.

指圧波形中の周波数成分を用いた図示平均有効圧算出法の2山指圧波形への適用

長島　慶一（本田技術研究所）・土屋　一雄（明治大学）

指圧波形中の低次周波数成分から図示平均有効圧を算出できることが明らかになっている．この方法は，定義式から解析的に求められた式を用いるので，容積型機械全般に，指圧波形の形状によらず適用できる．本稿では，2山の指圧波形も含めて，実機データとの検証を実施した．その場合も含めて適用可能であることが確認できた．

ピストン摩擦力計測技術の開発

鈴木　健了・中山　慶則・本田　篤史（SOKEN）・並木　元治・藤本　雅大（トヨタ自動車）・戸田　幸男（戸田レーシング）

エンジン実働状態のピストン摩擦力を高回転まで計測する浮動ライナー方式の計測技術を開発した．特徴は，ライナーを高い剛性で保持する両側支持構造の採用と，振動ノイズのキャンセル方法を新規に導入した点である．これにより，最大4000r/minまで高い繰り返し精度（FMEP 3σ＜0.5kPa）でピストン摩擦力を計測できることを確認した．

Data Enrichment Framework for Enhanced Automotive Durability Analysis

Abderrahim Mazroai･Anna Marin･Arturo Rubio Ferrando･Xavier Larroy Puig (Applus+ IDIADA)

This abstract presents PyEnricher, a framework enriching automotive MF4 measurement files with commercial geospatial and environmental databases. Traditional durability testing generates raw measurement data lacking environmental context critical for understanding correlations between component stress and real-world operating conditions. The PyEnricher application utilizes Python with asammdf libraries for MF4 file processing, integrating OpenStreetMap for road classification, Visual Crossing for meteorological data, and Astral libraries for solar positioning. The architecture implements circuit breaker patterns, connection pooling, and batch processing with queue management for robust fault-tolerance during API operations. Comprehensive MF4-commercial database integration establishing new benchmarks for automotive measurement data contextualization in durability testing applications. Enables durability analytics through environmental correlation and location testing strategies.