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.

Application of the Indicated Mean Effective Pressure Calculation Method Using Frequency Components in Cylinder Pressure to Two-peak Cylinder Pressure

Keiichi Nagashima (Honda R&D)･Kazuo Tuchiya (Meiji University)

It has been revealed that the indicated mean effective pressure can be calculated from the low-order frequency components in the pressure diagram. This method uses an analytically derived formula from the definition formula, so it can be applied to all positive displacement machines regardless of the shape of the cylinder pressure. In this paper, we conducted verification with actual machine data, including the two-peak cylinder pressure. It was confirmed that the method can be applied in this case as well.

A New Measurement Method of Piston Friction Force

Takanori Suzuki･Yoshinori Nakayama･Atsushi Honda (SOKEN)･Motoharu Namiki･Masahiro Fujimoto (Toyota Motor)･Yukio Toda (Toda Racing)

A new floating liner measurement equipment was developed. With the equipment, piston friction force under actual engine operating conditions can be evaluated across a wide range of engine speeds. The key features of the equipment are follows; 1) implementation of a support of both-side of liner; 2) introduction of a new vibration noise cancellation method. With these features, the equipment can measure of the piston friction force with high repeatability (FMEP 3σ < 0.5 kPa) up to 4000 r/min.

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.