Verification of Circuit Parameter Optimization Technology for ECU through Inter-Company Collaboration Using an Electro-Mechanical Coupled 1D Model

Masashi Inaba (DENSO)･Masanori Ueda (Siemens EDA Japan)･Osamu Seya (Institute of Science Tokyo)･Kota Saito (Murata Manufacturing)･Yoshiko Ikeda (Toshiba Electronic Devices & Storage)･Keita Inoue (DENSO)･Hiroki Nakamizo･Wataru Hijikata･Hideaki Fujita (Institute of Science Tokyo)･Takuya Shinoda (DENSO)

Recently, the demand for shorter ECU development cycles has increased, drawing attention to electromechanical coupled 1D modeling. Last year, using a model shared among companies, we analyzed actuator drive circuit behavior and simulated ECU heat generation, then fabricated an actual board to verify consistency between experimental and simulation results. This year, we investigate the application of this approach to circuit parameter optimization.

High Precision 3D Thermal Analysis of Printed Circuit Board Components using Transient Heat Generation Obtained from Circuit Simulation

Haruki Takei (Siemens)･Nakaomi Sawada (Persol Cross Technology)･Minoru Shibutani (Kozo Keikaku Engineering)･Masanari Ueda (Siemens EDA Japan)･Yoshiko Ikeda (Toshiba Electronic Devices & Storage)･Ryuta Yasui･Osamu Seya (Institute of Science Tokyo)･Kazunari Hashimoto･Keita Inoue･Takuya Shinoda (DENSO)

The Electronic Components and Thermal Design Working Group has been investigating the digitalization of the board design process as a contributory research project since 2024. In this presentation, we will report on our attempt to apply 3D thermal fluid simulation to the board design process.

Minimization of Discrepancy between Measurement and Thermal Fluid Analysis for ECUs Using Inverse Analysis

Minoru Shibutnai (Kozo Keikaku Engineering)･Ryuta Yasui (Institute of Science Tokyo)･Haruki Takei (Siemens)･Masanari Ueda (Siemens EDA Japan)･Yoshiko Ikeda (Toshiba Electronic Device & Storage)･Osamu Seya (Institute of Science Tokyo)･Kazunari Hashimoto･Keita Inoue･Takuya Shinoda (DENSO)

As part of the coupled circuit–thermal simulation initiative, we validate the accuracy of 3D thermal–fluid simulation using heat generation calculated from circuit simulations. Based on the results, we propose a process and technical guidelines to improve both simulation and experimental accuracy, thereby reducing discrepancies and enhancing thermal design reliability.

Verification of Surrogate Modeling and Optimization Design of ECU Heat Radiation Structure by Using MBD

Kazunari Hashimoto (DENSO)･Ryuta Yasui (Institute of Science Tokyo)･Masashi Inaba (DENSO)･Haruki Takei (Siemens)･Minoru Shibutani (Kozo Keikaku Engineering)･Masanari Ueda (Siemens Electronic Design Automation Japan)･Yoshiko Ikeda (Toshiba Electronic Devices & Storage)･Daisaku Mukaiyama (RUBYCON)･Kazuyoshi Fushinobu (Institute of Science Tokyo)･Takuya Shinoda (DENSO)

Acceleration of technological innovation is expected to shorten the development period by using CAE. Last year, we made an actual ECU that matched the actuator drive circuit model shared among companies and verified the accuracy of the thermal analysis model that matched the actual ECU. This year, we will verify the consistency between the analysis results of the optimized heat radiation structure design for the actual ECU and the corresponding experimental results.

Automotive Engineering-Centric Agentic AI Workflow Framework

Tong Duy Son･Zhihao Liu･Piero Brigida･Yerlan Akhmetov･Gurudevan Devarajan･Kai Liu･Ajinkya Bhave (Siemens Digital Industries Software)

AI Agents based on foundation models have potential to support automotive engineers in model-based design development. We present an industrial Copilot ecosystem with orchestrator and specialized agents managing complex automotive tasks. Engineers specify design requirements; agents coordinate 1D-3D simulations, CFD, ROM AI models, and design exploration tools. Moreover, AI agents could leverage historical data, requirements, codes, simulation configurations and test data analysis scripts. Our technologies enhance trustworthiness through engineer-centric design with feedback loops. Results demonstrate faster workflows, seamless integration across CAD-CFD tools, optimization, and human-AI collaboration for automotive applications.