ADAS & Vehicle SafetyFull-Vehicle Multiphysics Co-Simulation for Euro NCAP Active Safety Protocol Validation
Simulation AutomationIntelligent Multiphysics Automation bridging Safety Analysis and Fault Simulation via LLM
Battery IntelligencePINN-LSTM Battery Intelligence for BMS and Electric Powertrains
Global StagePresenting at one of the world's premier multiphysics simulation conferences
Technical Presentations
eShocan Sessions at Detroit
AI-driven multiphysics simulation and intelligent validation for automotive safety, ADAS, and battery health using LLMs, RAG, and physics-informed learning.
27 Oct 2026 · 16:30 EDT
Full-Vehicle Multiphysics ADAS Co-Simulation for Euro NCAP Active Safety Protocol Validation with Vehicle Dynamics and 3D Animation
Dr. Jaywant Mahajan — eShocan 27 October 2026, 16:30 EDT NAFEMS Multiphysics Conference, Detroit
This paper introduces a full-vehicle multiphysics ADAS co-simulation framework built around Euro NCAP active safety protocols. The methodology integrates vehicle dynamics with real-time 3D animation to validate ADAS performance under standardised crash-avoidance scenarios. The approach bridges high-fidelity simulation with regulatory-grade protocol compliance, providing a reproducible digital testing environment for modern active safety systems.
Intelligent Multiphysics Simulation Automation: Bridging Safety Analysis and Fault Simulation for Automotive Systems Using Large Language Models
Dr. Jaywant Mahajan — eShocan 28 October 2026, 10:00 EDT NAFEMS Multiphysics Conference, Detroit
This session presents an intelligent automation framework that uses Large Language Models (LLMs) to orchestrate multiphysics simulation workflows. The system connects safety analysis (FMEA/FTA) with fault-injection simulation pipelines, enabling autonomous generation, execution and reporting of simulation studies across ADAS, battery and structural domains — dramatically reducing manual engineering overhead.
PINN-LSTM Battery Intelligence: Physics-Informed Machine Learning for Real-Time Battery Management and Electric Powertrain Optimisation
Dr. Jaywant Mahajan — eShocan 29 October 2026, 11:00 EDT NAFEMS Multiphysics Conference, Detroit
A hybrid PINN-LSTM architecture for real-time battery state estimation and electric powertrain optimisation. The framework combines physics-informed neural networks (PINNs) with long-short-term memory (LSTM) recurrent layers to deliver accurate, computationally efficient predictions of battery state-of-charge, state-of-health and temperature — enabling smarter BMS decisions under variable load profiles.
Meet Dr. Jaywant Mahajan and our engineering delegation in Detroit.
Our lead author and simulation architects will be available on-site across all three days of the NAFEMS Multiphysics Conference in Detroit. Whether you want to review your simulation automation pipeline, evaluate Euro NCAP ADAS co-simulation, explore battery intelligence, or discuss your technical programs — reserve dedicated time to meet directly.
1-on-1 Author Access: Meet Dr. Jaywant Mahajan in person at Fort Shelby.
Tailored Program Discussion: Map presentation methodologies to your active vehicle & electronics architectures.
Live Workflow Walkthroughs: Deep-dive into LLM-driven automation, fault simulation, and PINN-LSTM toolchains.
eShocan presents AI-Enabled SPDM in CAE at the NAFEMS SPDM & AI/ML Conference in Munich (27–28 Oct 2026). Speakers: Dr. Tayeb Zeguer & Mayur Bachhav. Session 8A, Raum A — 28 Oct @ 16:30 CEST.
Dr. Jaywant Mahajan presents Full-Vehicle ADAS Co-Simulation for Euro NCAP Active Safety Protocol Validation at NAFEMS India Conference 2026 — Bengaluru, Track A on 17 Nov at 3:25 PM IST.
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