Iron Horse Acquisition II Corp.

APPENDIX

Our Investors 36

EVE-Ai: Predicting Thermal Runaway Before It Happens Understanding and Predicting Thermal Runaway Mechanical Abuse • Cause: Physical damage (compression & penetration) • What Happens: Internal deformation • Detection: Pressure monitoring Electrical Abuse • Cause: Overcharge or internal short circuit • What Happens: Rapid internal heating and instability • Detection: Electrochemical Impedance Spectroscopy (EIS), voltage and gas monitoring Thermal Abuse • Cause: Excess heat beyond safe limits • What Happens: Rapid internal heating & instability • Detection: Temperature monitoring Thermal Runaway Prediction Advantage EIS+EVE-Ai predicts thermal runaway faster than traditional methods 37

Types of Battery Faults Detected Identify and Predict Faults Before they Become Safety-critical Events Fault Type Root Cause Detection Electrical Faults Overcurrent, short circuits, resistance changes Voltage drops and abnormal current behavior Thermal Faults Overheating from rapid cycling or poor cooling Rising temperatures and prolonged heat exposure Overcharge / Overdischarge Operating outside safe voltage ranges Voltage spikes or drops under load Accelerated Degradation Abnormal aging and lithium plating Deviation from expected aging patterns Data / Sensor Issues Missing or noisy signals under stress Inconsistent or unreliable data patterns 38

Go-To-Market Strategy Two Complementary Growth Engines Battery Fleet Analytics (BFA) Scalable & Repeatable Growth Engine Scale, Speed, Adoption Fast Market Entry Driven by Data & Usage Expansion Adaptive Controls Embedded, High Margin Growth Engine Depth, Lock-in, Defensibility Deep Integration Drives Long Term Value ARR (SaaS Licensing) Reference Customers Data Collection Pipeline Engine PoC + ARR Fees High switching Long-term scalable revenues Next-gen battery standard Energy Infrastructure (BESS) Fleets & Mobility Asset Operators Automotive OEMs (Tier 1) Advanced Mobility & Robotics Embedded BMS Free Trial Subscription Asset Expansion PoC Joint Development Long-term Licensing 39

Current Board of Technical Advisors David Mebane Assoc. Professor of Mechanical & Aerospace Engineering West Virginia University Matthias Preindl Assoc. Professor of Electrical Engineering Columbia University Simona Onori Assoc. Professor of Energy Science Engineering Stanford University David Burg Sr Lecturer at Hemdat Academic College / Researcher, The Rockefeller University Baosen Zhang Assoc. Professor Electrical & Computer Eng., University of Washington Physics-Based Continuum- Level Thermodynamic And Kinetic Models Model Predictive Control, Sensorless Control, Optimization, High- Frequency Power Electronics Energy Management Control And Optimization, Battery Aging Modeling; SoH; Life Prediction; Damage Degradation Math & Statistical Model Development; Big Data, Complexity Theory, Multivariate Data And Statistical Analyses Power and Energy Systems, Data Science, Robotics and Controls 41

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