Internal Combustion Engines (ICEs) – from diesel generators to marine engines – waste a significant portion of fuel energy as low-grade heat. While recovering this energy has been technically challenging, especially below 150°C, AI is now unlocking new possibilities for low-temperature waste heat recovery that are efficient, smart, and scalable.
🎯 How AI Can Make This Product or Solution Much Better
🔁 Dynamic Waste Heat Recovery Optimization
AI controls real-time parameters of ORC systems, heat exchangers, and working fluids to capture low-grade heat from exhaust gases, coolant loops, and lubricants.
It adapts to varying engine loads, idle cycles, and ambient conditions to maximize usable heat extraction.
🧠 Engine-Integrated Energy Management
AI connects directly with engine control units (ECUs) to co-optimize engine and heat recovery operations.
It intelligently diverts waste heat to auxiliary loads, cabin heating, or energy storage based on fuel use, emissions, and load priority.
⚡ Smart Load Matching & Microgrid Coordination
In stationary gensets, marine vessels, or off-grid microgrids, AI ensures heat and power outputs are matched to local demand.
This enables smarter load dispatch and prevents underutilization or overheating of components.
Our specialty focus areas include
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View full playlist🛠️ Fault Detection & Thermal Degradation Monitoring
Machine learning identifies scaling, fouling, thermal fatigue, or pressure loss in ORC systems and heat exchangers.
This predictive maintenance reduces unplanned shutdowns and extends component life in harsh ICE environments.
🌞 Hybrid Integration with Renewable Systems
AI manages heat recovery alongside solar, batteries, or electric vehicle systems.
It supports resilient hybrid energy solutions for mobile, off-grid, or industrial operations.
🛠️ How AI Overcomes Key Challenges
| Challenge | AI Solution |
|---|---|
| Low-grade and intermittent heat | AI dynamically captures usable heat even during partial loads or idle cycles |
| Tight space/weight limits | AI simulates compact WHR system designs for mobile and space-constrained platforms |
| Fuel and ambient variability | AI tunes system performance in real time for changing conditions |
| Integration with legacy ICEs | Digital twins enable retrofit simulation and cost-benefit forecasting |
🤖 Main AI Tools and Concepts Used
- Reinforcement learning for dynamic heat exchanger/ORC control
- Predictive maintenance via thermal and vibration data analytics
- Supervised learning for heat and load forecasting
- AI-integrated digital twins for ICE-WHR systems
- Optimization algorithms balancing fuel economy and heat recovery
📊 Case Studies
- Caterpillar (Global):
Industrial gensets now feature AI-integrated heat recovery modules for secondary energy generation in mining and off-grid sites.
🚀 Relevant Startups & Providers
| Company | TRL | Highlights |
|---|---|---|
| Exergy (Italy) | 9 | Compact ORC systems with AI control for low-grade heat from engines in industrial settings |
| ElectraTherm (USA) | 9 | AI-optimized Power+ Generator for ORC-based ICE heat recovery in off-grid deployments |
| Boson Energy (Luxembourg) | 8–9 | Integrates AI, WHR, and renewables for resilient microgrid operations |
| Exodraft (Denmark) | 8 | AI-powered economizers and flue gas recovery for stationary ICEs and small CHP units |
| Enogia (France) | 8–9 | Delivers AI-integrated compact ORC modules for compressors, gensets, and process engines |
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