arXiv:2606.16171v1 Announce Type: cross Abstract: Multi-fuel compression ignition (CI) engines offer superior power density and fuel flexibility. However, achieving consistent and optimal combustion phasing across a wide range of operating conditions remains a major challenge, particularly in the presence of modeling uncertainties. This paper presents a novel, data-driven real-time uncertainty compensation framework for combustion control in multi-fuel CI engines. The proposed approach introduces a pseudo-engine speed that enables dynamic adaptation of control inputs in response to uncertainty
The increasing demand for fuel efficiency and reduced emissions in various sectors is driving innovation in engine control systems, particularly for multi-fuel engines facing complex operating conditions.
This development could significantly improve the efficiency and reliability of multi-fuel engines, offering greater energy independence and potentially reducing operational costs across industries from transportation to power generation.
Combustion control in multi-fuel engines can become more robust and adaptive to real-time uncertainties, moving away from reliance on perfect models towards data-driven compensation.
- · Engine manufacturers
- · Logistics and transportation sectors
- · Defense industry
- · AI/ML control system developers
- · Inefficient engine technologies
- · Fuel-intensive industries
More widespread adoption of multi-fuel engines due to enhanced reliability and performance enabled by AI-driven control.
Reduced reliance on single-fuel supply chains and greater fuel flexibility for critical infrastructure and mobile platforms.
Accelerated development of other data-driven control systems for complex physical processes, potentially impacting energy grids and manufacturing.
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Read at arXiv cs.LG