Condensate formation in exhaust systems at low temperatures

Condensate formation

The research project " Condensate formation in exhaust gas systems - Surface condensation on exhaust gas-carrying component surfaces under the influence of dynamic (cold start) operating conditions on a gasoline and diesel engine”, which is funded by the German Federal Ministry of Economics and Climate Protection (BMWK), is carried out in cooperation with the Institute of Internal Combustion Engines (IFKM) at Karlsruhe Institute of Technology (KIT) (https://www.ifkm.kit.edu).

Based on the previously gained knowledge within the project FVV 1316 - Exhaust Gas Composition at Low Temperatures - this follow-up project aims to elucidate in detail the essential mechanisms of surface condensation in the exhaust gas system of a gasoline/diesel engine under dynamic operating conditions, with a focus on the determination of component surface temperatures and surface properties.

Emphasis is on a comparison between conventional fuel and a CO2-neutral fuel as well as an e-fuel.
The optical analysis of the condensation tendency on exhaust-gas-integrated test carriers is possible with an automated real-time climate test rig at defined ambient temperatures as a function of the moisture and condensate content in the exhaust gas.
The dynamic evolution of surface temperatures can be tracked in detail via phosphor thermometry.
With regard to material type and surface roughness of predefined surfaces, deposits are systematically accumulated to allow monitoring of deposition effects during "long-term" deposition.
Extensive characterization of condensates and solid deposits using a variety of analytical methods (thermogravimetric analysis coupled with mass spectrometry and Fourier transform infrared spectrometer, gas chromatography coupled with mass spectrometry, UV-VIS spectroscopy, high resolution transmission electron microscopy including pattern recognition algorithms, elemental analysis, BET surface analysis via gas adsorption, energy dispersive X-ray spectroscopy, ...).
An experimental database for component surface temperatures and surface conditions and their effects on exhaust gas composition, condensation of exhaust gas constituents, deposit formation, and physicochemical properties of deposits is being established.
The possibility of describing the complex interactions using predictive models for exhaust gas composition, condensate and deposit properties during cold start of engines from large-scale experimental data based on machine learning approaches is exemplified.