Year: 2025
Type: article
Abstract: The article presents a comparative analysis of modern laboratory and on-board technologies for monitoring the quality of diesel fuel, which are critically important for ensuring the stable operation of Common Rail fuel supply systems under operating conditions. The relevance of the research is due to the need to increase the reliability and environmental safety of diesel engines against the background of growing requirements for fuel efficiency and adaptation to the Industry 5.0 concept. The purpose of the work is to systematize knowledge about existing methods for assessing fuel quality and to justify the prospects of using on-board sensor systems as an element of preventive maintenance of diesel systems. The main tasks are: analysis of standard laboratory methods for measuring the physicochemical characteristics of fuel (cetane number, density, viscosity, sulfur content, FAME, water, and aromatic compounds), review of existing technologies for integrating diagnostic tools directly on board a vehicle, and evaluation of the accuracy, reliability, and practical applicability of such technologies. The study uses methods of comparative analysis of literature sources, standards, and patent documentation, as well as the methodology of technical evaluation of the design and operating principles of sensor systems. The novelty of the approach lies in the comprehensive comparison of the capabilities of traditional laboratory diagnostics with the results provided by modern on-board sensors based on tuning fork technology, near-infrared spectroscopy, ultrasonic, MEMS, and dielectric technologies. The research results show that most laboratory methods provide high accuracy, but are resource-intensive, poorly suited to real-time conditions, and not always informative for rapid response of engine control systems. At the same time, on-board sensors have demonstrated the ability to assess key physical parameters of fuel with sufficient reliability – particularly density, viscosity, dielectric constant, and FAME content. It was found that the most promising are systems that combine several sensor technologies with machine learning algorithms to create a complete fuel profile. It has been established that such hybrid solutions can adapt engine operation parameters to changes in fuel quality in real time, reducing the risk of malfunctions and lowering emission toxicity. The conclusions note that the transition to expanded use of on-board monitoring tools is a logical stage in the development of diesel injection systems. It is recommended to actively research and implement multiparameter sensors, which will make it possible to realize adaptive engine control strategies and prevent damage to fuel equipment. Several technical directions for improving sensor systems are proposed: improving thermal stability, self-cleaning surfaces, and expanding the spectral range of IR analysis. The results obtained may have long-term significance in the context of the environmental modernization of diesel transport and the development of reliable intelligent systems for monitoring fuel quality in the energy sector.
Source: Internal combustion Engines
Authors: A.V. Savchenko, P.B. Kitsenko
Language: English
Topic: Engine and Fuel Emissions
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4414440517
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