Data-driven Approach for Condition Assessment of a Diesel Engine Powered with Various Biodiesels

, Yuchun Xu, Yu Jia

Research output: Contribution to journalArticlepeer-review


In recent years, various biodiesels have been developed to decrease pollutant emissions from compression ignition engine. However, the current research focuses on reducing the pollutant components without considering the mechanical vibration that occurred due to the changes in fuel properties such as viscosity, calorific values, density, and bulk modulus. It is important to explore the relationships between fuel properties and engine vibration. Mechanical vibration could cause power loss and affect the lifetime of the engine. In this investigation, a lister-pitter 3-cylinder diesel engine was used to analyse the mechanical vibration of three different fuels including diesel, waste cooking oil biodiesel (WCOB), and lamb fat biodiesel (LFB). The high-frequency vibration sensors were mounted on the cylinder head to monitor and assess the vibration performance. The vibration data were collected under various operating conditions including varying engine speed from 1500 to 2000 rpm and varying engine loads ranging from 20% to 100%. Three practical assessment features of vibration signals were investigated to evaluate the vibration characteristics. The experimental results clearly demonstrate the relative relations between vibration, and fuel properties of the tested fuels, used in the diesel engine. Compared with fossil diesel fuel, the total vibration level decreased by 17% and 23% for WCOB and LFB fuels, respectively. The engine performance powered with LFB and WCOB are better than diesel’s effect on both vibration and friction power (FP) perspective. Superior lubricity and viscosity of WCOB and LFB is the main reason causing good vibration performance.
Original languageEnglish
Article number2023-01-0422
JournalSAE Technical Papers
Issue number2023-01-0422
Publication statusPublished - 11 Apr 2023

Bibliographical note

Funding Information:
The authors acknowledge the supported by the RECLAIM project, named as “Remanufacturing and Refurbishment Large Industrial Equipment”, and received funding from the European Commission Horizon 2020 research and innovation programme: this research used SignalCalc software and Abacus 906 hardware from Data Physics company.

Publisher Copyright:
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