1. Torque Prediction Model of a CI Engine for Agricultural Purposes Based on Exhaust Gas Temperatures and CFD-FVM Methodologies Validated with Experimental Tests
- Author
-
Bietresato, M, Selmo, F, Renzi, M, and Mazzetto, F
- Subjects
Technology ,QH301-705.5 ,Physics ,QC1-999 ,indirect estimation ,RSM ,torque ,exhaust gas temperature ,compression-ignition engine ,thermocouples ,CFD ,FVM ,agricultural machines ,Engineering (General). Civil engineering (General) ,Chemistry ,TA1-2040 ,Biology (General) ,QD1-999 - Abstract
A truly universal system to optimize consumptions, monitor operation and predict maintenance interventions for internal combustion engines must be independent of onboard systems, if present. One of the least invasive methods of detecting engine performance involves the measurement of the exhaust gas temperature (EGT), which can be related to the instant torque through thermodynamic relations. The practical implementation of such a system requires great care since its torque-predictive capabilities are strongly influenced by the position chosen for the temperature-detection point(s) along the exhaust line, specific for each engine, the type of installation for the thermocouples, and the thermal characteristics of the interposed materials. After performing some preliminary tests at the dynamometric brake on a compression-ignition engine for agricultural purposes equipped with three thermocouples at different points in the exhaust duct, a novel procedure was developed to: (1) tune a CFD-FVM-model of the exhaust pipe and determine many unknown thermodynamic parameters concerning the engine (including the real EGT at the exhaust valve outlet in some engine operative conditions), (2) use the CFD-FVM results to considerably increase the predictive capability of an indirect torque-detection strategy based on the EGT. The joint use of the CFD-FVM software, Response Surface Method, and specific optimization algorithms was fundamental to these aims and granted the experimenters a full mastery of systems’ non-linearity and a maximum relative error on the torque estimations of 2.9%.
- Published
- 2021