|dc.description.abstract||For an engine running at a constant speed, both exhaust and intake processes are periodic in nature. This inspires the muffler designer to go for the much easier and faster frequency domain modeling. But analogous to electrical filter, as per Thevenin’s theorem, the acoustic filter or muffler requires prior knowledge of the load-independent source characteristics (acoustic pressure and internal impedance), corresponding to the open circuit voltage and internal impedance of an electrical source. Studies have shown that it is not feasible to evaluate these source characteristics making use of either the direct measurement method or the indirect evaluation method. Hence, prediction of the radiated exhaust or intake noise has been subject to trial and error.
Making use of the fact that pressure perturbation in a duct is a superposition of the forward moving wave and the reflected wave, a simple hybrid approach has been proposed making use of an interrelationship between progressive wave variables of the linear acoustic theory and Riemann variables of the method of characteristics. Neglecting the effect of nonlinearities, reflection of the forward moving wave has been duly incorporated at the exhaust valve. The reflection co-efficient of the system downstream of the exhaust valve has been calculated by means of the transfer matrix method at each of the several harmonics of the engine firing frequency. This simplified approach can predict exhaust noise with or without muffler for a naturally aspirated, single cylinder engine. However, this proves to be inadequate in predicting the exhaust noise of multi-cylinder engines. Thus, estimation of radiated noise has met only limited success in this approach.
Strictly speaking, unique source characteristics do not exist for an IC engine because of the associated non-linearity of the time-varying source. Yet, a designer would like to know the un-muffled noise level in order to assess the required insertion loss of a suitable muffler. As far as the analysis and design of a muffler is concerned, the linear frequency-domain analysis by means of the transfer matrix approach is most convenient and time saving. Therefore, from a practical point of view, it is very desirable to be able to evaluate source characteristics, even if grossly approximate. If somehow it were possible to parameterize the source characteristics of an engine in terms of basic engine parameters, then it would be possible to evaluate the un-muffled noise before a design is taken up as a first approximation. This aspect has been investigated in detail in this work. A finite-volume CFD (one dimensional) model has been used in conjunction with the two-load or multi-load method to evaluate the source characteristics at a point just downstream of the exhaust manifold for the exhaust system, and upstream of the air filter (dirty side) in the case of the intake system. These source characteristics have been extracted from the pressure time history calculated at that point using the electro-acoustic analogy. Systematic parametric studies have yielded approximate empirical expressions for the source characteristics of an engine in terms of the basic engine parameters like engine RPM, capacity (swept volume or displacement), air-fuel ratio, and the number of cylinders. The effect of other parameters has been found to be relatively insignificant.
Unlike exhaust noise, the intake system noise of an automobile cannot be measured because of the proximity of the engine at the point of measurement. Besides, the intake side is associated with turbocharger (booster), intercooler, cooling fan, etc., which will make the measurement of the intake noise erroneous. From the noise radiation point of view, intake noise used to be considered to be a minor source of noise as compared to the exhaust noise. Therefore, very little has been done or reported on prediction of the intake noise as compared to the exhaust noise. But nowadays, with efficient exhaust mufflers, the un-muffled intake noise has become a contributing factor to the passenger compartment noise level as a luxury decisive factor. Therefore, in this investigation both the intake and the exhaust side source characteristics have been found out for the compression ignition as well as the spark ignition engines. Besides, in the case of compression ignition engines, typical turbocharged as well as naturally aspirated engines have been considered.
One of the inputs to the time-domain simulation is the intake valve and exhaust valve lift histories as functions of crank angle. It is very cumbersome and time-consuming to measure and feed these data into the program. Sometimes, this data is not available or cannot be determined easily. So, a generalized formula for the valve lift has been developed by observing the valve lift curves of various engines. The maximum exhaust valve lift has been expressed as a function of the swept volume of the cylinder. This formulation is not intended for designing a cam profile; it is for the purpose of determining approximate thermodynamic quantities to help a muffler designer for an initial estimation. It has also been observed during the investigation that from the acoustic point of view, sometimes it is better to open the exhaust valve a little earlier, but very slowly and smoothly, and keep it open for a longer time.
Although the exact source characteristics for an automobile engine cannot be determined precisely, yet the values of source characteristics calculated using this methodology have been shown to be reasonably good for approximate prediction of the un-muffled noise as well as insertion loss of a given muffler. The resultant empirical expressions for the source characteristics enable the potential user to make use of the frequency-domain cum-transfer matrix approach throughout; the time consuming time-domain simulation of the engine exhaust source is no longer necessary. Predictions of the un-muffled sound pressure level of automotive engines have been corroborated against measured values as the well as the full scale time-domain predictions making use of a finite-volume software.||en_US