Characterization of composites with Al18Si alloy base and their application on tribological elements with linear reciprocating motion

[S. D. Miladinović]

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Razvoj automobilske industrije povećava zahteve za smanjenjem mase i povećanjem pouzdanosti vozila. Smanjenje mase vozila moguće je postići smanjenjem mase motora čiji je bitan deo klip, koji radi u otežanim uslovima. Sve veću primenu pri proizvodnji klipova imaju nadeutektičke Al-Si legure zbog svojih dobrih osobina kao što su dobra termička i električna provodljivost, visok odnos čvrstoće i mase i dobra otpornost na koroziju. U ovoj disertaciji izvršena su tribološka ispitivanja dve serije kompozitnih materijala (A i B) sa mikro i nano ojačavačima i osnovom od nadeutektičke Al18Si legure. Serija materijala A u svom sastavu je imala ukupno 6 materijala od kojih je jedan osnovna legura dok su ostali materijali kompoziti dobijeni dodavanjem 10 mas.% SiC (30 µm) i 0,5 mas.% Al2O3 (20–30 nm) i 1 mas.% ili 3 mas.% Gr (17 µm ili 200–800 µm). U okviru serije materijala B bilo je ukupno 8 materijala, odnosno osnova i 7 kompozita. Kompoziti ove serije materijala dobijeni su dodavanjem 0,5 mas.% Al2O3 (20–30 nm) i/ili 3 mas.% Al2O3 (36 µm) i/ili 3 mas.% SiC (40 µm) i/ili 3 mas.% Gr (250–500 µm). Pre triboloških ispitivanja izvršena je mikrostrukturna karakterizacija, kao i merenje tvrdoće i gustine navedenih materijala. Tribološka ispitivanja izvršena su u uslovima sa podmazivanjem pri brzini klizanja od 0,5 m/s, pređenom putu od 1000 m i normalnim opterećenjima od 100 N, 200 N i 300 N. S obzirom na to da je serija materijala A pokazala bolje karakteristike, za ovu seriju materijala sprovedena su i tribološka ispitivanja na uređaju sa pravolinijskim naizmeničnim kretanjem za iste uslove ispitivanja. Nakon izvršene tribološke analize primenjene su optimizacione metode Taguči-grej (Taguchi-grey) i veštačke neuronske mreže (Artificial neural networks – ANN) za predviđanje intenziteta habanja i koeficijenta trenja za obe serije materijala. Dobijena je optimalna kombinacija parametara i analizom varijanse (Analysis of Variance – ANOVA) dobijen je procentualni uticaj posmatranih faktora na intenzitet habanja i koeficijent trenja. Na kraju istraživanja izvršena je numerička analiza klipa metodom konačnih elemenata (MKE) pri pritisku od 7,5 MRa i temperaturama od 300°S do 400°S. Pri MKE analizi najviši naponi bili su sa unutrašnje strane čela klipa i kod ležišta osovinica i dokazano je da se ispitivani kompoziti mogu primeniti za proizvodnju klipova.

The development of the automotive industry increases the requirements for higher vehicle reliability and weight reduction. Weight reduction of the vehicle can be achieved by reduction of the weight of the engine. The important part of the engine is a piston, which works in aggressive conditions. Hypereutectic Al-Si alloys are increasingly used in the production of pistons due to their good properties such as good thermal and electrical conductivity, high strength-to-weight ratio and good corrosion resistance. In this dissertation, tribological tests were performed on two series of composite materials (А and B) with micro and nano reinforcements in hypereutectic Al18Si alloy base. The materials of A series included a total of 6 materials, one of which is a Al18Si alloy base, while the other materials are composites obtained by addition of 10 wt.% SiC (30 µm) and 1 wt.% or 3 wt.% Gr (17 µm or 200–800 µm). Within the B series of materials, there were a total of 8 materials, i.e. the alloy base and 7 composites. The composites of this series were obtained by addition of 0.5 wt.% Al2O3 (20–30 nm) and/or 3 wt.% Al2O3 (36 µm) and/or 3 wt.% SiC (40 µm) and/or 3 wt.% Gr (250–500 µm). Before the tribological tests, the microstructural characterization was performed, as well as the hardness and density measurements of the mentioned materials. Tribological tests were performed under lubricated sliding conditions at a sliding speed of 0.5 m/s, sliding distance of 1000 m and a normal load of 100 N, 200 N and 300 N. Considering that the series of materials in A showed better characteristics, tribological tests were conducted for this material series on apparatus with linear reciprocating motion and the same test conditions. After the tribological analysis, Taguchi-grey and artificial neural networks (ANN) optimization methods were applied to predict the behavior of wear rate and coefficient of friction for both series of materials. The optimal combination of parameters was obtained and the percentage influence of the observed factors on the wear rate and coefficient of friction was obtained by analysis of variance (ANOVA). At the end of the research, a numerical finite element method (FEM) analysis of the piston was performed at a pressure of 7.5 MPa and temperatures from 300°C to 400°C. During the FEM analysis, the highest stresses were on the inside of the piston head and at the bearing of the piston pins, and it was proven that the tested composites can be used for the production of pistons.

kompozit, aluminijum, nadeutektička Al18Si legura, optimizacija, veštačke neuronske mreže, Taguči-grej, habanje, trenje, klip.

composite, aluminum, hypereutectic Al18Si alloy, optimization, artificial neural networks, Taguchi-grey, wear, friction, piston

620.178.1:621.8(043.3)

Kompozitni materijali - Klipni motori - Tribološka ispitivanja

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