The present study is to examine the performance and emission characteristics of a Homogeneous Charge Compression Ignition (HCCI) engine where hydrous methanol (85% methanol and 15% water) is used as primary fuel and Diethyl ether (DEE) as an ignition improver. A modified diesel engine has been used as a HCCI engine. By measuring the excess air ratio (λDEE), the quantity of DEE flow rate is measured and excess air ratio (fiDEE) is varied from fiDEE5.6 to fiDEE 9.5. Experimental results reveal that HCCI engine gives better brake thermal efficiency (BTE) at high loads (λDEE 9.5). It shows decrease in oxides of nitrogen (NOx) emission, slightly high emission of carbon monoxide (CO) and unburned hydrocarbon (HC) compared to conventional compression ignition (CI) engine. Radial basis function neural network (RBFN) model has been developed with brake power, excess air ratio and energy share as input and BTE, CO, HC, NOx, rate of pressure rise as output. About 80% of total experimental data is used for training purposes, and 20% is used for testing. The performance of the developed RBFN model were compared with experimental data, and were statistically evaluated which was found to be in good agreement.
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