Prediction of Waste Heat Energy Recovery Performance in a Naturally Aspirated Engine Using Artificial Neural Network | Zendy

Safarudin Gazali Herawan | Zendy; Abdul Hakim Rohhaizan | Zendy; Azma Putra | Zendy; Ahmad Faris Ismail | Zendy

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Prediction of Waste Heat Energy Recovery Performance in a Naturally Aspirated Engine Using Artificial Neural Network

Author(s) -

Safarudin Gazali Herawan,

Abdul Hakim Rohhaizan,

Azma Putra,

Ahmad Faris Ismail

Publication year - 2014

Publication title -

isrn mechanical engineering

Language(s) - English

Resource type - Journals

eISSN - 2090-5130

pISSN - 2090-5122

DOI - 10.1155/2014/240942

Subject(s) - artificial neural network , naturally aspirated engine , waste heat recovery unit , heat engine , spark ignition engine , waste heat , ignition system , automotive engineering , energy recovery , thermal energy , power (physics) , process engineering , environmental science , energy (signal processing) , engineering , computer science , mechanical engineering , internal combustion engine , exhaust gas recirculation , heat exchanger , artificial intelligence , thermodynamics , aerospace engineering , statistics , physics , mathematics

The waste heat from exhaust gases represents a significant amount of thermal energy, which has conventionally been used for combined heating and power applications. This paper explores the performance of a naturally aspirated spark ignition engine equipped with waste heat recovery mechanism (WHRM). The experimental and simulation test results suggest that the concept is thermodynamically feasible and could significantly enhance the system performance depending on the load applied to the engine. The simulation method is created using an artificial neural network (ANN) which predicts the power produced from the WHRM.

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