Simulation of waste heat recovery system with fuzzy based evaporator model

Chowdhury, J I, Soulatiantork, P and Nguyen, B K (2017) Simulation of waste heat recovery system with fuzzy based evaporator model. The 2017 Asian Control Conference - ASCC 2017, Gold Coast, Australia, 17-20 December 2017. Published in: 2017 11th Asian Control Conference (ASCC). 2143-2147. ISBN 9781509015733

[img] PDF - Accepted Version
Available under License All Rights Reserved.

Download (561kB)

Abstract

The organic Rankine cycle (ORC) is one of the promising waste heat recovery (WHR) technologies used to improve the thermal efficiency, reduce the emissions and save the fuel costs of internal combustion engines. In the ORCWHR system, the evaporator is considered to be the most critical component as the heat transfer of this device influences the efficiency of the system. Although the conventional Finite Volume (FV) model can successfully capture the complex heat transfer process in the evaporator, the computation time for this model is high as it consists of many iterative loops. To reduce the computation time, a new evaporator model using the fuzzy inference technique is developed in this research. The developed fuzzy based model can predict the evaporator outputs with an accuracy of over 90% while it reduces the simulation time significantly. This model is then integrated with other components of the ORC to simulate a completed ORC-WHR system for internal combustion engines. The influence of operating parameters on the performance of the WHR system is investigated in this paper.

Item Type: Conference Proceedings
Schools and Departments: School of Engineering and Informatics > Engineering and Design
Research Centres and Groups: Dynamics, Control and Vehicle Research Group
Subjects: T Technology > TJ Mechanical engineering and machinery
T Technology > TK Electrical engineering. Electronics Nuclear engineering
T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL0001 Motor vehicles.Cycles
Related URLs:
Depositing User: Bao Kha Nguyen
Date Deposited: 02 May 2018 09:21
Last Modified: 02 May 2018 16:17
URI: http://sro.sussex.ac.uk/id/eprint/75082

View download statistics for this item

📧 Request an update