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 ORC-WHR 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.
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