Unsteady analysis of a bottoming Organic Rankine Cycle for exhaust heat recovery from an Internal Combustion Engine using Monte Carlo simulation

An optimization model is developed to maximize the net power output of a bottoming Organic Rankine Cycle (ORC) with ten working fluids for exhaust heat recovery from an Internal Combustion Engine (ICE) theoretically. The ICE-ORC system is influenced by several unsteady parameters which make it difficult to determine the optimal design parameters. Therefore, we introduce probability density functions in order to investigate the impacts of the ICE power output, the sink temperature and the pinch point temperature difference on the ORC performances. Each unsteady parameter is illustrated to analyze the performances of the ICE-ORC system. Furthermore, Monte Carlo simulation is introduced to investigate the role played by the unsteady parameters, each of which obeys different probability distributions. By these methods, we obtained the convergence values, the frequency distributions and the cumulative probability distributions of various performance parameters. These results can provide valuable suggestions for the design of ICE-ORC system.