Experimental Evaluation Of Evaporator Thermal Inertia For An Optimal Control Strategy Of An Organic Rankine Cycle Waste Heat Recovery System

Organic Rankine cycle (ORC) is considered to be a promising waste heat recovery (WHR) technique. In this article, the thermal inertia of an evaporator for an ORC system is evaluated. While the literature is rich in understanding open loop evaporator response, closed loop dynamic response with the controller is lacking. To understand the dynamic response of the evaporator, sinusoidal heat inputs with varying frequency are considered. A nonlinear model predictive control (NMPC) strategy is evaluated for a single evaporator experiencing this sinusoidal heat signal in both simulation and experimental cases. Experimental verification showed that the evaporator was most responsive to low-frequency sinusoidal heat signals. In such case, penalizing the control input helped in retaining the superheat tracking performance of the proposed NMPC.Further, while many studies have explored model predictive control (MPC) as a possible control strategy for an ORC-WHR system, none has exploited MPC's preview capability. In this study, the MPC's preview feature is utilized to investigate any potential benefits of knowing the future exhaust conditions. Simulations showed that utilizing knowledge of future exhaust conditions within the MPC preview is beneficial in minimizing control input variation and in minimizing superheat tracking errors for certain heat input frequency ranges.