A Look-ahead Model Predictive Control Strategy for an Organic Rankine Cycle - Waste Heat Recovery System in a Heavy Duty Diesel Engine Application 2019-01-1130
The Organic Rankine Cycle (ORC) is a promising technology for Waste Heat Recovery (WHR) systems in heavy-duty diesel engine applications. However, due to the time varying nature of the heat source, real-time control of the working fluid flow through the ORC system is challenging. If the transient heat source trajectory can be determined in advance, then predictive control strategies can potentially enhance the WHR power harvest. This work couples an experimentally validated and ORC system models to quantify potential WHR energy harvesting enhancements via look-ahead control implementation.
It is assumed that the future vehicle speed can be predicted utilizing road topography and V2V connectivity for utilization with a look-ahead non-linear model predictive (NMPC) ORC control design. This vehicle speed is then used to predict both engine speed and torque, which allows estimation of ORC relevant exhaust conditions. In this simulation study, a reference tracking controller is design based on the Model Predictive Control (MPC) methodology. Two variants of NMPC are evaluated: an NMPC with a look-ahead exhaust conditions and a baseline NMPC without knowledge of future exhaust conditions. Initial look-ahead NMPC simulation results exhibit evaporator outlet working fluid temperature variation reduction and a reduction in controller overshoot during a step-change in heat source power. Furthermore, the NMPC look-ahead period is optimized and a sensitivity study for the estimated exhaust conditions is evaluated to understand the necessary engine model accuracy for exhaust condition prediction based on the look-ahead period.
Dhruvang Rathod, Bin Xu, Adamu Yebi, Ardalan Vahidi, Zoran Filipi, Mark Hoffman