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Model predictive control of an Organic Rankine Cycle system
Xiaobing Liu, Adamu Yebi, Paul Anschel, John Shutty, Bin Xu, Mark Hoffman, Simona Onori
Session: Session 1B: Dynamic Simulation
Session starts: Wednesday 13 September, 10:30
Presentation starts: 10:30
Room: Building 27 - Lecture room 02

Xiaobing Liu (BorgWarner Inc.)
Adamu Yebi ()
Paul Anschel ()
John Shutty ()
Bin Xu ()
Mark Hoffman ()
Simona Onori ()

Organic Rankine Cycle (ORC) waste heat recovery systems offer promising engine fuel economy improvements for heavy-duty on-highway trucks. An ORC test rig with parallel evaporators to recover both tailpipe and EGR waste heat from a 13L heavy duty diesel engine was developed and used in this work to demonstrate a novel control strategy based on Model-Predictive Control (MPC). The main control objectives for the ORC system are: (i) regulation of working fluid temperature, (ii) safe turbine operation - away from 2-phase region, and (iii) maximization of waste heat recovery. The MPC uses a built-in moving boundary evaporator model to predict future system response and generate optimal actuator reference commands. Two variants of MPC were considered in this work: an adaptive linear MPC (LMPC) and a nonlinear MPC (NPMC). Compared with the traditionally used PID controller, MPC demonstrates more accurate temperature control and improved disturbance rejection in simulation. Finally, the LMPC and NMPC controllers were implemented on the ORC test rig and showing promising initial test results.