Nonlinear Model Predictive Control Strategies for a Parallel Evaporator Diesel Engine Waste Heat Recovery System

2016 ◽  
Author(s):  
Adamu Yebi ◽  
Bin Xu ◽  
Xiaobing Liu ◽  
John Shutty ◽  
Paul Anschel ◽  
...  
Keyword(s):  
Diesel Engine ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Nonlinear Model ◽  
Pid Control ◽  
Heat Recovery ◽  
Waste Heat Recovery ◽  
Waste Heat ◽  
Nonlinear Model Predictive Control ◽  
Working Fluid

This paper discusses the control challenges of a parallel evaporator organic Rankine cycle (ORC) waste heat recovery (WHR) system for a diesel engine. A nonlinear model predictive control (NMPC) is proposed to regulate the mixed working fluid outlet temperature of both evaporators, ensuring efficient and safe ORC system operation. The NMPC is designed using a reduced order control model of the moving boundary heat exchanger system. In the NMPC formulation, the temperature difference between evaporator outlets is penalized so that the mixed temperature can be controlled smoothly without exceeding maximum or minimum working fluid temperature limits in either evaporator. The NMPC performance is demonstrated in simulation over an experimentally validated, high fidelity, physics based ORC plant model. NMPC performance is further validated through comparison with a classical PID control for selected high load and low load engine operating conditions. Compared to PID control, NMPC provides significantly improved performance in terms of control response time, overshoot, and temperature regulation.

Experimental Validation of Nonlinear Model Predictive Control for a Heavy-Duty Diesel Engine Waste Heat Recovery System

2020 ◽  
Vol 142 (5) ◽  
Author(s):  
Bin Xu ◽  
Adamu Yebi ◽  
Dhruvang Rathod ◽  
Simona Onori ◽  
Zoran Filipi ◽  
...  
Keyword(s):  
Predictive Control ◽  
Pid Control ◽  
Heat Recovery ◽  
Waste Heat Recovery ◽  
Experimental Validation ◽  
Waste Heat ◽  
Nonlinear Model Predictive Control ◽  
Working Fluid ◽  
Control Scheme ◽  
Vapor Temperature

Abstract This paper discusses an experimental validation of a real-time augmented control scheme for an organic Rankine cycle (ORC) waste heat recovery (WHR) system. A nonlinear model predictive control (NMPC) is designed to regulate the working fluid vapor temperature after the evaporator. The NMPC utilizes a six-state reduced order moving boundary (MB) evaporator model. The state estimator is constructed using an extended Kalman filter (EKF) given the working fluid outlet vapor temperature and exhaust gas outlet temperature as measurements. Working fluid evaporation pressure is controlled by an external proportional-integral-derivative (PID) control loop. The experimental validation first compares the performance of the augmented control scheme with that of a traditional multiple loop PID control with a feedforward term over an engine transient. The experimental study shows that the augmented control scheme outperforms the baseline multiloop PID control in both terms tracking error and settling time during transient engine operation. The performance of the augmented control scheme is further validated over three additional transient conditions with alterations to both the engine transient and the working fluid reference temperature. The NMPC validation shows that the working fluid vapor temperature can be controlled within 1% error margin relative to the targeted reference.

scholarly journals Nonlinear Model Predictive Control of an Organic Rankine Cycle for Exhaust Waste Heat Recovery in Automotive Engines

2015 ◽  
Vol 48 (15) ◽  
pp. 411-418 ◽  
Author(s):  
Marco Crialesi Esposito ◽  
Nicola Pompini ◽  
Agostino Gambarotta ◽  
Vetrivel Chandrasekaran ◽  
Junqiang Zhou ◽  
...  
Keyword(s):  
Predictive Control ◽  
Nonlinear Model ◽  
Heat Recovery ◽  
Waste Heat Recovery ◽  
Waste Heat ◽  
Organic Rankine Cycle ◽  
Rankine Cycle ◽  
Nonlinear Model Predictive Control ◽  
Automotive Engines ◽  
Exhaust Waste Heat

scholarly journals Model Predictive Control of Offshore Power Stations With Waste Heat Recovery

2016 ◽  
Vol 138 (7) ◽  
Author(s):  
Leonardo Pierobon ◽  
Richard Chan ◽  
Xiangan Li ◽  
Krishna Iyengar ◽  
Fredrik Haglind ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Control Systems ◽  
Predictive Control ◽  
Gas Turbines ◽  
Heat Recovery ◽  
Waste Heat Recovery ◽  
Oil And Gas ◽  
Waste Heat ◽  
Integral Control ◽  
Power Stations

The implementation of waste heat recovery units on oil and gas offshore platforms demands advances in both design methods and control systems. Model-based control algorithms can play an important role in the operation of offshore power stations. A novel regulator based on a linear model predictive control (MPC) coupled with a steady-state performance optimizer has been developed in the simulink language and is documented in the paper. The test case is the regulation of a power system serving an oil and gas platform in the Norwegian Sea. One of the three gas turbines is combined with an organic Rankine cycle (ORC) turbogenerator to increase the energy conversion efficiency. Results show a potential reduction of frequency drop up to 40% for a step in the load set-point of 4 MW, compared to proportional–integral control systems. Fuel savings in the range of 2–3% are also expected by optimizing on-the-fly the thermal efficiency of the plant.

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