Browsing by Author "Nguyen, Bao Kha"

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    Control of supercritical organic Rankine cycle based waste heat recovery system using conventional and fuzzy self-tuned PID controllers
    (Springer, 2019-08-19) Chowdhury, Jahedul Islam; Thornhill, David; Soulatiantork, Payam; Hu, Yukun; Balta-Ozkan, Nazmiye; Varga, Liz; Nguyen, Bao Kha
    This research develops a supercritical organic Rankine cycle (ORC) based waste heat recovery (WHR) system for control system simulation. In supercritical ORC-WHR systems, the evaporator is a main contributor to the thermal inertia of the system, which is greatly affected by transient heat sources during operation. In order to capture the thermal inertia of the system and reduce the computation time in the simulation process, a fuzzy-based dynamic evaporator model was developed and integrated with other component models to provide a complete dynamic ORC-WHR model. This paper presents two control strategies for the ORC-WHR system: evaporator temperature control and expander output control, and two control algorithms: a conventional PID controller and a fuzzy-based self-tuning PID controller. The performances of the proposed controllers are tested for set point tracking and disturbance rejection ability in the presence of steady and transient thermal input conditions. The robustness of the proposed controllers is investigated with respect to various operating conditions. The results show that the fuzzy self-tuning PID controller outperformed the conventional PID controller in terms of set point tracking and disturbance rejection ability at all conditions encountered in the paper.
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    ItemOpen Access
    Fuzzy nonlinear dynamic evaporator model in supercritical organic Rankine cycle waste heat recovery systems
    (MDPI, 2018-04-11) Chowdhury, Jahedul Islam; Nguyen, Bao Kha; Thornhill, David; Hu, Yukun; Soulatiantork, Payam; Balta-Ozkan, Nazmiye; Varga, Liz
    The organic Rankine cycle (ORC)-based waste heat recovery (WHR) system operating under a supercritical condition has a higher potential of thermal efficiency and work output than a traditional subcritical cycle. However, the operation of supercritical cycles is more challenging due to the high pressure in the system and transient behavior of waste heat sources from industrial and automotive engines that affect the performance of the system and the evaporator, which is the most crucial component of the ORC. To take the transient behavior into account, the dynamic model of the evaporator using renowned finite volume (FV) technique is developed in this paper. Although the FV model can capture the transient effects accurately, the model has a limitation for real-time control applications due to its time-intensive computation. To capture the transient effects and reduce the simulation time, a novel fuzzy-based nonlinear dynamic evaporator model is also developed and presented in this paper. The results show that the fuzzy-based model was able to capture the transient effects at a data fitness of over 90%, while it has potential to complete the simulation 700 times faster than the FV model. By integrating with other subcomponent models of the system, such as pump, expander, and condenser, the predicted system output and pressure have a mean average percentage error of 3.11% and 0.001%, respectively. These results suggest that the developed fuzzy-based evaporator and the overall ORC-WHR system can be used for transient simulations and to develop control strategies for real-time applications.
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    ItemOpen Access
    Simulation of waste heat recovery system with fuzzy based evaporator model
    (IEEE, 2018-02-08) Chowdhury, Jahedul I.; Soulatiantork, Payam; Nguyen, Bao Kha
    The organic Rankine cycle (ORC) is one of the promising waste heat recovery (WHR) technologies used to improve the thermal efficiency, reduce the emissions and save the fuel costs of internal combustion engines. In the ORC-WHR system, the evaporator is considered to be the most critical component as the heat transfer of this device influences the efficiency of the system. Although the conventional Finite Volume (FV) model can successfully capture the complex heat transfer process in the evaporator, the computation time for this model is high as it consists of many iterative loops. To reduce the computation time, a new evaporator model using the fuzzy inference technique is developed in this research. The developed fuzzy based model can predict the evaporator outputs with an accuracy of over 90% while it reduces the simulation time significantly. This model is then integrated with other components of the ORC to simulate a completed ORC-WHR system for internal combustion engines. The influence of operating parameters on the performance of the WHR system is investigated in this paper.