Experimental Research on Heat Exchanger Control Based on Hybrid Time and Frequency Domain Identification

Abstract

Abstract:A heat exchanger is widely used for energy management or heat recovery in sustainable energy systems. In many application cases, the outlet temperature should be strictly controlled as desired. However, it is challenging to obtain an accurate dynamic model due to the high-order dynamics, thus reducing the control performance. To this end, this paper proposes a novel identification method by considering the heating process as an approximate second-order plus time delay (SOPDT) model. A normalized analysis indicates that the time-scaled step responses of the general second-order models almost intersect at the same point, which leads to an equation describing the sum of the time constants. Critical stability analysis based on the Nyquist criterion gives another two equations in the frequency domain. Hence the time constants and time delay can be obtained by solving the equations. Illustrative examples show the identification efficiency of the proposed method in the parameter estimation, model reduction, and anti-noise performance. With an effective identification, the high-fidelity SOPDT model makes the PID controller tuning less challengeable. The simulation results based on a benchmark heat exchanger model demonstrate the feasibility of the identification and control. Finally, a real heat exchanger control facility is built and the experimental performance agrees well with the simulation expectation, depicting a promising application prospect in future sustainable applications.

An Approximate Transfer Function Model for a Double-Pipe Counter-Flow Heat Exchanger

“…The steady-state temperature profiles can be calculated by assuming the time derivatives in Equations ( 1)-(3) equal to zero, and solving the resulting boundary value problem with the boundary conditions (6) given by the constant inlet temperatures of both fluids, θti and θsi (see [14,15]).…”

“…The above-mentioned feature is, in turn, typical of the system representation in the form of a transfer function G(s), which is commonly used, e.g., in signal processing and control systems engineering [1,2]. Transfer functions for the heat exchange processes are often given in the literature by very simple models, such as first or second order with or without time delay [3][4][5][6]. Some other authors consider more sophisticated, irrational transfer function models resulting from the PDEs describing the heat exchange phenomena [7][8][9][10][11][12][13][14].…”

Environmental Health Oriented Optimal Temperature Control for Refrigeration Systems Based on a Fruit Fly Intelligent Algorithm

“…With the merits of simplicity and reliability, PID controllers are still widely used for industrial process control [25,26,27]. The control equation of a PID controller is shown in (5):u(t)=Kpe(t)+Kitrue∫e(t)+Kdde(t)dt where u ( t ) is the control action, K p , K i , K d are the proportional, integral and derivative gain respectively, and e ( t ) is the tracking error.…”

Parameter identification of a delayed infinite-dimensional heat-exchanger process based on relay feedback and root loci analysis

“…For instance, a case study on an autotuning control method for a cross-flow heat exchanger was published in 87 . Jin et al 88 presented a Ziegler-Nichols-based method based on using the ultimate gain (instead of on a nonlinear element) to get the sustained oscillations. Some researchers use nonlinear models such as Wiener-type or Hammerstein-type 89 .…”