Supercritical pressure regulation of vapor compression system by regulation of adaptive control

• US 20040050080A1
• Filed: 09/05/2003
• Published: 03/18/2004
• Est. Priority Date: 09/05/2003
• Status: Active Grant

• Current Assignee: Carrier Corporation (Carrier Global Corporation)
• Original Assignee: Carrier Corporation (Carrier Global Corporation)
• Inventors: Park, Christopher G., Kang, Pengju P.K., Eisenhower, Bryan, Sienel, Tobias, Finn, Alan
• Granted Patent: US 6,813,895 B2
• Time in Patent Office: Days
• US Class Current: 62/190
• CPC Class Codes: C08F 2/46 Polymerisation initiated by wave energy or particle radiation
• CPC Class Codes: C09J 4/00 Adhesives based on organic non-macromolecular compounds having at least one polymerisable carbon-to-carbon unsaturated bond ; adhesives, based on monomers of macromolecular compounds of groups C09J183/00 - C09J183/16
• CPC Class Codes: F25B 2309/061 with cycle highest pressure above the supercritical pressure
• CPC Class Codes: F25B 2600/17 by controlling the pressure of the condenser
• CPC Class Codes: F25B 49/02 for compression type machines, plants or systems
• CPC Class Codes: F25B 9/008 the refrigerant being carbon dioxide
• CPC Class Codes: G05D 16/2066 using controlling means acting on the pressure source

Abstract

A vapor compression system includes a compressor, a gas cooler, an expansion device, and an evaporator. Refrigerant is circulated through the closed circuit cycle. Preferably, carbon dioxide is used as the refrigerant. Adaptive control is employed to optimize the coefficient of performance of the vapor compression system. As the system changes over time, a model that operates the system is modified. The model is determined by an adaptive control algorithm including variable coefficients. As the model changes, the variables of the adaptive control algorithm change. A control of the gas cooler is then adjusted to regulate the high pressure of the system, and therefore the coefficient of performance. In a first example, Least Mean Squares (LMS) is used to modify the variables of the adaptive control algorithm to optimize the coefficient of performance. In a second example, the coefficient of performance is optimized by a slowly varying periodic excitation method. A third example employs triangularization to find the optimal coefficient of performance.

Claims

1. A method of regulating a high pressure of a transcritical vapor compression system comprising the steps of:

(a) operating the system based on a model; and

(b) adapting said model to obtain a desired high pressure of the transcritical vapor compression system.

2. The method as recited in claim 1 further including the steps of:

(c) compressing a refrigerant to said high pressure;

(d) cooling said refrigerant;

(e) expanding said refrigerant; and

(f) evaporating said refrigerant.

3. The method as recited in claim 2 further including the steps of:

(g) controlling a flow of said refrigerant through the step of cooling; and

(h) adjusting the step of controlling said flow to obtain said desired high pressure.

4. The method as recited in claim 2 wherein said refrigerant is carbon dioxide.

5. The method as recited in claim 1 wherein said desired high pressure obtains a maximum coefficient of performance.

6. The method as recited in claim 1 further including the steps of:

(c) exciting the system with an excitation signal to generate a system output; and

(d) comparing said system output to a model output of said model.

7. The method as recited in claim 6 wherein an adaptive control algorithm having variable coefficients operates said model, and the step of adapting said model includes modifying said variable coefficients such that said model output of said model substantially equals said system output of the system.

8. The method as recited in claim 7 wherein the step of comparing the system output to said model output determines a system identification error.

9. The method as recited in claim 8 wherein the step of adapting said model includes employing said system identification error.

10. The method as recited in claim 1 wherein the step of adapting the model further includes the steps of:

1) sinusoidally exciting the system to generate a response;

2) filtering said response to generate a harmonic response;

3) multiplying said harmonic response by said excitation signal to demodulate said harmonic response to a demodulated harmonic response;

4) filtering an oscillation factor from said demodulated harmonic response to separate a static gain; and

5) utilizing said static gain as a new excitation signal.

11. The method as recited in claim 1 wherein the step of adapting the model further includes the steps of:

1) establishing a left input point, a right input point, and a middle input point therebetween;

2) determining a coefficient of performance for said left input point, said right input point, and said middle input point;

3) determining a left middle coefficient of performance of a left middle input point between said left input point and said middle input point and determining a right middle coefficient of performance of a right middle input point between said right input point and said middle input point;

4) comparing said left coefficient of performance and said right coefficient;

5) determining which of said left coefficient of performance and said right coefficient of performance is a greater value;

6) utilizing said greater value as a new middle input point; and

7) repeating step

     1) to step

     5) employing said new middle input point as said middle input point.