The present disclosure relates generally to electric motor and controller assemblies for blower systems (also referred to as air handler systems) and other fluid handling systems.
The statements in this section merely provide background information related to the present disclosure and may not constitute prior art.
Heating, ventilation and/or air conditioning (“HVAC”) systems commonly employ blower systems for moving air. These blower systems typically include a fan (such as a squirrel cage fan), an electric motor for driving rotation of the fan, and a controller for the electric motor. In some systems, the controller receives an air flow demand from a system controller, such as a thermostat, and converts the air flow demand into a motor torque demand. The controller then produces drive signals for the motor that are intended to produce the demanded torque so as to produce the demanded air flow. Thus, to accurately produce the demanded air flow in such systems, the controller must accurately convert the air flow demand into a corresponding torque demand.
A variety of schemes are known for converting air flow demands into torque demands. For example, U.S. Pat. No. 4,978,896 provides a multiple slope algorithm for maintaining desired airflow rate over a range of static pressures. In particular, different torque demand equations with different slopes are used depending upon the speed of the motor. At low speeds, torque is directly proportional to the square of the desired airflow rate. At speeds above the maximum operating speed, torque is reduced using a different equation, etc.
U.S. Pat. No. 5,447,414 presents another method for producing a torque demand from an airflow demand in accordance with the formula: Torque=K1*S*CFM+K2*S+K3*CFM+K4, where S is the speed of the motor, CFM is the demanded airflow, and K1, K2, K3 and K4 are coefficients relating to a particular blower system.
Most known methods require data to be collected in some form to establish a relation between torque, speed and airflow. The collected torque, speed and airflow data is then fitted, either linearly or using multiple slope methods as in U.S. Pat. No. 4,978,896, or by using a torque equation as in U.S. Pat. No. 5,447,414, to find the coefficients K1, K2, K3 and K4.
Although these known schemes are suitable for certain applications, improvements are needed to minimize prediction errors when converting an air flow demand (or another fluid flow demand) into a torque demand.
The present inventors have succeeded in reducing prediction errors when converting a fluid flow demand, such as an air flow demand, into a torque demand by introducing a term in the torque equation that includes the composite function S*(FFD)n, where S is a speed of the electric motor, FFD is the fluid flow demand, and n>1.
According to one aspect of this disclosure, a controller for an electric motor in a blower system includes an input for receiving an air flow demand. The controller is configured for producing drive signals for the electric motor from the air flow demand using an equation having a plurality of terms. At least one of the terms includes a composite function S*CFMn, where S is a speed of the electric motor, CFM is the air flow demand, and n>1.
According to another aspect of this disclosure, a method of controlling an electric motor in a blower system includes receiving an air flow demand, and producing drive signals for the electric motor from the air flow demand using an equation having a plurality of terms. At least one of the terms includes a composite function S*CFMn, where S is a speed of the electric motor, CFM is the air flow demand, and n>1.
According to yet another aspect of this disclosure, a motor assembly for a blower system includes an electric motor and a controller. The controller has an input for receiving an air flow demand. The controller is configured for converting the air flow demand into a torque demand for the electric motor using an equation having a plurality of terms, at least one of the terms including a composite function S*CFMn, and for producing drive signals for the electric motor corresponding to the torque demand, where S is a speed of the electric motor, CFM is the air flow demand, and n>1.
According to still another aspect of this disclosure, a controller for an electric motor in fluid handling system includes an input for receiving a fluid flow demand. The controller is configured for producing drive signals for the electric motor from the fluid flow demand using an equation having a plurality of terms. At least one of the terms includes a composite function S*(FFD)n, where S is a speed of the electric motor, FFD is the fluid flow demand, and n>1.
Further areas of applicability will become apparent from the description provided herein. It should be understood that the description and specific examples are provided for purposes of illustration only and are not intended to limit the scope of the present disclosure.
The drawings described herein are for illustration purposes only and are not intended to limit the scope of the present disclosure in any way.
The following description is merely exemplary in nature and is not intended to limit the present disclosure, its applications, or uses.
A blower system according to one embodiment of this disclosure is illustrated in
As further illustrated in
Although not shown in
While the controller 102, the drive 104 and the motor 106 are illustrated as physically separate components in
Torque=K1+K2*S+K3*CFM+K4*S*CFM2, where S represents motor speed and CFM represents the air flow demand 210 received by the air flow control module 214. K1-K4 are constants derived for a particular blower system (e.g., using test data and a least square regression analysis). In this particular embodiment, the last term of the equation includes the composite function S*CFMn, where n=2. It should be understood, however, that the CFM variable in this composite function can be raised to any power n, where n>1, without departing from the teachings of this disclosure.
Torque=K1+K2*S+K3*CFM+K4*S*CFM2+K5*S*CFM, where K1, K2, K3, K4 and K5 are constants derived for a particular blower system. Thus, in the embodiment of
The constants K1-K4 (or K1-K5) can be derived for a wide range of blower systems and provided to the controller 102 of
To solve for constants K1-K4, first a regression matrix X is made from T, S, CFM and S*CFM2 as follows:
Then, the coefficient matrix,
can be solved
where \ denotes left matrix division. As apparent to those skilled in matrix solving, the solution to this can be achieved using Gaussian Elimination technique. The coefficients calculated for the above example using Gaussian Elimination are as follows: K1=−341.8516; K2=1.8455; K3=1.1298; K4=0.7854.
To validate the model, one can calculate the errors (including prediction errors) by subtracting the calculated torque demand from the actual torque demand at a particular airflow rate. The errors for the particular blower system in the above example are plotted in
As apparent to those skilled in the art, the control modules illustrated generally in
Although various blower system embodiments have been described above, it should be understood that the teachings of this disclosure can also be applied to other types of fluid handling systems including, for example, air and liquid pumps.
A fluid handling system 600 according to another embodiment of this disclosure is illustrated in
Exemplary systems and methods for controlling the output torque and/or speed of an electric motor using sensors or sensorless techniques are described in U.S. application Ser. No. 11/293,743 filed Dec. 2, 2005 for Control Systems and Methods for Permanent Magnet Rotating Machines, and U.S. application Ser. No. 11/293,744 filed Dec. 2, 2005 for Sensorless Control Systems and Methods for Permanent Magnet Rotating Machines. The entire disclosures of these applications are incorporated herein by reference.
Number | Name | Date | Kind |
---|---|---|---|
4638233 | Erdman | Jan 1987 | A |
4806833 | Young | Feb 1989 | A |
4978896 | Shah | Dec 1990 | A |
5019757 | Beifus | May 1991 | A |
5447414 | Nordby et al. | Sep 1995 | A |
5692385 | Hollenbeck et al. | Dec 1997 | A |
5736823 | Nordby et al. | Apr 1998 | A |
5818194 | Nordby | Oct 1998 | A |
7208895 | Marcinkiewicz et al. | Apr 2007 | B2 |
7246997 | Liu et al. | Jul 2007 | B2 |
20030011342 | Eichorn | Jan 2003 | A1 |
20030042860 | Sulfstede | Mar 2003 | A1 |
20050280384 | Sulfstede | Dec 2005 | A1 |
20060265890 | Solan et al. | Nov 2006 | A1 |
20060290302 | Marcinkiewicz et al. | Dec 2006 | A1 |
20060290304 | Marcinkiewicz et al. | Dec 2006 | A1 |
20070170880 | Shahi et al. | Jul 2007 | A1 |
Number | Date | Country | |
---|---|---|---|
20070248467 A1 | Oct 2007 | US |