Ventilation system with automatic flow balancing derived from a neural network and methods of use
A ventilation system with automatic flow balancing derived from a neural network to consistently achieve a desired flow rate for inlet flow and/or outlet flow in various operating environments to optimize system performance. The system includes a ventilation device that includes an exhaust blower assembly with a blower motor and a control circuit having a mathematical equation that determines an estimated exhaust blower flow based upon select inputs. The ventilation device also includes a supply blower assembly with a blower motor and control circuit having a mathematical equation that determines an estimated supply blower flow based upon select inputs. When the estimated exhaust blower flow is different than an exhaust flow set point, the exhaust control circuit selectively alters power supplied to the exhaust motor. When the estimated supply blower flow is different than a supply flow set point, the supply control circuit selectively alters power supplied to the supply motor.
1. A ventilation device comprising:
a blower assembly having a blower motor and a control circuit, said control circuit programmed with a mathematical equation;
wherein the control circuit is capable of replacing the mathematical equation with an updated mathematical equation received from a remote location; and
wherein the updated mathematical equation is configured to determine an estimated blower air flow for the blower assembly based upon the following inputs: (i) parameters that are derived from the use of a neural network, (ii) a blower motor speed of the blower motor, and (iii) a blower motor current of the blower motor.
2. The ventilation device of claim 1 , wherein the estimated blower air flow is within 5% of an air flow rate generated by the blower motor.
3. The ventilation device of claim 1 , wherein the ventilation device is selected from a group of ventilation devices consisting of: (i) heat recovery ventilator, (ii) energy recovery ventilator, (iii) range hood, (iv) bathroom exhaust fan, and (v) supply fan.
4. The ventilation device of claim 1 , further comprising a damper operably associated with the blower assembly, the damper having a plurality of positional settings; and
wherein the updated mathematical equation is further configured to utilize the positional setting of the damper in determining the estimated blower air flow for the blower assembly.
5. The ventilation device of claim 1 , wherein the control circuit further includes a current limit for the blower motor; and
wherein a warning is provided to a user when an air flow set point is set to a value that requires current supplied to the blower motor to be greater than the current limit.
6. The ventilation device of claim 1 , wherein when the estimated blower air flow is different than an air flow set point, the control circuit is configured to selectively alter current supplied to the blower motor in order equate the estimated blower air flow equal and the air flow set point.
7. The ventilation device of claim 6 , wherein the ventilation device is installed in an operating environment, and the control circuit is configured to modify the air flow set point A based upon information received about a volume of air added or removed from the operating environment.
8. The ventilation device of claim 6 , wherein the control circuit is configured to modify the air flow set point based upon the information received from an indoor air quality controller.
9. The ventilation device of claim 1 , wherein the blower assembly is an exhaust blower assembly, the blower motor is an exhaust blower motor, the control circuit is an exhaust control circuit, the parameters of the blower motor are exhaust air path parameters, and the estimated blower air flow is an estimated exhaust blower air flow; and
wherein the ventilation device further includes:
a supply blower assembly having a supply blower motor and a supply control circuit, said supply control circuit is programmed with a supply mathematical equation, and
wherein the supply mathematical equation determines an estimated supply blower air flow for the supply blower assembly based upon the following inputs: (i) supply air path parameters derived from the use of a supply neural network, (ii) a supply blower motor speed of the supply blower motor, and (ii) a supply blower motor current of the supply blower motor.
10. A ventilation device configured to generate an air flow and comprising:
a blower assembly having a blower motor and a control circuit, wherein said control circuit is programmed with a mathematical equation;
wherein the ventilation device is capable of receiving an updated mathematical equation derived from the use of a neural network; and
wherein the control circuit is capable of replacing the mathematical equation with the updated mathematical equation.
11. The ventilation device of claim 10 , wherein the updated mathematical equation includes a plurality of parameters that are outputs of the neural network, and wherein said neural network was trained using measurements recorded at various operating points of the blower assembly.
12. The ventilation device of claim 10 , wherein the updated mathematical equation is configured to determine an estimated blower air flow for the blower assembly.
13. The ventilation device of claim 12 , wherein when the estimated blower air flow is different than an air flow set point, the control circuit is configured to selectively alter power supplied to the blower motor in order to equate the estimated blower air flow equal and the air flow set point.
14. The ventilation device of claim 13 , wherein the ventilation device is installed in an operating environment, and the control circuit is configured to modify the air flow set point based upon information received about a volume of air added or removed from the operating environment.
15. The ventilation device of claim 13 , wherein the control circuit is configured to modify the air flow set point based upon information received from an indoor air quality controller.
16. The ventilation device of claim 12 , wherein the estimated blower air flow is within 5% of an air flow rate generated by the blower motor.
17. A method of estimating air flow of a ventilation device using a control circuit of the ventilation device, the method comprises:
uploading an original mathematical equation to the control circuit of the ventilation device;
generating an updated mathematical equation using a neural network;
transmitting the updated mathematical equation to the control circuit of the ventilation device;
replacing the original mathematical equation with the updated mathematical equation; and
calculateing an estimated air flow of a blower assembly of the ventilation device using the updated mathematical equation.
18. The method of claim 17 , wherein the neural network was trained using measurements recorded at various operating points of the blower assembly.
19. The method of claim 17 , further comprising the step of modifying power supplied to a blower motor of the blower assembly in order to equate the estimated air flow and an air flow set point.
20. The method of claim 17 , wherein the blower assembly is installed in an operating environment; and
further comprising the step of modifying an air flow set point of the blower assembly based upon information received about a volume of air added or removed from the operating environment.
21. The method of claim 17 , further comprising the step of modifying an air flow set point of the blower assembly based upon information received from an indoor air quality controller.
22. The method of claim 17 , wherein the estimated air flow is within 5% of an air flow rate generated by the blower assembly.