US 11,732,967 B2
Heat exchanger system with machine-learning based optimization
Yohann Lilian Rousselet, Boston, MA (US); and Ellie M. Litwack, Columbia, MD (US)
Assigned to Baltimore Aircoil Company, Inc., Jessup, MD (US)
Filed by Baltimore Aircoil Company, Inc., Jessup, MD (US)
Filed on Dec. 11, 2020, as Appl. No. 17/118,818.
Claims priority of provisional application 62/946,778, filed on Dec. 11, 2019.
Prior Publication US 2021/0180891 A1, Jun. 17, 2021
Int. Cl. F28C 1/14 (2006.01); G05B 13/04 (2006.01); G05B 13/02 (2006.01); F28D 5/00 (2006.01); F28F 27/00 (2006.01); F24F 11/70 (2018.01); F24F 140/60 (2018.01)
CPC F28C 1/14 (2013.01) [F24F 11/70 (2018.01); F28D 5/00 (2013.01); F28F 27/003 (2013.01); G05B 13/0265 (2013.01); G05B 13/042 (2013.01); F24F 2140/60 (2018.01); G05B 2219/2639 (2013.01); G05B 2219/31264 (2013.01)] 55 Claims
OG exemplary drawing
 
1. A heat exchanger system comprising:
a cooling system comprising:
a heat generating apparatus configured to transfer heat to a process fluid;
a heat rejection apparatus configured to remove heat from the process fluid;
a sensor configured to detect a variable of the cooling system at a first time;
processor circuitry operably coupled to the sensor and configured to provide the variable and a plurality of potential operating parameters for operating the cooling system at a second time to a machine learning model representative of the cooling system to estimate at least one of energy consumption, water usage, and chemical usage of the cooling system for each of the potential operating parameters;
the processor circuitry configured to determine, based at least in part on the estimated at least one of energy consumption, water usage, and chemical consumption for the potential operating parameters, an optimal operating parameter of the cooling system to satisfy a target optimization criterion; and
the processor circuitry configured to cause the cooling system to utilize the optimal operating parameter as the cooling system operates at the second time.