Air conditioner, sensor system, and thermal sensation estimation method
US-2016363340-A1 · Dec 15, 2016 · US
US12137666B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12137666-B2 |
| Application number | US-202017761739-A |
| Country | US |
| Kind code | B2 |
| Filing date | Sep 22, 2020 |
| Priority date | Sep 22, 2019 |
| Publication date | Nov 12, 2024 |
| Grant date | Nov 12, 2024 |
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Systems and methods are provided for controlling heat stress and accumulations in livestock using the application of water sprays onto the animal in conjunction with fan induced airflow. The system has a controller with sensor inputs of the ambient environment including temperature, humidity, wind speed, and surrounding surface temperature sensors and fan and spray control outputs. To achieve savings in water and electricity, a transient, one-dimensional simultaneous heat and mass transfer model of evaporation within the wetted fur layer of a dairy cow is used to estimate drying time and heat rejection rate based on ambient conditions along with a control algorithm to predict the fan speed and sprinkler operation frequency needed to meet specified cooling load thresholds given the outdoor conditions. Estimated savings demonstrated that the model-based controller could reduce annual electricity and water consumption by 20% and 40%, respectively.
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What is claimed is: 1. An apparatus for controlling cooling of livestock, the apparatus comprising: (a) one or more input sensors selected from the group of sensors consisting of an air temperature sensor, a humidity sensor, a wind speed sensor, and a surrounding surface temperature sensor; (b) a processor configured to receive input from one or more of said input sensors; (c) a non-transitory memory storing instructions executable by the processor; and (d) a non-transitory memory storing a control algorithm that can be read by said processor; (e) wherein said instructions, when executed by the processor, perform one or more steps comprising: (i) using input from said one or more input sensors and said control algorithm, predicting heat transfer rate and drying time for a wet livestock; (ii) using the predicted heat transfer rate to control speed of a fan blowing air over livestock sprayed with water to ensure that a minimum cooling rate for the livestock is maintained; and (iii) using the predicted drying time to control frequency of said water spray to ensure that that the livestock is cooled without using more than water than is required to maintain the minimum cooling rate. 2. The apparatus of claim 1 , wherein said instructions when executed by said processor further perform one or more steps comprising calculating cumulative heat rejection rates over time and using weather forecast data to control said fan and water spray. 3. The apparatus of claim 1 , wherein said instructions comprise a control algorithm based on heat transfer rates and drying times calculated from best-fit correlations derived from a heat transfer model. 4. The apparatus of claim 1 , wherein said control algorithm comprises a lookup table or set of equations that select fan speed and water spray interval based on input from said one or more input sensors. 5. An apparatus for controlling water cooling of livestock, the apparatus comprising: (a) at least one fan with a fan speed producing an airflow; (b) at least one water sprayer with a flow rate; (c) one or more input sensors selected from the group of sensors consisting of a temperature sensor, a humidity sensor, a wind speed sensor, and a surrounding surface temperature sensor; (d) a controller with a processor configured to receive input from one or more of said input sensors and produce output control signals to said fan and said sprayer; and (e) a non-transitory memory storing instructions executable by the processor; (f) wherein said instructions, when executed by the processor, perform one or more steps comprising: (i) acquiring sensor data from said one or more input sensors; (ii) predicting a heat transfer rate and drying time of a subject from said sensor data; (iii) controlling sprayer actuation and sprayer duration to wet the subject; and (iv) controlling fan speed and airflow over a subject to transfer heat from the subject. 6. The apparatus of claim 5 , further comprising: a proximity sensor operably connected to the controller processor; wherein output control signals from the processor are not sent to the sprayer and fan unless the proximity sensor input indicates the proximity of the subject. 7. The apparatus of claim 5 , wherein said instructions when executed by the controller processor further perform steps comprising: calculating a minimum cooling rate; and increasing or decreasing the fan speed over time to ensure that the calculated minimum cooling rate for the subject is maintained. 8. The apparatus of claim 5 , wherein said instructions when executed by the controller processor further perform steps comprising: predicting a drying time for the subject; and matching a spray off time to the predicted drying time that corresponds to the current outdoor environmental conditions. 9. The apparatus of claim 8 , wherein said spray off time is matched with a selected percentage of the predicted drying time in the range of 50% to 100% of the predicted time. 10. The apparatus of claim 8 , wherein said drying time of the subject is predicted as a function of outdoor air temperature, air speed, humidity, and mean radiant temperature. 11. The apparatus of claim 5 , wherein said instructions when executed by said processor further perform one or more steps comprising: calculating cumulative heat rejection rates over time; and using weather forecast data to control said fan speed and water spray. 12. The apparatus of claim 5 , wherein said instructions when executed by said processor further perform one or more steps comprising: calculating cumulative heat rejection rates over time; calculating acquired heat load over time; and using calculated heat load and rejection rates to control said fan speed and water spray frequency. 13. The apparatus of claim 5 , wherein said instructions comprise a control algorithm based on heat transfer rates and drying times calculated from best-fit correlations derived from a heat transfer model. 14. The apparatus of claim 5 , wherein said control algorithm comprises a lookup table or set of equations that select fan speed and water spray interval based on input from said one or more input sensors. 15. The apparatus of claim 5 , wherein said instructions when executed by the controller processor further perform steps comprising: receiving sensor inputs at regular intervals; recalculating heat transfer rate and drying time at each interval; and modifying fan air speed and spray intervals from the recalculated heat transfer rate and drying time; wherein modifications of fan air speed and spray intervals over the course of the day accounts for changes in outdoor conditions. 16. A method for controlling heat stress in livestock, the method comprising: (a) providing outdoor air temperature, air speed, humidity, and mean radiant temperature sensor data; (b) predicting a heat rejection rate and drying time for a wet livestock from the sensor input; (c) calculating a cooling load threshold from the rejection rate and drying time; and (d) determining fan speed and sprinkler operation frequency needed to meet the cooling load threshold given the outdoor sensor data. 17. The method of claim 16 , further comprising: creating a one-dimensional simultaneous heat and mass transfer model of evaporation within wetted fur configured to estimate drying time and heat rejection rate based on ambient condition sensor data; and calculating the cooling load threshold from the rejection rate and drying time estimated by the model. 18. The method of claim 16 , further comprising: calculating a minimum cooling rate; and increasing or decreasing the fan speed over time to ensure that the minimum cooling rate for the livestock is maintained. 19. The method of claim 16 , further comprising: predicting a drying time for the livestock; and matching a spray off time to the predicted drying time that corresponds to the current outdoor environmental conditions. 20. The method of claim 19 , wherein said spray off time is matched with a selected percentage of the predicted drying time in the range of 50% to 100% of the predicted time. 21. The method of claim 16 , further comprising: receiving sensor inputs at regular intervals; recalculating heat transfer rate and drying time at each interval; and modifying fan air speed and spray intervals from the recalculated heat transfer rate and drying time; wherein modifications of fan air speed and spray intervals over the course of the day accounts for
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