The present disclosure relates to a heating, ventilation, and air conditioning (HVAC) system including a sensor system configured to detect heat indications within a plurality of areas of a conditioned space, wherein the sensor system comprise a thermal light detector, and a controller configured to receive feedback from the sensor system and, based on the feedback, control airflow distribution, via an airflow distribution system, such that airflow management for each of the plurality of areas is individually correlated to a heat indication detected for the respective area.

The subject matter of this specification can be embodied in, among other things, a method for time shifting when a cold storage facility is cooled that includes determining a thermal model of a cold storage facility, obtaining an energy cost model that describes a schedule of variable energy costs over a predetermined period of time in the future, determining an operational schedule for at least a portion of a refrigeration system based on the thermal model, the energy cost model, and a maximum allowed temperature, and powering on the portion the refrigeration system based on the operational schedule, cooling, by the powered portion of the refrigeration system to a temperature below the maximum allowed temperature, reducing power usage of the powered portion of the refrigeration system based on the operational schedule, and permitting the facility to be warmed by ambient temperatures toward the maximum allowed temperature.

An appliance hub for use in an upper portion of an enclosure can include a substrate configured to be positioned in an upper portion of an enclosure. The appliance hub can include a climate control apparatus mounted on the substrate and the climate control apparatus can be configured to regulate a temperature within the enclosure. The appliance hub can include one or more lighting elements configured to provide light within the enclosure, a plurality of fluid lines connected to the substrate and configured to provide fluid service and return to the climate control apparatus, and/or a plurality of electrical connections connected to the substrate and configured to provide electrical power and/or data to at least one of the climate control apparatus and the one or more lighting elements.

Systems and methods for controlling a heating Technologies for controlling a heating unit are disclosed. In embodiments, the systems and methods determine a heating unit target temperature based at least in part on a duty cycle of at least one thermostat. The systems and methods may then determine a simulated outdoor temperature corresponding to the heating unit target temperature, and a resistance value corresponding to the simulated outdoor temperature. The systems and methods may then cause a resistance signal including or indicative of the resistance value to be provided to an outdoor temperature input for the heating unit, e.g., to cause the heating unit to modulate to the heating unit target temperature.

Methods and apparatus for an autonomous stage-switching multi-stage cooling device are disclosed are disclosed. A disclosed example coolant distribution unit (CDU) includes an enclosure, an inlet and an outlet of the CDU to be fluidly coupled to a cooling block associated with a heat generating source, at least one sensor to measure a first temperature corresponding to the inlet and a second temperature corresponding to the outlet, and a plurality of valves to be controlled by a controller to control a flow of fluid from the inlet to at least one of an ambient cooler or a sub-ambient cooler based on: (i) a comparison of the first temperature to an ambient temperature and (ii) a comparison of the second temperature to a target temperature.

Personal thermal stability control herein provides for personalized temperature regulation dependent upon biometric sensor feedback, sleep stage, and so on, particularly for sleeping users, predicting and preemptively responding to fluctuations indicative of thermal stability, resulting from such things as transitions between sleep stages, hot flashes, night sweats, and general thermal instability. Specifically, in one embodiment, a system herein may comprise: an on-demand cooling system; one or more biometric sensors configured to monitor one or more corresponding indicators of thermal stability of a user; and a controller configured to: a) receive the one or more corresponding indicators of thermal stability of the user; b) predict an onset of a thermal instability of the user based on the one or more corresponding indicators of thermal stability of the user; and c) activate the on-demand cooling system to counteract the predicted onset of a thermal instability of the user.

A control method and a control system for temperature trajectory tracking are provided. The method includes: drawing a target temperature trajectory, discretizing the target temperature trajectory, and performing temperature trajectory control based on the discretized target temperature trajectory. The system includes a preset temperature trajectory processor for drawing a target temperature trajectory, a controlled object for characterizing an actual temperature, a platinum resistance sensor for detecting the actual temperature of the controlled object and inputting the actual temperature into a controller, and the controller for drawing an actual temperature trajectory, discretizing the target temperature trajectory, and operating a PID control program to complete temperature trajectory control. The traditional static constant temperature control can be realized, and close tracking of a preset temperature process trajectory in a second-level time level can be realized, thereby meeting requirements of application occasions with strict requirements on temperature change processes in a short time.

Systems and methods for characterization of retrofit opportunities are described. Some embodiments are directed to methods for determining the air leakage rate of a building, and accordingly, for determining suitability of sealing of air leaks to improve the energy efficiency of a building. The methods may comprise computing, using at least one computing device disposed remote from a building and based at least in part on heating, ventilation and air conditioning (HVAC) runtime data associated with the building, one or more thermal characteristics of the building. The HVAC runtime data may be computed based on data received from a thermostat or a meter, such as an electric or a gas meter. To isolate the impact of air leakage, subsets of the HVAC runtime data at time intervals selected to have substantially the same conditions, but different wind speeds, may be computed.

The present invention relates to a system with active learning and execution of user's preference functionalities for use in a garment. The present system includes a sensor module, an optional user input panel and/or interface, a printed circuit board, a power source and an output. In an event that a user of the present system voluntarily changes the output setting during the operation of the system, the system performs an active learning action to execute the output setting initiated by the user over a passive learning action triggered by a change in sensor data with respect to the changing environment. In other event, the present system performs passive learning action with respect to the changing environment and also any comparative data from similar user of a particular instance. The present invention also relates to a power management unit and how to use the same in a garment.

A thermostat for a building zone includes at least one of a model predictive controller and an equipment controller. The model predictive controller is configured to obtain a cost function that accounts for a cost of operating HVAC equipment during each of a plurality of time steps, use a predictive model to predict a temperature of the building zone during each of the plurality of time steps, and generate temperature setpoints for the building zone for each of the plurality of time steps by optimizing the cost function subject to a constraint on the predicted temperature. The equipment controller is configured to receive the temperature setpoints generated by the model predictive controller and drive the temperature of the building zone toward the temperature setpoints during each of the plurality of time steps by operating the HVAC equipment to provide heating or cooling to the building zone.