Methods and related systems for operating a climate control system for an indoor space are disclosed. In an embodiment, the method includes increasing a speed of a fan of the climate control system, and determining a first fitted external static pressure (ESP) function from a first plurality of airflow values and a first plurality of ESP values. Additionally, the method includes obtaining a baseline ESP from the first fitted ESP function, and determining a second fitted ESP function from a second plurality of airflow values and a second plurality of ESP values collected at least one week after the first plurality of airflow values and the first plurality of ESP values are collected. Further, the method includes comparing the first calculated ESP obtained from the second fitted ESP function to the baseline ESP to determine a condition of an air filter of the climate control system.

An air-conditioning apparatus includes a casing provided with an air inlet through which air is sucked and an air outlet through which the air is blown out, a plurality of heat exchangers being connected in parallel, and causing heat exchange to be performed between the air sucked from the air inlet and refrigerant, a plurality of fans each sending the air to a corresponding one of the plurality of heat exchangers, and a controller configured to control the plurality of fans so that they have different rotational speeds.

An HVAC system for enhanced source-to-load matching without sacrificing airflow delivery in low load structures. Embodiments of the present disclosure provide for an HVAC system for enhanced source-to-load matching in a low load environment, i.e. dwellings with a BTU/hour capacity of less than 18,000. Prior art HVAC equipment is oversized for dwellings with a BTU/hour capacity of less than 18,000 that are insulated to minimum code requirements. Embodiments of the present disclosure provide for an HVAC system that separates the delivery of airflow (CFM) output from that of the BTU capacity output, thereby enabling a distributed delivery system for optimal source-to-load matching without sacrificing airflow delivery in low load environments. The source-to-load matching enabled by the present disclosure ensures optimal indoor air quality, enhanced comfort for occupants of the dwelling, and approximately a 60% reduction in heating and cooling costs when compared to prior art HVAC systems.

A problem to be solved by the present disclosure is to realize a fan unit capable of determining occurrence or non-occurrence of a backflow during operation. In a second unit, a second controller calculates front-rear differential pressure by substituting a rotation speed and a volume of air or a wind speed that can be acquired in real time into a relational expression. The relational expression derives, from two values of the rotation speed, the volume of air or the wind speed, and the front-rear differential pressure, the remaining one value. Then, the second controller determines that a backflow occurs if the calculated front-rear differential pressure is within a range that cannot occur under a normal condition. Therefore, the occurrence of a backflow can be detected without using an expensive pressure sensor or a directional wind speed sensor.

The present invention is relative to a damper (5) adapted to regulate an air flow orifice (7) for passing of an air flow in a ventilation duct (2), wherein the damper (5) comprises a plate (11), a regulating device (12) and a mounting element (13), wherein the mounting element (13) is resilient and comprises a first and a second end (19, 20), the distance (L1, L2) between the first and the second end (19, 20) being arranged to change when the mounting element (13) bends resiliently, and wherein the first and a seconds end (19, 20) are adapted to cooperate with an inside of the ventilation duct (2) to removably mount the damper (5) in the ventilation duct (2), and a ventilation system (1) comprising such a damper (5).

An HVAC system for enhanced source-to-load matching without sacrificing airflow delivery in low load structures. Embodiments of the present disclosure provide for an HVAC system for enhanced source-to-load matching in a low load environment, i.e. dwellings with a BTU/hour capacity of less than 18,000. Prior art HVAC equipment is oversized for dwellings with a BTU/hour capacity of less than 18,000 that are insulated to minimum code requirements. Embodiments of the present disclosure provide for an HVAC system that separates the delivery of airflow (CFM) output from that of the BTU capacity output, thereby enabling a distributed delivery system for optimal source-to-load matching without sacrificing airflow delivery in low load environments. The source-to-load matching enabled by the present disclosure ensures optimal indoor air quality, enhanced comfort for occupants of the dwelling, and approximately a 60% reduction in heating and cooling costs when compared to prior art HVAC systems.

Interactions between a training server and a plurality of environment controllers are used for updating the weights of a predictive model used by a neural network executed by the plurality of environment controllers. Each environment controller executes the neural network using a current version of the predictive model to generate outputs based on inputs, modifies the outputs, and generates metrics representative of the effectiveness of the modified outputs for controlling the environment. The training server collects the inputs, the corresponding modified outputs, and the corresponding metrics from the plurality of environment controllers. The collected inputs, modified outputs and metrics are used by the training server for updating the weights of the current predictive model through reinforcement learning. A new predictive model comprising the updated weights is transmitted to the environment controllers to be used in place of the current predictive model.

An approach that collects sensor data associated with a building automation system having filters and determining the optimal timing of the replacement of filters that includes replacement dates based upon use, utility, and labor costs.

Interactions between a training server and a plurality of environment controllers are used for updating the weights of a predictive model used by a neural network executed by the plurality of environment controllers. Each environment controller executes the neural network using a current version of the predictive model to generate outputs based on inputs, modifies the outputs, and generates metrics representative of the effectiveness of the modified outputs for controlling the environment. The training server collects the inputs, the corresponding modified outputs, and the corresponding metrics from the plurality of environment controllers. The collected inputs, modified outputs and metrics are used by the training server for updating the weights of the current predictive model through reinforcement learning. A new predictive model comprising the updated weights is transmitted to the environment controllers to be used in place of the current predictive model.

An approach that collects sensor data associated with a building automation system having filters and determining the optimal timing of the replacement of filters that includes replacement dates based upon use, utility, and labor costs.