Control systems for heating ventilation and cooling systems
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Solution Overview
Problem
HVAC systems face challenges in efficiently controlling temperature and humidity levels in conditioned spaces, particularly in liquid desiccant air-conditioning systems, where existing control methods lack precision and adaptability to real-time sensor data and desired environmental conditions.
Innovation Solution
A control system comprising a computing device that receives data from temperature and humidity sensors to generate adjustment data for exhaust air flow, desiccant flow rate, water flow rate, total air flow rate, and liquid desiccant concentration, transmitting these adjustments to the conditioner system to maintain desired temperature and humidity levels, optimizing performance criteria such as cost and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a thermostat is used to set desired temperature and humidity level, then the basic control function is achieved, but the precision and adaptability to real-time sensor data are insufficient
Solution Approach 1:
The control system continuously receives real-time sensor data from temperature and humidity sensors, compares actual conditions with desired setpoints, and dynamically adjusts control settings. This closed-loop feedback mechanism enables precise adaptation to changing environmental conditions while maintaining manageable system complexity through automated control algorithms.
Solution Approach 2:
The system transitions from static thermostat control to dynamic control by continuously adjusting exhaust air flow, desiccant flow rate, water flow rate, and total air flow rate based on real-time sensor readings. This dynamic adjustment capability allows the system to respond precisely to changing conditions while using standardized HVAC components.
2Productivity
If existing control methods are used in liquid desiccant air-conditioning systems, then the system operates, but efficiency and cost optimization are lacking
Solution Approach 1:
The control system optimizes operational efficiency by dynamically adjusting multiple parameters including exhaust air flow rate, desiccant flow rate, water flow rate, and total air flow rate based on real-time sensor data. This multi-parameter optimization enables the system to achieve better cooling performance while reducing energy consumption and operational costs compared to fixed-control methods.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system effectively adjusts control settings in real-time to achieve precise temperature and humidity control, enhancing the operational efficiency and comfort of conditioned spaces while minimizing energy consumption and costs.
Implementation Method 1
Less frequently, the heat exchangers may include a liquid desiccant to dehumidify the air during the cooling process
Data Source
AI summary
The disclosure relates to control systems for heating ventilation and cooling systems. In some examples, a controller for a heating ventilation and cooling system receives, from a first temperature sensor, a first temperature of a first air flow entering a conditioner system. The controller also receives, from a first humidity sensor, a first dew point of the first air flow, and also receives, from a thermostat, a desired temperature for a conditioned space. The controller generates adjustment data characterizing an adjustment to at least one of: (1) an exhaust air flow, (2) a desiccant flow rate, (3) a water flow rate, (4) a total air flow rate, and (5) a liquid desiccant concentration of the conditioner system based on at least one of the first temperature, the first dew point, and the desired temperature. The controller transmits the adjustment data to the conditioner system to cause the adjustment.