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基于模糊逻辑控制的汽车采暖、通风与空调系统调节热舒适性和室内空气品质的仿真

Fuzzy Logic Controlled Simulation in Regulating Thermal Comfort and Indoor Air Quality Using a Vehicle Heating, Ventilation, and Air-Conditioning System.

机构信息

School of Engineering, STEM College, RMIT University, 124 La Trobe St, Melbourne, VIC 3000, Australia.

出版信息

Sensors (Basel). 2023 Jan 26;23(3):1395. doi: 10.3390/s23031395.

Abstract

Conventional heating ventilation and air-conditioning (HVAC) controllers have been designed to mainly control the temperature of a confined compartment, such as a room or a cabin of a vehicle. Other important parameters related to the thermal comfort and indoor air quality (IAQ) of the confined compartment have often been ignored. In this project, IAQ in the vehicle cabin was represented by its carbon dioxide (CO) concentration, and the occupants' thermal comfort levels were estimated with the predicted mean vote (PMV) index. A new fuzzy logic controller (FLC) was designed and developed using the MATLAB fuzzy logic toolbox and Simulink to provide a nonlinear mapping between the measured values, i.e., PMV, temperature, CO, and control parameters (recirculation flaps, blower's speed, and refrigerant mass flow rate) of a vehicle HVAC system. The new FLC aimed to regulate both in-cabin PMV and CO values without significantly increasing overall energy consumption. To evaluate the effectiveness of the proposed FLC, a cabin simulator was used to mimic the effects of different HVAC variables and indoor/outdoor environmental settings, which represented the in-cabin PMV and IAQ readings. Results demonstrated that the new FLC was effective in regulating the in-cabin PMV level and CO concentration, at desirable levels, by adaptively controlling the opening and closing of the recirculation flap based on in-cabin temperature and CO readings, while maintaining an average-to-good energy consumption level. The proposed FLC could be applied to a large variety of HVAC systems by utilizing low-cost sensors, without the need to significantly modify the internal design of the HVAC system.

摘要

传统的采暖通风与空调(HVAC)控制器主要设计用于控制封闭空间(如房间或车辆舱室)的温度。其他与封闭空间热舒适度和室内空气质量(IAQ)相关的重要参数通常被忽略。在本项目中,车辆座舱内的 IAQ 由其二氧化碳(CO)浓度表示,而乘员的热舒适度水平则通过预测平均投票(PMV)指数进行估计。使用 MATLAB 模糊逻辑工具箱和 Simulink 设计并开发了一种新的模糊逻辑控制器(FLC),以提供车辆 HVAC 系统的测量值(即 PMV、温度、CO 和控制参数(再循环风门、鼓风机速度和制冷剂质量流量)之间的非线性映射。新的 FLC 的目的是在不显著增加总能耗的情况下调节车内 PMV 和 CO 值。为了评估所提出的 FLC 的有效性,使用座舱模拟器来模拟不同 HVAC 变量和室内/室外环境设置的影响,这些变量和环境设置代表了车内 PMV 和 IAQ 读数。结果表明,新的 FLC 通过自适应控制再循环风门的开启和关闭,根据车内温度和 CO 读数来调节车内 PMV 水平和 CO 浓度,从而在可接受的水平上达到有效调节,同时保持平均到良好的能耗水平。该 FLC 可以通过利用低成本传感器应用于各种 HVAC 系统,而无需对 HVAC 系统的内部设计进行重大修改。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c1d/9921170/ff212128f5dc/sensors-23-01395-g0A1.jpg

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