電動車空調運用模糊控制之節能研究

The study of saving energy on electric vehicle air conditioning system using fuzzy control

楊斯琪(Shih-Chi Yang)

指導教授 ： 卓清松

國立臺北科技大學/機電學院/能源與冷凍空調工程系碩士班/碩士(2013年)

摘要

本研究採用模糊控制策略來進行車艙空調控制，以降低電動車之耗電量並兼顧車艙內溫度。實驗藉由模擬性的智慧車艙空間，改變不同熱負荷，並比較傳統控制策略、PI控制策略與模糊控制策略的節能差異。研究結果顯示，在穩態溫度控制上，模糊控制策略在與設定溫度的最大溫差約0.5°C為三者中最小，低於PI控制器與設定溫度的最大溫差約0.7°C與開-關控制器與設定溫度的最大溫差約1.2°C；模糊控制策略平均耗功也最少，模糊控制器平均耗功約640W，開-關控制器平均耗功約798W，模糊控制器平均耗電較開-關控制省電約19.8%。本研究證明此模糊策略適用於電動車空調系統，達到車艙內舒適溫度，並且比傳統控制消耗更少能源。

關鍵字

汽車空調 ； 電動車 ； 模糊控制 ； LabVIEW ； 節能

並列摘要

In this study, we design the fuzzy control strategy for electric vehicle cabin air-conditioning systems, in order to reduce the power consumption of electric vehicles and hold the car cabin on a comfortable temperature. Experiments are act with the simulating cabin, and change different thermal load, in order to compare with traditional control strategy and fuzzy control strategy on energy saving difference. The results showed that in the steady-state temperature control, the fuzzy control strategy is the smallest of three controller. The fuzzy control temperature difference with setting temperature is about 0.5°C which is lower than the PI control temperature difference with setting temperature is about 0.7°C and the on-off control temperature difference with setting temperature is about 1.2°C. Fuzzy control strategy on average power consumption is the smallest of three. The fuzzy control average energy consumption is 640W. The On-off control average energy consumption is 798W. The average value on saving energy is about 19.8% with On-off controller. This study demonstrates that this fuzzy control strategy for electric vehicle air conditioning systems can achieve comfortable cabin temperature and consume less energy than PI controller and On-off controller.

並列關鍵字

Electric Vehicle ； Fuzzy Controller ； Air Conditioning ； LabVIEW ； Savine energy

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