An Intelligent Car Temperature Control System

Nowadays, more and more residential cars apply various of services of energy saving to help themselves improve performances and decrease cost. As for the car air conditioning, some put forward ideas that using neuron-fuzzy method can precisely control the cooling capacity, the other hold the view that power line communication based photovoltaic (PV) system can effectively manage the energy. In this paper, it aims to deal with the shortcomings that aforementioned do not take the realistic environment and the neuron-fuzzy method's disadvantages into consideration. As a result, this paper comes up an intelligent car temperature control system(ICTCS), which, comparing with conventional temperature control systems, has two main advantages-one is using three criterions, namely light intensity outside cars(I), temperature inside cars(T) and sunshine incident angle(alpha), to judge what kind of environment the car is in on earth and decide car cooling capacity over, the other is applying neuron-fuzzy system to train the comprehensive temperature to try its best to decrease faster. It will refrigerate in different stalls in the standard of difference between temperature inside cars and calculated most suitable temperature. Applying the above system into actual experiments, we can find under the premise that cooling effect stays nearly the same, the energy consumption gets decreased, which is to say, the ICTCS gets good results.