Fuzzy Adaptive Algorithm Towards Automotive Air Conditioning Controller

With the booming development of science and technology,people demand for automobile air conditioning no longer simple temperature control but the efficiency of control.As traditional automotive air conditioning control technology,there still are some problems,for instance,easy to shock,time delay,poor comfort,and more research is needed.Air conditioning is an important research direction of the control system,which is based on fuzzy control method.Although Fuzzy control is robust and simple,it have exact demands on the sample set and rule base cannot be updated in the process of control,restricted the control effect.In this paper,we study the algorithm theory of fuzzy control,with the help of quadratic assignment problem,and put ant colony algorithm to self learning fuzzy rules.We used Improved method to simulate results and compare the algorithm’s recommendation effectiveness.The main contents of this paper are:First of all,we made a deep research on automotive air conditioning control system,and compared the advantages and disadvantages of the various algorithms and models.Then,summarized and analyzed the auto control theory,with the combination of fuzzy control technology in the field of the current situation.Once more,considering the traditional theoretical model is difficult in calculating,collecting data and defining data,we modeling objects based on the car for considering object,establish a new heat load balance equation.The model achieved better control effect with shortter time.Considering the traditional theoretical model have no requirement for air quality and there exits the poor air quality.According to air quality in China,by adding part of ventilation air in model,it will modified calorific value and correct the loss of calorific value.By combining the part of ventilation air with the new model,not only does it get shorter time in control,but also it get better air quality.Finally,the reference of ant colony algorithm in the application of the quadratic assignment problem,considered the fuzzy control rules cannot be updated,put forward a model based on fuzzy adaptive control.Ant colony algorithm is used to analyse the data rule learning,and real-time updated the rules to the rule base,to realize the fuzzy adaptive control.The model achieved better control effect.It effectively improved the effectively especially when the sample set is not comprehensive.This article uses the real car test data set to simulate the experiment,and compared the differences in accuracy of control,time and valve control accuracy of the control effect.Studies show that the based on the fuzzy adaptive control algorithm is much better than based on the fuzzy control algorithm algorithm in accuracy of the control effect,the performance in terms of time and accuracy of control.Therefore,the research of this topic have research significance and application value.