Research On Autonomous Dynamic Regulation Of Vehicle Operating Conditions

The actual condition of the vehicle engine has resulted in the difference between the actual road condition and the bench test condition,which brings great difficulties to the design of the control parameters of the central controller.At present,the general method of determining the working conditions is based on the use of a large number of test data samples to establish the identification model,and then based on the model to identify the new operating conditions.The disadvantage of this model is that it has no universal adaptation and can not match the vehicle operating conditions under different traffic structures,and can not be adjusted according to the actual road conditions.Therefore,it has great limitations and poor adaptability.Automotive engine speed control research has become a hotspot in the intelligent transportation system,through the forecast of future driving conditions,optimize the allocation of the output power of the engine,so in the actual driving to reduce fuel consumption,reduce emissions,reach the requirements of green energy conservation and environmental protection.This paper is based on the analysis of the traditional engine operating conditions,combined with the automobile engine speed prediction control technology,the establishment of an independent dynamic adaptive neural fuzzy inference system and immune feedback condition domain control algorithm combining the regulation model,based on the Matlab platform,through the speed deviation of the predicted in advance to dynamically adjust the steady state domain,improve the ability to adapt the engine in different road conditions,to improve and enhance the performance of the engine.The main contents of this paper are as follows:(1)The analysis of the existing prediction methods,mainly including: several BP neural network prediction method,prediction method,according to the history based on the grey system,through the analysis of the prediction effect of various methods,advantages and disadvantages of various prediction methods,to prepare for the following research.;(2)According to the prediction of the lack of method,put forward a new prediction method,the adaptive neuro fuzzy inference system based on engine speed prediction method to predict the control of engine speed,get the speed forecast error and the input signal as a dynamic adjustment model;(3)For shortcomings of traditional operation judgment method,put forward the concept of running condition domains,and fuzzy mathematical statistics principle based on fuzzy judgment model of automotive operation domain,using the actual road driving data,to determine the threshold boundary running condition domains,and analyzes several factors influencing operation boundary;(4)A dynamic vehicle operation domain adjustment model,control algorithm is used in the model is based on the principle of immune feedback control,immune feedback controller design for a working domain based on Matlab platform,the dynamic simulation model is established and tested the real-time dynamic adjustment of the operating conditions of the domain.