The Research Of Control Algorithms For Vehicle ASR On μ-Split Road

Nowadays, safe, environment protection and energy saving are three direction of automobile development. Improve vehicle safety is an important means of the manufacturers to enhance the competitiveness of their products. When vehicle starts or accelerates on the icy, snowy and wet road with low coefficient of friction, the wheels will slip excessively because of the low adhesion that the road surface provides. It causes the longitudinal and lateral adhesions to further reduce. And the vehicle stability, handling and acceleration will greatly reduce. Anti-Slip Regulation control system(ASR) is coming to be a popular feature on many vehicles because it can prevent the driven wheels from slip during vehicle accelerates especially when vehicle starts, accelerates or corners and improve vehicle's acceleration stability and handling.ASR, which gets the optimum longitudinal traction by regulating the driving wheels slip ratio, is a new active safety control system that was developed in the middle of 80's. In the present, the ASR has reached full development in overseas. Some of countries have ruled the ASR control system as requisite or optional equipment of new vehicles. But in China, the research of ASR is still in elementary phase and ASR is applied on vehicle more and more widely. So researching and developing the ASR products with our own intellectual property rights is very significant.It is to regulate the driving wheels slip ratio around the demanded slip ratio range so that the road adhesion coefficient is maximized and lateral stability is achieved. Based on this principle,this paper studies the Anti-Slip Regulation control system onμ-Split Road,use driving wheel braking torque regulation, it is imposed braking torque on the skid driving wheel, the speed of wheel lows to the best slip coefficient. This paper has discussed three control algorithms that is based on PID control, single neuron adapting PID control, fuzzy PID control, simulated these three control algorithms with MATALB/SIMULINK, and compared the performance with the situation without ASR.This thesis mainly includes four parts:1. Introducing the significance of ASR system, the research status of domestic and overseas, the principle of the working and the usually control algorithm presently.2. Vehicle system dynamics simulation model is the basis of ASR system simulation and analysis. Automobile transmission model is used to analyze the response of each subsystems, it includes engine model, transmission line model and the tire model. This paper established the Simulink model of vehicle system, which includes transmission line model and vehicle model, and with the course of their work introduces the brake pressure regulation devices and braking implementing agencies of ASR system. This is theoretical basis and foundation for control system design.3. Theoretically discussed ASR control algorithm which under PID control, single neuron adapting PID control and fuzzy PID control theory, and design their simulink model onμ-split road condition.In PID control, the main control object is vertical slip rates of slipping wheel, set the best slip rate is 0.1, use PID controller to control ASR system, is usually use the error between actual skating rate of the wheel and ideal slip rate, the PID algorithm calculates the needing traction control feedback to the brake, so to regulate brake pressure, then the wheels slip rate close to or equal to the ideal slip rate.In single neuron adapting PID control, neuron controller has the same characteristics of PID controller, it achieves adaptive, self-organization through the adjustment of weighting coefficients. So this neuron controller is online adaptive PID controller. This adaptive capacity is through a certain learning rules. This paper use Dalta learning algorithm, which has a better convergence and the ability to learn.In fuzzy PID control, the differential and its change of actual slip rate and the ideal slip rate are looked as input, changes of control is looked as output, build fuzzy inference system. Then under the actual control experience of traction control, formulated a number of fuzzy control rules, drawing neural network controller.4. The parameters in the algorithms are selected and these algorithms are simulated with SIMULINK, using active brake control on 0.1/0.5, 0.3/0.5 split-μroad surface respectively, and use the situation of road adhesion coefficient changed to demonstrate algorithm adaptability and effectiveness.The results of the simulation has shown that ASR system can effectively improve the vehicle traction,handling and stability. At the same time, it proves the control algorithms that are established are correct. This paper has discussed the applications of new control theories in ASR and established a foundation for further research of ASR.