Research On Fault Detection And Fault Estimation Algorithm Of Intelligent Electric Vehicle Based On Fuzzy Observer

In recent years,the increase of vehicle ownership has directly aggravated a series of social problems such as environmental pollution,road congestion and frequent traffic accidents.Traffic accidents,especially,have brought great harm to people’s life and property safety.Statistical data shows that more than 80% of traffic accidents are caused by human factors.Active vehicle safety control is considered to be one of the important means to effectively reduce traffic accidents caused by human error and has become an important research hotspot in the field of vehicle engineering.In view of this,a fuzzy observer based fault detection and fault estimation algorithm for intelligent electric vehicle is proposed in this paper.In this paper,the nonlinear lateral dynamics model of intelligent electric vehicle is considered and the TS fuzzy model is used to model it.Based on the universal approximation characteristics of TS fuzzy model and its linear subsystem,the mature linear system theory can be used to solve the observer-based fault detection and fault estimation algorithms for intelligent electric vehicles.However,this algorithm has some theoretical and practical challenges,such as complex algorithm structure and unmeasurable antecedent variables.Therefore,this paper proposes a TS fuzzy model modeling method with local nonlinear afterparts by using nonlinear partition method,namely N-TS fuzzy model.This model can not only effectively reduce the number of fuzzy rules of intelligent electric vehicle model and reduce the complexity of algorithm,but also avoid the appearance of unmeasurable antecedent variables,which greatly reduces the difficulty of algorithm design.The main research contents of this paper are as follows:1.The current research status of fault detection and fault estimation algorithm design for intelligent electric vehicle based on fuzzy observer is introduced.The significance and practical value of the proposed algorithm for the development of active safety control for intelligent electric vehicles are analyzed.2.The problems in designing observe-based fault detection and fault estimation algorithms for TS fuzzy model of intelligent electric vehicle are analyzed,and a new N-TS fuzzy model modeling method is proposed.3.When the intelligent electric vehicle system has external disturbance,the fuzzy fault detection algorithm is designed based on the N-TS fuzzy model of intelligent electric vehicle,so that the designed algorithm can realize the estimation of the unmeasurable state of the vehicle and the fault detection of the actuator.The linear matrix inequality conditions for the algorithm design are given,and the effectiveness of the proposed algorithm is verified by simulation and experiment.4.In the case of external disturbances in the intelligent electric vehicle system,a fuzzy fault estimation algorithm is designed based on the N-TS fuzzy model of intelligent electric vehicle,so that the designed algorithm can simultaneously estimate the unmeasured state of the vehicle and the fault of the actuator.The condition of linear matrix inequality is given,and the validity of the proposed fault detection algorithm is verified by simulation.