Longitudinal Speed Control For Electric Vehicles Based On State Observation

In order to reduce traffic accidents and the impact of internal combustion engine vehicles on energy consumption and environmental pollution,with the development of the Internet,information,electronics and intelligent technology,automotive intelligent and electrification technology has become an effective way to the above questions.Longitudinal speed control as the bottom control algorithm of electric intelligent vehicle,its control effect directly affects the safety and comfort of intelligent vehicle.In the process of vehicle longitudinal speed control,existing many kinds of constraints,among these constraints,motor torque constraints and braking torque constraints directly affect the safety of the system.So how to deal with these constraints is a difficult point in the process of controller design.While in the longitudinal control process,vehicle quality has a greater impact.So it needs to be online estimated and input to the vehicle speed controller.Taking into account the model predictive control(moving horizon optimization)method has many advantages on control system with constrained design.In this paper,we propose a moving horizon optimization controller based on observer,it could complete the real-time online optimization solution,explicit deal with constraints,and effectively compensate for the impact of interference factors.First of all,for the research needs of this subject and electric vehicle engineering structure,the vehicle model of the pure electric vehicle which satisfies the longitudinal performance is modeled in the commercial simulation software AMESim,and match the parameters and validate for it.This model is used as the verification platform for the subsequent controller.Secondly,the constraints and the nature of the model are analyzed,taking into account the nonlinearity of the model,the vehicle longitudinal controller is designed based on nonlinear moving horizon optimization method with the assumption that the vehicle mass is known.On this basis,in order to improve adaptivity of the controller on the main interference factors,proposed the drive shaft torque and vehicle quality joint estimator design method.The characteristics of vehicle quality change are analyzed,and least squares recursive identification method are adopted.According to the coupling relation between the vehicle mass and the drive shaft torque,the adaptive association combined observer is designed.Then,the identification result is fed back to the speed controller to complete the longitudinal speed controller design based on the state observation.Finally,the controller performance is analyzed in detail through joint simulation of AMESim and MATLAB/SIMULATION,the simulation results show that the designed speed controller has good control effect,at the same time the expected research objectives have been achieved.