Adaptive Decoupling Control Of Chassis Integrated System For4WD Electic Vehicle

Four-wheel-drive electric vehicle adopts wheel motor as its driving motor. Itintegrated motive and transmission mechanisms into wheels and compose to fourindependent driving control systems. The novel structure replaces the complextransmission mechanism of traditional vehicle and reduces the weight of the vehicle‘s body.Meanwhile, it provides more room for vehicle control. However, chassis integrated controlsystem integrates several subsystems which makes the coupling problem more complex.According to the features of wheel-drive electric vehicle and the coupling problem amongthe control systems, this thesis researches on the decoupling control of chassis integratedcontrol system for four-wheel-drive electric vehicle.With the complex structure, road condition and driving operation, the driving state ofthe wheel-drive electric vehicle varies frequently and presents serious non-linear andtime-variable features. By adopting artificial intelligence control algorithm, the system canachieve higher adaptive capacity and better control performance.According to the dynamics of four-wheel-drive electric vehicle, this thesis researcheson the coupling problem between AFS and DYC. A2-degree-freedom linear vehicle modelhas been established. By series with feedforward decoupling controller, chassis controlsystem is transferred to two independent controllers. Matlab simulation under differentconditions verifies the feasibility and availability of the decoupling control method intheory.Because of the non-linearity of the vehicle in real driving condition, a7-degree-freedom nonlinear vehicle model is established in order to describe the vehiclestate precisely. Pacejka tire model and Ackermann differential model is adopted in thethesis. The model regards sideslip angle and yaw rate as its control variables, steeringangle compensation and yaw moment compensation as its control outputs, establishes theAFS、DYC integrated control system. The operating stability, non-linearity and couplingfeature are analyzed under different conditions.Decoupling control of chassis integrated control system has been achieved based onBP neural network. The three layers neural network regards sideslip angle、yaw rate and their derivative values as its inputs, steering angle compensation and yaw momentcompensation as its control outputs. It can achieve non-linear real time decoupling, reducethe interference between stability control subsystems and enhance the control performanceof vehicle chassis. Simulation results under different conditions show that by decouplingcontrol, the ideal value tracking performance of vehicle attitude parameter has beenimproved and neural network decoupling controller achieves good performance.