Torque Allocation Control Of Distributed Electric Vehicles Considering Transient Tire Dynamics

From the perspective of vehicle dynamics,vehicle handling stability is the main use performance that determines its safe driving.The distributed electric vehicle responds quickly and has more controllable degrees of freedom.Thus,the vehicle steering characteristics can be controlled through the distribution of the four wheels' torque,which provides an important opportunity for improving the vehicle handling stability.But,there are also some problems: the four-wheel independent drive brings actuator redundancy,which needs to be coordinated.The rapid change of the in-wheel motor torque will excite the transient tire dynamics,causing a vehicle dynamic response delay and affecting the vehicle handling stability.Therefore,this paper aims to propose a model predictive torque allocation method for distributed electric vehicles with the tire force lag,so as to improve the vehicle transient response and furtherly enhance the vehicle handling stability.The integrated Model Predictive Control(abbreviated as MPC)mainly includes: the rolling calculation of control expectations,the vehicle state prediction and four-wheel torque dynamic optimization considering the transient tire dynamics,and the controller mode switching based on the vehicle stability prediction and gain scheduling.In terms of vehicle handling,the controller can compensate for the vehicle response delay caused by the transient tire dynamics.As for vehicle stability,the vehicles tending to lose stability are controlled to return to a stable state in time,judging by the vehicle stable boundary explored.The main research contents and conclusions of this paper are as follows:(1)Dynamic modeling of electric vehicles: Build a 14-DOF vehicle dynamics model;derive the UniTire transient tire model;propose a 2-DOF vehicle model considering fourwheel different transient tire dynamics,and perform frequency and time domain analysis.It is shown that the lateral tire lag can cause the delay and overshoot of vehicle transient response.Under complex conditions,the longitudinal tire lag furtherly increase the response delay but reduce the overshoot;there is longer tire force lag time and more obvious transient response,when driving at the low speed,high adhesion and small steering input conditions,etc..(2)Vehicle stability analysis and prediction: Analyze the vehicle stability through the phase plane and its characteristic points,and divide the stable area;reveal the law that how the stable area boundary changes with the vehicle driving conditions,construct the boundary equation and do the parameter fitting,finally,a vehicle stability prediction method is obtained.The results show that the boundary equation can accurately express the stable area position within the range that vehicle speed is 0~40 m/s,road friction coefficient is 0~1 and front wheel steering angle is 0~10 deg.Thus,it is convenient and has certain practicality.(3)Model predictive torque distribution control considering tire force lag: In the model predictive control,the compensation of delay is achieved in two parts: 1)Rolling calculation of the expected vehicle response utilizing the real-time feedback of tire secant stiffness;2)In the prediction model,the description of transient tire dynamics helps to predict the vehicle future dynamics more accurately.Then,through transforming the prediction model,the handling-oriented and the stability-oriented MPC controller are obtained separately,and the vehicle stability prediction is utilized to coordinate the two MPC controllers to obtain the optimal performance,named phase plane-based controller.(4)Simulation verification of torque distribution control: Set up the Simulink platform and carry out simulation verification.The results show that: 1)The MPC controller can improve vehicle response delay.2)The phase plane-based controller coordinates the handling and the stability controller,maintains the better vehicle steering characteristics and smaller control adjustments.As a result,it has a better effect on tracking the vehicle performance target,a better vehicle trajectory,and a lower energy consumption.