Energy Optimization And Multi-controller Hil Test Of Wheel Direct Drive Electric Vehicle Based On PMP Algorithm

At present,electric vehicles(EV)are mainly driven by the centralized motors.With the development of new energy vehicle technology,a variety of efficient driving conFig.urations have emerged.Hub-motor-direct-drive EV is sTab.,safe and cost-effective.Such advantages have become the focus of scholars at home and abroad.The controllable driving/braking force lead to rich dynamic characteristics.However,it also brings challenges to multi-motor coordination and vehicle performance.This paper puts forward to the problem that the actual driving environment is complex and variable,and the power requirements change frequently.A driving force allocation method for hubmotor-direct-drive EV with optimal vehicle energy efficiency is proposed.It is carried out in the following work.The rapid prototype control system has been built on the Hub-motordirect-drive EV which was rifted based on a concentrated drive miniature EV.The miniature EV has been matching the mechanical characteristics of the hub motor through the modification of the mechanical structure and the transmission system.The multi-domain co-simulation platform of the AMESim and Simulink was proposed after the analysis of the electromechanical coupling and power transmission path of the Hub-motor-direct-drive EV.The motor MAP and control law were obtained based on the wheel hub motor test.The Simulink model of the motor was established based on them.Driver closed loop model was also built in the Simulink.At the same time,the effectiveness of the co-simulation model was verified by real vehicle road test.According to the different power(speed)requirements of the driver and through the adjusted and controlled efficiency of the different working points of the motor,the driving force optimization method of the hub-motor-directdrive EV based on PMP was proposed.The objective function of energy optimization and the constraint of rotational speed of the hub motor are set up.Also,the EV driving force optimization design process has been done.Considering the frequent acceleration and deceleration of urban driving,selecting typical FTP and NEDC operating conditions and conducting test evaluation based on the co-simulation platform.The result shows that compared with the traditional driving force average distribution method,the global energy consumption of the former operating conditions is reduced by about 10.8.%,in the latter city operating condition,the energy consumption of the whole vehicle is also reduced by about 8.3%.Considering the dynamic stability problem in the actual operation of the hub-motor-direct-drive EV,the driving force was distributed second time through the yaw stability control based on the PMP energy-optimized vehicle system.A driving force distribution method for multi-objective optimization of the hub-motor-direct-drive EV was proposed.The corresponding hierarchical control system of it was designed soon.The upper layer is the torque distribution system based on PMP.The middle layer is the torque distribution system based on yaw stability control.And the lower layer is the hub motor driving force control system.Simulation analysis of the model in the loop was combined with the co-simulation platform.The result shows that the proposed hierarchical control method can effectively track the target yaw moment,keep the vehicle sTab.,and achieve the best energy consumption of the whole vehicle.The hub-motor-direct-drive EV’s driving system is a combination of multiple drive controllers and vehicle controllers.Based on the NI board architecture,multi-controller system HiL simulation test platform was built based on the super-performance FPGA board(running motor model),real-time system and analog unit.And the real-time simulation model of the hub-motordirect-drive EV was established.Multiple controller parameters were calibrated.And the effectiveness of the proposed optimization algorithm and hierarchical control method has been tested under multiple cycles.The HiL test result shows that the control algorithm is reliable and the multi-controllers work in coordination.The energy consumption after actual operation is reduced by 9.8% and 7.5% respectively under the two typical working conditions.It is basically consistent with the model-in-loop simulation tests.At the same time,the sTab.control system was transplanted to the prototype of electric vehicle for road test.Result shows that the effect of energy consumption optimization was obvious.It further proves that the method can effectively improve the economy of the electric vehicle and ensure the stability of the vehicle.