Research On Optimal Torque Allocation Control For Distributed Drive Electric Vehicle Via Multi-objective Coordination

Since the birth of automobile from 1886,the consumption of oil resources and environmental pollution have deeply affected the progress of human beings.The electric vehicle is widely considered as an important means to solve the problems of traffic emissions and energy security.Together with simplified chassis structure,fast torque response and accurate control execution,the distributed drive electric vehicle powered by hub motors is regarded as one of the most promising chassis structures for the future automotive industry.Thanks to the independent control mechanism from hub motors,the flexible torque distribution can realize the optimization-by-software for the vehicle performance.How to reasonably distribute the tire force and save as much as possible energy form powertrain is undoubtedly an attractive chassis control issue at home and abroad.This research focuses on the torque distribution of the distributed drive electric vehicle,to investigate the coupling effect of different torque distribution modes on vehicle dynamics performance and energy efficiency.The main purpose is to find how to distribute torque among hub motors via multi-objective optimization.The structure of this research is organized as follows.(1)In order to improve the acceleration performance,braking safety and economy performance of the vehicle under straight-ahead driving conditions,the power consumption relationship between the battery and the motors is analyzed firstly.To avoid the challenge to precisely estimate the road adhesion in practice,an energy-and-adhesion optimal torque distribution strategy with combination of online and offline methods is proposed.Both the workload utilization ratio and the energy efficiency are optimized.For real-time application,the analytical solution of the optimal problem has been derived which is expressed by structure and experimental parameters.The simulation results reveal that the proposed strategy can obtain the equivalent economy performance under WLTP test cycle as the energy-oriented torque distribution strategy does.In addition,the traction capability and the brake safety can be better guaranteed.(2)To decrease the energy consumption caused by the uneven hub motor workload distribution from left to right when differential steering,a novel torque vectoring control is proposed to coordinate the direct yaw moment and the cornering improvement performance.The hierarchical control architecture is adopted to realize the collaborative optimization of the energy efficiency and steering characteristics of the chassis system under steering conditions.Considering the motor capacity limit,the model predictive control algorithm is used to design the upper controller to track the target steering motion,which includes the executive constraints.The comprehensive indexes of motion tracking accuracy and direct yaw moment amplitude are integrated into the optimization objective.Then the optimization problem is transformed into a quadratic programming problem for online solution.The lower controller is constrained by the target yaw moment and the total longitudinal drive torque demand.Taking the tire load rate and the energy consumption of electric drive system as the optimization objectives,a global optimal torque distribution method among four wheels is derived based on the minimum principle.The proposed algorithm is verified by Carsim-Simulink software.The influence of different steering characteristics optimization objectives on system energy consumption is analyzed.(3)In order to obtain the necessary longitudinal speed for torque distribution control,an adaptative condition-free velocity estimation method based on the kinematic information fusion is proposed.The process noise and measurement noise adaptive algorithm based on the linear Kalman filter is designed to compensate the condition-related adverse influence on the sensor data.The difficulty to obtain the statistical characteristics of prior noise can be avoided as well.Combined the strong tracking filter with the fading factor,the velocity estimation algorithm can effectively solve the conflict between the optimal estimation requirements under normal conditions and stability requirements under critical conditions.The algorithm is verified in the Carsim-Simulink software and its real-time performance in the actual embedded microcontroller is tested in the developed processorin-the-loop experiment system.(4)By studying the engineering development of modern automobile electronic control system,the necessity and great advantages of the application of model-based design method in automobile control software development are analyzed.Combined with Chery New Energy Corporation,the project of the chassis system and the electronic and electrical architecture of the whole vehicle based on the mass production electric vehicle chassis platform are introduced.Then the collaborative development scheme,functional requirements and system integration specifications of the control software are determined.The controller framework and corresponding control functions are designed in detail,and the application layer control software is developed in a modular way under the Simulink environment.According to the V mode,the key functions of the developed software are tested via Simulink V&V toolbox and vehicle road tests.Thus,the effectiveness of control software is verified.