Research On Multi-Objective Torque Optimal Distribution And Control Of Distributed Electric Drive Vehicles

With the rapid development of the automotive industry,people's requirements for traditional performances such as vehicle dynamics,ride comfort and handling stability are constantly increasing.At the same time,automobiles are also under increasing pressure from the government,regulations and society in terms of energy and environmental protection.In recent years,the rapid development of new energy vehicles has received widespread attention as a new generation of important transportation vehicles recognized in the future.Among them,the distributed drive vehicle based on in-wheel motors has significant control advantages over traditional cars in terms of handling stability,driving safety,and reduced energy consumption.It is one of the most promising development directions for the next generation of electric vehicles.It is also an important research carrier for intelligent driving and unmanned driving.How to effectively take advantage of the independent and controllable torque of the wheels of a distributed electric drive vehicle and reasonably allocate the torque of each wheel through an optimization algorithm.Improving the steering stability and driving passability of distributed electric drive vehicles while taking into account the optimization of vehicle energy efficiency is the main research direction of many scholars at home and abroad,and also the focus of this article.First,based on multi-body system dynamics theory and vector mechanics,a modular modeling idea is adopted to establish a 14-degree-of-freedom dynamic model of the target vehicle.It includes six degrees of freedom of the vehicle body,four degrees of freedom of vertical motion of the four wheels,and four degrees of freedom of rotational angular velocity of the four wheels about their central axis.Among them,when establishing a hub motor model,considering that the motor efficiency is affected by both the motor speed and the motor torque,a response surface analysis method is used to establish a fourth-order regression equation of the motor efficiency on the motor speed and motor torque.And test the significance of the regression model by the remaining standard deviation.Further,by plotting a scatter plot,the effect of the regression model is intuitively represented.Finally,the accuracy and validity of the 14DOF vehicle model was verified by using a certain type of vehicle.It lays the foundation for the following researches on the control strategy of steering stability and the optimal torque distribution algorithm.Then,based on the direct yaw moment control method,a hierarchical control strategy is designed.Among them,the upper controller mainly solves the problems of uncertainty and non-linearity in vehicle motion control,and the lower controller mainly solves the torque distribution problem under constraint conditions.In the upper motion controller,the sliding mode variable structure control is adopted,and the longitudinal speed,the side slip angle and the yaw rate are taken as state variables.According to their deviation from the ideal state,the target control force(torque)is solved.The longitudinal speed slip mode controller,the yaw rate slip mode controller and the side slip angle slip mode controller are designed respectively.It realizes the joint control of motion states such as longitudinal speed,side slip angle and yaw rate,which effectively improves the vehicle's handling stability and driving safety under extreme conditions,and has good robustness.Furthermore,the lower-level controller is designed based on the multi-objective optimal control allocation method.The problem of the distribution of the target torque output by the upper motion controller on the electric wheels is transformed into an optimization problem under constraints.The objective functions that characterize the efficiency optimization of the drive system,the objective functions that characterize the vehicle's driving safety,and the objective functions that characterize the vehicle's handling stability are established.This paper analyzes some current multi-objective optimization algorithms,and introduces the second generation non-dominated genetic algorithm(NSGA-2)in detail.Based on the advantages and disadvantages of each optimization algorithm,a new and efficient multi-objective optimization algorithm is proposed based on genetic algorithm and tabu search algorithm:Hybrid Genetic Taboo Search Algorithm(HGTSA).Based on the 14DOF vehicle dynamics model built on the Matlab/Simulink simulation platform,the NSGA-2,HGTSA and the commonly used average distribution method were used to perform NEDC simulation working conditions experiments on high adhesion roads and low adhesion roads.Simulation results show that both NSGA-2 and HGTSA can improve the driving efficiency and vehicle driving safety of the distributed electric drive system compared to the equal distribution method.In particular,the optimization effect of HGTSA is more obvious,and the stabilization speed is faster.Finally,based on Matlab software and dSPACE real-time simulation system,a real-time simulation platform was built using DS1103 real-time simulator and MicroAutoBox.Using torque average distribution as a comparative experiment,the vehicle performance simulation experiment was carried out.The simulation results show that the proposed layered control strategy can effectively achieve the expected function,and the proposed control algorithm can improve the operation stability while taking into account energy saving.