| With the continuous development of science and technology,the trend of automobile intelligence is especially evident,and the sales of electric cars have risen in a straight line in recent years,so,it’s of great significance to the intelligent research of electric vehicles.As an important part of the electric car,automatic transmission’s shift strategy directly affects car’s driving performance and ride comfort,complexity and variability of roads require higher intelligence for automatic transmission.This paper took an electric vehicle equipped with two-gear AMT as the research object,using the parameters of vehicle and AMT system to establish vehicle and shifting models,and relevant research on simulation and test of intelligent control strategy for cars driving on the ramp has been done in this paper.Taking the structure of vehicle transmission system and the working principle of twogear AMT as reference,simulation model of pure electric vehicle with two-gear AMT was established based on MATLAB/Simulink,Sim Driveline and Stateflow,and the shift process simulation was completed.Besides,driver’s driving model was established with fuzzy control module for the cycle driving condition,and the simulation of the model was completed.The basic shift schedule has been established for the optimal power and the optimal economy,and its shortcomings were analyzed and explained when driving on the ramp,for this,this paper designed a ramp gradient identification device,which can identify the driving condition of uphill or downhill,based on Kalman filter,in order to achieve the goal that different driving conditions adopt different control strategies.Finally,in view of the phenomenon that the change of vehicle quality leads to inaccurate slope identification,a quality correction plan was developed in this paper,and the correct identification of the slope gradient was completed.This paper has made the analysis of the phenomenon of circulating shift when the basic shift schedule is used on the upslope driving condition,and designed the multi-parameter shift schedule by setting the ramp slop and accelerator pedal opening degree as input and the shift speed as output,based on BP neural network for the control target of the optimal power,simulation results show that correcting the shift schedule avoids frequent shifting when driving on the ramp.In order to reduce the situation that the vehicle is in a high speed and high gear positon for a long time,or the use of mechanical brake for a long time causes the brake to lose the braking efficiency,the shift strategy of downhill driving was made based on fuzzy control module.Besides,considering the condition of ramp starting,the torque of the motor is controlled with the brake pedal opening as a reference,avoiding the occurrence of the sliding slope or an unstable start.Finally,based on the TCU control model,an online simulation study of AMT system based on d SPACE was completed,hardware-in-the-loop test platform,which includes Auto Box,Acceleration pedals,motor and its controller,gearbox and transmission shaft,was built,and the hardware-in-the-loop test about shift strategy was completed,which can verify the correctness and feasibility of the shift strategy. |
