Research On Comprehensive Shifting Schedule Of AMT System For Pure Electric Bus

With the improvement of human living standards,cars have become a necessity for every household.The increase in car ownership has also brought tremendous pressure on the environment.Compared to fuel vehicles,in addition to being able to effectively reduce air pollution,pure electric vehicles have the characteristics of strong starting power and low noise in the car,which have also been favored by many owners.Due to the limitation of battery technology,the driving range of pure electric vehicles is always lower than that of ordinary fuel vehicles.Therefore,how to increase the vehicle’s driving range on the premise of ensuring dynamic performance is one of the research directions of pure electric vehicles.The automatic mechanical transmission has the characteristics of high transmission efficiency and compact structure,which can effectively increase the driving range of pure electric vehicles.It has been widely used in pure electric buses.The model used in this article is a bus equipped with a two-speed automatic mechanical transmission.The bus equipped with a two-speed transmission can adapt to the complex working conditions in the city and has stronger power.As the control part of the transmission,the shifting schedule plays a vital role in improving the vehicle’s power and economy.The main research contents of this article are as follows:(1)Discussing the background and necessity of the emergence of pure electric vehicles.Summarizing the current research status of AMT and shift schedule at home and abroad.(2)Analyzing the advantages and disadvantages of various shifting schedule.According to the known technical parameters of the vehicle and the efficiency curve of the motor,using the dynamic and economic evaluation indicators as the theoretical basis.Then,Single-performance shifting schedule is formulated using the mapping method.(3)Unscented Kalman filter is selected as the algorithm for vehicle quality estimation.Deriving equation of the UKF algorithm.Establishing a state space equation based on the car driving equation.Using the interpolation method to modify the traditional shifting schedule.(4)The driver’s intention and road conditions are used to correct the shifting schedule.The driver’s intention recognition adopts fuzzy logic controller for recognition.The driver’s control of the accelerator pedal and the brake pedal is used as an input variable.The output is set to four driving intentions,and the corresponding type of shifting schedule is selected according to the different driving intentions.The method used for road condition recognition is deep learning.Choosing different shifting strategies for different weather conditions.(5)The forward simulation method is used to establish a vehicle model which constructed by AMESIM and MATLAB/Simulink.First,the simulation determines the accuracy and arithmetic speed of the UKF for vehicle mass estimation,and the estimated vehicle mass can effectively correct the shifting schedules.Then proving that the modified shifting schedule is better than the unmodified shifting schedule.And then,on the basis of verifying that the fuzzy logic can accurately identify driving intentions,the performance difference between the traditional shifting schedule and the shifting schedule that considering the driver’s intensions is compared and analyzed.