Research On Road Grade Estimation And Driving Intention Identification Based Powertrain Shift Control

As a kind of special purpose vehicle,tracked vehicle always drive in the wild operation field or on the complicated and changeable road.Therefore,the environmental adaptability of the powertrian demanded is relatively higher.At present,the vast majority of tracked vehicles apply the two-parameter shift schedule which is made based on the static bench test.Not only is it difficult to adapt to the complex environment,but also the two-parameter shift control strategy can not adapt to the driver intention very well.Along with the development of the automatic driving technology,higher requirements for the powertrain control strategy are put forward.Therefore,the road slope estimation and driving intention research is developed.The development of the shift control strategy has important engineering and practical significance.Firstly,the Matlab/Simulink simulation model is built according to the structural characteristics and performance parameters of the powertrain,which provides the basis for the simulation research.In order to verify the real-time performance of the related algorithms and to prove the validity of the control strategy,a model platform based on hardware in the loop system(HILS)is built.Extended Kalman Filter(EKF)observer algorithm is developed to identify the road slope.This algorithm is developed based on the vehicle dynamic model.The three signals engine torque,gear and vehicle speed are taken as the input signals.The Matlab/Simulink model of the state space equation is built according to the powertian equilibrium equation.The filter observer is obtained.The road slope signal is the output signal for the final observation.EKF algorithm simulation is carried out off-line under the circular road spectrum constructed by the research group of Beijing Institute of Technology.And the simulation model is validated on the model based platform.The obtained slope value calculated by EKF observer is constructed to the actual value.One important factor of the human-machine-environment closed-loop system principle is the human influnce.The study of human driving intention based on the hidden Markov Model(HMM)algorithm is developed in this paper.The data indicates the driver's driving characteristics is acquised as training samples.The algorithm program is achieved applying the Hidden Markov Model toolbox(HMM Toolkit)functions.Then,the driving intention model is trained,and the accelerated intention,deceleration intention and maintain intention are aquired.Driving intention under single condition is verified through off-line simulation,and driving intentions under multi driving conditions are verified by data acquired from the vehicle test.After the study of the road slope identification and driving intention,the driving intention is used as the influence factor to carry on the research of the shift control strategy.Based on the two-parameter shift schedule,the gear shift control strategy based on the driving intention is carried out to eliminate the gear-up phenomenon when the powertrian decelerates.And the accelerating performance of the vehicle is optimized.Finally,off-line simulation and the model based platform test are carried on under the two conditions: without shift control strategy and with the shift control strategy.Through non-intervention and intervention conditions operating results,it demonstrates the effectiveness of the shift control strategy.