Study On System Modeling And Control Strategy For Power Split Hybrid Electric Mining Truck

Off-road mining dump truck is the main transportation for open-pit mining and materials transporting in the mining area,which undertakes the significant tasks of national infrastructure construction and national economic development.The development of hybrid technology can effectively solve the problems of high pollution and high energy consumption of mining trucks,which is of great significance for the construction of green mines and the promotion of sustainable development in the field of mining machinery.Firstly,the feedforward simulation model of the hybrid electric mining truck is established by combining the experimental and theoretical methods in the Matlab/Simulink environment,including engine,power battery,motors and dual planetary transmission etc.Then,the accuracy of the simulation model is verified using real vehicle on-road test data.The results show that the feedforward simulation model meet the accuracy requirements and can be used to support the test and verification of the control strategies.Secondly,when driving on a long downhill slope with heavy loads,the regenerative braking cannot be fully capitalized on since battery So C may be at a high level,and long-time mechanical braking may result in reduced braking performance and driving safety problems.To solve these problems,a predictive equivalent fuel consumption minimum strategy(P-ECMS)that combines slope information prediction and vehicle mass estimation is proposed.Firstly,GPS topographical data is utilized to realize road slope prediction,and a recursive least squares method is utilized to estimate the vehicle mass after loading operation.Then,a braking energy recovery estimation model is established to predict the target So C values before the downhill driving with full and empty loads,and the reference So C trajectory is further obtained based on the weighted sum of these two So C values.Finally,a traditional A-ECMS algorithm is adopted to track the reference So C trajectory while realizing power-split optimization instantaneously.The simulation results show that the proposed P-ECMS algorithm is suitable for different driving conditions and can improve the fuel economy up to 4.61% compared with the traditional A-ECMS.Thirdly,analyze the root cause of the system shock and process of the mode shifting,and an online engine torque estimation algorithm is established using the highly coupled characteristics of the planetary gear mechanism.Subsequently,based on the mechanism of the system shock,the torque change rate of the MG1 and MG2 motors is limited,and a dynamic coordination control strategy for design mode switching is designed.The simulation of shifting between the electric mode and hybrid modes is performed.The results show that the designed dynamic coordinated control strategy can significantly reduce the system shock during the shifting of working modes and can improve the vehicle ride.Finally,based on the vehicle rapid prototype controller and NI PXI real-time simulator,a hardware-in-the-loop experiment simulation platform is set up.Using automated code generation technology,the control algorithm model is downloaded into the controller,and the vehicle model is imported into the real-time simulator.HIL test results show that the designed energy management control strategy and dynamic coordination control strategy are able to meet the real-time computation requirement and can achieve good performance.